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  • 标题:COMBINING REMOTE SENSING DATA SOURCES AND TERRESTRIAL SAMPLE-BASED INVENTORY DATA FOR THE USE IN FOREST MANAGEMENT INVENTORIES
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  • 作者:Matthias DEES ; Jan DUVENHORST ; Claus Peter GROSS
  • 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:2000
  • 卷号:XXXIII Part B7(/1-4)
  • 页码:355-362
  • 出版社:Copernicus Publications
  • 摘要:This paper presents two elements of a study on forest inventory and mapping in the context of forest management with a test site in the state Nordrhein-Westfalen, Germany. The first section concerns the analysis of the sample based forest inventory in a systematic grid design. The use of aerial photos represents an inexpensive, exact means of mapping the borders of the stand. This is a requirement for the analysis of the sample based forest inventory as a stratified sample. This analysis option makes it possible to reduce the sampling error for the central assessment attributes compared to an analysis using the simple random sampling approach. Along with the possibility of increasing accuracy, it is also possible to reduce the size of the sample by 25% without any loss of accuracy for the central assessment attributes. The second section concerns the k-nearest-neighbour method, in which sample data and medium resolution satellite data (Landsat TM and IRS1C LISS) are used. This method can provide a representation of the spatial distribution of central attributes. So far the mapping of main tree species has been the subject of study. This method does not provide a sufficient information basis for the standwise forest management inventory under the forest conditions that apply to the area studied. It can, however, provide a good overview of the spatial distribution of the main tree types
  • 关键词:Forestry; Sample Inventory; Stratification; Data Fusion; Photogrammetrie; Landsat TM
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