Estimating annual cuttings using multi-temporal satellite data and field data from the Swedish NFI. Nilsson, M., Holm, S., Wallerman, J., Reese, H., & Olsson, H. International Journal of Remote Sensing, 30(19: ForestSAT 2007):5109-5116, 2009.
Estimating annual cuttings using multi-temporal satellite data and field data from the Swedish NFI [link]Paper  doi  abstract   bibtex   
Many countries have ongoing national forest inventories (NFIs) that provide reliable information on current forest conditions and changes in the forest landscape. These inventories are often based on data collected using field inventory procedures and the results are presented in terms of forest statistics for different geographical areas. The Swedish NFI has decided to combine their field data with optical satellite data by using post-stratification to obtain improved and unbiased estimates of forest variables. The method has been shown to reduce the sampling error (standard error) by 10–35% for variables such as stem volume and forest area. The objective of this study is to investigate the effect on sampling error for the estimated annual clear-felled area when the NFI plots are post-stratified by cuttings mapped from multi-temporal satellite images. Clear-felled areas mapped by the Swedish Forest Agency using image pairs (SPOT and Landsat) from the years 2001/2002, 2002/2003, 2003/2004, and 2004/2005 were used to post-stratify the NFI plots. The study area covers approximately a 1.3 Mha forest land area in Coastal Västerbotten. It was found that the sampling error (standard error) for the annually clear-felled area was reduced by 31% using post-stratification compared to use of field data alone.
@article{RN636,
   author = {Nilsson, M. and Holm, S. and Wallerman, J. and Reese, H. and Olsson, H.},
   title = {Estimating annual cuttings using multi-temporal satellite data and field data from the Swedish NFI},
   journal = {International Journal of Remote Sensing},
   volume = {30},
   number = {19: ForestSAT 2007},
   pages = {5109-5116},
   abstract = {Many countries have ongoing national forest inventories (NFIs) that provide reliable information on current forest conditions and changes in the forest landscape. These inventories are often based on data collected using field inventory procedures and the results are presented in terms of forest statistics for different geographical areas. The Swedish NFI has decided to combine their field data with optical satellite data by using post-stratification to obtain improved and unbiased estimates of forest variables. The method has been shown to reduce the sampling error (standard error) by 10–35% for variables such as stem volume and forest area. The objective of this study is to investigate the effect on sampling error for the estimated annual clear-felled area when the NFI plots are post-stratified by cuttings mapped from multi-temporal satellite images. Clear-felled areas mapped by the Swedish Forest Agency using image pairs (SPOT and Landsat) from the years 2001/2002, 2002/2003, 2003/2004, and 2004/2005 were used to post-stratify the NFI plots. The study area covers approximately a 1.3 Mha forest land area in Coastal Västerbotten. It was found that the sampling error (standard error) for the annually clear-felled area was reduced by 31% using post-stratification compared to use of field data alone.},
   ISSN = {0143-1161},
   DOI = {10.1080/01431160903022910},
   url = {https://doi.org/10.1080/01431160903022910},
   year = {2009},
   type = {Journal Article}
}

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