Nilsson, Mats
- Department of Forest Resource Management, Swedish University of Agricultural Sciences
Research article2009Peer reviewed
Nilsson, Mats; Holm, Sören; Wallerman, Jörgen; Reese, Heather; Olsson, Håkan
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 Vasterbotten. 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.
International Journal of Remote Sensing
2009, Volume: 30, number: 19, pages: 5109-5116 Publisher: TAYLOR & FRANCIS LTD
Forest Science
DOI: https://doi.org/10.1080/01431160903022910
https://res.slu.se/id/publ/61614