Accuracy 2012 Conference

 

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Proceedings of the Tenth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences

10-13th July 2012
Florianópolis, SC, Brazil

Edited by: Carlos Vieira, Vania Bogorny and Artur Ribeiro Aquino

 

 

All the papers are online now.

Welcome to download.

Proceedings of the Tenth International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences

10-13th July 2012
Florianópolis, SC, Brazil

Edited by: Carlos Vieira, Vania Bogorny and Artur Ribeiro Aquino

 

 

Local Organizing Committee
Carlos Antonio Oliveira Vieira (UFSC, BR) chair
Francisco Henrique de Oliveira (UDESC, BR)
Mariane Dal Santo (UDESC, BR)
Rodrigo Lilla Manzione (UNESP, BR)
Vania Bogorny (UFSC, BR)
Jose Alberto Quintanilha (USP, BR)
Gerard Heuvelink (Wageningen University, NL)
Antonio Henrique da F. Klein (UFSC, BR)
Mariane Dal Santo (UDESC, BR)

International Steering Committee
Linda Lilburne (Landcare Research, NZ)
Ron McRoberts (U.S. Forest Service, US)
Kim Lowell (University of Melbourne, AU)
Daniel Griffith (University of Texas Dallas, US)
Jingxiong Zhang (Wuhan University, CN)
Nicolas Tate (University of Leicester, UK)

Program Committee
Ali Bennasr (University of Sfax , Tunisia)
Aluir P. Dal Poz (São Paulo State University, BR)
Amilcar Soares (Technical University of Lisbon, PT)
Amilton Amorim (São Paulo State University, BR)
Andréa de Seixas (Federal University of Pernambuco, BR)
Antonio M. G. Tommaselli (São Paulo State University, BR)
Artur Caldas Brandão (Federal University of Bahia, BR)
Carlos Loch (Federal University of Santa Catarina, BR)
Cidália Costa Fonte (University of Coimbra / INESC Coimbra, PT)
Cira Souza Pitombo (Federal University of Bahia, BR)
Curtis Woodcock (Boston University, USA)
Daniel Griffith (University of Texas at Dallas, USA)
Francisco J. Ariza López (Universidad de Jaén, ES)
Gerard Heuvelink (Wageningen University, NL)
Giles Foody (University of Nottingham, UK)
Graham Clarke (University of Leeds, UK)
Guanhua Xu (Chinese Academy of Sciences, CHN)
Gutemberg França (Federal University of Rio de Janeiro, BR)
Heriberto Gómez (University of Los Andes, Venezuela)
Irineu da Silva (São Carlos School of Engineering – USP, BR)
Ivana Ivánová (University of Twente/ITC, NL)
Jarbas Bonetti Filho (Federal University of Santa Catarina, BR)
Jasmee Jaafar (Universiti Teknologi MARA, Malaysia)
Jennifer Mary McKinley (Queen’s University Belfast, UK)
Jinfeng Wang (Chinese Academy of Sciences, CHN)
Jingxiong Zhang (Wuhan University, CHN)
Jose Alberto Quintanilha (Polythenic School–University of Sao Paulo, BR)
Juliana Fosse Moulin (Federal Rural University of Rio de Janeiro, BR)
Jurgën Wilhelm Philips (Federal University of Santa Catarina, BR)
Kim Lowell (University of Melbourne/CRC-SI, AU)
Leonardo Castro de Oliveira (Military Institute of Engineering, BR)
Linda Lilburne (Landcare Research, NZ)
Luciene Stamato Delazari (Federal University of Paraná, BR)
Lucy Bastin (Aston University, UK)
Luisa Maria da Silva Gonçalves (Polytechnic Institute of Leiria, PT)
Mahmoud R. Delavar (University of Tehran, IR)
Manfred M. Fischer (Vienna University of Economics and Business, AUT)
Maria Cecilia B. Brandalize (Federal University of Paraná, BR)
Mário Caetano (Portuguese Geographic Institute, PT)
Mauricio Galo (São Paulo State University, BR)
Michael Goodchild (University of California, USA)
Nicholas J. Tate (Leicester University, UK)
Nilton Nobuhiro Imai (São Paulo State University, BR)
Paul Aplin (University of Nottingham, UK)
Paulo R. L. Menezes (Federal University of Rio de Janeiro, BR)
Pavlos Kanaroglou (McMaster University, Canada)
Peter Atkinson (University of Southampton, UK)
Peter Fisher (University of Leicester, UK)
Ramanathan Sugumaran (University of Northern Iowa, USA)
Ricardo Seixas Brites (University of Brasília, BR)
Rodrigo Lilla Manzione (UNESP – São Paulo State University, BR)
Ronald McRoberts (USDA Forest Service, USA)
Russell G. Congalton (University of New Hampshire, USA)
Rosemy da Silva Nascimento (Federal University of Santa Catarina, BR)
Stewart Fotheringham (National University of Ireland, Ireland)
Tania Landes (Institut National des Sciences Appliquées – INSA, FR)
Taskin KAVZOGLU (Gebze Institute of Technology, Turkey)
Therese Steenberghen (K. U. Leuven, Belgium)
Vicente Paulo Soares (Federal University of Viçosa, BR)
Vitor Haertel (Federal University of Rio Grande do Sul, BR)
Yee Leung (Chinese University of Hong Kong, HK, CHN)
Yukio Sadahiro (University of Tokyo, Japan)

 

Table of Content

On the quality of eigenvector spatial filtering based parameter estimates for the normal probability model: implications about uncertainty and specification error for georeferenced data
Yongwan Chun and Daniel A. Griffith

Areal Sample Units for Accuracy Evaluation of Singledate and Multi-temporal Image Classifications
Kim Lowell, Alex Held , Tony Milne, Anthea Mitchell, Ian Tapley, Peter Caccetta, Eric Lehmann, Zheng-shu Zhou

Uncertainties assessment in orbital or airborne sensors absolute calibration
Cibele Teixeira Pinto, Flávio Jorge Ponzoni, Giovanni Araújo, Boggione, Leila Maria Garcia Fonseca, RuyMorgado de Castro

In-lab radiometric instruments calibration and uncertainties assessment
Cibele Teixeira Pinto, Flávio Jorge Ponzonni, Ruy Morgado de Castro

A reference surface uniformity and isotropy evaluation for orbital or airborne sensors absolute calibration
Cibele Teixeira Pinto, Flávio Jorge Ponzonni, Ruy Morgado de Castro

A new way of calculating the sub-pixel confusion matrix: a comparative evaluation using an artificial dataset
Stien Heremans and Jos Van Orshoven

Uncertainty analysis of a spatiotemporal model for submerged vegetation colonization
Ligia Flávia Antunes Batista, Nilton Nobuhiro Imai, Luiz Henrique da Silva Rotta, Fernanda Sayuri Yoshino Watanabe, Edivaldo Domingues Velini

Error characterization of burned area products
M. Padilla, I. Alonso-Canas, E. Chuvieco

The use of spatial-temporal analysis for noise reduction in MODIS NDVI time series data 
Julio Cesar de Oliveira, José Carlos Neves Epiphanio, Camilo Daleles Rennó

Snakes-based approach for extraction of building roof contours from digital aerial images
Aluir P. Dal Poz and Antonio J. Fazan

Conversion of Digital Numbers of the HSS Sensor TIR Images into Radiance: Uncertainty Evaluation
Leidiane L. Andrade, Ruy M. Castro, Lênio S. Galvão

Living with Collinearity in Local Regression Models
Chris Brunsdon, Martin Charlton, Paul Harris

Land cover and land use in Brazil and the Environmental-Economic Accounts System
Rodrigo de Campos Macedo, Maurício Zacharias Moreira, Eloisa Domingues, Ângela Maria Resende Couto Gama, Fábio Eduardo de Giusti Sanson, Felipe Wolk Teixeira, Fernando Peres Dias, Fernando Yutaka Yamaguchi, Luiz Roberto de Campos Jacintho

Influence of human uncertainty in the elaboration of fuzzy reference databases for the accuracy assessment of land cover maps
Pedro Sarmento, Cidália C. Fonte, Joel Dinis, Mário Caetano

Estimating uncertainty in deriving spatial distribution of blue ling landings from vessel monitoring system (VMS) data and implications for delineating marine protection boundaries to the northwest of the British Isles
P. Posen, P. Large and J. Lee

Reliability of watershed area estimation using Digital Elevation Models
Fabiano Costa de Almeida, Márlon Crislei da Silva, Camilo Daleles Rennó, Márcio Bomfim Pereira Pinto, Agustin Justo Trigo and Marcis Gualberto Mendonça Júnior

Kriging and cokriging for spatial interpolation of rainfall in Espirito Santo State, Brazil
Alexson de Mello Cunha, Gerson Rodrigues dos Santos, Eliana de Souza, Filipe Silveira Trindade, Elpídio Inácio Fernandes Filho, João Luiz Lani, Michelle Milanez França

Accuracy of forest stand volume estimation by Landsat TM imagery with different geometric and atmospheric correction methods
Elias Fernando Berra, Denise Cybis Fontana, Rudiney Soares Pereira

On the use of synthetic images for change detection accuracy assessment
Hélio Radke Bittencourt, Daniel Capella Zanotta, Thiago Bazzan

Using of local indicators of spatial association for evaluation of spatial accuracy of DEM
Jana Svobodova, JakubMirijovsky, Ales Vavra, Jan Brus, Helena Kilianova

Geospatial Data Quality Indicators
Victoria Lush, Lucy Bastin, Jo Lumsden

The effects of training set size for performance of support vector machines and decision trees
Taskin Kavzoglu, Ismail Colkesen

An Assessment of the Effectiveness of Segmentation Methods on Classification Performance
Merve Yildiz, Taskin Kavzoglu, Ismail Colkesen, Emrehan K. Sahin

Study of the positional quality obtained by the method Precise Point Positioning, PPP, for use in georeferencing of rural properties
Michel Balin de Brum , Adriane Brill Thum

Assessment of geodetic coordinates processed using different baselines
Elmo Leonardo Xavier Tanajura, Rodrigo Mikosz Gonçalvez, Admilson da Penha Pacheco, Cláudia Pereira Krueger

On the interpolation algorithm ranking
Carlos López-Vázquez

Land Cover Change Analysis from Remote Sensing Images and Statistical data: Case Study Itaipú region, Border Paraguay/Brazil
Mauro Alixandrini and Hans-Peter Bähr

Spatial variability of the common bean Pratylenchus brachyurus
R. Noetzold, M.C. Alves, D. Cassetari-Neto, A.P. Pires

Assessment of SVM classification process for landslides identification
Luiz Augusto Manfré, Eduardo Jun Shinohara , Janaína Bezerra Silva, Raquel Nogueira Del Pintor Siqueira and José Alberto Quintanilha

Positional accuracy of Curitiba’s digital orthophoto map
Hamilton Carlos Vendrame Junior, Maria Cecilia Bonato Brandalize

Improving the relationship between reference frames by using the Thin-Plate Spline modeling
João Paulo Magna Júnior, Paulo de Oliveira Camargo, Maurício Galo

Comparison between Google Earth kml data and RTK data on a flight planning simulated to the Unmanned Aerial Vehicle Microdrone MD4-1000 
Antoninho João Pegoraro, Marcelo Costa Napoleão, Jürgen Wilhelm Philips

The Positional and Thematic Accuracy for Analysis of Multi-Temporal Satellite Images on Mangrove Areas
Paulo Rodrigo Zanin and Carlos Antonio O. Vieira

Comparison of two summer crop mapping methods in the state of Paraná in 2008
Daniel Garbellini Duft; Jerry Adriani Johann; Jansle Vieira Rocha; Rubens Augusto Camargo Lamparelli

Exploring the potential role of volunteer citizen sensors in land cover map accuracy assessment
Giles M. Foody and Doreen S. Boyd

Spatial data quality of herbarium datasets and implications for decision-making on biodiversity conservation in Brazil
Barros, F.S., Fernandes, R.A., Moraes, M.A., Pougy, N.M. , Caram, J.S. , Dalcin, E.C., Martinelli, G

Exploring Effectiveness of Uncertainty Visualization Methods by Eye-Tracking 
Jan Brus, Stanislav Popelka, Alzbeta Brychtova, and Jana Svobodova

Geographically weighted methods for examining the spatial variation in land cover accuracy
Alexis Comber, Peter Fisher, Chris Brunsdon, Abdulhakim Khmag

Larger geologic complexity implies larger uncertainty
Alessandro Samuel-Rosa, Ricardo Simão Diniz Dalmolin and Pablo Miguel

10-C Approach for Quality Assesment and Accuracy of Geospatial Information in Indonesia
Dr.-Ing Fahmi Amhar Vectorial analysis modeling to determine spatial uncertainty among different data production scales due to error propagation

Cárdenas A., Treviño E.J., Aguirre O.A., Jiménez J., González M.A., Antonio X., Sánchez G

Evaluation of hydrological consistency of DEMs derived from SRTM and ASTER2 in three levels of interpolation
Guilherme de Castro Oliveira, Maola Monique Faria, Elpídio Inácio Fernandes Filho

Expert elicitation for the variogram
Phuong N. Truong, Gerard B. M. Heuvelink, John Paul Gosling

Change Detection Analysis in Multitemporal Satellite Image Series
José Guilherme Fronza and Carlos Antônio Oliveira Vieira

Comparison between accuracy measures of images classified by Maximum likelihood and Artificial Neural Networks

Kamilla A. Oliveira, Antonio Nuno S. Rosa, Reginaldo S. Pereira, Paulo C. Emiliano, Gloria S. Almeida, Fabiano Emmert

Effect of control points distribution on the orthorectification accuracy of an Ikonos II image through rational polynomial functions

Marcela do Valle Machado, Mauro Homem Antunes, Paula Debiasi

Geostatistical assessment of the spatial variability of soil texture in the coffee plantation

Marcelly da Silva Sampaio, Marcelo de Carvalho Alves, Fábio Moreira da Silva, Edson Ampélio Pozza, Marcelo Silva de Oliveira, Luciana Sanches Canasat

Project accuracy assessment of sugarcane thematic maps
Marcio Pupin Mello, Marcos Adami, Bernardo F.T.Rudorff, Daniel Alves Aguiar

Visibility analysis and DEM uncertainty propagation
María Victoria Alvarez

Random field modelling of DEM uncertainty and its impact on terrain referenced navigation
Guy Ruckebusch

Using Spatial Uncertainties to Create Probability Maps for Continuous Attributes
Carlos Alberto Felgueiras, Eduardo Celso Gerbi Camargo, Jussara de Oliveira Ortiz, Sérgio Rosim

Site-specific Prediction of Mosquito Abundance using Spatio-Temporal Geostatistics
E.-H. Yoo, D. Chen and C. Russell

A Wanted Traffic
Jorge Xavier da Silva and Tiago Badre Marino

Estimation of DEM Uncertainty Using Clustering Analysis  
Laercio M. Namikawa

Generated by a Stereo pair of Images Ikonos
Sinara Fernandes Parreira, Mariane Alves Dal Santo, Pedro Henrique Machado Porath

Accounting for spatial and temporal uncertainties in spatio-temporal disaggregation of emission predictions using ATP simulation
Ulrich Leopold, Gerarad B.M. Hevelink, Daniel S. Zachary

Detection and Reduction of the Collinearity Effect for Improving Spectral Unmixing Accuracy
Xiuping Jia, Xiaofeng Li, Freek D. Van der Meer

Space-Time Universal Kriging of Precipitation in The Euphrates Basin, Turkey
P.A. Bostan, S.Z. Akyurek, G.B.M. Heuvelink

Network Accuracy: the impact of the 3D distances on location-allocation
Emeka Chukwusa, Alexis Comber and Chris Brunsdon  

Assessing yearly transition probability matrix for land use / land cover dynamics
Jean-François Mas, Ernesto Veja  

Changing the TIGER's stripes: detecting road network change under positional uncertainty 
Ashton Shortridge and Miaoying Shi  

Uncertainty in User-contributed Weather Data
Simon Bell, Dan Cornford, Lucy Bastin, and Mike Molyneux   

DEMHC generation from IBGE topographic maps using ArcGis software
Gabriela Vieira Capobiango, Demetrius David da Silva, Hugo Alexandre Soares Guedes, Barbara Batista Porto

Inaccuracies on morphometric characterization of watersheds on GIS ambient
Vitor Souza Martins; Demetrius David Da Silva; Hugo Alexandre Soares Guedes; Bárbara Batista Porto

An optimal control method for high accuracy surface modeling and its application to DTM construction
Tian-Xiang Yue, Dun-Jiang Song and Zheng-Ping Du

Some expectation-maximization (EM) algorithm simplifications for spatial data
Daniel A. Griffith  

Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
Rodrigo Lilla Manzione, Edson Wendland

A Note on the Uncertainty Analysis of Space-Time Prisms based on the Moment-Design Method
Yee Leung, Zi Zhao and Jiang-Hong Ma

10-C Approach for Quality Assesment and Accuracy of Geospatial Information in Indonesia

10-C Approach for Quality Assesment and Accuracy of Geospatial Information in Indonesia
Dr.-Ing Fahmi Amhar

Geospatial Information Agency, Jl. Jakarta-Bogor km. 46 Cibinong-Indonesia (famhar@yahoocom)

Abstract: This paper discuss about the accuracy and quality of geospatial information in Indonesia comprehensively. The 10C-approach is proven effectively during last 10 years, when this method is introduced for first time. The 10C-approach consisted of 7C-technical aspects and 3C-non-technical aspect. The 7C are Coverage, Completeness, Consistency, Correctness, Currentness, Creativity-level and Communicative; while the 3C are Cost-effective, Conform-to-the-law and Contextual. The Accuracy as Correctness will be diviede in Object, Sensor, Ackquisition, Process, and Visualization-Accuracy.

Keywords: accuracy, quality assesment, geospatial information, 10C-approach.

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A Note on the Uncertainty Analysis of Space-Time Prisms based on the Moment-Design Method

A Note on the Uncertainty Analysis of Space-Time Prisms based on the Moment-Design Method
Yee Leung1, Zi Zhao2 and Jiang-Hong Ma2

1.Department of Geography and Resource Management, Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, P. R. China (yeeleung@cuhk.edu.hk)
2.Department of Mathematics and Information Science, Chang’an University, Xi’an, P. R. China (jhma@chd.edu.cn)

Abstract: Space-time prism (STP) is a key concept in geography that measures the movement of objects in space and time. A space-time prism can be treated as a result of the potential path line revolving around in the three dimensional space. Though the concept has found applications in time geography, research on the analysis of uncertainty in space-time prism, particularly under high degree of nonlinearity, is scanty. Based on the moment-design (M-D) method, this paper proposes an approach to deal with nonlinear error propagation problems on the potential path areas and their intersections. In comparison with the Monte Carlo method and the implicit function method, simulation results show the advantages of the M-D method for the analysis of error propagation in space-time prisms.

Keywords: error propagation, space-time prism, spatial path area, moment design.

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LeungAccuracy2012.pdf142.34 KB

A Wanted Traffic

A Wanted Traffic
Jorge Xavier da Silva1, Tiago Badre Marino2

1.Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 274 - Bloco I-001 - Cidade Universitária - Rio de Janeiro - RJ – Brasil (xavier.lageop@gmail.com)
2.Universidade Federal Rural do Rio de Janeiro, Instituto de Agronomia - Departamento de Geociências BR-465, Km 7 - Seropédica - Rio de Janeiro – Brasil (tiagomarino@ufrrj.br)

Abstract: Attention is called for the need and use of conceptual/methodological guiding structures for environmental data acquisition, so that conclusive error prone results of costly application of techniques have smaller chances of occurrence. Geoprocessing, understood as a research field dedicated to change environmental data, i.e. simple registers of occurrences, into information, i.e. meaningful gain of knowledge about the environment, is pointed as having a role in the building of the above mentioned theoretical guiding structures.

Keywords: Geoprocessing, Geoinclusion, Geodiversity, Entity, Event, Vigilance, Control.

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SilvaAccuracy2012.pdf82.5 KB

A new way of calculating the sub-pixel confusion matrix: a comparative evaluation using an artificial dataset

A new way of calculating the sub-pixel confusion matrix: a comparative evaluation using an artificial dataset

Stien Heremans and Jos Van Orshoven

KU Leuven, Department of Earth and Environmental Sciences Celestijnenlaan 200E, 3000 Leuven (Belgium) (stien.heremans@ees.kuleuven.be)

Abstract: This paper introduces a new, alternative method for calculating the sub-pixel confusion matrix. It calculates the off-diagonal matrix elements from the slope coefficients of the regression relations between the overestimations and the underestimations of the area fractions. The new method is set against existing approaches for calculating the sub-pixel confusion matrix through the use of an artificial dataset. The results show that it is able to compete with the existing approaches and in some cases even outperforms the latter.

Keywords: sub-pixel classification, confusion matrix, off-diagonal elements

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HeremansAccuracy2012.pdf77.25 KB

A reference surface uniformity and isotropy evaluation for orbital or airborne sensors absolute calibration

A reference surface uniformity and isotropy evaluation for orbital or airborne sensors absolute calibration
Cibele Teixeira Pinto1,2, Flávio Jorge Ponzonni1 and Ruy Morgado de Castro2,3

1.Instituto Nacional de Pesquisas Espaciais – INPE, Caixa Postal 515 - 12227-010 - São José dos Campos - SP, Brasil (cibele@dsr.inpe.br, flavio@dsr.inpe.br)
2.Instituto de Estudos Avançados - IEAv/CTA, Caixa Postal 6044 - 12.231-970 - São José dos Campos - SP, Brasil (cibele@ieav.cta.br, rmcastro@ieav.cta.br)
3.Universidade de Taubaté – UNITAU, Caixa Postal 515 - 12201-970 - Taubaté - SP, Brasil (rmcastro@unitau.br)

Abstract:The aim of this work is to present the methodology used to evaluate two features of a surface potentially considered as a reference in imaging sensors absolute calibration missions: uniformity radiometric and isotropy. Addition this work also estimates the main sources of uncertainties associated with radiometric measurement process.

Keywords: calibration, reference surfaces, uniformity, isotropy, uncertainties

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Pinto3Accuracy2012.pdf76.68 KB

Accuracy of forest stand volume estimation by Landsat TM imagery with different geometric and atmospheric correction methods

Accuracy of forest stand volume estimation by Landsat TM imagery with different geometric and atmospheric correction methods
Elias Fernando Berra1, Denise Cybis Fontana2 and Rudiney Soares Pereira3

1. Engenheiro Florestal, Mestrando PPG Sensoriamento Remoto, UFRGS, Av. Bento Gonçalvez, 9500, Porto Alegre, RS, Brazil. (eliasberra@yahoo.com.br)
2. Engenheira Agrônoma, Profa Dra, Fac. de Agronomia da UFRGS. Av Bento Gonçalves, 7712, Porto Alegre, RS, Brasil. Bolsista CNPq. (dfontana@ufrgs.br)
3. Engenheiro Florestal, Profº Dr, Departamento de Engenharia Rural da UFSM, Av. Roraima, 1000, Santa Maria, RS, Brasil. (rudiney.s.pereira@gmail.com)

Abstract: Stem volume of Pinus elliottii were estimated from Landsat TM data with different methods of geometric and atmospheric correction. Regressions were used to estimate the stem volume (m³/ha), where the independent variable was the value of NDVI (Normalized Difference Vegetation Index) related to the sampling unit measured in the field. The reflectance used in the NDVI calculation were obtained by four different methods: 1) geometric correction with nearest-neighbor (NN) resampling + atmospheric correction using dark object subtraction (DOS), 2) NN resampling + atmospheric correction using MODTRAN (Moderate Resolution Transmittance), 3) geometric correction with bilinear resampling + DOS, and 4) bilinear resampling + MODTRAN. The reliability of the estimates was measured by means of bias (Bias) and standard error (RMSE). Among the atmospheric correction methods, the errors were higher with DOS. Regarding the geometric correction methods, the RMSE and Bias were higher with the NN resampling. Thus, the combination of DOS + NN had the highest RMSE (62.3%) and Bias (15.9%). The best estimate was the combination of bilinear resampling + MODTRAN, with RMSE of 56.5% and Bias of 13.3%. Therefore, it was verified that different methods of geometric and atmospheric correction should be tested to improve the estimates.

Keywords: Stem volume, geometric correction, atmospheric correction, pixel level

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BerraAccuracy2012.pdf72.07 KB

An Assessment of the Effectiveness of Segmentation Methods on Classification Performance

An Assessment of the Effectiveness of Segmentation Methods on Classification Performance
Merve Yildiz, Taskin Kavzoglu, Ismail Colkesen, Emrehan K. Sahin Gebze

Institute of Technology, Department of Geodetic and Photogrammetric Engineering, Cayirova Campus, 41400, Gebze-KOCAELI, TURKEY (m.yildiz, kavzoglu, e.sahin, icolkesen@gyte.edu.tr)

Abstract: Object-based classification approaches have been recently employed successfully in many research studies. These approaches aim to create segments on the image considering spectral similarity of the neighboring pixels, which is known as image segmentation. Segmentation methods use spectral information as well as textural and semantic information of the pixels. It is a fact that parameter setting of segmentation methods is of considerable importance in producing accurate classification results. Therefore, determining optimum values for the parameters is regarded as a critical stage in segmentation processes. In this study, effectiveness and applicability of the segmentation approach was analyzed utilizing a high resolution Quickbird satellite image. Multi-resolution segmentation technique, which has been reported to be a robust method, was employed with its optimal parameters for scale, shape and compactness that were defined after an extensive trail process on the data set. Resulting image object was then used in supervised classification using the nearest neighbor algorithm with fuzzy membership functions. Classification performances produced for different parameter settings were thoroughly analyzed and it was found that parameter setting in segmentation applications produced highly varied classification accuracies. It was also observed that segmentation algorithms could help to improve spectral discrimination, particularly for spectrally similar classes.

Keywords: Segmentation, object-based classification, nearest neighbor, accuracy assessment.

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YildizAccuracy2012.pdf268.05 KB

An optimal control method for high accuracy surface modeling and its application to DTM construction

An optimal control method for high accuracy surface modeling and its application to DTM construction
Tian-Xiang Yue1, Dun-Jiang Song2 and Zheng-Ping Du1

1.State Key Laboratory of Resources and Environment Information System, Institute of Geographical Sciences and Natural Resources Research, 11A, Datun Road, Anwai, 100101 Beijing, China (Yue@lreis.ac.cn)
2.Institute of Policy and Management, No.15 Zhongguancun Bei Yi Tiao, 100190 Beijing, China (songdj@casipm.ac.cn)

Abstract: An optimal control method of high accuracy surface modelling (HASM-OC) is developed to improve DTM as accurate as possible in this paper. One numerical test is conducted to validate HASM-OC by comparing with Thin Plate Spline (TPS). Datasets with various contour intervals are selected to simulate DTMs in different spatial resolutions. Then, retrieved contour lines, respectively by HASM-OC and TPS, are compared with the original ones. The results indicate that the contour lines retrieved by HASM-OC almost coincide with the original contour lines in appropriate spatial resolutions while the ones done by TPS have a considerable difference from the original ones. The difference between the retrieved contour lines by HASM-OC and the original ones is less than 6.5% of grid size. Errors of contour lines retrieved by HASM-OC monotonically decease with spatial resolution becoming finer but TPS presents oscillating errors. HASM-OC has much higher accuracy and performs much more stable. 

Keywords: HASM, TPS, optimal control, DTM, accuracy, error

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YueAccuracy2012.pdf102.51 KB

Areal Sample Units for Accuracy Evaluation of Single-date and Multi-temporal Image Classifications

Areal Sample Units for Accuracy Evaluation of Single-date and Multi-temporal Image Classifications

Kim Lowell1, Alex Held2 , Tony Milne3, Anthea Mitchell3, Ian Tapley3, Peter Caccetta4, Eric Lehmann4, Zheng-shu Zhou4

1. Cooperative Research Centre for Spatial Information, Dept. of Infrastructure Engineering, University of Melbourne, Carlton, VIC 3053 AUSTRALIA (klowell@crcsi.com.au)
2. CSIRO Canberra, ACT 2601 (alex.held@csiro.au)
3. Cooperative Research Centre for Spatial Information, School of Biological, Earth, and Environmental Sciences, The University of New South Wales, Kensington, NSW 2052 ( t.milne@unsw.edu.au, a.mitchell@unsw.edu.au, hgciant@bigpond.net.au)
4. CSIRO Mathematics, Informatics & Statistics, Floreat, WA 6014 (peter.caccetta@csiro.au, eric.lehmann@csiro.au, zheng-shu.zhou@csiro.au)
 

Abstract: Areal sample units are explored as an alternative to conventional point-based samples for map accuracy assessment. Three analyses are examined: confidence limits on estimates of the total amount of each landcover, regression of map data versus reference data, and a two-part confusion matrix approach. It is concluded that areal sample units provide some advantages compared to point-based samples, but are nonetheless subject to problems associated with providing robust accuracy assessment metrics for rare classes.

Keywords: landcover change, rare event sampling, regression, modified confusion matrix

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LowellAccuracy2012.pdf395.71 KB

Assessing yearly transition probability matrix for land use / land cover dynamics

Assessing yearly transition probability matrix for land use / land cover dynamics
Jean-François Mas 1, Ernesto Vega 2 1

1.Universidad Nacional Autónoma de México (UNAM), Centro de Investigaciones en Geografía Ambiental (jfmas@ciga.unam.mx)
2.Universidad Nacional Autónoma de México (UNAM), Centro de Investigaciones en Ecosistemas (evega@oikos.unam.mx)

Abstract: In order to generate land cover projections and model land use and cover changes (LUCC), probability-based transition matrices are obtained through the overlaying of two maps of two different dates. However, the observation interval may differ because maps are not available every year or at a constant time interval and a matricial algorithm is commonly used to adjust the matrix. However, although the obtained yearly matrix is mathematically correct, it does not necessary represent adequately the yearly transitions due to the spatial coincidence of various transitions over the entire period of time and because some transitions that are observed over a large period are not possible over a shorter (e.g. yearly) period. In this paper, a novel approach, based on a genetic algorithm (GA), is applied to adjust yearly transition matrices taking into account criteria to produce more realistic transitions. A LUCC model was used to produce land cover maps at different dates using transition rules defined by the user. Yearly matrices were then obtained from these maps by both matricial and genetic algorithms and were compared. For certain periods of time, the matricial algorithm was unable to find a yearly matrix or found a matrix with impossible transitions. The GA approach was able to find realistic matrices from all the periods.

Keywords: Markov matrix, modelling, land cover change.

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MasAccuracy2012.pdf79.93 KB

Assessment of SVM classification process for landslides identification

Assessment of SVM classification process for landslides identification
Luiz Augusto Manfré1, Eduardo Jun Shinohara , Janaína Bezerra Silva, Raquel Nogueira Del Pintor Siqueira and José Alberto Quintanilha

GIS Lab - EPUSP, Av. Prof. Almeida Prado, Travessa 2, n° 83, Cidade Universitária – São Paulo – SP, CEP: 05508-900 (luizmanfre@usp.br, edjun@usp.br, janas@usp.br, raquelsiq@gmail.com, jaquinta@usp.br)

Abstract: The Support Vector Machines (SVM) algorithm has been used for landcover classifications. The theoretical assumption of SVM indicates that the quality of the results increases with the use of more bands. This paper aimed to evaluate the accuracy of SVM algorithm applied over several bands compositions for the identification of landslides at Sao Paulo State Coast. LANDSAT images for the year 2000 were used. To minimize the effect of the shadows, the Normalized Difference Vegetation Index (NDVI) enhancement was calculated. We applied the SVM to the NDVI enhancement and to the following compositions: bands 1, 2; 3, 4; 1, 2, 3; and 1, 2, 3, 4. The NDVI based classification presented the highest Overall Accuracy and the Kappa Index. A huge difference in the Debris Flow areas was found, except NDVI based classification, all other overestimated this class. The NDVI presents the smallest percent of commission errors, and the best results for user accuracy. Therefore, depending on the natural conditions of the area, there are factors that are more important for the classification process with the SVM algorithm. The use of enhancements may facilitate the classification process and also produce better results than the use of a many of bands.

Keywords: Classification Assessment, Omission and Comission Errors, User Accuracy, Landslides Mapping.

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manfreAccuracy2012.pdf87.71 KB

Assessment of geodetic coordinates processed using different baselines

Assessment of geodetic coordinates processed using different baselines
Elmo Leonardo Xavier Tanajura1, Rodrigo Mikosz Gonçalvez2, Admilson da Penha Pacheco3, Cláudia Pereira Krueger4

1.Center of Technological and Exacts Sciences, Federal University of Acre (UFAC), Rio Branco, AC, Brazil (elmo@ufac.br, elmotanajura@yahoo.com.br)
2,3.Department of Cartography Engineering, Federal University of Pernambuco (UFPE), Geodetic Science and Technology of Geoinformation Post Graduation Program, Recife, PE, Brazil. (rodrigo.mikosz@ufpe.br, admilpp@ufpe.br)
4.Geodetic Science Post Graduation Program, Federal University of Parana (UFPR); Curitiba, PR, Brazil (ckrueger@ufpr.br)

Abstract: The relative kinematic methods of GNSS positioning are characterized by the movement of a rover station, tracking simultaneously at least one fixed base station, for trajectory coordinate solution. The purpose of this work is to evaluate the accuracy of geodetic coordinates from kinematic surveying, processed using different baselines. The relative kinematic surveying was made with a GPS receiver along a sand spur located in Ilha do Mel in Paraná State, Brazil. Use was made of 4 base stations for data processing, where 3 stations belonged to the Brazilian network called Rede Brasileira de Monitoramento Contínuo (RBMC): NEIA; UFPR, and IMBT. A fourth station called CASA was a static base station near the survey. After data processing, these stations generated baselines with lengths averaging around 0.7km, 70km, 90km and 300km for vectors generated by CASA, NEIA, UFPR and IMBT, respectively. The vectors were classified according to the ambiguities solution. The survey precision limit was fixed to 0.1m + 1 ppm for horizontal and vertical coordinates. The tridimensional standard deviations in meters obtained in processing were 0.044; 0.321; 2.522; 7.00. The deviations values obtained, represent the degradation of generated coordinates, where their values increase depending on the increase of baseline.

Keywords: GNSS, geodetic coordinates, baseline processing, coastal application

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TanajuraAccuracy2012.pdf642.96 KB

Canasat Project accuracy assessment of sugarcane thematic maps

Canasat Project accuracy assessment of sugarcane thematic maps
Marcio Pupin Mello, Marcos Adami, Bernardo F. T. Rudorff and Daniel Alves Aguiar

National Institute for Space Research (INPE), Remote Sensing Division (DSR) Av. dos Astronautas, 1758 – Jd. Granja – São José dos Campos – SP, 12227-010, Brazil (mello@ieee.org, adami@dsr.inpe.br, bernardo@dsr.inpe.br, daniel@dsr.inpe.br)

Abstract: In order to perform the thematic accuracy assessment of Canasat Project mapping, we used a novel approach to construct the reference dataset which consists of a web platform used to integrate remote sensing images, time series, and ancillary data. Results showed that, although Canasat Project mapping of sugarcane areas has a mean overall accuracy of 98%, the mean thematic error associated with sugarcane area estimates was of –0.7%, since part of the omission errors was compensated by the inclusion errors. Despite assessing only one crop year (2010/2011) we would also expect to obtain very similar results for other crop years due to the consistent method and the careful visual interpretation carried out by the Canasat Project experienced team.

Keywords: Remote sensing, web platform, sampling, Monte Carlo method.

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MelloAccuracy2012.pdf263.25 KB

Change Detection Analysis in Multitemporal Satellite Image Series

Change Detection Analysis in Multitemporal Satellite Image Series
José Guilherme Fronza and Carlos Antônio Oliveira Vieira

Federal University of Santa Catarina – UFSC - Campus Universitário Trindade – CEP 88040-900 – Florianópolis, Santa Catarina. Phone: ++55 48 3721-8593 (guilherme.fronza@gmail.com, carlos.vieira@cfh.ufsc.br)

Abstract: The present work aims to perform ratio and difference techniques to detect changes in Nova Friburgo, Rio de Janeiro – Brazil caused by landslides. Using Landsat-5 images obtained before and after the landslides in January 2011 that was possible. These techniques allow identifying abrupt change on spectral response in remotely sensed images. There are many factors influencing the success of applying change detection techniques, among them, one could mention: atmospheric condition, sensors calibration procedures, water content in soil, differences in sun angle at the image obtaining. Neighborhoods and forested areas were destroyed causing major problems to citizens and slopes subject to new landslides. Given a set of spectral bands, it is difficult to define a good threshold for histogram and the best bands in order to use change detection analysis. The better result was obtained by using the band TM7 and TM5 (infrared) with difference between images technique. Kappa was set in 0,9255 and 0,9243, respectively to detect changed areas in landscape. Noise in result was frequently and its minimization was essential. To image ratio technique was obtained good results (TM3 with 0,8582 Kappa) but with great difficulties to define a good threshold cut-off in image histogram.

Keywords: Change Detection, feature selection, remote sensing, landslides.

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FronzaAccuracy2012.pdf198.08 KB

Change Detection Analysis in Multitemporal Satellite Image Series

Change Detection Analysis in Multitemporal Satellite Image Series
José Guilherme Fronza and Carlos Antônio Oliveira Vieira

Federal University of Santa Catarina – UFSC - Campus Universitário Trindade – CEP 88040-900 – Florianópolis, Santa Catarina. Phone: ++55 48 3721-8593 (guilherme.fronza@gmail.com, carlos.vieira@cfh.ufsc.br)

Abstract: The present work aims to perform ratio and difference techniques to detect changes in Nova Friburgo, Rio de Janeiro – Brazil caused by landslides. Using Landsat-5 images obtained before and after the landslides in January 2011 that was possible. These techniques allow identifying abrupt change on spectral response in remotely sensed images. There are many factors influencing the success of applying change detection techniques, among them, one could mention: atmospheric condition, sensors calibration procedures, water content in soil, differences in sun angle at the image obtaining. Neighborhoods and forested areas were destroyed causing major problems to citizens and slopes subject to new landslides. Given a set of spectral bands, it is difficult to define a good threshold for histogram and the best bands in order to use change detection analysis. The better result was obtained by using the band TM7 and TM5 (infrared) with difference between images technique. Kappa was set in 0,9255 and 0,9243, respectively to detect changed areas in landscape. Noise in result was frequently and its minimization was essential. To image ratio technique was obtained good results (TM3 with 0,8582 Kappa) but with great difficulties to define a good threshold cut-off in image histogram.

Keywords: Change Detection, feature selection, remote sensing, landslides.

Changing the TIGER's stripes: detecting road network change under positional uncertainty

Changing the TIGER's stripes: detecting road network change under positional uncertainty
Ashton Shortridge1 and Miaoying Shi2

1.Department of Geography, Michigan State University, USA 48824 (ashton@msu.edu)
2.Department of Forestry, Michigan State University, USA 48824 (miaoyingshi23@gmail.com)

Abstract: Many sets of linear features (e.g., streets in a city) can change over time, and the identification of these changes is an important geoprocessing challenge. This challenge is exacerbated by the often low accuracy of historic network datasets: positional discrepancies between features at different times may reflect actual change, or they may simply be the product of error. While there is a substantial body of work on modeling positional uncertainty in linear features, these contributions do not appear to have been widely integrated with feature change detection algorithms. In the present work, we address this research gap by developing several uncertainty modeling approaches for use in detecting significant network change. The following paragraphs review relevant approaches to characterizing positional uncertainty and then present a typology of network data mismatch. We then describe a geostatistical approach to model this uncertainty, and contrast it with conventional epsilon band technique to identify significant change. The approach is demonstrated in a case study with US Census TIGER line data

Keywords: positional error, vector uncertainty, kriging, epsilon bands

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ShortridgeAccuracy2012.pdf457.45 KB

Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series

Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
Rodrigo Lilla Manzione1, Edson Wendland2

1 .UNESP/Campus of Ourinhos, Av. Vitalina Marcusso 1500 CEP: 19910-206 Ourinhos (SP) Brazil (manzione@ourinhos.unesp.br)
2 .USP/EESC/SHS, Av. Trabalhador Sãocarlence 400 CEP: 13560-970 São Carlos (SP) Brazil (ew@sc.usp.br)

Abstract: Time series modeling provides an empirical stochastic method to model monitoring data from observation wells, without the complexity of physical mechanistic models. In the same direction, geostatiscal methods are used to make probabilistic statements about quantities of interest at non-measured locations. The aim of this work was to present water-table levels scenarios results of a combination of time series modeling and geostatistics to predict and discuss the communication via probability maps. The study case was held in a watershed located in an outcrop of the Guarani Aquifer System (GAS). The Onça Creek watershed has a monitoring scheme with 23 wells spatially distributed over the area. The water heads are measured with a semi-monthly frequency. First, the time series are inspected and modeled with a special type of Transfer-function noise model, the so called PIRFICT-model and then the model outputs are interpolated spatially using geostatistics. How communicate this results is discussed via the resulted maps that contain probabilistic measures about model uncertainty. Understand uncertainty and communicate it to practitioners, decision makers and stakeholders in a clear and simple form is a key element for efficient water resources planning.

Keywords: time series, geostatistics, groundwater, land use planning

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ManzioneAccuracy2012.pdf136.39 KB

Comparative Analysis of Ellipsoidal Elevation Surveyed by GNSS System, SRTM and ASTER GDEM

COMPARATIVE ANALYSIS OF ELLIPSOIDAL ELEVATION SURVEYED BY GNSS SYSTEM, SRTM AND ASTER GDEM
R. Noetzold1,2, M.C. Alves1,3, J.A.F. Sobrinho1, R.A. Gallon, M.J.P.A. Oliveira1, H.H.T. Borges1,R.T. Silva1

1.Federal University of Mato Grosso, Cuiabá – MT
2 Capes Support
3 CNPq Support
(rafael_noetzold@hotmail.com, marcelocarvalhoalves@gmail.com, jeziel.andre@hotmail.com, ragallon@yahoo.com.br, maicon.oliveira53@gmail.com,hhans_borges@hotmail.com, rayzatrindde@rocketmail.com)

Abstract: The aim of this study was to compare the ellipsoidal height using the GNSS system, SRTM images and Aster GDEM images. The survey was conducted on the campus of Federal University of Mato Grosso, Cuiabá - MT. The static surveying was performed in 27 neighboring points, where a Global Navigation Satellite Systems (GNSS) receiver was installed as a base. Subsequently, we performed the real time kinematic survey supported on adjusted basis to obtain the correct elevation data of 3883 points. Then, the data base were processed and corrected by the Precise Point Positioning Method. The elevation data from SRTM and Aster GDEM models, extracted by the nearest neighbor technique were used for comparation. Subsequently we compared the GNSS data with the data extracted from the images, SRTM and ASTER, by linear regression, and we performed the calculation of Root Mean Square Error (RMSE). The results showed: R² of 0,84 between Aster GDEM and GNSS; 0,86 between GNSS and SRTM and 0,83 between Aster GDEM and SRTM . A similar result was obtained by RMSE, where the biggest error occurred in the comparison between Aster GDEM and SRTM data.

Keywords:Digital elevation model, Accuracy, Global navigation satellite survey.

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NoetzoldAccuracy2012.pdf276.5 KB

Comparison between Google Earth kml data and RTK data on a flight planning simulated to the Unmanned Aerial Vehicle Microdrone MD4-1000

Comparison between Google Earth kml data and RTK data on a flight planning simulated to the Unmanned Aerial Vehicle Microdrone MD4-1000
Antoninho João Pegoraro1, Marcelo Costa Napoleão2, Jürgen Wilhelm Philips3

1.University of Santa Catarina - Campus Universitário Reitor João David Ferreira Lima,Trindade - Florianópolis - Santa Catarina – Brasil (ajpegoraro@gmail.com)
2. University of Santa Catarina, University of Santa Catarina - Campus Universitário Reitor João David Ferreira Lima,Trindade - Florianópolis - Santa Catarina – Brasil (marcnapol@gmail.com)
3. University of Santa Catarina, University of Santa Catarina - Campus Universitário Reitor João David Ferreira Lima,Trindade - Florianópolis - Santa Catarina – Brasil (juergen.philips@gmail.com)

Abstract: The unmanned aerial vehicles (UAVs) and the use of graphical data files, of extension kml, have become popular nowadays. The kml files are associated to the Google Earth applications. Developed by Microdrone company for planning, overflight simulation and data flight analysis, the program mdCockpit was used in this experiment. The UAV Microdrone’s flight path was programmed in two ways: using georeferenced images from Google Earth and entering points coordinates into the program. These points have had their geographical decimal coordinates collected by GPS (RTK) method. The aim here is to describe a way of evaluating the difference between the alternatives of flight planning. A flight path, defined a route with 22 points, was also simulated in the program mdCockpit. The points were collected and saved, while the images captured by the program went automatically forming a georeferenced mosaic. A comparison between the difference of coordinates to each point was made by choosing on the images and also by a RTK positioning. The result was up to 14.20 m to a 100 meters flight height. There is a significant change of position and this can result in unwanted over flights in locations or even jeopardizing the safety of air activity.

Keywords: simulation flight path, md4-1000, kml data, RTK data

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PegoraroAccuracy2012.pdf200.63 KB

Comparison between accuracy measures of images classified by Maximum likelihood and Artificial Neural Networks

Comparison between accuracy measures of images classified by Maximum likelihood and Artificial Neural Networks
Kamilla A. Oliveira1, Antonio Nuno S. Rosa1,2, Reginaldo S. Pereira1,3, Paulo C. Emiliano4, Gloria S. Almeida1,6 and Fabiano Emmert1,6

1.Universidade de Brasília, Campus Universitário Darcy Ribeiro, CEP 70910-900 , Brasília (kamillarbr@gmail.com1,nuno@unb.br1,2, reginaldosp@gmail.com1,3, gloriaf@gmail.com1,6, fabianoemmert@yahoo.com.br1,7)
4.UniversidadeFederal de Lavras, Campus Universitário, Caixa Postal 3037, CEP 37200-000 Lavras – MG (pequenokaiser2002@yahoo.com.br)

Abstract: This work presents a comparison between the performances of the supervised classification with maximum likelihood algorithm and neural networks in the classification of three LANDSAT/TM sensor scenes in the south of the Amazonas State through Envi 4.6. The maxver classifier obtained better results with the parameters default of the computer system not adopting values for the control of the sample standard deviation. The best results obtained followed the contribution of the internal weight with 0.9 level of activation for the point Training Threshold Contribution and 0.2 for the Training Rate. The experimental results show that the maxver algorithm presented better performance with accuracy over 88% in all the scenes.

Keywords: Neural Networks, Maxver, kappa, accuracy.

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Oliveira1Accuracy2012.pdf231.58 KB

Comparison of two summer crop mapping methods in the state of Paraná in 2008

Comparison of two summer crop mapping methods in the state of Paraná in 2008
Daniel Garbellini Duft1; Jerry Adriani Johann2; Jansle Vieira Rocha1; Rubens Augusto Camargo Lamparelli3

1. State University of Campinas - FEAGRI/UNICAMP, P.O. Box: 6011, ZIP Code:13081-970- Campinas, SP, Brasil (danielduft@gmail.com; jansle.rocha@feagri.unicamp.br)
2. State University of West Paraná – UNIOESTE, P.O. Box: 0701, ZIP Code: 85819-110 – Cascavel, PR, Brasil (jerry.johann@hotmail.com)
3. Interdisciplinary Center for Energy Planning – NIPE, Campinas, SP, Brasil (rubens.lamparelli@gmail.com)

Abstract: The accuracy of crop mapping is still very dependent on the quality of processing remote sensing data, so the objective of this paper is to compare the accuracy of two different methodologies for mapping summer crops in the State of Paraná, Brazil. EVI (Enhanced Vegetation Index) images were used for this purpose, following these methodologies: classic mask generation by the difference in EVI this methodology were used in some studies such as (Schroeder et al. 1999; Labus et al. 2002; Jakubauskas et al, 2002;Fontana et al, 2007), and the RGB method, as used by Johann et al (2011).The quality of the methods was measured using higher spatial resolution images (LANDSAT and AWIFS / IRS) as a reference to calculate the Kappa Index (KI) (Congalton, 1991), Overall Accuracy(EG), omission (EO) and commission (EI) errors. With 400 random samples for each mask, an error matrix was drawn up. The results for the classic methodology presented values of: KI=0.78, EO=11% and EI=11%, while the RGB methodology presented a KI=0.895, EO=6.1% EI=5.9%. KI was 12.8% higher for the RGB methodology as EO and EI were 4.9% and 5.1% lower, respectively. The RGB method presented a greater accuracy potential than the conventional method.

Keywords: Mapping, Crops, Paraná, EVI, Kappa Index

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DuftAccuracy2012.pdf164.38 KB

DEMHC generation from IBGE topographic maps using ArcGis software

DEMHC generation from IBGE topographic maps using ArcGis software
Gabriela Vieira Capobiango1, Demetrius David da Silva2, Hugo Alexandre Soares Guedes3, Barbara Batista Porto4

1 Majoring in Environmental Engineering, at Federal University of Viçosa (UFV); scientific initiation scholarship from FAPEMIG. (gabicapobiango@yahoo.com.br) 2 UFV third associate professor; 1A Productivity Research Fellow from CNPq. (demetrius@ufv.br) 3 UFV substitute professor; PhD researcher in Water and Environment Resources. Sponsored by CNPq.(hugo.guedes@ufv.br) 4. Majoring in Environmental Engineering, at Federal University of Viçosa (UFV); scientific initiation scholarship from CNPq. (barbara.porto@ufv.br)

Abstract: The hydrographically conditioned digital elevation models (DEMHCs) is a grid of regular valueted cells that allowed the representation of the water main way trough relief, been indicated in hydrologic studies for showing consistence between relief and superficial drainage. This paper has, as objective, presents the initial steps to generate the HCDEM from data supplied by IBGE, subsidizing it uses in hydrologic studies. In this sense, were selected three topographic vectorial maps, from the systematic mapping, scale 1:50.0000, supplied by IBGE (Instituto Brasileiro de Geografia e Estatística) on the website www.ibge.gov.br , which includes the Formoso river extension, a trybutary of Pomba river, named: Santos Dumont (26454), Paiva (26463) and Pomba river (26464). Were adopted projected coordinate system UTM (Universal Transversal de Mercator), using “Córrego Alegre” datum on 23 south zone. The HCDEM was generated using ArcGIS 10® software, having as databases vectorial level curves, spaced in 20 meters distance between one and another, higher elevation points e hydrograph already digitized. To process data on ArcMap mode, a shape file for each data was generated on ArcCatalog, corresponding to the level curves and hydrograph in polyline.dgn shape. IBGE had distributed, for free, those files already vectorized and georreferencized, and also, the hydrograph with flow direction, making easier to carrying out the work. The preparation of level curves was based on merge the disconnected lines, with “merge” command, in “Editor”, and to insert its elevation values on the attribute table. A similar procedure was done with the valuated points. The available hydrograph had presented a few imperfections, such as double river borders, discontinuity of the rivers between the maps and others nonconformities that changes the congruency relation of the generated model with reality. Therefore, it was necessary their adjustment from available tools on Spatial Adjustment interface. The prepared files (level curves, valuated points, and hydrograph of each map) were merged by “Merge” command, of ArcToolbox, and interpolated by “Topo to Raster” command, generating DEM, which it was treated, to remove undesirable characteristics, and after that, the HCDEM was generated. Finally, the model was validated comparing the generated numerical drainage with the drainage mapped by IBGE and the watershed automatic delimitation, been observed a superposition between numerical drainage and drainage mapped by 365 IBGE, considered as a Brazilian standard, and that the drainage area delimitation was consistent. The appropriate processing of data from IBGE on ArcGis software had allowed generate solids and reliable results in a fast way, compared with manual methods.

Keywords: Geographic information system, watershed, digital elevation model, topology.

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CapobiangoAccuracy2012.pdf203.31 KB

Effect of control points distribution on the orthorectification accuracy of an Ikonos II image through rational polynomial functions

Effect of control points distribution on the orthorectification accuracy of an Ikonos II image through rational polynomial functions
Marcela do Valle Machado, Mauro Homem Antunes and Paula Debiasi

Federal Rural University of Rio de Janeiro, B4 465, km 7 – 23890-000 - Seropédica - RJ, Brazil (marcelamachado046@hotmail.com, mauroantunes@ufrrj.br, paula@ufrrj.br)

Abstract:  This paper evaluated the orthorectification of a high resolution image for distribution of points between a flat and a rugged area, using the rational polynomial functions. An Ikonos II image was orthorectified using a DEM from contour maps and points obtained in an orthophoto. Fifty-seven points were collected over the entire image, from which 13 and 8 control points were randomly selected from the flat and rugged areas. Thirty points from the entire area and 15 points randomly selected from these were also used in the orthorectification process for comparison purposes. The remaining points were used as check points. The vector errors using 30 or 15 points had the same standard deviation and errors increased with altitude. From the flat area 8 or 13 points yielded the same results and vector errors increased with terrain height. When points were only from the rugged area the average vector errors were smaller as compared with the points only from the flat area. A high correlation between height and vector errors was found when 30 points all over the area were used. It is concluded that the orthorectification using the rational polynomial functions is sensible to ground height and the point distribution.

Keywords: orthorectification, rational polynomial functions, Ikonos II.

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MachadoAccuracy2012.pdf387.41 KB

Error characterization of burned area products

Error characterization of burned area products

M. Padilla, I. Alonso-Canas and E. Chuvieco

Departamento de Geografía, Universidad de Alcalá. C/ Colegios, 2. 28801 Alcalá de Henares (Spain) (marc.padilla@uah.es, itziar.alonsoc@uah.es, emilio.chuvieco@uah.es)

Abstract:This study presents a method to assess (1) the influence of intra-pixel burned area fragmentation and extent on the final global product binary prediction and (2) the relationship between error types (i.e. commission or omission errors) and land cover types. As an example of this methodology, we used the MERIS burned area product developed within the framework of the ESA fire CCI project. Reference data is generated from Landsat imagery for three study sites (Portugal, Brazil, and Australia), covering the 2005 fire season. Exploratory analysis of this study shows that burned are proportion affects the product estimates. Contingency table analysis shows that land cover affects significantly errors in two of the three study sites. Results indicate that, for at least some regions, error regimes may vary depending on land cover type.

 Keywords: Burned Area, Validation, Error Characterization, Reference Data, Land Cover.

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PadillaAccuracy2012.pdf206.41 KB

Estimating uncertainty in deriving spatial distribution of blue ling landings from vessel monitoring system data and implications for delineating marine protection boundaries to the northwest of the British Isles

Estimating uncertainty in deriving spatial distribution of blue ling landings from vessel monitoring system (VMS) data and implications for delineating marine protection boundaries to the northwest of the British Isles
P. Posen, P. Large and J. Lee

Centre for Environment, Fisheries and Aquaculture Science, Pakefield Road, Lowestoft, Suffolk, NR33 0HT, UK (paulette.posen@cefas.co.uk, phil.large@cefas.co.uk, janette.lee@cefas.co.uk)

Abstract: Recent years have seen a rapid increase in the development of restricted fishing areas to protect vulnerable marine ecosystems and species-specific fish stocks. The current study focuses on one such area to the northwest of the British Isles where, in 2009, the European Commission (EC) introduced protection areas for spawning aggregations of southern blue ling (Molva dypterygia) in European Union (EU) waters. High-resolution data derived from logbook entries and satellite-based vessel monitoring systems (VMS) are used to estimate spatial and temporal patterns of blue ling fishing activity. However, certain assumptions must be made regarding whether vessels are engaging in fishing activity at any individual monitoring point, leading to uncertainty in estimating activity in the vicinity of protection area boundaries. The study aims to apportion blue ling landings reported by ICES rectangles of 1° latitude × 0.5° longitude inside and outside the protection areas and the data are assessed at different spatial and temporal scales. From the methods evaluated, initial results of the impact of EU conservation measures on fishing activity during the spawning period are inconclusive.

Keywords: blue ling, GIS, marine protection areas, spatial management

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P_PosenAccuracy2012.pdf198.65 KB

Estimation of DEM Uncertainty Using Clustering Analysis

Estimation of DEM Uncertainty Using Clustering Analysis
Laercio M. Namikawa

INPE - Instituto Nacional de Pesquisas Espaciais, C.P. 515, S.J.Campos, SP, 12201, Brazil (laercio@dpi.inpe.br)

Abstract: This paper presents a method to estimate the uncertainty in a DEM using Cluster Analysis. The method considers that there are always more than one DEM available for a specific area, therefore, a statistical analysis can be performed and used to create a map with clusters of high and low uncertainty in elevation. The resulting map is particularly important for simulation applications, where the simulation process can apply the uncertainty information to select the best DEM for a region and to define the spatial uncertainty of the simulated result. The method is tested in a region of Sao Paulo State in Brazil, with heterogeneous terrain features. The results show that the method can be used not only in simulation, but also to define geographic regions where data collection can be improved.

Keywords: DEM, Uncertainty, Cluster Analysis, SRTM, ASTER GDEM.

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NamikawaAccuracy2012.pdf326.63 KB

Evaluation of hydrological consistency of DEMs derived from SRTM and ASTER2 in three levels of interpolation

Evaluation of hydrological consistency of DEMs derived from SRTM and ASTER2 in three levels of interpolation
Guilherme de Castro Oliveira1, Maola Monique Faria2 and Elpídio Inácio Fernandes Filho3

1.Department Lands, Federal University of Viçosa, Av.Ph Rolfs s/n, Viçosa-MG (guilhermecastrol86@gmail.com)
2. Department Lands, Federal University of Viçosa, Av.Ph Rolfs s/n, Viçosa-MG (maolageo@gmail.com)
3. Department Lands, Federal University of Viçosa, Av.Ph Rolfs s/n, Viçosa-MG (elpidio@ufv.br)

Abstract: This study evaluated the accuracy of drainage models generated from the interpolation of SRTM and ASTER2 by Topo to Raster in three levels for a basin in Viçosa (MG). The standard used to classify the mapping quality was the PEC (Cartographic Accuracy Standards). We also evaluated the proportional representation of drainage in relation to reference database (IBGE) and the total area of sinks in each DEM generated interpolated. The interpolation increased the planimetric accuracy of generated drainage networks and the addition of hydrographic contributed to its better design. The PEC scale 1:100.000 for ASTER2 and SRTM was Class B and C, respectively. The representation of the drainage of the models compared to reference responded positively to the interpolation, but the maximum value reached was 59.8% for treatment 3 in ASTER2.

Keywords: Accuracy, ASTER 2, SRTM, interpolation, PEC, drainage network.

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CastroOliveiraAccuracy2012.pdf167.15 KB

Evaluation of the Cartographic Accuracy of the DEM Generated by a Stereo pair of Images Ikonos

Evaluation of the Cartographic Accuracy of the DEM Generated by a Stereo pair of Images Ikonos
Sinara Fernandes Parreira1, Mariane Alves Dal Santo2  and Pedro Henrique Machado Porath3

1. Universidade do Estado de Santa Catarina (sinaraparreira@hotmail.com)
2. Universidade do Estado de Santa Catarina (marianedalsanto@udesc.br)
3. Universidade do Estado de Santa Catarina (phporath@gmail.com)

Abstract: The purpose of this paper is to present the results of the assessment of Digital Elevation Model (DEM) generated from the IKONOS images stereo pair. The DEM was generated by an automated photogrammetric process in the software ERDAS LPS ATE. The methodology is based on rational function polynomial using the Rational Polynomial Coefficient (RPC) as the main information on triangulation and DEM extraction. The DEM is a cartographic product key for study and analysis of altitude. So evaluate the accuracy of even become indispensable for these product is reliable source of information for project about environmental management and territorial planning. Were used to evaluate the parameters required by Padrão de Exatidão Cartográfica (PEC). The study area was the city of Luís Alves, situated in the northern state of Santa Catarina.

 Keywords: Rational Polynomial Coefficient, Process photogrammetric rational function polynomial

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Expert elicitation for the variogram

Expert elicitation for the variogram
Phuong N. Truong1, Gerard B. M. Heuvelink1 and John Paul Gosling2

1. Department of Environmental Sciences, Wageningen University, P.O. Box 47, 6700 AA, Wageningen, The Netherlands (phuong.truong@wur.nl, gerard.heuvelink@wur.nl)
2. Department of Statistics, University of Leeds, Leeds, LS2 9JT, UK (j.p.gosling@leeds.ac.uk)

Abstract: The variogram is the keystone of Kriging. Much research has been devoted to modelling the variogram from structural analysis of observations. However, there are many instances when the variogram is needed and there are no observations to base on. This can be due to budget constraints, physical or temporal obstacles, or a demand for a priori variogram in Bayesian geostatistics and spatial sampling design. Using expert knowledge that is elicited with a formal statistical expert elicitation procedure is suggested. In this study, we designed a protocol for a wellstructured elicitation procedure to elicit the variogram from expert knowledge. The protocol has two main stages: elicitation of the marginal probability distribution and elicitation of the variogram. We built a web-based tool to facilitate the procedure. A case study was carried out to quantify spatial accuracy of a legacy map of the volumetric soil water content at field capacity. Expert elicitation returns a variogram that has a Matérn model shape with nugget = 0.45, partial sill = 54.57, range = 25410 meters and kappa = 0.40. The results show that the online elicitation tool satisfactorily captured expert opinion although, currently, it is only a prototype that needs to be further developed.

Keywords: Spatial variability, Variogram, Expert knowledge, Soil property map, Uncertainty quantification.

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Exploring Effectiveness of Uncertainty Visualization Methods by Eye-Tracking

Exploring Effectiveness of Uncertainty Visualization Methods by Eye-Tracking
Jan Brus, Stanislav Popelka, Alzbeta Brychtova, and Jana Svobodova

Department of Geoinformatics, Palacký University in Olomouc, Czech Republic (jan.brus@upol.cz, stanislav.popelka@upol.cz, alzbeta.brychtova@upol.cz,j.svobodova@upol.cz)

Abstract: Several visualization techniques for the portrayal of uncertainty have been developed, but there is a gap in transferring knowledge between researchers and final users due to the lack of knowledge about the effectiveness of these visualizations. In this paper, we present a user study that evaluates the perception of uncertainty of the most commonly used techniques for visualizing uncertainty. The study uses data that was designed to represent the uncertainty on maps and images. An eye-tracking study was conducted to assess the differences in user behaviour during scanning the uncertainty visualizations. The search tasks involved primarily finding areas with the least or the most uncertainty. The second part of the research dealt with the usage of uncertainty legends. Eye-tracking can help to understand questions concerning the user’s strategy of the information searching. The eye-tracking method can be considered as the objective one, because it is not influenced by the opinion of the monitored person. To assess graphic effectiveness, eye-tracking methods can help to provide a deeper understanding of scanning strategies that underlie more traditional, high-level accuracy and task completion time results. Eye-tracking methods entail many challenges, such as defining fixations, assigning fixations to areas of interest, choosing appropriate metrics, addressing potential errors in gaze location, and handling scanning interruptions. Special considerations are also required before the designing, preparing, and conducting of eye-tracking studies. Discovered principles can be used in incoming theoretical evaluations of existing or newly developed uncertainty visualization techniques. In addition, the framework developed in this user study presents a structured approach to evaluate uncertainty visualization techniques, as well as provides a basis for future research in uncertainty visualization.

Keywords: eye-tracking, uncertainty, gaze, visualisation

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BrusAccuracy2012.pdf88.38 KB

Exploring the potential role of volunteer citizen sensors in land cover map accuracy assessment

Exploring the potential role of volunteer citizen sensors in land cover map accuracy assessment
Giles M. Foody and Doreen S. Boyd

School of Geography, University of Nottingham, Nottingham, NG7 2RD, UK (giles.foody@nottingham.ac.uk, doreen.boyd@nottingham.ac.uk)

Abstract: Two sources of volunteered geographical information are used to provide reference data on forest to inform the evaluation of the accuracy of the Globcover land cover map for West Africa. Ground based photographs acquired through an internetbased collaborative project were interpreted by a further set of four volunteers to provide reference data on forest. Little agreement was found between a set of four volunteer interpreters but the set of labels they generated enabled a latent class model to be used to estimate forest cover. The latter is a key environmental variable as well as a basic indicator of accuracy on a non site-specific basis. The lack of gold standard reference makes detailed assessment difficult but the close correspondence between the model derived estimate of forest cover and that depicted in the map suggest the approach, based on volunteered data, may have value in accuracy assessment.

Keywords: remote sensing, citizen sensing, neogeography, crowd-sourcing, accuracy, latent class model, forest, Globcover.

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FoodyAccuracy2012.pdf96.04 KB

Geographically weighted methods for examining the spatial variation in land cover accuracy

Geographically weighted methods for examining the spatial variation in land cover accuracy
Alexis Comber1, Peter Fisher1, Chris Brunsdon2, Abdulhakim Khmag1

1. Department of Geography, University of Leicester, Leicester, LE1 7RH, UK (ajc36@le.ac.uk, pff1@le.ac.uk, aek9@le.ac.uk)
2. Department of Geography, University of Liverpool, Liverpool, L69 3BK, UK (Christopher.Brunsdon@liverpool.ac.uk)

Abstract: The confusion matrix is used to describe land cover accuracy. It describes correspondence between alternative sources of land cover information and is a standard technique in remote sensing. BUT the confusion matrix is aspatial – it provides no information about the spatial distribution of accuracy. And, despite much work suggesting methods for describing the spatial variation of accuracy (Foody, 2002; 2005), these have not been adopted by the remote sensing community. This paper demonstrates how geographically weighted approaches can be used to analyse the spatial relationships between land cover data classified from remotely sensed data and data collected in the field, for both Boolean and Fuzzy classifications. These approaches each use a moving window or kernel to compute local accuracy measures, whose size is specified dynamically, and are ‘geographically weighted’ because the kernel allows for the fact that the more distant observations may be of less local relevance and their influence is weighted accordingly. Fuzzy and Boolean maps of the spatial distribution of accuracy were generated. This research demonstrates that data collected as part of a standard remote sensing validation exercise can be used to derive measures of accuracy that vary spatially and suggests that there is potential to move land cover validation from the aspatial to spatially explicit reporting of accuracy.

Keywords: confusion matrix, geographically weighted regression, spatial variation of accuracy, fuzzy difference

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ComberAccuracy2012.pdf97.97 KB

Geospatial Data Quality Indicators

Geospatial Data Quality Indicators
Victoria Lush, Lucy Bastin and Jo Lumsden

Knowledge Engineering Group, Aston University, Birmingham, B4 7ET, UK (lushv@aston.ac.uk, l.bastin@aston.ac.uk, j.lumsden@aston.ac.uk)

Abstract: Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset’s fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label.

Keywords: Geospatial data, geospatial data quality, geospatial data quality indicators,quality evaluation.

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LushAccuracy2012.pdf68.71 KB

Geostatistical assessment of the spatial variability of soil texture in the coffee plantation

Geostatistical assessment of the spatial variability of soil texture in the coffee plantation
Marcelly da Silva Sampaio1, Marcelo de Carvalho Alves1, Fábio Moreira da Silva2, Edson Ampélio Pozza2, Marcelo Silva de Oliveira2, Luciana Sanches1

1 Universidade Federal de Mato Grosso, Cuiabá, MT – Brasil (arcellysampaio@gmail.com, marcelocarvalhoalves@gmail.com, lsanches@ufmt.br)
2 Universidade Federal de Lavras, Lavras, MG – Brasil (fmsilva@ufla.br, eapozza@ufla.com.br, marcelo.oliveira@ufla.br)

Abstract: The aim of this study was to evaluate the variability of soil texture in coffee plantation by geostatistics, using simple kriging as linear interpolator to analyze the prediction errors. The research was conducted in Cafua Farm where 67 sample points were collected in an area of 6.5 ha. Spherical model variograms were adjusted by the methods of ordinary least squares (OLS), weighted least squares (WLS), maximum likelihood (ML) and restricted maximum likelihood (REML) for the data of clay, sand and silt. The best method of assessment was performed using the Akaike information criterion, where the REML method showed better performance for all attributes. The simple kriging was done for the data and for the standard deviation of the data. It was observed by kriging that the highest percentage of clay and silt were located in the northern area, while the highest percentage of sand concentrate in the south. Analyzing the standard deviation, data higher variation was found in clay, especially in places with sample deficiency. The range of spatial dependence of clay, sand and silt were 143.7m, 245.2m and 141.2m, respectively. The minor variations of the standard deviation are associated with the sampling points.

Keywords: simple kriging, Akaike information criterion, spherical model, prediction errors.

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SampaioAccuracy2012.pdf165.92 KB

Images into Radiance: Uncertainty Evaluation

Images into Radiance: Uncertainty Evaluation
Leidiane L. Andrade1, Ruy M. Castro1 Lênio S. Galvão 2

1.Instituto de Estudos Avançados - IEAv/DCTA, Caixa Postal 6044 – 12.231-970 – São José dos Campos - SP, Brasil (Leidiane.andrade@ieav.cta.br, rmcastro@ieav.cta.br)
2.Instituto Nacional de Pesquisas Espaciais – INPE, Caixa Postal 515 - 12227-010 - São José dos Campos - SP, Brasil (lenio@dsr.inpe.br)

Abstract: One goal of remote sensing in the thermal infrared region is the determination of the temperature and surface emissivity in urban areas. For the conversion of Digital Numbers (DN) into radiance values, it is important to characterize the uncertainty sources associated with the process of data acquisition itself and with other important factors such as the atmospheric correction. This study addresses this topic. Results showed that the uncertainties due to the atmospheric influence was the factor that most contributed to the final data uncertainty (3%), followed by the uncertainties associated with the radiance determination (0.5%). As a result, the final uncertainties in temperature data obtained for each pixel was 1.8 ° C, which varied with the studied urban material.

Keywords: Thermal Remote Sensing, Emissivity, Temperature.

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AndradeAccuracy2012.pdf82.67 KB

Improving the relationship between reference frames by using the Thin-Plate Spline modelling

Improving the relationship between reference frames by using the Thin-Plate Spline modelling
João Paulo Magna Júnior1, Paulo de Oliveira Camargo2 and Maurício Galo2

1.Federal Institute on Education, Science and Technology of Goiás (magnajr@gmail.com)
2.São Paulo State University, Department of Cartography, Presidente Prudente, SP (paulo@@fct.unesp.br, galo@fct.unesp.br)

Abstract: The adoption of new geodetic reference systems and/or the availability of new reference frames occur, mainly, by the availability of new data sets. For the use of products in different reference frames, methods are necessary to transform the coordinates and modelling the distortions that compromise the transformation. In this paper a method is presented for three-dimensional coordinates transformation with modeling of distortions based on Thin-Plate Splines (TPS) mapping functions. Experiments were performed with real data of SAD 69 (South American Datum – 69) stations in the realization of 1996 (SAD69/96) and its homologous coordinates in SIRGAS2000. In the control points, the values of the root mean square error (RMSE) of the discrepancies in latitude and longitude, respectively, were 0.9 mm and 0.6 mm, and in the check points of 7.8 cm and 6.7 cm. By using distinct points of the network, the comparison of direct and inverse transformation results in the standard deviation were of 0.5 mm in latitude and 0.3 mm in longitude. In the comparison between the TPS model and the ProGriD, the statistical indicators were reduced by 97% (average), indicating that the proposed method is promising.

Keywords: reference systems, coordinate transformation, distortion modelling, thin-plate splines.

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JuniorAccuracy2012.pdf86.79 KB

In-lab radiometric instruments calibration and uncertainties assessment

In-lab radiometric instruments calibration and uncertainties assessment
Cibele Teixeira Pinto1,2, Flávio Jorge Ponzonni1 and Ruy Morgado de Castro
2,3

1. Instituto Nacional de Pesquisas Espaciais – INPE, Caixa Postal 515 - 12227-010 - São José dos Campos - SP, Brasil (cibele@dsr.inpe.br, flavio@dsr.inpe.br)
2.Instituto de Estudos Avançados - IEAv/CTA, Caixa Postal 6044 - 12.231-970 - São José dos Campos - SP, Brasil (cibele@ieav.cta.br, rmcastro@ieav.cta.br)
3.Universidade de Taubaté – UNITAU, Caixa Postal 515 - 12201-970 - Taubaté - SP, Brasil (rmcastro@unitau.br)

Abstract: Extracting quantitative information from both airborne and orbital sensors data requires information about their absolute calibration. The most common in-flight absolute calibration method is based on radiometric data collected from a reference surface located on the Earth. The first step of that method is the surface characterization, which involves radiometric measurements to determine the average Reflectance Factor of the surface. Frequently these reference surfaces are relatively large and the radiometric measurements have been performed by instruments, which must be calibrated. Thus, analyzing the instruments conditions and their respective contributions to the final uncertainty of the measurements experiments have to be performed in laboratory. The objective of this paper is to describe some in-lab instruments calibration procedures including the uncertainties assessment.

Keywords: calibration, uncertainty estimation

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Pinto2Accuracy2012.pdf226.8 KB

Inaccuracies on morphometric characterization of watersheds on GIS ambient

Inaccuracies on morphometric characterization of watersheds on GIS ambient
Vitor Souza Martins1; Demetrius David Da Silva2; Hugo Alexandre Soares Guedes3; Bárbara Batista Porto4

1. Majoring in Agricultural and Environmental Engineering, at Federal University of Viçosa (UFV), scientific initiation scholarship from CNPq. (vitormartins9@hotmail.com)
2.UFV third associate professor; 1A Productivity Research Fellow from CNPq. (demetrius@ufv.br)
3. UFV substitute professor; PhD researcher in Water and Environment Resources. Sponsored by CNPq. (hugo.guedes@ufv.br)
4.Majoring in Environmental Engineering, at Federal University of Viçosa (UFV); scientific initiation scholarship from CNPq. (barbara.porto@ufv.br)

Abstract: The morphometric characterization of watersheds is done, nowadays, with the integration of relief information in Geographic Information System (GIS) interface, extremely applicable on planning and management of water resources. The study objective was to analyze the vegetation and relief influence on the morphometric characterization of “Pedras Negras” stream, at Petróplolis-RJ, comparing the hydrographically conditioned digital elevation models (HCDEMs), generated from sensor VNIR of ASTER (Advanced Spaceborn Thermal Emission and Reflection Radiometer) data, with the model obtained from the processing of IBGE’s topographic maps on the scale of 1:50.000. The study area is characterized for gneissic stone outcrops up to 2263 meters elevation, and surrounded by Atlantic forest, which has full vegetation with trees that reach 40 meters high. The processing and treating of the models had guaranteed the hydrographic conditioning, resulting in models with no spurious depressions, with stream flow originated from riverheads and a detailed and ramified drainage system. The percentage variation of the morphometric data valued by DEMHC ASTER compared with those valued by DEMHC IBGE were superior to 10% for main river length results (22.5%), total length drainage system (24%), watershed contribution area (10.9%), shape factor (-41.3%), drainage density (14.7%) and the river axial length (20.9%). The expressive variations between the models came from the vegetation behavior, which inclines and shadows the river border, causing inaccuracy on the river channel reconnaissance. The DEMHC ASTER presented an average slope variation of (20.9%) compared with IBGE maps, showing a tendency of the models to soothe the relief, loosing curacy on the determination of riverhead points and tributary rivers points also. In a general way, we can see good congruity between DEMHC ASTER and IBGE for hydrologic studies, where the most appropriate on the current study was to work with DEMHC generated from IBGE’s maps.

Keywords: Geographic Information System, Watershed, digital elevation models, morphometric characterization.

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MartinsAccuracy2012.pdf204.43 KB

Influence of human uncertainty in the elaboration of fuzzy reference databases for the accuracy assessment of land cover maps

Influence of human uncertainty in the elaboration of fuzzy reference databases for the accuracy assessment of land cover maps
Pedro Sarmento1,2,3, Cidália C. Fonte3,4, Joel Dinis2 and Mário Caetano1

1.ISEGI, Universidade Nova de Lisboa, 1070-312, Lisboa (psarmento@igeo.pt, mario.caetano@fct.mctes.pt)
2.Portuguese Geographic Institute (IGP), Remote Sensing Unit (RSU), Lisboa, Portugal (jdsilva@igeo.pt)
3. Institute for Systems and Computers Engineering at Coimbra, Portugal (cfonte@mat.uc.pt)
4 Department of Mathematics, University of Coimbra, Portugal

Abstract: Reference databases for the accuracy assessment of land cover maps are assumed to represent the true land cover in a set of selected locations. Although, the elaboration of reference databases through field visits or photo interpretation of aerial images is a hard and difficult task due to uncertainty in the assignment of the most correct land cover class at each sample location because of landscape fragmentation. To capture the diversity of land cover in each pixel of the reference data, a linguistic scale composed by five linguistic values is used in this paper and a methodology to translate the linguistic values to fuzzy intervals is proposed, based on the responses of the photo interpreters to a set of chosen pixels. These fuzzy intervals are then used to build a fuzzy confusion matrix and fuzzy thematic accuracy measures are derived. The main goal of this study is to quantify the differences of perception of photo-interpreters when assigning a linguistic scale to the sample pixels of the reference database. The proposed approach is tested on a case study where the accuracy assessment of a map of Continental Portugal with five land cover classes, derived from MERIS images, is made.

Keywords: reference database uncertainty, photo-interpretation, linguistic scale, fuzzy confusion matrix, fuzzy intervals.

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SarmentoAccuracy2012.pdf139.53 KB

Kriging and cokriging for spatial interpolation of rainfall in Espirito Santo State, Brazil

Kriging and cokriging for spatial interpolation of rainfall in Espirito Santo State, Brazil
Alexson de Mello Cunha1,Gerson Rodrigues dos Santos2, Eliana de Souza1;Filipe Silveira Trindade3; Elpídio Inácio Fernandes Filho2; João Luiz Lani2; Michelle Milanez França1

1 Postgraduate Course on Soils and Plant Nutrition, Soils Department, Viçosa Federal University.CEP 36570-000. Viçosa (MG).
2.University Viçosa Federal University, CEP 36570-000. Viçosa (MG). (alexson.cunha@vta.incra.gov.br, gerson.santos@ufv.br, elianadsouza@yahoo.com.br, filipe.trindade@ufv.br, elpidio@ufv.br, lani@ufv.br, milanezmichelle@gmail.com)

Abstract: Kriging has become a widely used method for spatial distribution of hydroclimatic variables. The aim of this work was to evaluate the simple kriging and cokriging on the spatial distribution of rainfall in Espírito Santo state, Brazil. Data model elevation and distance from the sea, obtained from sampling points in regular and irregular grids were used as covariates in co-kriging. Also, we used average annual rainfall of 108 rain gauge stations geographically distributed in the state. The evaluation of methods and variables was based on cross-validation, considering the errors of the predicted values, adjusting the first degree linear regression model of the observed values as a function of the estimated values and the coefficient of determination. In general, the regular grid sampling of the covariates showed a slight trend toward better prediction accuracy compared to the irregular grid. Also, co-kriging provided more accurate results than kriging, which was verified by the average absolute errors, ranging from 7.066% to 7.924%, and by the root mean squared errors, varying from 109.6 mm and 120.4 mm. The results suggest that, wherenever possible, it is better to use cokriging and regular grids for sampling.

Keywords: elevation, coastline, geostatistic, spatial prediction

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CunhaAccuracy2012.pdf327.32 KB

Land Cover Change Analysis from Remote Sensing Images and Statistical data: Case Study Itaipú region, Border Paraguay/Brazil

Land Cover Change Analysis from Remote Sensing Images and Statistical data: Case Study Itaipú region, Border Paraguay/Brazil
Mauro Alixandrini1, Hans-Peter Bähr2

1.UFBA, Salvador/Brazil (Mauro.Alixandrinni@ufba.br)
2.KIT,Karlsruhe /Germany (hans-peter.baehr@ipf.uni-karlsruhe.de)

Abstract: The historical context of the region was compared to the results obtained from the set of adopted images. Based on the analyzed documents we can define the main anthropogenic phenomena responsible for the changes in the vegetation cover in the region. We identified the Paraguayan agricultural expansionism and the predominantly agricultural Brazilian migratory movements to the border region between Brazil and Paraguay. The results show that the systematic process of deforestation had already been established before the beginning of the construction of Itaipú. Migratory processes associated with previous factors to the construction of hydroelectric show mainly correlations with the deforestation observed in the region. Furthermore, the analysis verifies the incoherent documentation about the current situation in the protected areas. The conclusions prove the characteristics of the employed method showing that its use is valid in a context of the analysis of the regional development.

Keywords: Land Cover Change, Thematic Map comparison, Itaipú.

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AlixandriniAccuracy2012.pdf109.13 KB

Land cover and land use in Brazil and the Environmental-Economic Accounts System

Land cover and land use in Brazil and the Environmental-Economic Accounts System 
Rodrigo de Campos Macedo 1, Maurício Zacharias Moreira 2, Eloisa Domingues3, Ângela Maria Resende Couto Gama 4, Fábio Eduardo de Giusti Sanson 5, Felipe Wolk Teixeira 6, Fernando Peres Dias 7, Fernando Yutaka Yamaguchi 8, and Luiz Roberto de Campos Jacintho9 

Instituto Brasileiro de Geografia e Estatística. Rua Tenente Silveira, 94 – 12º andar – Florianópolis, SC – Brasil (1 rodrigo.macedo@ibge.gov.br; 2 mauricio.moreira@ibge.gov.br; 3 eloisa.domingues@ibge.gov.br; 4 angela.gama@ibge.gov.br; 5 fabio.sanson@ibge.gov.br; 6 felipe.teixeira@ibge.gov.br; 7 fernando.dias@ibge.gov.br; 8 fernando.yamaguchi@ibge.gov.br; 9 luiz.jacintho@ibge.gov.br) 

Abstract: The objective of this work is to produce statistics that are going to show changes occurred in Brazil’s ecosystems and these statistics are going to join the Environmental-Economic Accounts System – SEEA. It’s based by a SEEA's methodology, diffused by United Nations - UN, which aims an approach between economic and environmental statistics, producing international comparability and conceptual uniformity to evaluate change process in land cover and land use that occurs in several countries. It’s necessary to verifying the suitability of methodological procedures to Brazilian reality and the access to all information and files needed. The first step was analysing MODIS as orbital instrument on the purposed classification method. The choice of this sensor was made because of the product’s quality and its capacity to generate images of a large area, though the challenge is to identify accurate Land usage's categories in images with a spatial resolution of approximately 250 meters. After the final classification, the next step is to make a quantification and comparison of data from these different years using a 1km² grids, as proposed in an already used methodology by The European Environment Agency. This procedure will allow evaluate and identify the process of changing in each grid of the land cover and land use, and provide historical series of the chosen years.

Keywords: Remote Sensing. Land Use and Cover Change, Environmental Statistics, Geoprocessing.

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MacedoAccuracy2012.pdf70.42 KB

Larger geologic complexity implies larger uncertainty

Larger geologic complexity implies larger uncertainty
Alessandro Samuel-Rosa¹, Ricardo Simão Diniz Dalmolin² and Pablo Miguel³

1. Curso de Pós-Graduação em Agronomia-Ciência do Solo da Universidade Federal Rural do Rio de Janeiro, Seropédica, RJ, Brazil. (alessandrosamuel@yahoo.com.br)

2.Departamento de Solos da Universidade Federal de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil. (dalmolinrsd@gmail.com)
3.Programa de Pós-Graduação em Ciência do Solo da Universidade Federal de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil. (tchemiguel@yahoo.com.br)

Abstract: The prediction of soil attributes through predictive models became popular in the last decade. Land-surface parameters are the ones used at the largest extend as predictor variables. However, the relation between land-surface parameters and soil attributes is not evident in all land surfaces: it might be strong in one but weak in another. Besides, this relation usually varies across the landscape due to the other soil forming factors influence such as the parent material. Using the results of a study carried out in a geologically complex small catchment in Southern Brazil we show that soil particle-size distribution can be estimated from land-surface parameters. The prediction functions can explain more than half the overall data variance. The literature shows that such performance is superior to that of the conventional soil mapping approach. However, when we evaluate the spatial accuracy of the predictive models we see that in locations of larger geological heterogeneity the predictive models present large prediction errors. Thus, larger geological heterogeneity implies larger uncertainty. Unfortunately the geological information available is not sufficiently accurate to help improving significantly the spatial accuracy of the prediction functions.

Keywords: predictive models, linear regression models, geology, soil information user

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SamuelRosaAccuracy2012.pdf138.22 KB

Living with Collinearity in Local Regression Models

Living with Collinearity in Local Regression Models
Chris Brunsdon1, Martin Charlton2 and Paul Harris2

1.People, Space and Place, Roxby Building, University of Liverpool, L69 7ZT, UK (Christopher.Brunsdon@liverpool.ac.uk)
2.National Centre for Geocomputation, National University of Ireland Maynooth, Maynooth, Co. Kildare, Ireland (Martin.Charlton@nuim.ie; Paul.Harris@nuim.ie)

Abstract: In this study, we investigate the issue of local collinearity in the predictor data when using geographically weighted regression (GWR) to explore spatial relationships between response and predictor variables. Here we show how the ideas of condition numbers and variance inflation factors may be `localised’ to detect and respond to problems caused by this phenomenon. Furthermore, we introduce two adapted forms of GWR where localised regressions that are resistant to collinearity effects are specified only at locations where collinearity is considered detrimental to the standard local fit. We present initial findings via the use of a simulation study designed to assess the sensitivity of GWR outputs to various levels of collinearity. This study aims to build upon, and respond to, recent research in this area.

Keywords: Geographically Weighted Regression, Variance Inflation Factor, Condition Number, Ridge Regression

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BrunsdonAccuracy2012.pdf116.45 KB

Network Accuracy: the impact of the 3D distances on location-allocation

Network Accuracy: the impact of the 3D distances on location-allocation
Emeka Chukwusa1, Alexis Comber1 and Chris Brunsdon2

1.Department of Geography, University of Leicester, Leicester, LE1 7RH, UK (ec102@le.ac.uk, ajc36@le.ac.uk)
2.Department of Geography, University of Liverpool, Liverpool, L69 3BK, UK (Christopher.Brunsdon@liverpool.ac.uk)

Abstract: Distance metrics derived from road networks are used in location-allocation models to support facility planning. Typically, road networks model 2-dimensional distance (i.e. over X and Y dimensions). This paper introduces the notion of ‘3D distance’ that incorporates elevation as the Z-dimension in the network. A comparison of distance modelled in 3D networks with that in 2D networks demonstrates the impact of 3D distance with that each distance type resulting in different sets of optimal locations given same P-median problem.

Keywords: Location-allocation, P-median, networks

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ChukwusaAccuracy2012.pdf123.96 KB

On the interpolation algorithm ranking

On the interpolation algorithm ranking
Carlos López-Vázquez

LatinGEO Lab, SGM+Universidad ORT del Uruguay (carlos.lopez@ieee.org)

Abstract: Interpolation of data gathered at a finite number of locations is an everyday issue with spatial data. The choice of the best interpolation algorithm has been a topic of interest for a long time. Typical papers take a single dataset, a single set of data points, and a handful of algorithms. They report results of considering a subset A of the data points, application of each algorithm to the complement of A, and evaluating the MAD/RMSE over such points. The lower the better, so a ranking among methods (without confidence level) can be derived based upon it. We believe that the best interpolation algorithm should consider not merely the function value at some designated points, but also the spectral properties of the original field. We have used a metric named ESAM for that. Using a sample of N = 500, 2500 and 5000 irregularly distributed points taken from a reference DEM, we applied a number of interpolation methods and create a ranking among them using MAD, RMSE and ESAM as the figure of merit. ESAM ranking does not agree with the others. In addition, in this paper we will show how to build a ranking with a confidence level.

Keywords: Interpolation, RMSE, MAD, ESAM, ranking

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LópezVázquezAccuracy2012.pdf87.94 KB

On the quality of eigenvector spatial filtering based parameter estimates for the normal probability model: implications about uncertainty and specification error for georeferenced data

Yongwan Chun1 and Daniel A. Griffith2

 

1.  University of Texas at Dallas, 800 W. Campbell rd. Richardson, Texas75093, USA. ywchun@utdallas.edu  

2. Ashbel Smith Professor, University of Texas at Dallas, 800 W. Campbell rd. Richardson, Texas 75093, USA.

    dagriffith@utdallas.edu

 

Abstract: Eigenvector spatial filtering, which introduces a subset of eigenvectors extracted from a spatial weights matrix as synthetic control variables in a regression model specification, furnishes a solution  to extraordinarily intricate statistical modeling problems involving spatial dependencies. It accounts for spatial autocorrelation in standard specifications of regression models. But the quality of the resulting regression parameter estimates has yet to be ascertained. The estimator properties to establish include unbiasedness, efficiency and consistency. The purpose of this paper is to demonstrate these estimator properties for linear regression parameters based on eigenvector spatial filtering, including a comparison with the simultaneous autoregressive (SAR) model. Eigenvector spatial filtering methodology requires the judicious selection of eigenvectors, whose number tends to increase with both level of linear regression residual spatial autocorrelation and number of areal units. A logistic regression description of the number of eigenvectors selected in a simulation pilot study suggests estimator consistency.

Keywords: Eigenvector spatial filtering, unbiasedness, efficiency, consistency.

from a spatial weights matrix as synthetic control variables in a regression model

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GriffithAccuracy2012.pdf131.54 KB

On the use of synthetic images for change detection accuracy assessment

On the use of synthetic images for change detection accuracy assessment
Hélio Radke Bittencourt1, Daniel Capella Zanotta2 and Thiago Bazzan3

1.Departamento de Estatística, Pontifícia Universidade Católica do Rio Grande do Sul(PUCRS), Brazil Av. Ipiranga, 6681 – 90619-900 – Porto Alegre – RS, Brasil (heliorb@pucrs.br)
2.Instituto Nacional de Pesquisas Espaciais (INPE) and Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS), Brazil. (danielczanotta@gmail.com)
3.Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Brazil (thiagobaz@yahoo.com.br)

Abstract: Land cover change detection is the major goal in multitemporal remote sensing studies. It is well known that remotely-sensed images of the same area acquired on different dates tend to be affected by radiometric differences and registration problems. These influences are considered as noise in the process and may induce the user to both: signalling false changes and masking real surface changes. The difference image produced by subtracting two co-registered images is a standard initial step in change detection algorithms. This image naturally appears to be noisier than the original ones and has at least two populations: i) the noise-like and ii) the real changes. The problem that arises is how to discriminate them. There are several approaches to perform change detection reported in the literature and some studies have employed synthetic images. By using synthetic images, the accuracy assessment of specific algorithm can be done more accurately. The question at this point is: what is the acceptable noise level to be added on the synthetic images to simulate a real problem? This paper attempts to answer this question by suggesting values of SNR (signal-to-noise ratio) obtained from experiments performed on TM-Landsat-5 and CCD-CBERS-2B images.

Keywords: Change detection, accuracy assessment, signal-to-noise ratio, SNR

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Positional accuracy of Curitiba’s digital orthophoto map

Positional accuracy of Curitiba’s digital orthophoto map
Hamilton Carlos Vendrame Junior1, Maria Cecilia Bonato Brandalize2

1. Universidade Federal do Paraná, Curitiba – Paraná – Brasil (hcvjunior@gmail.com)
2.Universidade Federal do Paraná, Curitiba – Paraná – Brasil (Maria.brandalize@ufpr.br)

Abstract: This work evaluates the positional quality of maps produced by the municipality of Curitiba. The Brazilian Cartographic Accuracy Standard (PEC) was applied in order to evaluate the geometrical quality of the orthophoto maps at scales 1:3.000 e 1:5.000. For this purpose, it was used the prescriptions of Decree No. 89817 of June 20, 1984, which deals with the technical requirements of National Mapping, establishing regulatory instructions for the systematic mapping at Brazilian territory. The study methodology comprehended the: availability of digital orthophoto maps at scales 1:3,000 and 1:5,000; determination of the sample size; establishment of a methodology for the identification, distribution and collection of ground control points; data collection and processing of ground control points coordinates, identification and collection of coordinates of homologous points in the digital orthophoto maps; statistical analysis of the collected coordinates and quality assessment according to the PEC. The initial results of the transformations between coordinate systems resulted unsatisfactory once were found discrepancies between the parameters officially adopted and made available by the Institute of Geography and Statistics and those adopted by the municipality. After investigation of the parameters, the products were finally classified as "A" (optimal geometric quality), according to the PEC

Keywords: urban cartography; mapping standards; geodetic systems.

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VendrameJuniorAccuracy2012.pdf368.58 KB

Random field modelling of DEM uncertainty and its impact on terrain referenced navigation

Random field modelling of DEM uncertainty and its impact on terrain referenced navigation
Guy Ruckebusch

IC3i, 5 rue de Villequoy, 78610 Auffargis, France (guy.ruckebusch@orange.fr)

Abstract: Terrain Referenced Navigation (TRN) is an integrated navigation solution, where terrain height measurements from a radar altimeter are compared to a Digital Elevation Model (DEM) to filter the errors of the Inertial Navigation System. Most conventional systems incorrectly assume that the DEM errors are Gaussian and uncorrelated, with a standard deviation linearly related to the slope. This is all the more annoying as any departure from these assumptions is known to adversely impact the TRN performance. In this paper, two new random field models of DEM altimetric error are described. The first model is a doubly stochastic random field. The error is Gaussian, conditioned on its standard deviation, modeled as a lognormal random field, whose mean is a logistic function of the DEM slope. This model is statistically learned by analyzing the difference of the DEM with a highquality reference DEM. The second model is limited to Reference3D DEMs, with the availability of the (two) stereoscopic images used to produce the DEM. The approach relies on a Bayesian modelling of the altimetric error, where the prior is precisely the first model. The impact of the DEM uncertainty model on the TRN performance is evaluated through Monte Carlo simulation.

Keywords: DEM uncertainty, random field model, statistical learning, Bayesian stereo modelling, Terrain Referenced Navigation, uncertainty propagation.

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RuckebuschAccuracy2012.pdf312.62 KB

Reliability of watershed area estimation using Digital Elevation Models

Reliability of watershed area estimation using Digital Elevation Models
Fabiano Costa de Almeida1, Márlon Crislei da Silva1, Camilo Daleles Rennó2, Márcio Bomfim Pereira Pinto1, Agustin Justo Trigo1 and Marcis Gualberto Mendonça Júnior3

1.Agência Nacional de Águas – ANA, Setor Policial, Área 5, Qd 3, Bl B, 70610-200,Brasília/DF, Brasil (fabiano.almeida@ana.gov.br, marlon.silva@ana.gov.br, marcio.bomfim@ana.gov.br,agustin.trigo@ana.gov.br)
2.Instituto Nacional de Pesquisas Espaciais – INPE, Av dos Astronautas, 1758, 12227-010,São José dos Campos/SP, Brasil (camilo@dpi.inpe.br)
3. Diretoria de Serviço Geográfico – DSG, Quartel General do Exército, Bl F, 70630-901,Setor Militar Urbano, Brasília/DF, Brasil (marcis@dsg.eb.mil.br)

Abstract: Digital elevation models (DEM) have become very useful for delineating catchment basins to obtain more accurate area estimations in the last decades. As a discretization of a continuous surface, DEM’s ground sample data (GSD) delimit the elementary watershed boundary segments. The finer the GSD resolution, the closer tends to be the true drainage basin edge and its area to those estimated by DEM processing. Our goal is to establish the minimum area estimation that fits a desired degree of reliability for any catchment shape, considering the GSD of the DEM, the admitted tolerance and the shape of the basin. This approach starts with the area assessment of perfect circles which are then converted to raster format using a regular matrix of pixels. The squared Gravelius Index of a watershed is taken as a multiplicative factor that will allow the comparison between different shapes of basins, aiming to establish the minimum circular area compliant with the desired tolerance, in this case acknowledged as 0.5 percent and an equivalent GSD of 3-second-arc (90m) from SRTM. The estimation of mean response for the minimum area according to a least squares regression model is 0.641 Km².

Keywords: Watershed area, Gravelius Index, digital elevation models, SRTM.

Site-specific Pr ediction of Mosquito Abundance using Spatio-Temporal Geostatistics

Site-specific Pr ediction of Mosquito Abundance using Spatio-Temporal Geostatistics
E.-H. Yoo1, D. Chen2 and C. Russell3

1. Department of Geography, University at Buffalo, SUNY, Buffalo, NY, USA (eunhye@buffalo.edu)
2.Department of Geography, Queen’s University, Kingston, Ontario, Canada (chendm@queensu.ca)
3. Enteric, Zoonotic and Vector-Borne Diseases, Public Health Ontario, Canada

Abstract: Adult mosquito surveillance programs provide a primary means to understand mosquito vector population dynamics, but such data are typically sparse in space and irregular in time, due to the limit to the available resources for trapping and/or extreme physical conditions. Particularly, missing observations often encountered in long-term surveillance data may hinder a comprehensive analysis of the landscape epidemiology of vector-borne disease and limit our efforts to establish significant and stationary relationship with weather conditions. We developed a West Nile virus (WNV) mosquito abundance model for a sitespecific prediction and associated uncertainty measure, where any point prediction is obtained by a linear combination of a spatio-temporal drift estimate and a stochastic residual. The effects of meteorological and environmental conditions on mosquito population are incorporated in the drift model, while the variations around the drift is modeled by a spatio-temporal random field. The proposed model accounts for discrete counts in nature of the mosquito surveillance data within a generalized linear mixed model and tackles the non-stationarity in WNV mosquito abundance data by limiting the decision of stationarity only to local neighborhoods around any prediction point where the target prediction is sought after.

 Keywords: Poisson Generalized Linear Model, geostatistical space-time model, West Nile Virus, moving local neighborhoods.

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Snakes-based approach for extraction of building roof contours from digital aerial images

Snakes-based approach for extraction of building roof contours from digital aerial images

Aluir P. Dal Poz and Antonio J. Fazan

São Paulo State University – Dept. of Cartography, R. Roberto Simonsen 305 – 19060-900 Presidente Prudente, SP – Brazil (aluir@fct.unesp.br, ajfazan@gmail.com.cr)

Abstract: This paper presents a method for building roof contour extraction from digital images taken over complex urban scenes. The proposed method is based on a snakes-based energy function that represents building roof contours in digital images, which is optimized by using the dynamic programming (DP) algorithm. As most of the building roof contours are characterized by rectilinear sides intercepting at right angles, appropriate geometrics constraints are enforced into the original snakes energy function. The main advantage of using the DP algorithm for optimizing the proposed snakes-based energy function is its better radius of convergence, when compared to the one that is usually obtained in the original solution based on variational approaches. Experimental evaluation, including visual inspection and numeric analysis, was performed by using real data and the obtained results showed the potentiality of the proposed method for extracting building roof contours from digital images. Keywords: Snakes, dynamic programming, building extraction, image analysis.

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PozAccuracy2012.pdf117.67 KB

Some expectation-maximization (EM) algorithm simplifications for spatial data

Some expectation-maximization (EM) algorithm simplifications for spatial data
Daniel A. Griffith

University of Texas at Dallas, School of Economic, Political, and Policy Sciences, 800 W. Campbell Rd., GR31, Richardson, TX 75080-3021, USA (dagriffith@utdallas.edu)

Abstract: The EM algorithm is a generic tool that offers maximum likelihood solutions when data sets are incomplete with data values missing at random or completely at random. At least for its simplest form, the algorithm can be rewritten in terms of an ANCOVA regression specification. This formulation allows several analytical results to be derived that permit the EM algorithm solution to be expressed in terms of new observation predictions and their variances. Implementations can be made with a linear regression, with a nonlinear regression, and with a generalized linear model routine, allowing missing value imputations, even when they must satisfy constraints or involve dependent observations. This paper extends to spatially correlated data findings already reported for non-spatial data, linking the EM algorithm solution with spatial autoregression, geostatistical kriging, and eigenvector spatial filtering. One theorem is proved, and two corollaries are derived that broadly contextualize imputation findings in terms of the theory, methodology, and practice of spatial statistical science.

Keywords: ANCOVA, eigenvector spatial filter, EM algorithm, kriging, spatial autoregression.

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Griffith2Accuracy2012.pdf79.9 KB

Spatial data quality of herbarium datasets and implications for decision-making on biodiversity conservation in Brazil

Spatial data quality of herbarium datasets and implications for decision-making on biodiversity conservation in Brazil
Barros, F.S.1, Fernandes, R.A.1, Moraes, M.A.1, Pougy, N.M.1, Caram, J.S.1, Dalcin, E.C.2 and Martinelli, G.2

1 Centro Nacional de Conservação da Flora/Jardim Botânico do Rio de Janeiro, Rua Pacheco Leão 915, 22460-030, Rio de Janeiro – Brazil.
2 Instituto de Pesquisa Jardim Botânico do Rio de Janeiro, Rua Pacheco Leão 915, 22460- 030, Rio de Janeiro – Brazil.

Abstract: The present level of biodiversity depletion and loss makes quality datasets important for biodiversity conservation. However poor data quality is still critical and limits the usefulness of these datasets. Thereby, data quality assessments are important to ensure a responsible use of those datasets. The Brazilian National Centre for Flora Conservation was created with the objective of assessing the extinction risk of plant species, enabling conservation action planning. In this context, a dataset was created after the compilation of occurrence records of threatened species. The present study aims to assess quality of the dataset and records, and to test quality improvement after data cleaning efforts. We have used the five-component scheme for assessing dataset quality. Significance of the differences between expected and observed proportions were tested using the degree of confidence between them. The Mann-Whitney test was used to compare errors between the original dataset and the cleaned out one. Results indicate poor quality, not only for dataset (p<0.10) but also for records (p<0,10). Only 54,306 records (22.30%) were considered of good quality. Logical inconsistencies in the dataset were present in 8,237 records (3.37%).

Keywords: biodiversity conservation, data cleaning, data quality, spatial accuracy.

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BarrosAccuracy2012.pdf95.26 KB

Study of the positional quality obtained by the method Precise Point Positioning, PPP, for use in georeferencing of rural properties

Study of the positional quality obtained by the method Precise Point Positioning, PPP, for use in georeferencing of rural properties
Michel Balin de Brum1 , Adriane Brill Thum2

1. Unisinos, Av. Unisinos, 950-Esp. em Informações Espaciais Georreferenciadas michelbrum@ibest.com.br
2. Unisinos, Av. Unisinos, 950 adrianebt@unisinos.br

Abstract: Precise Point Positioning - PPP, which are used the precise ephemeris and clock corrections of satellite data with the carrier wave, so static or kinematic. Established itself as the choice of statistical test every Monday, from 28/02/2005 to 22/11/2010 totaling 296 days of raw GNSS data files of twenty four hours. The observation files tablets were sent individually to the IBGE-PPP to make the postprocessing. The PPP has been converted into geodetic coordinates in UTM coordinate plane. Comparisons made by subtraction of coordinates of the Brazilian Network for Continuous Monitoring -RBMC SMAR, coordinates Officers SIRGAS 2000, the date of survey coordinates and coordinates of two, four and 24 hours. The latter resulted in a comparison between the different screening times. The results are satisfactory as to the positional accuracy required by INCRA. Which remained throughout the six years studied. Observing small variations in the position of the coordinates, including shortening the time of screening, two hours. Therefore, the PPP technique proved a modern, safe and easy to use in providing precision geodetic surveys.

Keywords: GPS, PPP, Precise Point Positioning.

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The Positional and Thematic Accuracy for Analysis of Multi-Temporal Satellite Images on Mangrove Areas

The Positional and Thematic Accuracy for Analysis of Multi-Temporal Satellite Images on Mangrove Areas
Paulo Rodrigo Zanin¹, Carlos Antonio O. Vieira²

1.Universidade Federal de Santa Catarina, Campus Universitário Reitor João David Ferreira Lima, Trindade-Florianópolis-SC, CEP 88040-970 (paulorzgeo@gmail.com)
2.Universidade Federal de Santa Catarina, Campus Universitário Reitor João David Ferreira Lima, Trindade-Florianópolis-SC, CEP 88040-970 (carlos.vieira@ufsc.br)

Abstract: This article presents standard procedures on the positional and thematic accuracy for analysis of multi-temporal satellite images on mangrove areas. The Landsat TM 5 imagery for the years: 1986, 1997, and 2010 were used to identify and quantify the anthropogenic pressure, through the process of urbanization on coastal marine ecosystems surrounding neighborhoods at the city of Florianópolis – SC, Brazil. Geometric correction of these images reached a positional accuracy ¼ pixels. On the thematic accuracy, a supervised classification, using a maximum likelihood classifier, was validated using Kappa Index statistics (Conglaton and Green, 1999). The results show that high classification accuracies were reached. However, marine processes, such as coastal erosion on the shoreline and dynamics of ecosystems (e.g., natural succession of species of different vegetation types, as well as the seasonal variation of reflectance of plants) are factors to consider when assessing the reliability of image classifications. 

 Keywords: Mangrove Areas, Multi-Temporal Analysis, Land Cover Classification.

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ZaninAccuracy2012.pdf148.47 KB

The effects of training set size for performance of support vector machines and decision trees

The effects of training set size for performance of support vector machines and decision trees
Taskin Kavzoglu and Ismail Colkesen Gebze 

Institute of Technology, Department of Geodetic and Photogrammetric Engineering, Cayirova Campus, 41400, Gebze-KOCAELI, TURKEY. (1kavzoglu@gyte.edu.tr, icolkesen@gyte.edu.tr)

Abstract: Thematic maps representing the characteristics of the Earth’s surface have been widely used as a primary input in many land related studies. Classification of remotely sensed images is an effective way to produce these maps. Selecting proper number of samples and classification method are essential issues to produce accurate thematic maps. In the literature, many classification algorithms have been developed and their performances have been analyzed for different data sets. In this study, support vector machines (SVMs) and decision trees (DTs), relatively new and widely used methods, were applied to produce land use/land cover thematic map of the study area, which covers the center of Trabzon province of Turkey. Training data sets at various sizes were used to investigate the effect of the training set size on the classification accuracy. Variations in the classification performances were analyzed using overall classification accuracy and Kappa coefficient derived from the error matrix. Furthermore, McNemar’s and z tests were employed to determine the statistical significance of differences in classifier performances depending on the training sample size. Results showed that classification performances of SVMs and DTs improved till a certain level

Keywords: Support vector machines, decision trees, accuracy comparison, McNemar’s test.

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kavzogluAccuracy2012.pdf71.68 KB

The use of spatial-temporal analysis for noise reduction in MODIS NDVI time series data

The use of spatial-temporal analysis for noise reduction in MODIS NDVI time series data

Julio Cesar de Oliveira1,2, José Carlos Neves Epiphanio1, Camilo DalelesRennó1

1.Instituto Nacional de Pesquisas Espaciais (INPE), Divisão de Sensoriamento Remoto, Av.dos Astronautas, 1758, Caixa Postal 515, 12245-970, São José dos Campos/SP, Brazil. (oliveirajc@ufv.br, epiphanio@dsr.inpe.br, camilo@dpi.inpe.br)
2. Universidade Federal de Viçosa (UFV), Departamento de Engenharia Civil – Setor de Engenharia de Agrimensura, Campus UFV, 36570-000, Viçosa, MG, Brazil.

Abstract: Time series of satellite data can be employed for mapping the development of vegetation in space and time. However, noise induced by cloud contamination and atmospheric variability affects data quality. Science Datasets is an integral part of the MODIS Land production chain that focuses on evaluating and documenting the scientific quality of products. This study aims at the reconstruction of time series of MODIS NDVI data based on the reliability of the science data sets and on a spatial-temporal analysis of the low quality pixels. The MOD13Q1 product was analyzed over a period of one year. After identifying the pixel with the lowest guarantee of quality, it is estimated by regression analysis among neighboring pixels classified as high-quality. The combination of the per-pixel quality and spatial-temporal information is a promising method for reconstructing high-quality MODIS NDVI time series. 

Keywords: Time Series, MODIS NDVI, Reliability, Spatial-temporal analysis.

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OliveiraAccuracy2012.pdf477.02 KB

Uncertainties assessment in orbital or airborne sensors absolute calibration

Uncertainties assessment in orbital or airborne sensors absolute calibration

Cibele Teixeira Pinto1,2, Flávio Jorge Ponzoni1, Giovanni Araújo Boggione1, Leila Maria Garcia Fonseca1,
Ruy Morgado de Castro
2,3

1. Instituto Nacional de Pesquisas Espaciais – INPE, Caixa Postal 515 - 12227-010 - São José dos Campos - SP, Brasil (cibele@dsr.inpe.br, flavio@dsr.inpe.br, giovanni@dsr.inpe.br, leila@dsr.inpe.br)
2. Instituto de Estudos Avançados - IEAv/CTA, Caixa Postal 6044 - 12.231-970 - São José dos Campos - SP, Brasil (cibele@ieav.cta.br, rmcastro@ieav.cta.br)
3. Universidade de Taubaté – UNITAU, Caixa Postal 515 - 12201-970 - Taubaté - SP, Brasil (rmcastro@unitau.br)

Abstract: The electro-optical sensor absolute calibration (orbital or airborne) aims to transform the digital numbers present in the images into physical quantities. The orbital sensor calibration procedure frequently considers a reference surface on the ground. Radiometric measurements are taken from this reference surface and the results are compared to those acquired by the sensors to be calibrated. Obviously the complete calibration procedure includes uncertainties that have to be estimated in order to provide confidence to the sensor data. This work aims to evaluate the main uncertainties involved in the process of absolute calibration of eletro-optical sensors in the visible, near and middle infrared regions of the electromagnetic spectrum.

Keywords: absolute calibration, electro-optical sensor, uncertainty, Tuz Gölü

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PintoAccuracy2012.pdf66.88 KB

Uncertainty analysis of a spatiotemporal model for submerged vegetation colonization

Uncertainty analysis of a spatiotemporal model for submerged vegetation colonization

Ligia Flávia Antunes Batista1,2, Nilton Nobuhiro Imai2 ,Luiz Henrique da Silva Rotta2 , Fernanda Sayuri Yoshino Watanabe 2 and Edivaldo Domingues Velini3

1.Federal University of Technology - Parana (UTFPR), Londrina, PR, 86036-370, Brazil (ligia@utfpr.edu.br )
2.Sao Paulo State University, Presidente Prudente, SP, 19060-900, Brazil (nnimai@fct.unesp.br, luizhrotta@yahoo.com.br, fernandasyw@yahoo.com.br)
3.Sao Paulo State University, Botucatu, SP, 18603-970, Brazil (velini@fct.unesp.br)

Abstract:This work presents an uncertainty analysis applied to the results of an ecological model. This model describes the development of submerged macrophytes colonization in a brazilian reservoir, between Sao Paulo and Parana states. To build the model we map the submerged vegetation with hydroacoustic technique to estimate submerged canopy height. Data about the light penetration into the water were also collected in some points. The dynamic model was elaborated with two variables: depth and attenuation coefficient (kt). Monte Carlo technique was used to evaluate how the existing uncertainty in the data acquisition process and measurement tools, propagated to the kriging interpolation, affects the model results. It was possible to evaluate the model output histograms, and the Root Mean Square Error (RMSE) of each simulated point in relation to the observed one. The confidence intervals were also calculated with the 5th and 95th percentiles. With this uncertainty analysis, the interval time and the points with the lowest uncertainty could be identified. 

 Keywords: Monte Carlo, kriging, mapping, ecology, macrophytes.

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BatistaAccuracy2012.pdf207.66 KB

Using Spatial Uncertainties to Create Probability Maps for Continuous Attributes

Using Spatial Uncertainties to Create Probability Maps for Continuous Attributes
Carlos Alberto Felgueiras, Eduardo Celso Gerbi Camargo, Jussara de Oliveira Ortiz and Sérgio Rosim

DPI-INPE, Av. Dos Astronautas, 1758, Jardim da Granja, São José dos Campos, SP (carlos@dpi.inpe.br, eduardo@dpi.inpe.br, jussara@dpi.inpe.br, sergio@dpi.inpe.br)

Abstract: This work presents a methodology to create probability maps for spatial continuous attributes based on indicator geostatistical approaches. The indicator kriging and the indication simulation approaches can be used to infer approximations of conditional cumulative distribution functions (cdf) for continuous attributes at different spatial locations of interest. The cdfs are conditioned to a set of spatial points containing continuous attribute values and sampled in a geographic region of interest. The conditional cdfs are then used to infer probability maps of exceeding, or being smaller than, a given threshold, or a predefined attribute, value. In this work it was used an elevation data set sampled in Florianópolis Island, the capital of Brazilian state Santa Catarina, as a case study to illustrate the methodology to create such probability maps.

Keywords: uncertainty modeling, indicator geostatistics, kriging, simulation, probability maps.

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FelgueirasAccuracy2012.pdf175.76 KB

Using of local indicators of spatial association for evaluation of spatial accuracy of DEM

Using of local indicators of spatial association for evaluation of spatial accuracy of DEM
Jana Svobodova, JakubMirijovsky, Ales Vavra, Jan Brus and Helena Kilianova Palacky 

University in Olomouc, tr. Svobody 26, Olomouc, 771 46 (j.svobodova@upol.cz, jakub.mirijovsky@upol.cz, ales.vavra@upol.cz, jan.brus@upol.cz, helena.kilianova@upol.cz)

Abstract: In the study, whose results are presented in the paper, the statistical method LISA (local indicators of spatial association) has been used for the delimitation of the areas with the statistical significant error values. The error values obtained by subtraction of estimated values of altitude (DEM) from the reference surface were used as the input data for the local spatial cluster analysis. The aim of an interpretation of the results of local cluster analysis was to determine the behaviour of errors (location and size) from the perspective of different quality DEMs, i.e. DEMs created by different interpolation methods and their settings. The main significance of LISA lies in the spatial expression that allows you to monitor the extent, distribution and overall structure of clusters. When comparing the results derived from selected high-quality and low-quality DEM or DEM created by the different interpolation methods it is necessary to realize the different importance of these three aspects. This was reflected in the creation of rules for interpretation and evaluation the results of local cluster analysis, which is one of the main results of the study.

Keywords: DEM, LISA, clusters, statistical significance, spatial accuracy.

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SvobodovaAccuracy2012.pdf484.7 KB

Vectorial analysis modeling to determine spatial uncertainty among different data production scales due to error propagation

Vectorial analysis modeling to determine spatial uncertainty among different data production scales due to error propagation
Cárdenas A1., Treviño E.J2., Aguirre O.A2., Jiménez J2., González M.A2., Antonio X3., and Sánchez G1 .

1. Abraham Cárdenas Tristán, Guillermo Sánchez Díaz. Universidad Autónoma de San Luis Potosí (UASLP), Facultad de Ingeniería, Av. Dr. Manuel Nava #8, Zona Universitaria. C.P. 78290, San Luis Potosí, S.L.P. México. (abraham.cardenas@uaslp.mx, guillermo.sanchez@uaslp.mx)
2. Eduardo Javier Treviño Garza, Oscar Alberto Aguirre Calderón, Javier Jiménez Pérez, Marco Aurelio González Tagle. Universidad Autónoma de Nuevo León (UANL), Facultad de Ciencias Forestales. Carretera Nacional km. 145. AP 41. C.P. 67700. Linares, Nuevo León, México. (ejtrevin@gmail.com, oscar.aguirrecl@uanl.edu.mx, javier.jimenezp@uanl.edu.mx, marco.tagle@gmail.com)
3 Xanat Antonio Némiga. Universidad Autónoma del Estado de México (UAEM), Facultad de Geografía. Cerro de Coatepec s/n, Ciudad Universitaria, Toluca, Edo, de México. C.P. 50100. (xanynemiga@rocketmail.com)

Abstract: Given different processes in recent years to analyze vectorial data production at different scales as well as quality analysis of it, geometric primitive geocodes were analyzed forming the geographic objects representation in order to carry out a geometric-topological recognition from different ways of representing reality vectorially. We used the nearest neighbor rule combined with a classification, determining an iterative search algorithm to analyze polylines that form curves or geographic objects. This algorithm allows modeling certain spatial uncertainty indicators from different types of topological-geometric errors that have propagated significant differences between various scales correspondence of vectorial information.

Keywords: Spatial uncertainty, data quality, maps production, vectorial data, error propagation.

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CardenasAccuracy2012.pdf142.31 KB

Visibility analysis and DEM uncertainty propagation

Visibility analysis and DEM uncertainty propagation
María Victoria Alvarez

LatinGEO Lab, SGM+Universidad ORT del Uruguay (valvarez@adinet.com.uy)

Abstract: This study focuses on the problem of determining the accuracy of the calculated visibility analysis of an iconic building at Montevideo city, the Telecommunication Tower. This 157 m tall building is a very important architectural piece and also a central telecommunication tower. These two aspects must be considered in a visibility analysis: a) the building is expected to take a central role in the urban landscape, on the sightline of a significant part of the city; and b) the transmission scope of the tower must reach as many other telecommunication antennas as possible. The first matter can be considered as a sightline issue that requires calculating unobstructed line-of-sight between two points. The second one requires calculating Fresnel zone clearance to analyze interference by obstacles near the path of the electric radio-wave. In any case, the minimum height for the building is a function of the DEM of the city, conditioned to its expected visibility area. The study focuses particularly on the problem of determining the accuracy of the visibility analysis, by studying the propagation of DEM uncertainty.

Keywords: DEM uncertainty, visibility analysis, Monte Carlo, variogram.

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AlvarezAccuracy2012.pdf113.39 KB