Version 1
: Received: 7 March 2024 / Approved: 8 March 2024 / Online: 8 March 2024 (10:09:20 CET)
How to cite:
Song, Y.; Xun, X.; Zheng, H.; Chen, X.; Bao, A.; Luo, G.; Lei, J.; Xu, W.; Liu, T.; Hellwich, O.; Guan, Q. Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model. Preprints2024, 2024030514. https://doi.org/10.20944/preprints202403.0514.v1
Song, Y.; Xun, X.; Zheng, H.; Chen, X.; Bao, A.; Luo, G.; Lei, J.; Xu, W.; Liu, T.; Hellwich, O.; Guan, Q. Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model. Preprints 2024, 2024030514. https://doi.org/10.20944/preprints202403.0514.v1
Song, Y.; Xun, X.; Zheng, H.; Chen, X.; Bao, A.; Luo, G.; Lei, J.; Xu, W.; Liu, T.; Hellwich, O.; Guan, Q. Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model. Preprints2024, 2024030514. https://doi.org/10.20944/preprints202403.0514.v1
APA Style
Song, Y., Xun, X., Zheng, H., Chen, X., Bao, A., Luo, G., Lei, J., Xu, W., Liu, T., Hellwich, O., & Guan, Q. (2024). Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model. Preprints. https://doi.org/10.20944/preprints202403.0514.v1
Chicago/Turabian Style
Song, Y., Olaf Hellwich and Qing Guan. 2024 "Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model" Preprints. https://doi.org/10.20944/preprints202403.0514.v1
Abstract
The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the sur-rounding 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 re-ported in the current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a resolution unit was defined in this paper based on the deformation due to the wind erosion in this resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). The ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within one resolution unit, the ITD signal usually includes soil and vegetation contributions, and few studies are referred to this. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a resolution unit. The least-squares method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a 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 June 23, 2020, to July 05, 2020, was mapped. The results confirmed that (1) Based on the ITDDM model, the SITD can be accurately estimated by the LSM method, (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.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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