RENalyzer: A tool to facilitate the spatial accuracy assessment of digital cartography

Thomas Bartoschek 1,2, Marco Painho 1, Roberto Henriques 1, Miguel Peixoto 1, Ana Cristina Costa 1
1 Instituto Superior de Estatística e Gestão de Informação
Universidade Nova de Lisboa
Campus de Campolide, 1070-312 Lisboa, Portugal
Tel.: + 351 21 387 04 13; Fax: + 351 21 387 21 40
tbarto@isegi.unl.pt, painho@isegi.unl.pt, roberto@isegi.unl.pt, mpeixoto@isegi.unl.pt, ccosta@isegi.unl.pt
2 Institute for Geoinformatics
University of Münster
Robert-Koch-Str. 26-28, 48149 Münster, Germany
Tel.: +49 (0) 251 83 33083; Fax: +49 (0) 251 83 39763
bartoschek@uni-muenster.de

Abstract
Managing spatial data in paper maps is quite different from managing digital spatial information. Sometimes manual vectorization  of scanned maps is the only way to produce digital cartography, especially when the only  source of spatial information is a paper map. Digital scanning and manual vectorization are  two processes well known for adding error to data and accuracy is a particularly important issue for users of spatial information. The National Ecological Reserve (REN) established in the Portuguese national law protects areas with a diversified bio-physical structure and specific ecological characteristics. This information is often required to manage several human activities, such as mineral extraction, real estate, industry, tourism, etc. REN maps were originally produced in paper and were vectorized to produce digital cartography. The objective of this study is to measure the spatial accuracy and to assure the conformity with the original cartography. The accuracy of the REN digital cartography was assessed through a stratified sampling scheme, as described in Peixoto et al. (2006). The preparation of the digitized maps for the needs and the appliance of the sampling method as well as the data quality control were combined in the RENalyzer application. The application calculates areas of all polygons respective to their attribute classes using object oriented computation methods. As described in the sampling method, all class combinations (overlaying polygons) are considered. These areas and the global area are the base of the global sample size and the sample size per class  and class combination. Considering these guidelines  the application creates random  points in randomly chosen polygons. The data quality control is done by facilitating the map reviewing process. After adding the scanned map and automatically setting map properties, the application zooms to each point and allows a fast and accurate quality control. Errors in digitizing are computed and classified in spatial and thematic errors. The attributes  distance to original class and error description are added to the table.

Keywords: data quality, quality control, geocomputation, National Ecological Reserve

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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