This dataset is based on Landsat satellite remote sensing data, WorldView-4 satellite data and GLC_FCS30-1985_2020 surface monitoring data, and interprets and analyzes the information of geographic entities on the subsurface of typical flood storage areas such as Arakusa 2-3 polder area, Artemisia polder, and Wangbo Dongdang, etc., and acquires the study area's The basic geographic elevation information and land type information of the subsurface were obtained.
WorldView-4 satellite data with a spatial resolution of 0.15 m, and land use type data GLC_FCS30-1985_2020 surface monitoring data with a resolution of 30 m. After analysis, the data can be analyzed to provide a scientific basis and decision-making support for the rational planning, effective management and sustainable development of the flood storage area, and at the same time provide a scientific basis and decision-making support for the construction of flood refinement simulation model of the flood storage and retention area. At the same time, it provides data support for the construction of the flood simulation model.
Geographic elevation information is derived from Landsat and WorldView-4, which is the U.S. Land Exploration Satellite System (LES) that has successfully delivered a large amount of high-quality Earth surface information observations to the ground.
Currently the latest Landsat-8 satellite carries two sensors, respectively OLI land imager and TIRS thermal infrared sensors, a total of 11 bands, bands 1-7, 9-11 spatial resolution of 30 meters, band 8 for the 15-meter resolution of panchromatic bands, satellites can be achieved once every 16 days global coverage. WorldView-4 is DigitalGlobe's commercial high-resolution remote sensing satellite, launched in November 2016 aboard the U.S. Optimus Prime 5 launch vehicle and weighing 0.13 m. It has ultra-high resolution, with a panchromatic resolution of 31 cm; its multispectral resolution can reach 1.24 m, and it has a high positional accuracy as well as large storage capacity under a variety of image acquisition modes. It has a high resolution of 31 cm in panchromatic, 1.24 meters in multispectral, high positioning accuracy and large storage capacity in multiple image acquisition modes.
The land use data is a global 30-meter fine ground cover dynamic monitoring product for 1985-2020 produced by the Institute of Space and Astronautical Information Innovation (ISAI) of the Chinese Academy of Sciences (CAS), using all Landsat satellite data (Landsat TM, ETM+ and OLI) from 1984 to 2020. The product follows the classification system of the 2020 baseline data and contains a total of 29 surface cover types, with an update cycle of five years.
For the GLC_FCS30-1985_2020 surface monitoring data, the ArcGIS raster reclassification tool was used to classify the main coverage types into multiple categories, which are buildings, forests, water bodies, paddy fields, cultivated land, grasslands, etc. For the Landsat-8 satellite data, the image resampling process was carried out to correct the image deviation of the output image, so as to establish a new image matrix, and the image was resampled by bilinear interpolation, and the band synthesis function in ArcGIS raster processing was utilized to select 2, 3, and 4 waves. For Landsat-8 satellite data, the image resampling process is carried out to correct the image deviation of the output image, so as to establish a new image matrix, resample the image by bilinear interpolation, use the band synthesis function in ArcGIS raster processing, select 2, 3, 4 bands for true color band synthesis, and then fusion process the multispectral image 8-band panchromatic image, so as to make it have a high resolution.
Data research and organization found that the barren grass two or three dike, artemisia dike, eighteen lianxu flood storage area, arable land is the first major category of land-use types, followed by water bodies or paddy fields, and the least is the building. 2020 all of the stagnant flood storage area of arable land area accounted for the largest proportion of the eighteen lianxu dike, about 93.9%, the smallest is the artemisia dike, about 67.6%; water bodies and paddy fields, Building area accounted for the largest are Artemisia pike, about 27.6%, 4.4%, the smallest are eighteen Lianxu, only 4.5%, 1.1%; barren grass two or three pikes in the forest area accounted for more than Artemisia pike and eighteen Lianxu. With the actual situation fit. At the same time, the geographic elevation information obtained by the research institute is also consistent with the actual situation, therefore, this dataset can be used as a reliable basic data for the evaluation and analysis of typical flood storage area.
| # | number | name | type |
| 1 | 2021YFC3000100 | Lower Yangtze River Flood Disaster Integration and Control and Emergency De-risking Technology and Equipment | National key R & D plan |
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CSTR:11738.11.NCDC.NHRI.DB6799.2025
10.12072/ncdc.nhri.db6799.2025