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来源类型 | Article |
规范类型 | 其他 |
DOI | 10.1016/j.rse.2015.07.005 |
Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. | |
Santoro M; Beaudoin A; Beer C; Cartus O; Fransson JES; Hall RJ; Schmullius C; Schepaschenko D | |
发表日期 | 2015 |
出处 | Remote Sensing of Environment 168: 316-334 |
出版年 | 2015 |
语种 | 英语 |
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 GV 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 admnistrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (> 30 m^3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE betwen ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%). |
主题 | Ecosystems Services and Management (ESM) |
关键词 | Envisat ASAR Forest Growing stock volume Biomass MODIS Vegetation Continuous Fields BIOMASAR Northern hemisphere |
URL | http://pure.iiasa.ac.at/id/eprint/11410/ |
来源智库 | International Institute for Applied Systems Analysis (Austria) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130336 |
推荐引用方式 GB/T 7714 | Santoro M,Beaudoin A,Beer C,et al. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR.. 2015. |
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