Forestry Applications for Satellite Lidar Remote Sensing
Forestry Applications for Satellite Lidar Remote Sensing
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DOI：
10.14358/pers.77.3.271
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发表时间：
2011
影响因子：
1.3
通讯作者：
J. Rosette;J. Suárez;P. North;S. Los
中科院分区：
文献类型：
--
作者：
J. Rosette;J. Suárez;P. North;S. Los
本文介绍了一种方法来估计森林参数和表面地形从美国宇航局的地球科学激光高度计系统（GLAS）。他们的潜在用途作为观测输入模型证明使用风风险模型为英国，ForestGALES。地面以上的相对高度被用作生物物理参数估计。顶高估算值R2 = 0.73，RMSE = 4.5m.针叶林为主的林分（R2 = 0.72，RMSE = 0.07 m）和阔叶林为主的林分（R2 = 0.41，RMSE = 0.11 m），胸径估计值不同。地面高程估计得到R2 = 0.997，RMSE = 2.2m.这三个参数被应用到F orestGALES林分水平的风抛风险评估。稳定性对树木尺寸的微小差异很敏感，因此植被参数需要比目前从GLAS检索的参数更高的精度，以更可靠地确定风吹风险。未来的卫星激光雷达任务，如美国宇航局的DESDynI传感器的目标是产生改进的植被参数估计加上更大的空间覆盖范围，这将提供更适当的输入林业模型。
This paper presents a method to estimate forest parameters and surface topography from NASA's Geosciences Laser Altimeter System (GLAS). Their potential use as observational inputs to models is demonstrated using a wind-risk model for the UK, ForestGALES. Relative heights above ground were used as biophysical parameter estimators. Top Height was estimated with R 2 = 0.73, RMSE = 4.5 m. Diameter at breast height estimates differed for conifer-dominated stands (R 2 = 0.72, RMSE = 0.07 m) and for stands containing mostly broadleaves (R 2 = 0.41, RMSE = 0.11 m). Ground elevation estimation produced R 2 = 0.997, RMSE = 2.2 m. These three parameters were applied to F orestGALES for stand-level assessment of wind-throw risk. Stability is sensitive to small differences in tree dimensions, and therefore vegetation parameters require greater accuracy than those currently retrievable from GLAS to more reliably determine risk of wind-throw. Future satellite lidar missions such as NASA's DESDynI sensor aim to produce improved vegetation parameter estimation plus greater spatial coverage which would offer more appropriate inputs for forestry models.