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Retrieval of savanna vegetation canopy height from ICESat-GLAS spaceborne LiDAR with terrain correction

机译:利用地形校正从ICESat-GLAS星载LiDAR反演大草原植被冠层高度

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摘要

Light detection and ranging (LiDAR) remote sensing enables accurate estimation and monitoring of vegetation structural properties. Airborne and spaceborne LiDAR is known to provide reliable information on terrain elevation and forest canopy height over closed forests. However, it has rarely been used to characterize savannas, which have a complex structure of trees coexisting with grasses. This letter presents the first validation of spaceborne Ice Cloud and land Elevation Satellite Geoscience Laser Altimeter System (GLAS) full-waveform data to retrieve savanna vegetation canopy height that uses field data specifically collected within the GLAS footprints. Two methods were explored in the Kruger National Park, South Africa: one based on the Level 2 Global Land Surface Altimetry Data product and the other using Level 1A Global Altimetry Data (GLA01) with terrain correction. Both methods use Gaussian decomposition of the full waveform. Airborne LiDAR (AL) was also used to quantify terrain variability (slope) and canopy height within the GLAS footprints. The canopy height retrievals were validated with field observations in 23 GLAS footprints and show that the direct method works well over flat areas (Pearson correlation coefficient r = 0.70, , and n = 8 for GLA01) and moderate slopes (r = 0.68, , and n = 9 for GLA01). Over steep slopes in the footprint, however, the retrievals showed no significant correlation and required a statistical correction method to remove the effect of terrain variability on the waveform extent. This method improved the estimation accuracy of maximum vegetation height with correlations (R2 = 0.93, , and n = 6 using the terrain index (g) generated from AL data and R2 = 0.91,, and n = 6 using the GLAS returned waveform width parameter). The results suggest that GLAS can provide savanna canopy height estimations in complex tree/grass plant communities.
机译:光检测和测距(LiDAR)遥感技术可以准确估算和监测植被的结构特性。机载和机载LiDAR已知可提供有关封闭森林上的地形高度和森林冠层高度的可靠信息。然而,它很少用于表征稀树草原,稀树草原具有树木和草类并存的复杂结构。这封信是对星载冰云和陆地高程卫星地球科学激光测高仪系统(GLAS)全波形数据进行的首次验证,该数据用于检索使用GLAS足迹内专门收集的野外数据的稀树草原植被冠层高度。在南非的克鲁格国家公园,探索了两种方法:一种基于2级全球陆地海拔测高数据产品,另一种基于1A级全球测高数据(GLA01)进行地形校正。两种方法都使用整个波形的高斯分解。机载LiDAR(AL)还用于量化GLAS足迹内的地形变化性(坡度)和冠层高度。在23个GLAS足迹中通过实地观测对冠层高度进行了验证,结果表明直接方法在平坦区域(Pearson相关系数r = 0.70,对于GLA01为n = 8)和中等坡度(r = 0.68,以及对于GLA01,n = 9)。但是,在覆盖区的陡坡上,检索结果没有显示出显着的相关性,因此需要一种统计校正方法来消除地形变化对波形范围的影响。此方法使用从AL数据生成的地形指数(g)和R2 = 0.91且使用GLAS返回的波形宽度参数n = 6的相关性(R2 = 0.93,n = 6)提高了最大植被高度的估计精度。 )。结果表明,GLAS可以在复杂的树/草植物群落中提供稀树草原冠层高度估计。

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