DocumentCode
2527676
Title
Application research of MODIS data in monitoring land use change in Fujian
Author
Pan, Weihua ; Zhang, Chungui ; Chen, Hui ; Cai, Yiyong ; Chen, Jiajin ; Li, Lichun
Author_Institution
Inst. of Meteorol. Sci. in Fujian, Fuzhou, China
fYear
2011
fDate
June 29 2011-July 1 2011
Firstpage
413
Lastpage
416
Abstract
It was necessary and significant to explore the low-cost, high-precision and real-time access method of land-use/cover using the MODIS data multi-temporal and multi-spectral for quickly assess regional land use/cover change. Firstly, the study used maximum values compose (MVC) to select the optimal MODIS data in Fujian study area because there were mountainous landform and cloudy climatic condition in study area. Secondly, the characteristic variables of surface albedo, vegetation index(NDVI), water index(NDWI) and so on were combined, Moreover, the decision tree classifier system was established based on multi-factors composition for land cover/use classification in Fujian province. The results showed that the decision tree classifier was better than conventional maximum likelihood classifier, and was well applied the MODIS data to classify the land-use/cover of Fujian, because the decision tree classifier system took advantage of the MODIS multi-spectrum characters and artificial intelligence and could achieve a certain high precision, which made an important impact on monitoring land change and protecting arable land.
Keywords
decision trees; geophysical image processing; land use planning; maximum likelihood estimation; vegetation; China; Fujian; MODIS data; artificial intelligence; cloudy climatic condition; decision tree classifier; land use change monitoring; maximum likelihood classifier; maximum values compose; mountainous landform; surface albedo; vegetation index; water index; Accuracy; Decision trees; Economics; MODIS; Monitoring; Remote sensing; Vegetation; Decision tree classifier system; Fujian; Land-use/cover; NDVI; Remote sensing;
fLanguage
English
Publisher
ieee
Conference_Titel
Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on
Conference_Location
Fuzhou
Print_ISBN
978-1-4244-8352-5
Type
conf
DOI
10.1109/ICSDM.2011.5969077
Filename
5969077
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