A silt dam is a soil and water conservation engineering measure built in multi sediment channels for stabilizing gullies, reducing erosion, storing floodwaters, and controlling sediment transport. It has good soil and water conservation effects and plays an important role in blocking silt and siltation, storing floodwaters, constructing farmland, consolidating farmland for afforestation (grassland), developing production, reducing sediment in the Yellow River, and improving the ecological environment. Based on Google Earth 19 level remote sensing image data, 714 sediment dam samples were visually interpreted and labeled in the upper and middle reaches of the Yellow River basin. Each sample underwent image enhancement, resulting in a total of 3570 sediment dam samples. This sample set can serve as the basic data for image recognition of silt dams, promoting research on automatic recognition of silt dams in the upper and middle reaches of the Yellow River p>
collect time | 2018/10/23 - 2022/11/30 |
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collect place | The upper and middle reaches of the Yellow River region |
data size | 1.6 GiB |
data format | *.tif, *.twf, *.xml |
Coordinate system | WGS84 |
The sample is based on Google Earth remote sensing image data, and the BIGEMAP map downloader is used to obtain Google Earth satellite images with a zoom level of 19, with a resolution of 0.54m/pixel, including red, green, and blue bands p>
A silt dam is generally located in a channel, resembling a dam, narrow at the top and wide at the bottom; At least one side of the dam body is silted land, cultivated land, or water; There can be multiple silt dams in a channel. Slice the image and label each slice after slicing. Use ArcGIS Pro's training sample manager to label samples p>
The sample markers come from the densely built areas of silt dams in the upper and middle reaches of the Yellow River, mainly including Yulin area in Shaanxi Province, Lvliang and Fenxi County in Shanxi Province. According to statistical data analysis, the number of silt dams built in these two areas accounts for more than 60% of the national total, indicating the universality of the sample p>
# | number | name | type |
1 | 2021YFF0704200 | National key R & D plan |
# | title | file size |
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1 | _ncdc_meta_.json | 5.1 KiB |
2 | check-dam samples.zip | 1.6 GiB |
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