期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN:2194-9042
电子版ISSN:2194-9050
出版年度:2012
卷号:XXXIX - B8
页码:525-528
DOI:10.5194/isprsarchives-XXXIX-B8-525-2012
出版社:Copernicus Publications
摘要:The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year) SR(Surface Reflectance 8-Day L3) and NBAR(Nadir BRDF-Adjusted Reflectance 16-Day L3) products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR product and NBAR product showed similar classification accuracy of 99%
关键词:Global; Land Cover; Classification; Algorithms; Multi-temporal; Multi-spectral