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首页> 外文期刊>International journal of remote sensing >Results from the EO-1 experiment—A comparative study of Earth Observing-1 Advanced Land Imager (ALI) and Landsat ETM + data for land cover mapping in the Okavango Delta, Botswana
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Results from the EO-1 experiment—A comparative study of Earth Observing-1 Advanced Land Imager (ALI) and Landsat ETM + data for land cover mapping in the Okavango Delta, Botswana

机译:EO-1实验的结果-博茨瓦纳奥卡万戈三角洲的Earth-1先进陆地成像仪(ALI)和Landsat ETM +土地覆盖制图数据的比较研究

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摘要

The Earth Observing-1 (EO-1) satellite acquired a sequence of data in 2001 and 2002 that highlighted the annual flooding of the lower Okavango Delta. The data were collected as part of the calibration/validation programme for the Advanced Land Imager (ALI) sensor on the NASA EO-1 satellite. The primary purpose of this study was to compare the capability of ALI to that of Landsat ETM + for large-scale mapping applications in the Okavango Delta. While the extent and inaccessibility of many areas of the Delta make application of remote sensing attractive, the availability of data with adequate spatial and spectral resolution has limited the characterization of the complex patterns of land cover and geomorphology in the Delta. Initial analysis of the ALI data via supervised classification clearly showed macro-flood features, delineation of downstream channel flow areas, and lateral-downstream inundation of the floodplain. These patterns and the proportions of flooding of the channel compared to that of the floodplain (impoundment) varied annually, from the wetter seasonal swamps through the drier seasonal and occasional swamps. Consistently higher classification accuracies achieved using ALI data relative to ETM+ data are attributed to the higher signal-to-noise ratio and the increased dynamic range of the ALI data.
机译:地球观测1号(EO-1)卫星在2001年和2002年获得了一系列数据,这些数据突出了奥卡万戈下游三角洲的年度洪水。收集的数据是NASA EO-1卫星上高级陆地成像仪(ALI)传感器的校准/验证程序的一部分。这项研究的主要目的是比较ALI和Landsat ETM +在Okavango三角洲进行大规模制图应用的能力。尽管三角洲许多地区的范围和不可及性使遥感的应用具有吸引力,但具有足够空间和光谱分辨率的数据可用性限制了三角洲土地覆盖和地貌的复杂模式的特征。通过监督分类对ALI数据进行的初步分析清楚地显示了大洪水特征,下游河道流量区域的划分以及洪泛区的横向-下游淹没。从湿润的季节性沼泽到干燥的季节性和偶发性沼泽,这些模式和河道与洪泛区(蓄水)相比的洪水比例每年都在变化。相对于ETM +数据,使用ALI数据获得的更高的分类精度始终归因于更高的信噪比和ALI数据的动态范围增加。

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