基于高时空分辨率遥感数据协同的作物种植结构调查
Investigation on crop planting structure based on synergy of high spatial-temporal resolution remote sensing data
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摘要: 目的充分发掘遥感影像的空间、时间和光谱等特征谱信息,探索地块基元支持下的多源遥感数据作物种植信息自动识别方法,为作物种植结构信息的快速、精细化调查提供借鉴.方法以广西扶绥县为研究区,通过对高空间分辨率影像的多尺度分割和对象廓线编辑,提取精细农田地块信息;以地块为基元获取覆盖作物生育期内的时序光谱特征;基于时序光谱及其变化定义与作物长势状况相关的描述参量,形成静态光谱与动态过程特征结合的多维特征空间,结合作物的物候节律特征构建作物种植信息提取模型,实现主要农作物种植结构信息的提取.结果依据上述方法绘制出广西扶绥县甘蔗、水稻和其他作物农田及草地、林地、水体、城镇建设用地等的精细地块图,其中,提取广西扶绥县甘蔗和水稻作物的总面积分别为82420.01和6806.67 ha,作物提取的总体分类精度为86.8%,Kappa系数为0.84.结论提取的广西扶绥县作物种植结构的成果满足使用精度要求,可为精准农业补贴投放、农业灾害定损等政策制定提供依据,而技术方法对于作物种植结构信息的快速、精细化调查具有借鉴意义.Abstract: ObjectiveThe present study explored information including space, time and spectrum in remote sensing image, explored automatic identification of multi-source remote sensing crop information supported by plot. The research techniques could provide reference for rapid and refined survey of crop planting structure. Method Fusui county was taken as research region. Firstly, boundary of fine farmland block information were extracted by multi-scale segmentation and object contour editing of high spatial resolution images. Then, time series spectrum features of the covering crop during growth period were obtained by blot. Finally, multidimensional feature space combining static spectrum and dynamic pro-cess feature was formed based on temporal spectrum and its changing definition as well as description parameters of crop growth conditions. Crop planting information extraction model was established based on crop phenology rhythm characteris-tics, which realized extraction of main crop planting structure information. ResultBased on this method, fine plots of sugarcane, rice and other crops in Fusui, as well as grassland, woodland, water and urban construction land were drawn. The extracted area of sugarcane in Fusui was 82420.01 ha and that of rice was 6806.67 ha. The overall classification accuracy was 86.8% and Kappa coefficient 0.84.ConclusionThe extracted crop planting structure in Fusui is in accor-dance with usage precision demand, which can serve as basis for agricultural subsidy granting and loss assessment of agri-cultural disaster. The technique used in the research can provide reference for rapid and refined survey of crop planting in-formation.