@article{RN138,
   author = {Fazakas, Z. and Nilsson, M.},
   title = {Volume and forest cover estimation over southern Sweden using AVHRR data calibrated with TM data},
   journal = {International Journal of Remote Sensing},
   volume = {17},
   number = {9},
   pages = {1701-1709},
   abstract = {In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest. In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest.},
   ISSN = {0143-1161},
   DOI = {10.1080/01431169608948733},
   url = {http://dx.doi.org/10.1080/01431169608948733},
   year = {1996},
   type = {Journal Article}
}

{"_id":"5ZvSKx2GxN3NMCiYy","bibbaseid":"fazakas-nilsson-volumeandforestcoverestimationoversouthernswedenusingavhrrdatacalibratedwithtmdata-1996","author_short":["Fazakas, Z.","Nilsson, M."],"bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Fazakas"],"firstnames":["Z."],"suffixes":[]},{"propositions":[],"lastnames":["Nilsson"],"firstnames":["M."],"suffixes":[]}],"title":"Volume and forest cover estimation over southern Sweden using AVHRR data calibrated with TM data","journal":"International Journal of Remote Sensing","volume":"17","number":"9","pages":"1701-1709","abstract":"In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest. In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest.","issn":"0143-1161","doi":"10.1080/01431169608948733","url":"http://dx.doi.org/10.1080/01431169608948733","year":"1996","bibtex":"@article{RN138,\r\n author = {Fazakas, Z. and Nilsson, M.},\r\n title = {Volume and forest cover estimation over southern Sweden using AVHRR data calibrated with TM data},\r\n journal = {International Journal of Remote Sensing},\r\n volume = {17},\r\n number = {9},\r\n pages = {1701-1709},\r\n abstract = {In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest. In this paper an approach to extend field information across large regions is presented and validated. Total wood volume and volume for different tree-species were estimated in a calibration area using field data, digital map information and a partial Landsat Thematic Mapper (TM) scene. Forest cover information was obtained from digital maps in the same area. The TM estimates and the forest cover information were then used to determine the statistical relations between these parameters and the spectral signature of NOAA-AVHRR pixels covering the same location. Regression analysis was used to develop this relation. The regression equations developed from the calibration area were then applied to a much larger area covering southern Sweden to estimate the forest parameters of interest.},\r\n ISSN = {0143-1161},\r\n DOI = {10.1080/01431169608948733},\r\n url = {http://dx.doi.org/10.1080/01431169608948733},\r\n year = {1996},\r\n type = {Journal Article}\r\n}\r\n\r\n","author_short":["Fazakas, Z.","Nilsson, M."],"key":"RN138","id":"RN138","bibbaseid":"fazakas-nilsson-volumeandforestcoverestimationoversouthernswedenusingavhrrdatacalibratedwithtmdata-1996","role":"author","urls":{"Paper":"http://dx.doi.org/10.1080/01431169608948733"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://www.slu.se/globalassets/ew/org/centrb/rt/dokument/publikationslistor/rikskogstaxeringsprojektet_bibtex_ny.txt","dataSources":["Cac5nog9ND5ndLYhY","xTmt4jq9swAwpBHJB","LXbacBrgTRDPkh9C2","dLPsL5XH9N5Pjush7"],"keywords":[],"search_terms":["volume","forest","cover","estimation","over","southern","sweden","using","avhrr","data","calibrated","data","fazakas","nilsson"],"title":"Volume and forest cover estimation over southern Sweden using AVHRR data calibrated with TM data","year":1996}