首页> 外文期刊>Remote Sensing >Comparison of TanDEM-X DEM with LiDAR Data for Accuracy Assessment in a Coastal Urban Area
【24h】

Comparison of TanDEM-X DEM with LiDAR Data for Accuracy Assessment in a Coastal Urban Area

机译:TanDEM-X DEM与LiDAR数据的比较,用于沿海城市地区的精度评估

获取原文
       

摘要

The TanDEM-X (TDX) mission launched by the German Aerospace Center delivers unprecedented global coverage of a high-quality digital elevation model (DEM) with a pixel spacing of 12 m. To examine the relationships of terrain, vegetation, and building elevations with hydrologic, geologic, geomorphologic, or ecologic factors, quantification of TDX DEM errors at a local scale is necessary. We estimated the errors of TDX data for open ground, forested, and built areas in a coastal urban environment by comparing the TDX DEM with LiDAR data for the same areas, using a series of error measures including root mean square error (RMSE) and absolute deviation at the 90% quantile (LE90). RMSE and LE90 values were 0.49 m and 0.79 m, respectively, for open ground. These values, which are much lower than the 10 m LE90 specified for the TDX DEM, highlight the promise of TDX DEM data for mapping hydrologic and geomorphic features in coastal areas. The RMSE/LE90 values for mangrove forest, tropical hardwood hammock forest, pine forest, dense residential, sparse residential, and downtown areas were 1.15/1.75, 2.28/3.37, 3.16/5.00, 1.89/2.90, 2.62/4.29 and 35.70/51.67 m, respectively. Regression analysis indicated that variation in canopy height of densely forested mangrove and hardwood hammock was well represented by the TDX DEM. Thus, TDX DEM data can be used to estimate tree height in densely vegetated forest on nearly flat topography next to the shoreline. TDX DEM errors for pine forest and residential areas were larger because of multiple reflection and shadow effects. Furthermore, the TDX DEM failed to capture the many high-rise buildings in downtown, resulting in the lowest accuracy among the different land cover types. Therefore, caution should be exercised in using TDX DEM data to reconstruct building models in a highly developed metropolitan area with many tall buildings separated by narrow open spaces.
机译:德国航空航天中心发射的TanDEM-X(TDX)任务以像素间距12 m的高质量数字高程模型(DEM)提供了前所未有的全球覆盖范围。要检查地形,植被和建筑物标高与水文,地质,地貌或生态因素之间的关系,必须在本地范围内量化TDX DEM误差。我们通过将TDX DEM与相同地区的LiDAR数据进行比较,使用一系列均方根误差(RMSE)和绝对误差的误差度量,我们估算了沿海城市环境中空旷,森林和建筑区域的TDX数据的误差90%分位数(LE90)的偏差。对于开阔地面,RMSE和LE90值分别为0.49 m和0.79 m。这些值远低于为TDX DEM指定的10 m LE90,这凸显了TDX DEM数据有望绘制沿海地区的水文和地貌特征。红树林,热带硬木吊床森林,松树林,茂密的居民区,稀疏的居民区和市区的RMSE / LE90值分别为1.15 / 1.75、2.28 / 3.37、3.16 / 5.00、1.89 / 2.90、2.62 / 4.29和35.70 / 51.67米,分别。回归分析表明,TDX DEM很好地代表了茂密的红树林和硬木吊床的冠层高度变化。因此,TDX DEM数据可用于在靠近海岸线的近乎平坦地形上的茂密植被森林中估计树木的高度。由于多重反射和阴影效应,松树林和居民区的TDX DEM误差较大。此外,TDX DEM无法捕获市区内的许多高层建筑,导致不同土地覆盖类型中的精度最低。因此,在高度发达的大都市地区,用许多狭窄的开放空间隔开许多高层建筑时,应谨慎使用TDX DEM数据重建建筑模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号