DocumentCode
1582616
Title
Preliminary research on macro valuation approach of vegetation ecology in islands based on RS
Author
Tan, Yong-hua ; Zhao, Qing-Ying ; Ding, Zhao-dong ; Yu, Miao
Author_Institution
Second Institute of Oceanography, SOA, Hangzhou, China
fYear
2012
Firstpage
1
Lastpage
6
Abstract
The vegetation plays an important role in island ecosystems, it is necessary to explore a fast and effective evaluation approach of vegetation ecology in resource management. As we know, the remote sensing has the advantages of real time, dynamic, and large-scale synchronous observation. Using the remote sensing data to evaluate vegetation gives a relatively low-cost and efficient approach in island development and protection activities. A certain evaluation approach is needed to compare the vegetation status in different islands, and also some criteria to outline the vegetation status on an island. This paper summers up an evaluation approach for evaluating the whole vegetation ecology. Based on the dimidiate pixel model and NDVI, this paper provides an Island Vegetation Ecological Evaluation Index, which is used to estimate ecosystem´s developing status. The related method based on remote sensing data is also demonstrated in the case study. The three largest islands of Zhoushan archipelago are chosen as the case study objects. Using TM data, the vegetation coverage in each island is calculated, classified, and finally the Island Vegetation Ecological Evaluation Index is evaluated. The result shows that Zhoushan Island has the highest index value, refers to good ecological status, followed by Liuheng Island, then Daishan Island, and it is matched with the land use type and the intensity of human development on the island
Keywords
Island Vegetation Ecological Evaluation Index; NDVI; island; remote sensing; vegetation coverage;
fLanguage
English
Publisher
ieee
Conference_Titel
World Automation Congress (WAC), 2012
Conference_Location
Puerto Vallarta, Mexico
ISSN
2154-4824
Print_ISBN
978-1-4673-4497-5
Type
conf
Filename
6321377
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