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Land use/land cover (LULC) classification with MODIS time series data and validation in the Amur River Basin |
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| Authors: | Kaishan Song Zongmin Wang Qingfeng Liu Dianwei Liu V V Ermoshin S S Ganzei Bai Zhang Chunying Ren Lihong Zeng Jia Du |
| Institution: | 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China 2. Tourism and Geography College, Jilin Normal University, Siping, China 3. Pacific Institute of Geography, Far-Eastern Branch, Russian Academy of Sciences, Vladivostok, Russia |
| Abstract: | There is a need for improved and up-to-date land use/land cover (LULC) data sets over an intensively changing area in the Amur River Basin (ARB) in support of science and policy applications focused on understanding of the role and response of the LULC to environmental change issues. The main goal of this study was to map LULC in the ARB using MODIS 250-m Normalized Difference Vegetation Index (NDVI), Land Surface Vegetation Index (LSWI), and reflectance time series data for 2001 and 2007. Another goal was to test the consistency of the classification results using relatively coarse resolution MODIS imagery data in order to develop a methodology for rapid production of an up-to-date LULC data set. The results on MODIS land cover were evaluated using existing land use/cover data as derived from Landsat TM data. It was found that the MODIS 250-m NDVI data sets featured sufficient spatial, spectral and temporal resolution to detect unique multi-temporal signatures for the region’s major land cover types. It turned out that MODIS 250 NDVI time series data have high potential for large-basin land use/land cover monitoring and information updating for purposes of environmental basin research and management. |
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