首页> 外文期刊>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences >UNMANNED AERIAL VEHICLE LASER SCANNING FOR EROSION MONITORING IN ALPINE GRASSLAND
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UNMANNED AERIAL VEHICLE LASER SCANNING FOR EROSION MONITORING IN ALPINE GRASSLAND

机译:高山草原侵蚀监测的无人空中车辆激光扫描

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With this contribution we assess the potential of unmanned aerial vehicle (UAV) based laser scanning for monitoring shallow erosion in Alpine grassland. A 3D point cloud has been acquired by unmanned aerial vehicle laser scanning (ULS) at a test site in the subalpine/alpine elevation zone of the Dolomites (South Tyrol, Italy). To assess its accuracy, this point cloud is compared with (i) differential global navigation satellite system (GNSS) reference measurements and (ii) a terrestrial laser scanning (TLS) point cloud. The ULS point cloud and an airborne laser scanning (ALS) point cloud are rasterized into digital surface models (DSMs) and, as a proof-of-concept for erosion quantification, we calculate the elevation difference between the ULS DSM from 2018 and the ALS DSM from 2010. For contiguous spatial objects of elevation change, the volumetric difference is calculated and a land cover class (bare earth, grassland, trees), derived from the ULS reflectance and RGB colour, is assigned to each change object. In this test, the accuracy and density of the ALS point cloud is mainly limiting the detection of geomorphological changes. Nevertheless, the plausibility of the results is confirmed by geomorphological interpretation and documentation in the field. A total eroded volume of 672 m3 is estimated for the test site (48 ha). Such volumetric estimates of erosion over multiple years are a key information for improving sustainable soil management. Based on this proof-of-concept and the accuracy analysis, we conclude that repeated ULS campaigns are a well-suited tool for erosion monitoring in Alpine grassland.
机译:通过这一贡献,我们评估了无人驾驶飞行器(UAV)激光扫描的潜力,用于监测高山草原的浅层侵蚀。在白云岩(南蒂罗尔,意大利南蒂罗尔)的亚高山/高山仰地区的测试部位,通过无人的空中车辆激光扫描(ULS)获得了3D点云。为了评估其准确性,将该点云与(i)差分全球导航卫星系统(GNSS)参考测量值和(ii)进行比较,并且(ii)陆地激光扫描(TLS)点云。 ULS点云和空降激光扫描(ALS)点云在数字表面模型(DSMS)中,作为侵蚀量化的验证,我们从2018年和ALS计算ULS DSM之间的高度差异DSM从2010年开始。对于高程变化的连续空间物体,计算体积差异,并为每个变更对象分配了从ULS反射率和RGB颜色的陆地覆盖类(裸地,草地,树木)。在该测试中,ALS点云的准确性和密度主要限制了地貌变化的检测。尽管如此,结果的合理性通过领域的地貌解释和文件证实了。估计测试部位(48公顷)估计总侵蚀的672m 3体积。多年来的这种体积估计是改善可持续土壤管理的关键信息。基于这种概念证明和准确性分析,我们得出结论,重复的ULS运动是高山草原中侵蚀监测的一个很好的工具。

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