@article{RN139,
   author = {Fazakas, Z. and Nilsson, M. and Olsson, H.},
   title = {Regional forest biomass and wood volume estimation using satellite data and ancillary data},
   journal = {Agricultural and Forest Meteorology},
   volume = {98-99},
   pages = {417-425},
   abstract = {Tree biomass and wood volume was estimated for parts of the NOPEX region in Central Sweden (latitude 60°00', longitude 17°00'). National Forest Inventory (NFI) sample plot data was combined with Landsat TM data using an inverse-squared distance weighting in a feature space defined by TM bands 1-5, and 7. This estimation method is known as the 'k nearest-neighbor' method. Estimates are produced for all forest land pixels in the TM image and are represented as a grid of 25 m x 25 m raster cells. The estimates were evaluated, both using cross validation and with the help of plots from an intensively sampled validation area. The accuracy on grid-cell level was poor, but increased when aggregations of cells were evaluated. The mean RMSE error as a function of area of aggregation is presented. The obtained RMSE for an aggregation area of 510 ha forests land, was 8.7% for biomass and 4.6% for wood volume.},
   keywords = {Digital Satellite Images
Forest Biomass
Forest Wood Volume},
   ISSN = {01681923},
   DOI = {10.1016/S0168-1923(99)00112-4},
   url = {http://www.sciencedirect.com/science/article/pii/S0168192399001124},
   year = {1999},
   type = {Journal Article}
}

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