Preprints
https://doi.org/10.5194/essd-2022-251
https://doi.org/10.5194/essd-2022-251
12 Aug 2022
 | 12 Aug 2022
Status: this discussion paper is a preprint. It has been under review for the journal Earth System Science Data (ESSD). The manuscript was not accepted for further review after discussion.

High-resolution and Multitemporal Impervious Surface Mapping in the Lancang-Mekong Basin with Google Earth Engine

Genyun Sun, Zheng Li, Aizhu Zhang, Xin Wang, Sunjinyan Ding, Xiuping Jia, Jing Li, and Qinhuo Liu

Abstract. High-resolution and multitemporal impervious surface maps on large scales are crucial for environmental and socioeconomic studies. However, recently available multitemporal impervious surface maps of the Lancang-Mekong basin were limited at 30-m resolution with considerably low accuracy. Hence, the development of up-to-date, accurate, and multitemporal impervious surface maps with the 10-m resolution is urgently needed. In this article, a machine learning framework is demonstrated by fusing Sentinel-1 Synthetic Aperture Radar images and Sentinel-2 Multispectral Sensor images to map and study the annual dynamics of impervious surfaces in the Lancang-Mekong basin from 2016 to 2021 facilitated by Google Earth Engine. Moreover, a train sample migration strategy is proposed to automate impervious surface mapping for various time periods eliminating the need to collect additional train samples from this vast study area. Finally, qualitative and quantitative assessments are conducted using test samples from Google Earth and four existing state-of-the-art datasets. The result shows that the overall accuracy and Kappa of the final impervious surface maps range from 91.45 % to 92.44 % and 0.829 to 0.848, respectively, which demonstrates the feasibility and reliability of the proposed method and results. The LMISD is freely available from https://doi.org/10.5281/zenodo.6968739 (Sun et al., 2022).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Genyun Sun, Zheng Li, Aizhu Zhang, Xin Wang, Sunjinyan Ding, Xiuping Jia, Jing Li, and Qinhuo Liu

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-251', Anonymous Referee #1, 04 Sep 2022
    • CC1: 'Reply on RC1', Aizhu Zhang, 17 Sep 2022
  • RC2: 'Comment on essd-2022-251', Anonymous Referee #2, 04 Sep 2022
    • CC2: 'Reply on RC2', Aizhu Zhang, 17 Sep 2022
  • RC3: 'Comment on essd-2022-251', Christopher Brown, 20 Sep 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-251', Anonymous Referee #1, 04 Sep 2022
    • CC1: 'Reply on RC1', Aizhu Zhang, 17 Sep 2022
  • RC2: 'Comment on essd-2022-251', Anonymous Referee #2, 04 Sep 2022
    • CC2: 'Reply on RC2', Aizhu Zhang, 17 Sep 2022
  • RC3: 'Comment on essd-2022-251', Christopher Brown, 20 Sep 2022
Genyun Sun, Zheng Li, Aizhu Zhang, Xin Wang, Sunjinyan Ding, Xiuping Jia, Jing Li, and Qinhuo Liu
Genyun Sun, Zheng Li, Aizhu Zhang, Xin Wang, Sunjinyan Ding, Xiuping Jia, Jing Li, and Qinhuo Liu

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Latest update: 18 May 2024
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Short summary
Understanding IS dynamic is vital for ensuring sustainable development in the Lancang-Mekong basin and worldwide. By integrating multi-source and multi-temporal data, we developed a 10m-resolution IS extraction approach to map accurate continuous IS in the Lancang-Mekong basin (LMISD). The derived complementary features enable LMISD to outperform existing products in mapping accuracy and detail. Numerically, results show that a large and uneven IS area increase occurs here from 2016 to 2021.
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