IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i3p443-d93347.html
   My bibliography  Save this article

The Dynamic Change of Vegetation Cover and Associated Driving Forces in Nanxiong Basin, China

Author

Listed:
  • Luobin Yan

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Ruixiang He

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Milica Kašanin-Grubin

    (Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade 11000, Serbia)

  • Gusong Luo

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Hua Peng

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Jianxiu Qiu

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

Abstract

Natural climate change and human activities are the main driving forces associated with vegetation coverage change. Nanxiong Basin is a key ecosystem-service area at the national level with a dense population and highly representative of red-bed basins, which are considered as fragile ecological units in humid regions. In this study, the authors aimed to determine the trends in vegetation cover change over past two decades and the associated driving forces in this study area. The Normalized Difference Vegetation Index (NDVI) of 2000–2015, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing dataset along with the application of statistical methods and GIS (geographic information system) techniques were used to quantify vegetation cover change. The results show that human-induced factors can explain most variations at sites with significant cover change. That is to say that human activities are the main drivers of vegetation dynamics in this study area, which shows a significant reduction trend in vegetation cover during the industrialization and urbanization processes of the study period and noticeable recovery trend in 2000–2015 under the plantation and enclosed forest policy.

Suggested Citation

  • Luobin Yan & Ruixiang He & Milica Kašanin-Grubin & Gusong Luo & Hua Peng & Jianxiu Qiu, 2017. "The Dynamic Change of Vegetation Cover and Associated Driving Forces in Nanxiong Basin, China," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:3:p:443-:d:93347
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/3/443/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/3/443/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. B. Myneni & C. D. Keeling & C. J. Tucker & G. Asrar & R. R. Nemani, 1997. "Increased plant growth in the northern high latitudes from 1981 to 1991," Nature, Nature, vol. 386(6626), pages 698-702, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiaqi Li & Yi Tian, 2024. "Assessment of Ecological Quality and Analysis of Influencing Factors in Coal-Bearing Hilly Areas of Northern China: An Exploration of Human Mining and Natural Topography," Land, MDPI, vol. 13(7), pages 1-23, July.
    2. Mary Thornbush, 2017. "Physical Geography and Environmental Sustainability," Sustainability, MDPI, vol. 9(12), pages 1-5, November.
    3. Pariha Helili & Mei Zan, 2023. "Coupling Coordination Development of Urbanization and Ecological Environment in the Urban Agglomeration on the Northern Slope of the Tianshan Mountains, China," Sustainability, MDPI, vol. 15(5), pages 1-16, February.
    4. Ming Shi & Fei Lin & Xia Jing & Bingyu Li & Jingsha Qin & Manqi Wang & Yang Shi & Yimin Hu, 2023. "Research on the Spatio-Temporal Changes of Vegetation and Its Driving Forces in Shaanxi Province in the Past 20 Years," Sustainability, MDPI, vol. 15(23), pages 1-25, November.
    5. Ruihao Cui & Jiazheng Han & Zhenqi Hu, 2022. "Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China," Land, MDPI, vol. 11(6), pages 1-19, June.
    6. Jianbo Zhou & Wanqing Liu, 2022. "Monitoring and Evaluation of Eco-Environment Quality Based on Remote Sensing-Based Ecological Index (RSEI) in Taihu Lake Basin, China," Sustainability, MDPI, vol. 14(9), pages 1-21, May.
    7. Liu, Moyang & Hamilton, Serena H. & Jakeman, Anthony J. & Lerat, Julien & Savage, Callum & Croke, Barry F.W., 2024. "Assessing the contribution of hydrologic and climatic factors on vegetation condition changes in semi-arid wetlands: An analysis for the Narran Lakes," Ecological Modelling, Elsevier, vol. 487(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiuchen Wu & Hongyan Liu & Dali Guo & Oleg A Anenkhonov & Natalya K Badmaeva & Denis V Sandanov, 2012. "Growth Decline Linked to Warming-Induced Water Limitation in Hemi-Boreal Forests," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    2. Akhlaq Amin Wani & Amir Farooq Bhat & Aaasif Ali Gatoo & Shiba Zahoor & Basira Mehraj & Naveed Najam & Qaisar Shafi Wani & M A Islam & Shah Murtaza & Moonisa Aslam Dervash & P K Joshi, 2021. "Assessing relationship of forest biophysical factors with NDVI for carbon management in key coniferous strata of temperate Himalayas," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(1), pages 1-22, January.
    3. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    4. F. Nelson & O. Anisimov & N. Shiklomanov, 2002. "Climate Change and Hazard Zonation in the Circum-Arctic Permafrost Regions," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 26(3), pages 203-225, July.
    5. Jinting Guo & Yuanman Hu & Zaiping Xiong & Xiaolu Yan & Chunlin Li & Rencang Bu, 2017. "Variations in Growing-Season NDVI and Its Response to Permafrost Degradation in Northeast China," Sustainability, MDPI, vol. 9(4), pages 1-15, April.
    6. Zhang, Jiarui & Jørgensen, Sven E. & Lu, Jianjian & Nielsen, Søren N. & Wang, Qiang, 2014. "A model for the contribution of macrophyte-derived organic carbon in harvested tidal freshwater marshes to surrounding estuarine and oceanic ecosystems and its response to global warming," Ecological Modelling, Elsevier, vol. 294(C), pages 105-116.
    7. Zhang, Yixiao & He, Tao & Liang, Shunlin & Zhao, Zhongguo, 2023. "A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches," Agricultural Water Management, Elsevier, vol. 289(C).
    8. Craig D. Idso, 2001. "Earth's Rising Atmospheric Co2 Concentration: Impacts on the Biosphere," Energy & Environment, , vol. 12(4), pages 287-310, July.
    9. Jörg Kaduk & Sietse Los, 2011. "Predicting the time of green up in temperate and boreal biomes," Climatic Change, Springer, vol. 107(3), pages 277-304, August.
    10. Patricia Arrogante-Funes & Carlos J. Novillo & Raúl Romero-Calcerrada, 2018. "Monitoring NDVI Inter-Annual Behavior in Mountain Areas of Mainland Spain (2001–2016)," Sustainability, MDPI, vol. 10(12), pages 1-24, November.
    11. Lausch, Angela & Salbach, Christoph & Schmidt, Andreas & Doktor, Daniel & Merbach, Ines & Pause, Marion, 2015. "Deriving phenology of barley with imaging hyperspectral remote sensing," Ecological Modelling, Elsevier, vol. 295(C), pages 123-135.
    12. Mette, Tobias & Albrecht, Axel & Ammer, Christian & Biber, Peter & Kohnle, Ulrich & Pretzsch, Hans, 2009. "Evaluation of the forest growth simulator SILVA on dominant trees in mature mixed Silver fir–Norway spruce stands in South-West Germany," Ecological Modelling, Elsevier, vol. 220(13), pages 1670-1680.
    13. Vanessa M. Comeau & Lori D. Daniels, 2022. "Multiple divergent patterns in yellow-cedar growth driven by anthropogenic climate change," Climatic Change, Springer, vol. 170(3), pages 1-20, February.
    14. Jan Verbesselt & Achim Zeileis & Martin Herold, 2011. "Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia," Working Papers 2011-18, Faculty of Economics and Statistics, Universität Innsbruck.
    15. Zhao, Chunli & Yan, Yan & Ma, Wenyong & Shang, Xu & Chen, Jianguo & Rong, Yuejing & Xie, Tian & Quan, Yuan, 2021. "RESTREND-based assessment of factors affecting vegetation dynamics on the Mongolian Plateau," Ecological Modelling, Elsevier, vol. 440(C).
    16. Bolin, David & Lindström, Johan & Eklundh, Lars & Lindgren, Finn, 2009. "Fast estimation of spatially dependent temporal vegetation trends using Gaussian Markov random fields," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2885-2896, June.
    17. Shi, Yusheng & Sasai, Takahiro & Yamaguchi, Yasushi, 2014. "Spatio-temporal evaluation of carbon emissions from biomass burning in Southeast Asia during the period 2001–2010," Ecological Modelling, Elsevier, vol. 272(C), pages 98-115.
    18. Zongxing, Li & Qi, Feng & Zongjie, Li & Xufeng, Wang & Juan, Gui & Baijuan, Zhang & Yuchen, Li & Xiaohong, Deng & Jian, Xue & Wende, Gao & Anle, Yang & Fusen, Nan & Pengfei, Liang, 2021. "Reversing conflict between humans and the environment － The experience in the Qilian Mountains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    19. Kathuroju, Naven & White, Michael A. & Symanzik, Jürgen & Schwartz, Mark D. & Powell, James A. & Nemani, Ramakrishna R., 2007. "On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models," Ecological Modelling, Elsevier, vol. 201(2), pages 144-156.
    20. Jinyun Tang & Qianlai Zhuang, 2011. "Modeling soil thermal and hydrological dynamics and changes of growing season in Alaskan terrestrial ecosystems," Climatic Change, Springer, vol. 107(3), pages 481-510, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:3:p:443-:d:93347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.