The Driving Force Analysis of NDVI Dynamics in the Trans-Boundary Tumen River Basin between 2000 and 2015
CholHyok Kang,
Yili Zhang,
Zhaofeng Wang,
Linshan Liu,
Huamin Zhang and
Yilgwang Jo
Additional contact information
CholHyok Kang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, China
Yili Zhang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, China
Zhaofeng Wang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, China
Linshan Liu: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, China
Huamin Zhang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing 100101, China
Yilgwang Jo: Institute of Earth Environmental Information (IEEI), Pyongyang, Democratic People’s Republic of Korea
Sustainability, 2017, vol. 9, issue 12, 1-19
Abstract:
Vegetation dynamics in relation to climatic changes and anthropogenic activities is critical for terrestrial ecosystem management. The objective of this study was to investigate spatiotemporal change of vegetation and their driving forces during growing seasons (between April and October and including the spring, summer and autumn) in the Tumen River Basin (TRB) using Normalized Difference Vegetation Index (NDVI) and climate data spanning from 2000 to 2015. A linear regression, Pearson correlation coefficients and the residual trend (RESTREND) was applied for this study. Our results demonstrate that vegetation increased during different periods of the growing season in most of the areas of the TRB over 16 years. Our results demonstrate that vegetation increased during different periods of the growing season in most of the areas of the TRB over 16 years; those in growing season (spring, summer, and autumn) were characterized by the increase in rates by 0.0012/year, 0.0022/year, 0.0011/year, and 0.0019/year, respectively. Forested regions are characterized by the largest increase (0.0021/year) in NDVI compared with other vegetation types across the entire study area. The trends in NDVI across the study area were influenced by both climatic variations and human disturbances. The human activities such as reforestation and agricultural practices are the primary driver, greater than climatic factors, during growing season, including summer and autumn. Temperature and precipitation has had a significant influence on NDVI in a limited area (temp = 0.86%, p < 0.05 and precipitation = 1.93%, p < 0.05) during growing season. The significant role of precipitation on NDVI change throughout growing season and the summer is larger than that of temperature across the TRB, although the influence of the latter becomes most significant during the spring and autumn. The RESTREND method shows that human activity during the growing season, including the spring, summer, and autumn, have led to enhancements in NDVI across more than 70% of the TRB over the last 16 years, with the most significant improvements seen in forested land and farmland. At the same time, a significant reduction in residual (i.e., degraded areas) NDVI values for different growing seasons had characterized farmland and urban land at low altitudes. This study provides important background information regarding the influence of human activities on land degradation and provides a scientific foundation for the development of ecological restoration policies within the TRB. We found that the RESTREND method can be used to detect human drivers of vegetation in the regions with semi-humid and humid monsoon, where the significant correlation between NDVI and climatic factors exists.
Keywords: NDVI; trend analysis; climatic effects; residual trend; Tumen River Basin (TRB) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:9:y:2017:i:12:p:2350-:d:123287
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