Abstract: In order to improve the extraction ability of farmland flood disaster information, the automatic extraction method of water body and farmland boundary information of SAR satellite remote sensing image was explored. Taking a heavy rainfall process in Fengcheng, Jiangxi Province as an example, the threshold segmentation method, radar and optical image fusion method was adopted, Sentinel 1 satellite image was used to extract water information before the disaster, and chaohu 1 satellite image was used to extract water information in the disaster. The two results were superimposed and the new water body range of the heavy precipitation was obtained. The satellite images of Sentinel 2 were used to superimpose the sky map images to extract the farmland boundary range of the study area, and this boundary was superimposed with the new water body range to obtain the scope of the farmland flood disaster area affected by the heavy rainfall. Through evaluation, this method could effectively improve the classification accuracy of ground scattering features, and the integrity rate of the extracted 11 flooded farmland verification plots was above 80%. SAR remote sensing image was not affected by cloud and rain weather, and could provide strong data support in the emergency monitoring of the flood disaster. This analysis method was conducive to the relevant departments to fully grasp the farmland disaster data, make emergency response quickly, and improve the emergency rescue and management ability of flood.

Key words: radar, remote sensing, flood disaster, threshold segmentation, data fusion, land classification