知识与财富的链接
为了从海量遥感数据中有效地提取地表水体信息,并提高自动化提取效率,提出了一种基于遥感特征指数的地表水体自动提取方法.该方法选取归一化植被指数(NDVI)、归一化建筑指数(NDBI)和修正归一化水体指数(MNDWI)作为遥感特征指数集,并根据这些指数构建了遥感特征指数曲线.通过分析,发现地表水体在特征曲线中单调上升,植被在特征曲线中单调下降,而其它地物并无此特征.因此,根据这一规律,利用ERDAS IMAGINE软件建立了自动化提取模型.通过与其他方法对比,表明所建立的模型在精度和自动化方面都明显优于其他方法,可用于海量数据地表水体的自动提取.最后,在ARCGIS环境下,并通过决策树模型初步实现了地表水体的自动分类.
Aimed at extracting surface water information from the mass remote sensing data effectively, and improving the efficiency of automatic extraction, a new method is presented in this paper by producing a curve based on Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-up Index (NDBI), and Modified Normalized Difference Water Index (MNDWI). According to the analysis, a rule is found, that is, the DN value of surface water increases monotonically in the curve, the DN value of vegetation decreases monotonically, but other typical objects, like soils and vegetation, do not have the character. Based on this rule, an automatic extraction model is built by the ERDAS IMAGINE software. Compared with the existing methods, the precision of the model is better than those of others. At last, the surface water is automatically classified by the decision tree model under the ARCGIS software context.
