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Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data / Niels Lindgren in Scandinavian journal of forest research, vol 36 n° 5 ([01/07/2021])  

Public [article]  inScandinavian journal of forest research > vol 36 n° 5 [01/07/2021] . - pp 401 - 407 Titre : Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data Type de document : Article/Communication Auteurs : Niels Lindgren, Auteur ; André Wästlund, Auteur ; Inka Bohlin, Auteur ; Kenneth Nyström, Auteur ; Mats Nilsson, Auteur ; Hakan Olsson, Auteur Année de publication : 2021 Article en page(s) : pp 401 - 407 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] orthoimage [Termes IGN] photogrammétrie numérique [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Accurate and up-to-date data about growing stock volume are essential for forest management planning. Airborne Laser Scanning (ALS) is known for producing accurate wall-to-wall predictions but the data are at present collected at long time intervals. Digital Photogrammetry (DP) is cheaper and often more frequently available but known to be less accurate. This study investigates the potential of using contemporary DP data together with older ALS data and compares this with the case when only old ALS data are trained with recent field data. Combining ALS data from 2010 to 2011 with DP data from 2015, both trained with National Forest Inventory (NFI) field plot data from 2015, improved predictions of growing stock volume. Validation using data from 100 stands inventoried in 2015 gave an RMSE of 24.3% utilizing both old ALS data and recent DP data, 26.0% for old ALS only and 24.9% for recent DP only. If information about management actions were assumed available, combining old ALS and recent DP gave RMSE of 23.0%, only ALS 23.3% and only DP 23.8%. Numéro de notice : A2021-604 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1080/02827581.2021.1936153 En ligne : https://doi.org/10.1080/02827581.2021.1936153 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98333 [article]

Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)  

Public [article]  inSilva fennica > vol 51 n° 2 (2017) Titre : Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory Type de document : Article/Communication Auteurs : Jonas Bohlin, Auteur ; Inka Bohlin, Auteur ; Jonas Jonzén, Auteur ; Mats Nilsson, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] régression linéaire [Termes IGN] semis de points [Termes IGN] Suède [Termes IGN] surface terrière [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping. Numéro de notice : A2017-648 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.2021 En ligne : https://doi.org/10.14214/sf.2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87007 [article]

Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)  

Public [article]  inSilva fennica > vol 51 n° 2 (2017) . - 18 p. Titre : Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory Type de document : Article/Communication Auteurs : Jonas Bohlin, Auteur ; Inka Bohlin, Auteur ; Jonas Jonzén, Auteur ; Mats Nilsson, Auteur Année de publication : 2017 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] appariement d'images [Termes IGN] carte forestière [Termes IGN] données dendrométriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation statistique [Termes IGN] image aérienne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] photogrammétrie numérique [Termes IGN] régression [Termes IGN] station forestière [Termes IGN] Suède [Termes IGN] surface terrière Résumé : (auteur) Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m × 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping. Numéro de notice : A2017-185 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.2021 En ligne : https://doi.org/10.14214/sf.2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84764 [article]