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FOREST DRAGON 2: FINAL RESULTS OF THE EUROPEAN PARTNERS

机译:森林龙2:欧洲合作伙伴的最终结果

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The European contribution to the Forest DRAGON 2 focused on the evaluation of multi-temporal, multisensor and multi-scale Earth Observation images and data products within the vegetation ecosystem of Northeast China. The forest growing stock volume (GSV) map produced with ERS-1/2 coherence images for 1995-1998 and two GSV maps produced from Envisat ASAR ScanSAR data for 2005 and 2010 were inter-compared with respect to several datasets (in situ, EO images and EO data products) to assess the plausibility of the GSV estimates, the contribution to land cover mapping and the dynamics over time. For this purpose, a multi-source database was set up including in situ data and EO data products. Land use / land cover (LULC) datasets identified mis-classification of GSV in the ERS dataset primarily for cropland. An a posteriori correction of the GSV resulted in an increase of overall accuracy up to 7%. LULC products can also support the fine tuning of the algorithm to estimate GSV from ASAR data particularly in transition regions between forest and shrubland. The ASAR-based GSV estimates were consistent and highlighted areas of change. From the two ASAR maps, slight loss of volume from 2005 to 2010 was estimated.
机译:到森林DRAGON 2欧洲贡献侧重于多时相的评价,多传感器和多尺度中国东北地区的植被生态系统内的地球观测图像和数据产品。森林蓄积量(GSV)产生地图ERS-1/2为1995-1998相干图像和两个GSV映射从ENVISAT ASAR扫描SAR数据产生为2005和2010是相互比较相对于几个数据集(原位,EO图像和EO数据产品)以评估GSV估计的似然性,土地覆盖映射的贡献,并随着时间的推移动态。为了这个目的,一个多源数据库成立包括原位数据和EO数据产品。土地利用/土地覆盖(LULC)数据集识别错误分类GSV在ERS的主要数据集农田。在GSV的后验校正导致高达7%的增加总体精度。 LULC产品还可以支持算法的微调,以从ASAR数据特别是在森林和灌木之间的过渡区域估计GSV。基于ASAR-GSV估计是变化一致,并强调区域。从这两个ASAR地图,2005年至2010批量的轻微损失估计。

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