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    Risk zoning of hail disaster in tobacco area of Jianshi County based on GEE and Sentinel-2 images
    ZHENG Xiang-tian, LUO Ju-ying, WANG Chuan-yi, TAN Yan-li, LIU Qiao, WAN Jun
    HUBEI AGRICULTURAL SCIENCES    2024, 63 (8): 182-187.   DOI: 10.14088/j.cnki.issn0439-8114.2024.08.031
    Abstract189)      PDF (6108KB)(61)       Save
    Sentinel-2 remote sensing images of Jianshi County in 2021 were selected, and based on GEE cloud platform, the parameters of NDVI, NDWI and NDBI were calculated. The random forest method was used to divide Jianshi County into five categories: water area, forest land, construction land, cultivated land and tobacco leaf. Combined with the results of the meteorological disaster risk survey in Jianshi County, the tobacco hail disaster risk regionalization model was established, and the risk grade of tobacco leaves subjected to hail disaster was evaluated. The results showed that the tobacco planting areas in Jianshi County were mainly distributed in the central and western parts of Guandian Town, most of Huaping Town, and the line from Gaoping Town to Maotian. Most of them were located in areas with low to medium risk of hail disasters in the tobacco growing areas. It was necessary to strengthen monitoring and early warning, and timely carry out artificial hail prevention operations. The risk level of hail disasters was low in the southern areas of Liangxiang, Sanli Township, and Gaoping Town, and the tobacco planting area could be appropriately increased. The risk level of hail disasters in the northeast and southern mountainous areas of Jianshi County was relatively high, and it was necessary to strengthen disaster prevention and appropriately reduce tobacco planting. The results of this study, as a typical case of the 2022 Enshi Prefecture disaster risk survey, had been applied in practical business, providing a good reference basis for tobacco planting production and meteorological disaster prevention and reduction.
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    The information extraction technology of farmland flood disaster based on SAR satellite remote sensing technology
    FAN Bing, MA Liang, YUAN Xiu-zhen, LI Fu-lin, DUAN Zhou, WU Jia-mei
    HUBEI AGRICULTURAL SCIENCES    2024, 63 (8): 188-193.   DOI: 10.14088/j.cnki.issn0439-8114.2024.08.032
    Abstract155)      PDF (15241KB)(33)       Save
    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.
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