Montesano Paul M, Neigh Christopher, Sun Guoqing, Duncanson Laura, Hoek Jamon Van Den, Jon Ranson K
Science Systems and Applications, Inc., 10210 Greenbelt Road, Lanham, MD 20706, USA.
Code 618, Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt MD 20771.
Remote Sens Environ. 2017 Jul;196:76-88. doi: 10.1016/j.rse.2017.04.024. Epub 2017 May 7.
Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; < 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereopairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereopairs, (2) identify multiple spatially coincident DSMs whose stereopairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and (4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereopair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian forests with slopes < 10°, our results show that HRSI DSMs acquired with sun elevation angles > 35° and < 25° (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors < 0.68 m relative to lidar. The latter, particularly those with angles < 10°, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (μ = 6.0 m, σ = 1.4 m) was consistent with the distribution of plot-level mean tree heights (μ = 6.5 m, σ = 1.2 m). We conclude that the variation in sun elevation angle at time of stereopair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register and difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.
将立体测量法应用于全球可用的高分辨率星载影像(HRSI;空间分辨率小于5米)可生成精细尺度的高程数字表面模型(DSM)。这些DSM可能代表从地面到植被冠层表面的高程,由具有各种采集特征的立体图像对(立体像对)生成,并已与森林结构和地面高程的激光雷达数据相结合以研究森林高度。这项工作探索了在开阔冠层森林中通过两种类型采集得到的HRSI DSM的表面高程。我们(1)将自动化大规模生产立体测量工作流程应用于沿轨HRSI立体像对,(2)识别多个空间重合的DSM,其立体像对是在不同太阳几何条件下采集的,(3)以重合的星载激光雷达足迹(来自ICESat - GLAS)为参考对这些DSM进行垂直配准,以及(4)研究参考激光雷达与配准后的HRSI DSM之间表面高程的差异,这些差异与来自不同太阳仰角的两种一般采集类型(DSM类型)相关。我们发现,这些以立体像对采集时的太阳仰角区分的DSM类型,与开阔冠层森林中通过自动立体测量估计的不同表面高程相关。对于在坡度小于10°的西伯利亚北部开阔冠层森林中具有来自星载激光雷达足迹的相应参考地面高程的DSM值,我们的结果表明,在无雪条件下太阳仰角大于35°和小于25°时采集的HRSI DSM产生了与参考激光雷达不同的特征性且始终明显的高程差异分布。前者包括相对于激光雷达均方根误差小于0.68米的近地面表面DSM。后者,特别是那些仰角小于10°的,显示出与激光雷达差异更大的分布,这与植被表面高程被捕获的开阔冠层森林有关。地形坡向对植被表面的分布没有强烈影响。将这两种DSM类型结合使用,森林中DSM差值高度的分布(μ = 6.0米,σ = 1.4米)与样地水平平均树高的分布(μ = 6.5米,σ = 1.2米)一致。我们得出结论,立体像对采集时太阳仰角的变化可以创造有利于捕获近地面或与植被冠层相关表面高程的光照条件。了解HRSI采集的太阳几何条件和积雪覆盖情况可用于理解和组合立体测量表面高程估计值,以配准和区分重叠的DSM,提供一种在精细尺度上绘制森林高度的方法,从星载平台解析开阔冠层森林中树木群体的垂直结构。