Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Matti Katila"'
Publikováno v:
Remote Sensing, Vol 16, Iss 14, p 2513 (2024)
Forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, multispectral satellite images and numerical map data. We evaluated k-nearest neighbors (k-NN) method-based predictions of
Externí odkaz:
https://doaj.org/article/25f81535a6e841b3a667450171e626aa
Publikováno v:
Metsätieteen aikakauskirja, Vol 2020 (2020)
Externí odkaz:
https://doaj.org/article/1125b9ae988445d3b1bce9ca613be8cd
Autor:
Matti Katila
Publikováno v:
Metsätieteen aikakauskirja, Vol 2006, Iss 4 (2006)
Externí odkaz:
https://doaj.org/article/a20aae583ce3485495265f8fc39b4864
Publikováno v:
Canadian Journal of Forest Research. 50:359-370
National forest inventories (NFIs) are designed to provide accurate information on forest resources at the national and regional levels, but there is also a demand for such information at smaller spatial scales. Auxiliary data such as satellite image
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd559678c18f8fa5709420b629ce64e1
https://doi.org/10.1139/cjfr-2019-0139
https://doi.org/10.1139/cjfr-2019-0139
Autor:
Juha Heikkinen, Matti Katila
Publikováno v:
Forestry: An International Journal of Forest Research. 93:471-480
Since the 1990s, forest resource maps and forest variable estimates for small areas have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data. A non-parametric $k$-NN method has f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e07fa1ccb21001dd52bfdb04d8e18a9
https://doi.org/10.1093/foresj/cpz076
https://doi.org/10.1093/foresj/cpz076
Publikováno v:
Silva Fennica, Vol 54, Iss 4 (2020)
Since the 1990âs, forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data using a non-parametric -nearest neighbour method. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8338e2f71dd0946223bc0d149d1e0e0e
https://doi.org/10.14214/sf.10347
https://doi.org/10.14214/sf.10347
Publikováno v:
Annals of Forest Science
Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2019, 76 (1), pp.9. ⟨10.1007/s13595-018-0795-6⟩
Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2019, 76 (1), pp.9. ⟨10.1007/s13595-018-0795-6⟩
Key message Post-stratification based on remotely sensed data is an efficient method in estimating regional-level results in the operational National Forest Inventory. It also enables calculating the results accurately for smaller areas than with the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c07108eda00454ca51af89edee6b1a17
https://doi.org/10.1007/s13595-018-0795-6
https://doi.org/10.1007/s13595-018-0795-6
Publikováno v:
Scandinavian Journal of Forest Research. 32:488-500
The effects of field plot configurations on the uncertainties of plot-level forest resource estimates were analyzed using airborne laser scanner data, aerial photographs and field measurements. The aim was to select a field sample plot configuration
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd5295bf37ee438fefcfd7e6c30f4c5d
https://doi.org/10.1080/02827581.2016.1259425
https://doi.org/10.1080/02827581.2016.1259425
Publikováno v:
Remote Sensing of Environment. 113:500-517
The k-Nearest Neighbour (k-NN) estimation and prediction technique is widely used to produce pixel-level predictions and areal estimates of continuous forest variables such as area and volume, often by subcategories such as species. An advantage of k
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::641dcb0aeb5a8362b224405e5c143717
https://doi.org/10.1016/j.rse.2008.05.021
https://doi.org/10.1016/j.rse.2008.05.021
Publikováno v:
Remote Sensing of Environment. 112:1982-1999
Information about forest cover is needed by all of the nine societal benefit areas identified by the Group of Earth Observation (GEO). In particular, the biodiversity and ecosystem areas need information on landscape composition, structure of forests
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::583a106d87077c132ea39712179e2555
https://doi.org/10.1016/j.rse.2007.03.032
https://doi.org/10.1016/j.rse.2007.03.032