首页> 外文会议>Conference on Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III; Sep 9-11, 2003; Barcelona, Spain >Hydrologic land cover classification mapping at local level with the combined use of ASTER multispectral imagery and GPS measurements
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Hydrologic land cover classification mapping at local level with the combined use of ASTER multispectral imagery and GPS measurements

机译:结合使用ASTER多光谱图像和GPS测量,在当地进行水文土地覆被分类制图

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Digital Elevation Models (DEMs) and land cover products are primary inputs for hydrologic models of surface runoff that affects infiltration, erosion, and evapotranspiration. DEM and land cover play important role in determining the runoff characteristics of specific catchment areas. Recently, at local level, a number of data sources have been used to derive land cover products for high resolution studies. These studies have been carried out for a number of different applications, including estimation of biomass and vegetation mapping. A hydrologic land cover classification includes information not only about vegetation species, but also about the land surface and what classes are important hydrologically. This kind of classification must therefore incorporate information on elevation, slope, aspect, surface roughness, as well as vegetation species derived from satellite added-value products. The main problems when generating hydrologic land cover maps is the lack of accurate DEMs and the confusion of spectral responses from different features. In this study, a Terra/ASTER image acquired over the region of Heraklion, Crete, Greece was used. ASTER stereo imagery is used for DEM production because it gives a strong advantage in terms of radiometric variations versus the multi-date stereo-data acquisition with across-track stereo, which can then compensate for the weaker stereo geometry. GCPs (Ground Control Points) derived from differential GPS measurements were also used for absolute DEM production. A hydrologic land cover classification scheme was developed by combining ASTER multispectral imagery, ASTER DEM products and the spectral signatures derived from field observations at predefined training sites.
机译:数字高程模型(DEM)和土地覆盖产品是影响渗透,侵蚀和蒸散作用的地表径流水文模型的主要输入。 DEM和土地覆盖对于确定特定集水区的径流特征起着重要作用。最近,在地方一级,已经使用了许多数据源来推导用于高分辨率研究的土地覆盖产品。这些研究已经针对许多不同的应用进行,包括生物量估计和植被测绘。水文土地覆被分类不仅包括有关植被种类的信息,而且还包括有关地表和什么类别在水文上很重要的信息。因此,这种分类必须包含有关海拔,坡度,纵横比,表面粗糙度以及源自卫星增值产品的植被种类的信息。生成水文土地覆盖图时的主要问题是缺乏准确的DEM,以及来自不同特征的光谱响应的混乱。在这项研究中,使用了在希腊克里特岛伊拉克利翁地区上获得的Terra / ASTER图像。 ASTER立体影像可用于DEM制作,因为与跨轨立体影像的多日期立体数据采集相比,ASTER立体影像在辐射度变化方面具有强大的优势,因此可以补偿较弱的立体几何图形。由差分GPS测量得出的GCP(地面控制点)也用于绝对DEM生产。通过结合ASTER多光谱图像,ASTER DEM产品和从预定义培训地点的野外观测获得的光谱特征,开发了水文土地覆盖分类方案。

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