EGU21-766, updated on 14 Oct 2024
https://doi.org/10.5194/egusphere-egu21-766
EGU General Assembly 2021
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

A Novel Multitask CNN for Automatically Extracting Shoreline Variations of Lakes in Qinghai-Tibet Plateau from 1970 to 2020

Chen Xingyu1, Ran Jiangjun1,2, Xin Linyang1, and Yan Zhengwen1
Chen Xingyu et al.
  • 1Southern University of Science and Technology, Faculty of science, Department of Earth and Space Sciences, Shenzhen, China (11930407@mail.sustech.edu.cn)
  • 2Shenzhen Key Laboratory of Deep Offshore Oil and Gas Exploration Technology, Southern University of Science and Technology, China(rjj@sustech.edu.cn)

Variations of lake areas and shorelines can effectively reflect hydrological and climatic changes. This research focuses on the automatic and simultaneous extraction of lake areas and shorelines from optical remote sensing images and SAR images, and then analyze the area changes of lakes in Tibet Plateau, in order to provide some insights for Plateau wetland environment changes. In our research, we design a novel end-to-end lightweight multitask CNN and a modified deep CNN to automatically extract those. The experimental results over the testing image patches achieve the Accuracy of 0.9962, Precision of 0.9912, Recall of 0.9982, F1-score of 0.9941, and mIoU of 0.9879, which align with or even are better than those of mainstream semantic segmentation models (UNet, DeepLabV3+, etc.). Especially, the in-situ shoreline of the Selinco Lake located in the Central and Southern Tibetan Plateau is also collected by GPS measurements to evaluate the results of the proposed method further and the validation indicates a high accuracy in our results (DRMSE: 30.84 m, DMAE: 22.49 m, DSTD: 21.11 m), with only about one-pixel deviation for Landsat-8 images. On the basis of the preceding verification results, the sequential variations of Tibetan Plateau lakes are captured and reveal Tibetan Plateau lakes generally show an increasing trend. Such as the Selinco Lake which has an expansion trend from 1660 Square kilometers to 2410 Square kilometers, grown by 45% over half a century. It is expected that these conclusions will provide some valuable information on the variations of the Tibetan Plateau wetland environment.

Figure 1. In-situ GPS trajectory (orange line) and the predictive edge pixels (black line) in the comparison region (yellow box).

Figure 2. The variation of Selinco Lake in the Tibetan Plateau over time. The orange line is the area variation we get, other color variations are obtained by other agencies.

Figure 3. Temporal and spatial distribution of shoreline in the eastern and western regions of Selinco Lake.

How to cite: Xingyu, C., Jiangjun, R., Linyang, X., and Zhengwen, Y.: A Novel Multitask CNN for Automatically Extracting Shoreline Variations of Lakes in Qinghai-Tibet Plateau from 1970 to 2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-766, https://doi.org/10.5194/egusphere-egu21-766, 2021.

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