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The Driving Force Analysis of NDVI Dynamics in the Trans-Boundary Tumen River Basin between 2000 and 2015

Author

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  • 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
    University of Chinese Academy of Sciences, Beijing 100049, 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
    University of Chinese Academy of Sciences, Beijing 100049, China
    CAS Centre for Excellence in Tibetan Plateau Earth Sciences, 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)

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.

Suggested Citation

  • CholHyok Kang & Yili Zhang & Zhaofeng Wang & Linshan Liu & Huamin Zhang & Yilgwang Jo, 2017. "The Driving Force Analysis of NDVI Dynamics in the Trans-Boundary Tumen River Basin between 2000 and 2015," Sustainability, MDPI, vol. 9(12), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2350-:d:123287
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    References listed on IDEAS

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    1. Li, Zhihui & Deng, Xiangzheng & Yin, Fang & Yang, Cuiyuan, 2015. "Analysis of climate and land use changes impacts on land degradation in the North China Plain," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1-11.
    2. Fang Huang & Shuangling Xu, 2016. "Spatio-Temporal Variations of Rain-Use Efficiency in the West of Songliao Plain, China," Sustainability, MDPI, vol. 8(4), pages 1-19, March.
    3. Jie Lian & Xueyong Zhao & Xin Li & Tonghui Zhang & Shaokun Wang & Yongqing Luo & Yangchun Zhu & Jing Feng, 2017. "Detecting Sustainability of Desertification Reversion: Vegetation Trend Analysis in Part of the Agro-Pastoral Transitional Zone in Inner Mongolia, China," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
    4. Haidong Li & Yingkui Li & Yuanyun Gao & Changxin Zou & Shouguang Yan & Jixi Gao, 2016. "Human Impact on Vegetation Dynamics around Lhasa, Southern Tibetan Plateau, China," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
    5. Jiaxin Jin & Ying Wang & Hong Jiang & Min Cheng, 2016. "Recent NDVI-Based Variation in Growth of Boreal Intact Forest Landscapes and Its Correlation with Climatic Variables," Sustainability, MDPI, vol. 8(4), pages 1-10, April.
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    1. Hu, Xuhua & Chen, Mengting & Liu, Dong & Li, Dan & Jin, Li & Liu, Shaohui & Cui, Yuanlai & Dong, Bin & Khan, Shahbaz & Luo, Yufeng, 2021. "Reference evapotranspiration change in Heilongjiang Province, China from 1951 to 2018: The role of climate change and rice area expansion," Agricultural Water Management, Elsevier, vol. 253(C).
    2. Qun Liu & Zhaoping Yang & Cuirong Wang & Fang Han, 2019. "Temporal-Spatial Variations and Influencing Factor of Land Use Change in Xinjiang, Central Asia, from 1995 to 2015," Sustainability, MDPI, vol. 11(3), pages 1-14, January.

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