IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i7p1309-d1182129.html
   My bibliography  Save this article

Detecting Long-Term Series Eco-Environmental Quality Changes and Driving Factors Using the Remote Sensing Ecological Index with Salinity Adaptability (RSEI SI ): A Case Study in the Tarim River Basin, China

Author

Listed:
  • Wen Chen

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China
    These authors contributed equally to this work.)

  • Jinjie Wang

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China
    These authors contributed equally to this work.)

  • Jianli Ding

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Xiangyu Ge

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Lijing Han

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

  • Shaofeng Qin

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China)

Abstract

Ecological challenges resulting from soil salinization in the Tarim River Basin (TRB), exacerbated by climate change and human activities, have emphasized the need for a quick and accurate assessment of regional ecological environmental quality (EEQ) and driving mechanisms. To address this issue, this study has developed a remote-sensing ecological index with salinity adaptability (RSEI SI ) for EEQ assessment in the Tarim River Basin by integrating the comprehensive salinity index (CSI) into the remote-sensing ecological index (RSEI). The RSEI SI enhances the sensitivity of soil salinity and characterizes the surface features of arid regions, thus expanding the applicability. Then, we used time-series analysis methods and a geodetector to quantify the spatial temporal trends and driving factors of EEQ in the TRB from 2000 to 2022. The results show that the RSEI SI with salinity adaptation effectively monitors the EEQ of the TRB. The EEQ of the TRB displayed the situation of oasis expansion, desert deterioration, and glacier melting, and the multiyear average EEQ grades were dominated by medium and poor grades in desert and saline areas, while medium, good, and excellent grades were concentrated in oasis and mountainous areas. Looking at the trend of change in conjunction with land-use types, the EEQ of the TRB showed a mild degradation trend mainly in unused land, followed by a mild improvement trend in cropland and grassland. The Hurst index indicated that the EEQ of most areas of the TRB will improve in the future. Soil type, land use, precipitation, and temperature were considered to be key factors affecting the EEQ across the TRB, and changes in the EEQ were found to be the interaction of multiple factors. This study may provide innovative concepts and methodologies, scientific and technological support for ecological management, and green development models in the northwest arid zone.

Suggested Citation

  • Wen Chen & Jinjie Wang & Jianli Ding & Xiangyu Ge & Lijing Han & Shaofeng Qin, 2023. "Detecting Long-Term Series Eco-Environmental Quality Changes and Driving Factors Using the Remote Sensing Ecological Index with Salinity Adaptability (RSEI SI ): A Case Study in the Tarim River Basin,," Land, MDPI, vol. 12(7), pages 1-23, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1309-:d:1182129
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/7/1309/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/7/1309/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yong Zhang & Chengbang An & Luyu Liu & Yanzhen Zhang & Chao Lu & Wensheng Zhang, 2021. "High Mountains Becoming Wetter While Deserts Getting Drier in Xinjiang, China since the 1980s," Land, MDPI, vol. 10(11), pages 1-14, October.
    2. Ebrahimi, Nader & Pflughoeft, Kurt & Soofi, Ehsan S., 1994. "Two measures of sample entropy," Statistics & Probability Letters, Elsevier, vol. 20(3), pages 225-234, June.
    3. Qifei Zhang & Congjian Sun & Yaning Chen & Wei Chen & Yanyun Xiang & Jiao Li & Yuting Liu, 2022. "Recent Oasis Dynamics and Ecological Security in the Tarim River Basin, Central Asia," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    4. Maomao Zhang & Abdulla-Al Kafy & Bing Ren & Yanwei Zhang & Shukui Tan & Jianxing Li, 2022. "Application of the Optimal Parameter Geographic Detector Model in the Identification of Influencing Factors of Ecological Quality in Guangzhou, China," Land, MDPI, vol. 11(8), pages 1-20, August.
    Full references (including those not matched with items on IDEAS)

    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. Qifei Zhang & Yaning Chen & Zhi Li & Congjian Sun & Yanyun Xiang & Zhihui Liu, 2023. "Spatio-Temporal Development of Vegetation Carbon Sinks and Sources in the Arid Region of Northwest China," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    2. Zhaoxue Gai & Ying Xu & Guoming Du, 2023. "Spatio-Temporal Differentiation and Driving Factors of Carbon Storage in Cultivated Land-Use Transition," Sustainability, MDPI, vol. 15(5), pages 1-16, February.
    3. Qifei Zhang & Congjian Sun & Yaning Chen & Wei Chen & Yanyun Xiang & Jiao Li & Yuting Liu, 2022. "Recent Oasis Dynamics and Ecological Security in the Tarim River Basin, Central Asia," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    4. Weijia Liang & Quan Quan & Bohua Wu & Shuhong Mo, 2023. "Response of Vegetation Dynamics in the Three-North Region of China to Climate and Human Activities from 1982 to 2018," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    5. Chan Lu & Lei Shi & Lihua Fu & Simian Liu & Jianqiao Li & Zhenchun Mo, 2023. "Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    6. Menéndez, M. & Morales, D. & Pardo, L., 1997. "Maximum entropy principle and statistical inference on condensed ordered data," Statistics & Probability Letters, Elsevier, vol. 34(1), pages 85-93, May.
    7. Yunlin He & Yanhua Mo & Jiangming Ma, 2022. "Spatio-Temporal Evolution and Influence Mechanism of Habitat Quality in Guilin City, China," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    8. Jinlong Zhang & Yuan Qi & Rui Yang & Xiaofang Ma & Juan Zhang & Wanqiang Qi & Qianhong Guo & Hongwei Wang, 2023. "Impacts of Climate Change and Land Use/Cover Change on the Net Primary Productivity of Vegetation in the Qinghai Lake Basin," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
    9. Ji Zhang & Pei Zhang & Xinchen Gu & Mingjiang Deng & Xiaoying Lai & Aihua Long & Xiaoya Deng, 2023. "Analysis of Spatio-Temporal Pattern Changes and Driving Forces of Xinjiang Plain Oases Based on Geodetector," Land, MDPI, vol. 12(8), pages 1-15, July.
    10. Jan Rosenzweig, 2023. "A Tale of Tail Covariances (and Diversified Tails)," Papers 2302.13646, arXiv.org.
    11. Mengba Liu & Yanfei Xiong & Anlu Zhang, 2024. "Can China’s Cross-Regional Ecological Fiscal Transfers Help Improve the Ecological Environment?—Evidence from Hubei Province," Land, MDPI, vol. 13(8), pages 1-23, July.
    12. Xiuhua Cai & Wenqian Zhang & Cunjie Zhang & Qiang Zhang & Jingli Sun & Chen Cheng & Wenjie Fan & Ying Yu & Xiaoling Liu, 2022. "Identification and Spatial-Temporal Variation Characteristics of Regional Drought Processes in China," Land, MDPI, vol. 11(6), pages 1-21, June.
    13. Weiwei Zhang & Wanqian Zhang & Jianwan Ji & Chao Chen, 2024. "Urban Ecological Quality Assessment Based on Google Earth Engine and Driving Factors Analysis: A Case Study of Wuhan City, China," Sustainability, MDPI, vol. 16(9), pages 1-23, April.
    14. Shanshan Wang & Qiting Zuo & Kefa Zhou & Jinlin Wang & Wei Wang, 2023. "Predictions of Land Use/Land Cover Change and Landscape Pattern Analysis in the Lower Reaches of the Tarim River, China," Land, MDPI, vol. 12(5), pages 1-17, May.
    15. Qin Wang & Qin Ju & Yueyang Wang & Quanxi Shao & Rongrong Zhang & Yanli Liu & Zhenchun Hao, 2022. "Vegetation Changing Patterns and Its Sensitivity to Climate Variability across Seven Major Watersheds in China," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    16. Bo Liu & Wei Song & Zhan Meng & Xinwei Liu, 2023. "Review of Land Use Change Detection—A Method Combining Machine Learning and Bibliometric Analysis," Land, MDPI, vol. 12(5), pages 1-26, May.
    17. Yating Zhao & Chunming Hu & Xi Dong & Jun Li, 2023. "NDVI Characteristics and Influencing Factors of Typical Ecosystems in the Semi-Arid Region of Northern China: A Case Study of the Hulunbuir Grassland," Land, MDPI, vol. 12(3), pages 1-21, March.
    18. Lu Zhang & Xuehan Lin & Bingkui Qiu & Maomao Zhang & Qingsong He, 2022. "The Industrial Sprawl in China from 2010 to 2019: A Multi-Level Spatial Analysis Based on Urban Scaling Law," IJERPH, MDPI, vol. 19(23), pages 1-14, December.
    19. Yazhou Zhao & Shengyu Li & Dazhi Yang & Jiaqiang Lei & Jinglong Fan, 2023. "Spatiotemporal Changes and Driving Force Analysis of Land Sensitivity to Desertification in Xinjiang Based on GEE," Land, MDPI, vol. 12(4), pages 1-20, April.
    20. Guoxin Qiu & Kai Jia, 2018. "Extropy estimators with applications in testing uniformity," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 182-196, January.

    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:jlands:v:12:y:2023:i:7:p:1309-:d:1182129. 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.