DocumentCode
410896
Title
Land cover change analysis using the NOAA/AVHRR NDVI datasets, northwest of China
Author
Fuli, Yan ; Zhen, Li ; Xiangtao, Fan ; Hu, Yang ; Yun, Shao ; Huafu, Lu ; Huanyin, Yue ; Xiao, Cheng
Author_Institution
Inst. of Remote Sensing Applications, Chinese Acad. of Sci., Beijing, China
Volume
4
fYear
2003
fDate
21-25 July 2003
Firstpage
2287
Abstract
This paper analyzes the long sequence time series NDVI datasets and yields statistic results respectively, using simple differencing, slope map of biomass, and principle component analysis techniques. The correlation characteristics for the images of change acquired according to the algorithms mentioned above, implies that the majority pixels of the different land covers have experienced nearly the same changes in change direction and magnitude. The change of biomass of land-cover classifications between the 1980s and present are detected from the satellite data, and the land covers of the former 10 years (1981-1991) are in a better growth than the latter 10 years (1991-2001). Based on the discussion of the exotic factors affected the NDVI, like satellite shift or sensor degradation, the statistics on the slope images of biomass indicates that land cover deteriorated extensively in the past few years. The degradation of grassland or deforestation of forest regions confirmed such a fact that the status of the vegetation of the west part of China in the past 20 years (1981-2001) is suffering an extensive deterioration and only an improvement in part of the region.
Keywords
geophysical signal processing; terrain mapping; vegetation mapping; AD 1981 to 2001; AVHRR datasets; China; NDVI datasets; NOAA datasets; biomass; deforestation; forest regions; grassland degradation; land cover change analysis; land cover classifications; principle component analysis; satellite data; satellite shift; sensor degradation; slope images; slope map; vegetation; Biomass; Biosensors; Change detection algorithms; Degradation; Image sensors; Image sequence analysis; Pixel; Satellites; Statistical analysis; Time series analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
Print_ISBN
0-7803-7929-2
Type
conf
DOI
10.1109/IGARSS.2003.1294417
Filename
1294417
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