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Estimation of stem volume in hemi-boreal forests using airborne low-frequency Synthetic Aperture Radar and lidar data

机译:利用机载低频合成孔径雷达和激光雷达数据估算半北方森林的茎量

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Synthetic Aperture Radar (SAR) backscatter data from the Swedish airborne CARABAS-II and LORA systems were used to estimate stem volume at stand level. The study was performed in hemi-boreal forests at the Remningstorp test site, located in southern Sweden. In total, ten 80 m × 80 m stands, where all trees were measured in situ, with stem volumes in the range of 70-530 m3 ha-1 (on average 347 m3 ha-1) were analyzed. SAR data from CARABAS-II and LORA were acquired from two different years, with nine unique flight headings that were repeated for each system and year. Regression analysis was used to estimate stem volume and the accuracy was assessed in terms of Root Mean Square Error (RMSE). As a first step, stem volume was estimated for each flight heading separately. The accuracy assessment was then performed by weighting the separate estimates for each system and year inversely proportionally to the variance about the regression function. The best results for CARABAS-II and LORA showed a relative RMSE of 7% and 24% of the mean stem volume, respectively. In a previous study, stem volume was estimated using LiDAR data and the same forest stands, resulting in an RMSE of about 12%. In conclusion, the estimation accuracy of stem volume using combined low-frequency CARABAS SAR images was found to be superior to that from using LiDAR data for the stands investigated.
机译:来自瑞典机载CARABAS-II和LORA系统的合成孔径雷达(SAR)背向散射数据用于估算林分水平的茎干体积。这项研究是在位于瑞典南部的Remningstorp测试地点的半北方森林中进行的。总共有10个80 m×80 m的林分,其中所有树木都进行了现场测量,茎体积在70-530 m 3 ha -1 范围内(在平均347 m 3 ha -1 )。来自CARABAS-II和LORA的SAR数据是从两个不同的年份获取的,每个系统和年份都重复了9个独特的飞行方向。回归分析用于估计茎体积,并根据均方根误差(RMSE)评估准确性。第一步,分别估算每个飞行航向的茎体积。然后,通过对每个系统和年份的独立估计值加权,与回归函数的方差成反比地进行准确性评估。 CARABAS-II和LORA的最佳结果分别显示相对RMSE分别为平均茎体积的7%和24%。在先前的研究中,使用LiDAR数据和相同的林分估算了茎的体积,导致RMSE约为12%。总之,发现使用组合低频CARABAS SAR图像进行茎量估计的准确性优于使用LiDAR数据进行研究的立场。

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