Mapping forest type using Landsat TM images encoun ters many problems especially when applied in montane landscapes with complex terrain. In this paper we evaluated the effects of selected data inputs and c lassification methods on the accuracy of forest type mapping in a complex terrain landscape in mountainous southwest China. Results show that the accuracy of a forest type map produce d by the original Landsat TM bands data alone is not acceptable, but the integration of top ographic data with Normalised Difference Vegetation Index (NDVI) and Principle Components (P Cs) improves the mapping accuracy by 15% and 14%, respectively. In addition, the compari son of two-classification methods showed that a GIS expert system (EXPERT) outperforms the m aximum likelihood classifier (MLC) by 9%. It is concluded that combination of topographic data together with NDVI or PCs enable production of more reliable and accurate forest map s in landscapes with complex terrain. Where reliable field knowledge is available, expert systems show potential for producing affordable forest type maps as accuracy as those ob tained by conventional classifiers.
Publication year
2007
Authors
Yang X F; Skidmore A K; Melick D R; Zhou Z M; Xu, J.
Language
English
Keywords
expert systems, mapping
Geographic
China
