以湖南洞庭湖为研究区,MOS-1b/MESSR影像数据作为遥感信息源,应用ERDAS I MAG-INE处理系统,对枯水期和洪水期两个不同时相的各波段影像数据进行组合运算、比值变换等处理,以及影像、光谱、直方图的对比分析。基于处理与分析结果,利用分...以湖南洞庭湖为研究区,MOS-1b/MESSR影像数据作为遥感信息源,应用ERDAS I MAG-INE处理系统,对枯水期和洪水期两个不同时相的各波段影像数据进行组合运算、比值变换等处理,以及影像、光谱、直方图的对比分析。基于处理与分析结果,利用分类技术,建立了水体分类模型(B1+B2)/(B3+B4)>t,可快速准确地提取水体信息;同时,还提取和建立了水深系数模型WDI=B1/B2,得出了基于非线性回归分析的水体深度探测模型。依据洪水信息提取模型,对枯水期与洪水期的分类专题图进行叠加分析,得到了洞庭湖区洪水期的洪水分布图与洪水淹没信息,可为防洪救灾决策提供重要的科学依据。展开更多
Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and ...Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and histogram comparison of the MESSR image data of all bands for the flood season and dry season with the ER-DAS IMAGINE system, a classification model was established, which can be used to acquire the spatial distributing information of water bodies. Meanwhile a water depth index model was derived and built, and then a model for detecting the depth of water body based on the non-linear recursive analysis was presented. By the overlay analysis of the classification thematic images based on the model for extracting flood information, the flooding area and distributing information were acquired.展开更多
文摘以湖南洞庭湖为研究区,MOS-1b/MESSR影像数据作为遥感信息源,应用ERDAS I MAG-INE处理系统,对枯水期和洪水期两个不同时相的各波段影像数据进行组合运算、比值变换等处理,以及影像、光谱、直方图的对比分析。基于处理与分析结果,利用分类技术,建立了水体分类模型(B1+B2)/(B3+B4)>t,可快速准确地提取水体信息;同时,还提取和建立了水深系数模型WDI=B1/B2,得出了基于非线性回归分析的水体深度探测模型。依据洪水信息提取模型,对枯水期与洪水期的分类专题图进行叠加分析,得到了洞庭湖区洪水期的洪水分布图与洪水淹没信息,可为防洪救灾决策提供重要的科学依据。
文摘Taking Dongting Lake district as the studying area and utilizing multi-temporal MOS-lb/MESSR data as remote sensing info source, by the combination operation and ratio transform processing and the image, spectrum and histogram comparison of the MESSR image data of all bands for the flood season and dry season with the ER-DAS IMAGINE system, a classification model was established, which can be used to acquire the spatial distributing information of water bodies. Meanwhile a water depth index model was derived and built, and then a model for detecting the depth of water body based on the non-linear recursive analysis was presented. By the overlay analysis of the classification thematic images based on the model for extracting flood information, the flooding area and distributing information were acquired.
