DocumentCode :
3286055
Title :
Land Cover Classification in Heihe River Basin with Time Series - MODIS NDVI Data
Author :
Gu, Juan ; Li, Xin ; Huang, Chunlin
Author_Institution :
Cold & Arid Region Environ. & Eng. Res. Inst., Lanzhou
Volume :
2
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
477
Lastpage :
481
Abstract :
Normalized difference vegetation index (NDVI) is a very important vegetation index, which has been widely applied in research regarding global environmental and climatic change. In this work, 16-Day L3 Global 1 km SIN Grid NDVI data sets in Heihe River Basin from MODIS vegetation index (VI) products (MOD13A2) during 2003-2005 are extracted and used for generating a one-year new NDVI data based on a simple three-point smoothing technique which can generally capture the annual feature of vegetation change. Then we obtain the independent component images by performing independent component analysis (ICA) transform on the smoothing NDVI data as a feature extractor. Then a support vector machine (SVM) is utilized to construct classifiers based on the ICA-extracted new features for land cover classification and a land cover map of Heihe river basin was obtained. At last, the accuracy assessment results prove that the classification framework proposed in this paper is efficient.
Keywords :
feature extraction; support vector machines; time series; vegetation mapping; Heihe river basin; ICA; MODIS vegetation index; SVM; feature extraction; feature extractor; independent component analysis; land cover classification; normalized difference vegetation index; support vector machine; three-point smoothing technique; time series; Data mining; Independent component analysis; MODIS; Mesh generation; Rivers; Silicon compounds; Smoothing methods; Support vector machine classification; Support vector machines; Vegetation mapping; Land cover classification; NDVI; Time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
Type :
conf
DOI :
10.1109/FSKD.2008.517
Filename :
4666163
Link To Document :
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