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Estimating annual c...
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Nilsson, MatsSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management
(author)
Estimating annual cuttings using multi-temporal satellite data and field data from the Swedish NFI
- Article/chapterEnglish2009
Publisher, publication year, extent ...
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2009-09-22
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Informa UK Limited,2009
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Taylor & Francis: STM, Behavioural Science and Public Health Titles,2024
Numbers
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LIBRIS-ID:oai:slubar.slu.se:61614
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https://res.slu.se/id/publ/61614URI
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https://doi.org/10.1080/01431160903022910DOI
Supplementary language notes
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Language:English
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Summary in:English
Part of subdatabase
Classification
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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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.
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Added entries (persons, corporate bodies, meetings, titles ...)
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Holm, SörenSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management(Swepub:slu)47683
(author)
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Wallerman, JörgenSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management(Swepub:slu)47239
(author)
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Reese, HeatherSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management(Swepub:slu)48457
(author)
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Olsson, HåkanSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skoglig resurshushållning,Department of Forest Resource Management(Swepub:slu)46943
(author)
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Sveriges lantbruksuniversitetInstitutionen för skoglig resurshushållning
(creator_code:org_t)
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Sveriges lantbruksuniversitet
Related titles
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In:International Journal of Remote Sensing: Informa UK Limited30, s. 5109-51160143-11611366-5901
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