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Object-based classification of vegetation and terrain topography in Southwestern Amazonia (Brazil) as a tool for detecting ancient fluvial geomorphic features

机译:基于对象的西南亚马逊地区(巴西)植被和地形地貌分类,作为检测古代河流地貌特征的工具

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Reconstructing the evolution of large tropical fluvial systems over the geological time is challenging, particularly in areas such as the Amazonian lowlands where basic geological and geomorphological data are still scarce relatively to the large dimension of the region. In such areas, remote sensing data are useful for detecting ancient morphological features that may reveal past fluvial dynamics. In this study, we explored object-based image analysis (OBIA) in the Madeira-Purus interfluve, Southwestern Brazilian Amazonia, integrating geospatial data including Landsat satellite multispectral images, the digital elevation model (DEM) acquired during the Shuttle Radar Topography Mission (SRTM), and stream channels digitized from topographic maps. This approach provided the basis to categorize automatically classes with contrasting vegetation and/or topographic characteristics within the dense tropical forest over an extensive and relatively flat forested area. The main goal was to use these classes as a surrogate for the recognition of ancient geomorphic features consisting mainly of paleochannels that may help reconstructing fluvial history in space and time. Landsat optical images with stream vector were appropriate to classify open vegetation areas that grow over paleochannels, but failed to identify these objects when they were located over forested areas. However, the digital elevation model (DEM) derived from the Shuttle Radar Topography Mission (SRTM) was successful to detect these objects even in forested areas. Topographic survey undertaken in the field increased the classification reliability by demonstrating true terrain variations along transects measured across the paleochannels. Based on this technique, networks of dendritic paleochannels were mapped and related to ancient tributaries of the Madeira River that had their courses flowing opposite to main modern streams. This denotes a significant change in fluvial dynamics over time, most likely resulting from tectonic tilting.
机译:在地质时期重建大型热带河流系统的演化具有挑战性,特别是在亚马逊地区低地等地区,相对于该地区的大范围而言,基本地质和地貌数据仍然匮乏。在此类地区,遥感数据可用于检测可能揭示过去河流动力学的古老形态特征。在这项研究中,我们探索了巴西西南亚马逊地区马德拉-普鲁斯交汇处的基于对象的图像分析(OBIA),整合了包括Landsat卫星多光谱图像的地理空间数据,在航天飞机雷达地形任务(SRTM)期间获得的数字高程模型(DEM) ),以及从地形图数字化的流渠道。该方法为在广阔且相对平坦的森林区域内茂密的热带森林中具有鲜明对比的植被和/或地形特征的类别进行自动分类提供了基础。主要目标是使用这些类别作为替代,以识别主要由古河道组成的古代地貌特征,这些特征可能有助于重建河流的时空历史。具有流矢量的Landsat光学图像适合对在古河道上生长的开放植被区域进行分类,但是当它们位于森林区域上方时无法识别这些物体。但是,从航天飞机雷达地形任务(SRTM)派生的数字高程模型(DEM)即使在森林地区也能成功检测到这些物体。在野外进行的地形调查通过展示沿整个古河道测量的横断面的真实地形变化,提高了分类的可靠性。基于这种技术,对树突状古河道网络进行了映射,并与马德拉河的古代支流相关,这些支流的水流与现代主要河流相反。这表明河流动力学随时间发生了重大变化,这很可能是由于构造倾斜造成的。

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