Modeling Vegetation Index Changes in Taiwan from 2000 to 2020
DOI:
https://doi.org/10.53840/myjict6-2-84Kata kunci:
Normalized difference vegetation index, cubic spline function, multivariate regression modelAbstrak
Vegetation changes play an important roles in climate change. Information from patterns and trends of these factor reveals the state of the climate in a particular area and can be used to set up a proper monitoring program. This study aimed to investigate the annual seasonal patterns and trends of Normalized Difference Vegetation Index (NDVI) by sub-region and by region and to estimate NDVI increase per decade by region in Taiwan. NDVI time series data from 2000 to 2020 were downloaded from the MODIS website. The natural cubic spline method was used to model NDVI annual seasonal patterns and linear regression was used to investigate the trends. Furthermore, multivariate regression was applied to adjust spatial correlation and to estimate NDVI increases in each sub-region and region. The results show the NDVI increase in March of sub-region 1, 2, 3, 4, and 7 and sub-region 3 and 6 show two peaks in each year. The trends show sub-region 8 in region 1 had the highest mean NDVI which was above 0.8, while sub-region 2 had the lowest mean NDVI which was below 0.4. However, NDVI shows increasing trend in almost sub-region except sub-region 15, 22, 23, 27 and 36. In addition, the NDVI in all regions had increasing trends, except in the eastern Taiwan with stable trend. The average increased of NDVI was 0.01 per decade. In conclusion, vegetation index in Taiwan is considerably increasing while the causes of the increasing trends need to be examined in further studies.
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Rujukan
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