• DocumentCode
    291406
  • Title

    Vegetation mapping of forested ecosystems in interior Central Alaska

  • Author

    Ustin, Susan L. ; Szeto, Lai-Han ; Xiao, Qing-Fu ; Hart, J. ; Kasischke, Eric S.

  • Author_Institution
    Dept. of Land Air & Water Resources, California Univ., Davis, CA, USA
  • Volume
    1
  • fYear
    1994
  • fDate
    8-12 Aug 1994
  • Firstpage
    229
  • Abstract
    A digital elevation map (DEM), digital soil survey map, and a 1991 Systeme Probatoire d´Observation de la Terre (SPOT) satellite image were used in a geographical information system (GIS) to identify 12 forest types at the Bonanza Creek Experimental Forest (BCEF) in Central Alaska. A potential vegetation distribution map for the boreal forest ecosystem in the interior of Alaska was created using a hierarchical decision tree. The site was first stratified into montane, flood plain, and lowland zones based on topography. Within the montane zone, topographic information (elevation, aspect, and slope) used to define potential vegetation classes. SPOT band 3 (0.50-0.59 μm) data was used to identify the boundary of a 1983 wildfire within the zone. The forests in the flood plain and lowland zones were not strongly associated with topographic features due to the low relief, so the Normalized Difference Vegetation Index (NDVI) was the primary basis for defining forest types. Separating the flood plain from the lowland zone was done based on variance ranges in NDVI. This method has promise for mapping vegetation distributions in other boreal regions when little or no ground data is available for validation
  • Keywords
    forestry; geophysical techniques; remote sensing; GIS; NDVI; Normalized Difference Vegetation Index; SPOT satellite image; USA United States Alaska; boreal forest type forestry; digital elevation map; geographical information system; geophysical measurement technique; hierarchical decision tree; optical imaging; remote sensing; soil survey map; topographic information; vegetation class; vegetation mapping; visible infrared image IR; Decision trees; Ecosystems; Floods; Gases; Remote monitoring; Satellites; Space technology; Surfaces; Vegetation mapping; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
  • Conference_Location
    Pasadena, CA
  • Print_ISBN
    0-7803-1497-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.1994.399088
  • Filename
    399088