Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model

Yiting Su; Dongchuan Wang; Shuang Zhao; Jiancong Shi; Yanqing Shi; Dongying Wei

doi:10.7717/peerj.10747

Examining long-term natural vegetation dynamics in the Aral Sea Basin applying the linear spectral mixture model

PeerJ. 2021 Mar 2:9:e10747. doi: 10.7717/peerj.10747. eCollection 2021.

Authors

Yiting Su¹, Dongchuan Wang^{1

2}, Shuang Zhao¹, Jiancong Shi¹, Yanqing Shi¹, Dongying Wei¹

Affiliations

¹ School of Geology and Geomatics, Tianjin Chengjian University, Tianjin, China.
² Tianjin Key Laboratory of Civil Structure Protection and Reinforcement, Tianjin, China.

Abstract

Background: Associated with the significant decrease in water resources, natural vegetation degradation has also led to many widespread environmental problems in the Aral Sea Basin. However, few studies have examined long-term vegetation dynamics in the Aral Sea Basin or distinguished between natural vegetation and cultivated land when calculating the fractional vegetation cover.

Methods: Based on the multi-temporal Moderate Resolution Imaging Spectroradiometer, this study examined the natural vegetation coverage by introducing the Linear Spectral Mixture Model to the Google Earth Engine platform, which greatly reduces the experimental time. Further, trend line analysis, Sen trend analysis, and Mann-Kendall trend test methods were employed to explore the characteristics of natural vegetation cover change in the Aral Sea Basin from 2000 to 2018.

Results: Analyses of the results suggest three major conclusions. First, the development of irrigated agriculture in the desert area is the main reason for the decrease in downstream water. Second, with the reduction of water, the natural vegetation coverage in the Aral Sea Basin showed an upward trend of 17.77% from 2000 to 2018. Finally, the main driving factor of vegetation cover changes in the Aral Sea Basin is the migration of cultivated land to the desert.

Keywords: Fractional vegetation cover; Google earth engine; The Aral Sea Basin; The linear spectral mixture model.

Grants and funding

This work was supported by the National Natural Science Foundation of China (No. 41971310), the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (No. 2019QZKK0608) and the Scientific Research Project of Tianjin Education Commission (2020KJ052). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.