Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model

Author:

Song Yubin123,Xun Xuelian1,Zheng Hongwei234ORCID,Chen Xi234,Bao Anming234,Liu Ying234,Luo Geping234ORCID,Lei Jiaqiang234,Xu Wenqiang234ORCID,Liu Tie234ORCID,Hellwich Olaf5ORCID,Guan Qing6

Affiliation:

1. School of Remote Sensing and Information Engineering, North China Institute of Aerospace Engineering, Langfang 065000, China

2. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China

3. Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. Computer Vision and Remote Sensing, Technical University Berlin, 10623 Berlin, Germany

6. Langfang Natural Resources and Planning Bureau, Langfang 065000, China

Abstract

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the surrounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators reported in this current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a pixel resolution unit was defined in this paper based on deformation due to the wind erosion in this pixel resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within a pixel resolution unit, the ITD signal usually includes soil and vegetation contributions, and extant studies concerning this issue are considerably limited. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a pixel resolution unit. The least-square method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a pixel resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from 23 June 2020, to 5 July 2020 was mapped. The results confirmed that (1) based on the ITDDM model, the SITD can be accurately estimated by the LSM; (2) the Aral Sea is experiencing severe wind erosion; and (3) the middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur.

Funder

Key R&D Program of Xinjiang Uygur Autonomous Region

National Natural Science Foundation of China

“Western Light” Talents Training Program of CAS

Tianshan Talent Training Program of Xinjiang Uygur Autonomous Region

High-End Foreign Experts Project

West Light Foundation of The Chinese Academy of Sciences

Science and Technology Project of Hebei Education Department

Department of Education, Hebei Province

Department of Education, North China Institute of Aerospace Engineering

Youth Fund project of the Department of Education of Hebei Province

central government guides local science and technology development fund projects

Publisher

MDPI AG

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