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Remote Sens. 2016, 8(4), 290; doi:10.3390/rs8040290

Exploring Long Term Spatial Vegetation Trends in Taiwan from AVHRR NDVI3g Dataset Using RDA and HCA Analyses

1
Department of Civil Engineering, National Chung Hsing University, 145, Xingda Rd., South Dist., Taichung 402, Taiwan
2
Center for Environmental Restoration and Disaster Reduction, National Chung Hsing University, 145, Xingda Rd., South Dist., Taichung 402, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Heiko Balzter, Alfredo R. Huete and Prasad S. Thenkabail
Received: 30 November 2015 / Revised: 2 March 2016 / Accepted: 21 March 2016 / Published: 29 March 2016
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Abstract

Due to 4000 m elevation variation with temperature differences equivalent to 50 degrees of latitudinal gradient, exploring Taiwan’s spatial vegetation trends is valuable in terms of diverse ecosystems and climatic types covering a relatively small island with an area of 36,000 km2. This study analyzed Taiwan’s spatial vegetation trends with controlling environmental variables through redundancy (RDA) and hierarchical cluster (HCA) analyses over three decades (1982–2012) of monthly normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) NDVI3g data for 19 selected weather stations over the island. Results showed two spatially distinct vegetation response groups. Group 1 comprises weather stations which remained relatively natural showing a slight increasing NDVI tendency accompanied with rising temperature, whereas Group 2 comprises stations with high level of human development showing a slight decreasing NDVI tendency associated with increasing temperature-induced moisture stress. Statistically significant controlling variables include climatic factors (temperature and precipitation), orographic factors (mean slope and aspects), and anthropogenic factor (population density). Given the potential trajectories for future warming, variable precipitation, and population pressure, challenges, such as land-cover and water-induced vegetation stress, need to be considered simultaneously for establishing adequate adaptation strategies to combat climate change challenges in Taiwan. View Full-Text
Keywords: NDVI; spatial vegetation trend; environmental variables; adaptation strategy; climate change; Taiwan NDVI; spatial vegetation trend; environmental variables; adaptation strategy; climate change; Taiwan
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tsai, H.P.; Lin, Y.-H.; Yang, M.-D. Exploring Long Term Spatial Vegetation Trends in Taiwan from AVHRR NDVI3g Dataset Using RDA and HCA Analyses. Remote Sens. 2016, 8, 290.

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