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ESTIMATING SEMIARID VEGETATION HEIGHT FROM GLAS DATA

机译:从GLAS数据估算半干旱植被高度

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The Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud and land Elevation Satellite (ICESat), was designed primarily for ice information measurement, but has been recently used to characterize vegetation structure and estimate canopy heights and biomass over a range of forest types and topography. GLAS data, however, have not been used to estimate semiarid vegetation, with typically low height stature. We investigate the ability of GLAS data to estimate vegetation height and density at the Idaho National Laboratory (INL) in southeastern Idaho, USA, an area of low topographic relief, minimizing within-footprint topographic and vegetation variation. Vegetation derivatives obtained from GLAS data are compared to airborne LiDAR data collected over the same area in 2006 for uncertainty estimates. Accurate vegetation canopy characterization with GLAS will provide large-scale biomass estimates, along with roughness estimates for surface energy balance models and weather forecasting.
机译:Geoscience激光高度计系统(GLAS)在冰,云和陆地海拔卫星(ICESAT)上主要用于冰信息测量,但最近用于在一系列森林类型上表征植被结构和估算冠层高度和生物量和地形。然而,GLAS数据尚未用于估计半干旱植被,通常具有低高度的身材。我们调查了Glas数据在美国东南部的伊达荷州国家实验室(INL)估算了植被高度和密度的能力,这是一个低地形救济区域,最大限度地减少了占地面积内的地形和植被变化。将Glas数据获得的植被衍生物与2006年在同一地区收集的空气传播的LIDAR数据进行比较,以便不确定性估计。用格拉斯准确的植被冠层表征将提供大规模的生物量估计,以及表面能量平衡模型和天气预报的粗糙度估计。

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