Comparing accuracy of classified Landsat data with land use maps reclassified from the stand type maps

Fatih Sivrikaya, Sedat Keles, Günay Cakir, Emin Zeki Baskent And Selahattin Köse
Karadeniz Technical University, Faculty of Forestry
61080, Trabzon, Turkey
Tel: +90 462 377 37 34, Fax: +90 462 325 74 99;,,,

A key step in natural resource management is the delineation of land units that are similar relative to type, structure, and productivity of vegetation in a given area. This is accomplished by land classification system on the basis of satellite images with appropriate specifications that serves as an essential database for forest management planning. Managing forests on an ecosystem basis relies upon accurate estimation of forest land classification that responds in a similar manner to management practices. The integration of remotely sensed data into a GIS offers a wide variety of new perspectives and  possibilities for the analysis, evaluation and interpretation of such data, in combination with auxiliary digital information maps.The aim of this study is to compare accuracy of classified data with land use maps reclassified from the stand type maps. Two forest planning areas, Artvin and Bulanıkdere Forest Planning Unit (FPU) in Turkey, were selected as case study areas. Two land use maps were produced using Landsat ETM+ (2000) data and reclassified the  stand type maps. The results suggest that accuracies of classified Landsat ETM+ for Artvin and Bulanıkdere FPU are 82.14 and 88.75%, respectively. Later, classified Landsat ETM+ data were converted to vector database. Landsat ETM+ data and reclassified stand type maps were overlaid the appropriate spatial analysis carried out using GIS. As a result of spatial analysis, accuracy of vectorized Landsat ETM+ data is around 5-10 %, lower than classified Landsat ETM+ data. In addition, according to land use map derived from stand  type map, accuracy of land use map derived from Landsat ETM+ data is 64.2% in Bulanıkdere FPU and 44.2%  Artvin FPU. These differences are resulted from slope and vegetation homogeneity of case study areas, and geometric accuracy. 

Keywords: supervised classification, Landsat, forest management planning, accuracy 

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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