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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR
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Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR

机译:北半球森林蓄积量:根据Envisat ASAR得出的2010年空间明确估计

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摘要

This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10 degrees N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01 degrees were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (<30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (>300 m(3)/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%). (C) 2015 Elsevier Inc. All rights reserved.
机译:本文使用BIOMASAR算法通过对Envisat先进合成孔径雷达(ASAR)背向散射强度的超时间观测,提出并评估了北半球(北纬10度以北)的森林生长蓄积量(GSV)的空间显式估计。像素大小为0.01度的大约70,000张ASAR图像用于估算2010年的GSV代表性。基于ASAR的估算可以很好地捕获GSV在四个生态区(极地,寒带,温带,亚热带)的空间分布。 。在寒带和温带森林中,所获得的GSV的不确定性最小(对于大约80%的森林面积,<30%),在亚热带森林中,不确定性最大。行政单位一级由ASAR得出的GSV平均值与由清单得出的估计值基本一致。低估发生在GSV很高(> 300 m(3)/ ha)和林地零散的地区。对于研究区域内的主要森林国家,ASAR得出的省级GSV平均值与国家森林清单的相应值之间的相对RMSE在12%至45%之间(平均值:29%)。 (C)2015 Elsevier Inc.保留所有权利。

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