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ZHANG Jie, SHEN Fang, LIU Zhi-guo. Spectral Analysis and Remote Sensing Detection of Tidal Shoal′sVegetation in the Estuary of Yangtse River(Chinese)[J]. Journal of East China Normal University (Natural Sciences), 2007, (4): 42-48.
Citation:
ZHANG Jie, SHEN Fang, LIU Zhi-guo. Spectral Analysis and Remote Sensing Detection of Tidal Shoal′sVegetation in the Estuary of Yangtse River(Chinese)[J]. Journal of East China Normal University (Natural Sciences), 2007, (4): 42-48.
ZHANG Jie, SHEN Fang, LIU Zhi-guo. Spectral Analysis and Remote Sensing Detection of Tidal Shoal′sVegetation in the Estuary of Yangtse River(Chinese)[J]. Journal of East China Normal University (Natural Sciences), 2007, (4): 42-48.
Citation:
ZHANG Jie, SHEN Fang, LIU Zhi-guo. Spectral Analysis and Remote Sensing Detection of Tidal Shoal′sVegetation in the Estuary of Yangtse River(Chinese)[J]. Journal of East China Normal University (Natural Sciences), 2007, (4): 42-48.
This paper analyzed the spectrum character of preponderant vegetables and distilled wave band using the spectrum of the vegetation through field measure in the estuary of Yangtse River. Considering influence factors such as vegetation growth characteristic, season, vegetation cover in tidal shoal,vegetation index of combined characteristic wave bands was used to detect tide shoal's vegetation, in order that it could improve the vegetation classification precision and detect the changes of vegetation environment. The paper computed Vegetation Index of Ratio Vegetation Index(RVI), Normalized Difference Vegetation Index(NDVI), SoilAdjusted Vegetation Index(SAVI) and Modified SoilAdjusted Vegetation Index (MSAVI), and analyzed the advantages and disadvantages of the four vegetation indexes in different covers and seasons. Then used these indexes to detect the vegetation classification in TM image. In conclusion, combining the field measure and taking season factor into account for better classification. MSAVI wins the advantage of each vegetation index in classification.