<p>The data includes vector data of the Aral Sea Lake surface in 2018 and 2019, and the data is stored in shp format. Based on the Landsat images of 2018 and 2019, the lake area information was extracted using a "global-local" adaptive iterative threshold segmentation method. </p>
The raw image data comes from the U.S. Geological Survey (http://glovis.usgs.gov), including 2018 and 2019 Landsat TM/ETM+/OLI data, with a resolution of 30 meters. The selected data meets the following requirements: ① Less cloud coverage (cloud coverage rate of 30%);② Less shadows and clear color layers;③ No noise. Vector data products are part of the results of the Class A Strategic Pilot Science and Technology Special Project (XDA20060301) of the China Academy of Sciences.
Based on the Landsat images of 2018 and 2019, a "global-local" adaptive iterative threshold segmentation method is used to extract lake area information.
After combined with visual correction, the automatically interpreted vector data achieves high accuracy and can meet research needs.
| # | number | name | type |
| 1 | XDA20000000 | Other |
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CSTR:33110.11.ariddc.00441
10.12389/ariddc.00441
