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  • 标题:Geoss possibilities and challenges related to nation wide forest monitoring
  • 本地全文:下载
  • 作者:H. Olsson ; M. Nilsson ; A. Persson
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2006
  • 卷号:XXXVI Part 7
  • 出版社:Copernicus Publications
  • 摘要:The Global Earth Observation System of Systems (GEOSS) is structured into nine societal benefit areas, which all will require information related to the forest cover. Utilisation of methods that combine satellite remote sensing and in-situ observations are the focus of GEOSS. The best way to feed forest information into GEOSS is most likely from the national level. In Sweden and Finland, nationwide raster based estimates of forest resources are already being made operationally by combining Landsat / SPOT type of satellite images with National Forest Inventory (NFI) sample plots. Another example of combined use of image data and local observations is that the Swedish forest administration yearly maps all new clear felled areas (about 50 000 in total), using multitemporal satellite data. The image analysis work done by the district foresters in 60 forest districts. Detected fellings are compared with cutting permits and verified in field if needed. A similar routine could also be used for Kyoto reporting of deforestation areas. The coordination of observation systems that will be achieved trough GEOSS is essential also for the continuation of these national level inventories. Satellite systems have global capacity, but each nation that relies on satellite systems for their operational monitoring would benefit from long-term coordination plans between nations that ensure a redundant capacity of future remote sensing satellites. Nations could also supply GEOSS with field plot information. This opportunity would motivate an increased harmonisation of the field observations made for example among the NFI's
  • 关键词:National forest monitoring; Landsat; SPOT; National Forest Inventory; GEO; GEOSS
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