洪涝不同损毁程度农田遥感数据集

洪涝不同损毁程度农田遥感数据集包含中等分辨率灾前影像和灾中影像、损毁农田标签等数据。该数据集提供比低分辨率遥感卫星更详细的洪涝灾害不同损毁程度农田光谱信息，以及缓解混合像元造成损毁农田识别精度较低的问题。同时该数据集可以解决农田损失评估回归模型依赖地方政府历史数据、获取时间滞后影像的洪水淹没范围等问题，实现了我国华北平原地区洪涝不同损毁程度农田高精度变化检测。
由于洪涝状态持续时间短，很容易错过灾中洪涝损毁农田最佳识别周期，其拥有比高分辨率遥感卫星更短时间获得数据的优势。这些特点满足在洪涝灾害应急时快速响应和灾区范围覆盖的要求。在地理状态上，农田通常分布集中，并且面积大。中等分辨率遥感影像的大幅宽特别有助于洪涝灾害农田损毁监测。为政府部门或保险公司提供更精细化的致损农田面积数据支撑，辅助他们科学制定救助或理赔决策。还可以为国家粮食安全目标的制定提供数据参考和技术支撑。

The Remote Sensing Dataset of Farmlands with Different Flood Damage Degrees contains pre-disaster and in-disaster medium-resolution remote sensing images, labels of damaged farmlands and other relevant data. This dataset provides more detailed spectral information of farmlands with different flood damage degrees compared to low-resolution remote sensing satellites, and alleviates the problem of low recognition accuracy of damaged farmlands caused by mixed pixels. Meanwhile, it solves the problems that regression models for farmland loss assessment rely on historical data from local governments and obtain flood inundation ranges from time-lagged images, and has enabled high-precision change detection of farmlands with different flood damage degrees in the North China Plain of China.

Since flood disasters have a short duration, it is easy to miss the optimal identification period for in-disaster flood-damaged farmlands. This dataset has the advantage of acquiring data in a shorter time frame than high-resolution remote sensing satellites. These characteristics meet the requirements for rapid response and full coverage of disaster-stricken areas during flood emergency responses. Geographically, farmlands are usually concentrated and cover large areas, and the wide swath of medium-resolution remote sensing images is particularly conducive to flood damage monitoring of farmlands. It provides more refined data support on the area of damaged farmlands for government departments or insurance companies, helping them scientifically formulate rescue or claim settlement decisions. It can also provide data references and technical support for the formulation of national food security goals.