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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhiming Zhan Qiming Qin Xin Wang Ghulam, A. |
| Copyright Year | 2004 |
| Description | Author affiliation: Inst. of Remote Sensing & GIS, Peking Univ., Beijing (Zhiming Zhan; Qiming Qin) |
| Abstract | NDVI is a land surface parameter which plays an important role in ecology. It is also sensitive in the circulation process between land surface and atmosphere. The earlier research indicated that NDVI has closely relationship with some main biophysics parameters such as photosynthetically active radiation, leaf area index, biomass of vegetation, and so on. So NDVI is widely used in the study of global vegetation. In this article, it was presented that ecological indexes have been derived from NDVI using NOAA/AVHRR data by the method of principle component analysis (PCA). After the PCA of NDVI which calculated form the NOAA/AVHRR data, the relationship analysis aimed at the four ecological parameters which derived from NDVI. Then the results show that the PCA can compress the key information into four foremost principal components which would be called the ecological indices (EI). And the first principal component reflects the basic situation of vegetation overlay (EI_all), the second (EI_ss), the third (EI_ws) and the fourth (EI_aw) principal components indicated the vegetation change in seasons respectively. According to the direction curves of seasonal vegetation change, the four principal components seem to be their biological significance |
| Starting Page | 3650 |
| Ending Page | 3653 |
| File Size | 898708 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780387422 |
| DOI | 10.1109/IGARSS.2004.1369910 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-09-20 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Principal component analysis Land surface Vegetation mapping Remote sensing Environmental factors Atmosphere Biophysics Biomass Springs Geographic Information Systems |
| Content Type | Text |
| Resource Type | Article |
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