Spatiotemporal analysis of vegetation index after typhoons in the mountainous watershed |
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| Affiliation: | 1. Kibbutzim College, Mordechai Namir 149, Tel Aviv-Yafo, Israel;2. Porter School of Environmental Studies, Tel-Aviv University, Israel;3. Underwater Archaeology Unit of the Israel Antiquities Authority, Rockfeller Museum, Jerusalem, Israel;4. Institute of Archaeology of Tel-Aviv University, Israel;5. Survey of Israel, Lincoln St 1, Tel Aviv-Yafo, Israel;6. Department of Geography, Man and Environment, Beit Berl College, 44905, Israel;1. Graduate School of Agriculture, Hokkaido University, Sapporo 060-8589, Japan;2. Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589, Japan;3. Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo 060-8589, Japan;4. Institute of Arctic Climate and Environment Research, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showamachi, Kanazawa-ku, Yokohama 236-0001, Japan;5. School of Agriculture, Meiji University, Kawasaki 214-8571, Japan |
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| Abstract: | An extensive land cover change was triggered by a series of typhoons, especially Typhoon Morakot in 2009 in Taiwan. The normalized difference vegetation index (NDVI) series from multiple satellite images were applied to monitor the change processes of land cover. This study applied spatiotemporal analysis tools, including empirical orthogonal functions (EOF), and multiple variograms in analyzing space–time NDVI data, and detected the effects of large chronological disturbances in the characteristics of land cover changes. Spatiotemporal analysis delineated the temporal patterns and spatial variability of NDVI caused by these large typhoons. Results showed that mean of NDVI decreased but spatial variablity of NDVI increased after typhoons in the study area. The EOF can clarify the major component of NDVI variations and identify the core area of the NDVI changes. Various approaches showed consistent results that Typhoon Morakot significantly lowered the NDVI in land cover change process. Furthermore, the spatiotemporal analysis is an effective monitoring tool, which advocates the use of the index for the quantification of land cover change and resilience. |
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| Keywords: | Land cover change NDVI Empirical orthogonal functions Variograms Typhoon Remotely sensed images |
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