대한원격탐사학회:학술대회논문집 (Proceedings of the KSRS Conference)
- 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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- Pages.429-432
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- 1999
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- 1226-9743(pISSN)
Vegetation Classification from Time Series NOAA/AVHRR Data
- Yasuoka, Yoshifumi (Institute of Industrial Science, University of Tokyo) ;
- Nakagawa, Ai (Institute of Industrial Science, University of Tokyo) ;
- Kokubu, Keiko (Institute of Industrial Science, University of Tokyo) ;
- Pahari, Krishna (Institute of Industrial Science, University of Tokyo) ;
- Sugita, Mikio (Yamanashi Institute of Environmental Sciences) ;
- Tamura, Masayuki (National Institute for Environmental Studies)
- 발행 : 1999.11.01
초록
Vegetation cover classification is examined based on a time series NOAA/AVHRR data. Time series data analysis methods including Fourier transform, Auto-Regressive (AR) model and temporal signature similarity matching are developed to extract phenological features of vegetation from a time series NDVI data from NOAA/AVHRR and to classify vegetation types. In the Fourier transform method, typical three spectral components expressing the phenological features of vegetation are selected for classification, and also in the AR model method AR coefficients are selected. In the temporal signature similarity matching method a new index evaluating the similarity of temporal pattern of the NDVI is introduced for classification.