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Satellite scatterometer estimation of urban built-up volume: Validation with airborne lidar data

机译:卫星散射仪估计城市建筑卷:验证空气传播的LIDAR数据

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Accurately mapping urban infrastructure and extent is a high priority for resource management and service allocation as well as for addressing environmental, socioeconomic, and geopolitical concerns. Most available data products only document surficial (two-dimensional) land use and land cover (LULC), yet a substantial component of urban growth occurs in the vertical dimension. Light detection and ranging (lidar) data offer the potential for monitoring three-dimensional (3D) change, but the extreme lack of systematic lidar coverage worldwide inflicts considerable gaps in both spatial and temporal coverage. Satellite scatterometer (radar) data may serve as an alternative data source for characterizing urban growth and development in both the horizontal and vertical directions. The accuracy of these radar-based datasets for estimating building volumes remains to be validated quantitatively. For nine U.S. cities, we test whether scatterometer data can be used to estimate 3D urban built-up volume. We found strong, linear correlations between the lidar-derived and radar-derived building volume estimates for all cities with r(2) values as high as 0.98 when using spatial trend analysis. Given the high expense that limits lidar data acquisition to small areas at sporadic points in time, satellite scatterometer data provide a breakthrough method for monitoring both vertical growth and horizontal expansion of cities across the world with a continuous decadal time scale.
机译:准确地绘制城市基础设施和范围是资源管理和服务分配的高度优先考虑,以及解决环境,社会经济和地缘政治问题。最可用的数据产品仅限于文件表演(二维)土地使用和陆地覆盖(LULC),但垂直尺寸发生了大量的城市生长分量。光检测和测距(LIDAR)数据提供了监控三维(3D)变化的可能性,但全球极端缺乏系统的激光乐队覆盖范围在空间和时间覆盖范围内造成了相当大的差距。卫星散射仪(雷达)数据可以用作在水平和垂直方向上表征城市生长和发展的替代数据源。用于估计建筑卷的基于雷达的数据集的准确性仍然是定量验证的。对于九个美国城市,我们测试散射计数据是否可用于估算3D城市建筑体积。我们在使用空间趋势分析时发现了LIDAR导出和雷达推导的建筑物估计的LIDAR导出和雷达推导的建筑物估计的强劲,线性相关性,并且在使用空间趋势分析时,高达0.98。鉴于将LIDAR数据采集限制在零星点的小区的高费用,卫星散射仪数据提供了一种突破性的方法,用于监测全球各地的垂直增长和横向扩展,具有连续的分支时间尺度。

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