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A posteriori bias correction of three models used for environmental reporting / Bogdan M. Strimbu in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 49 - 62 Titre : A posteriori bias correction of three models used for environmental reporting Type de document : Article/Communication Auteurs : Bogdan M. Strimbu, Auteur ; Alexandru Amarioarei, Auteur ; John Paul McTague, Auteur ; Mihaela M. Paun, Auteur Année de publication : 2018 Article en page(s) : pp 49 - 62 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes descripteurs IGN] correction [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] Louisiane (Etats-Unis) [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] Oregon (Etats-Unis) [Termes descripteurs IGN] Pinus ponderosa [Termes descripteurs IGN] pseudotsuga menziesii [Termes descripteurs IGN] résidu [Termes descripteurs IGN] Roumanie [Termes descripteurs IGN] Texas (Etats-Unis) Résumé : (Auteur) A plethora of forest models were developed by transforming the dependent variable, which introduces bias if appropriate corrections are not applied when back-transformed. Many recognized models are still biased and the original data sets are no longer available, which suggests ad hoc bias corrections. The present research presents a procedure for bias correction in the absence of needed information from summary statistics. Additionally, we developed a realistic correction of the square root transformation based on a truncated normal distribution. The transformations considered in this study are the logarithm, the square root and arcsine square root. Using simulated data we found that uncorrected back-transformation created biases by as much as 100 percent. The generated data revealed that depending on available information, that bias can still be present after correction. In addition to generated data we corrected the site index of Douglas-fir and ponderosa pine in Oregon USA, tree volume of 27 species from Romania, stand merchantable volume for longleaf pine in Louisiana and East Texas USA, and canopy fuel weight in Washington USA. Using only the available information, the unbiased back-transformed estimates can change from ≤1 percent (i.e. the site index and canopy fuel weight) to ≥⅓ (tree and stand volume). Numéro de notice : A2018-631 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx032 date de publication en ligne : 10/08/2017 En ligne : https://doi.org/10.1093/forestry/cpx032 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93217 [article]

Diameter caps for thinning southwestern ponderosa pine forests: viewpoints, effects and tradeoffs / Scott R. Abella in The Journal of Forestry, Vol 104 n° 8 (December 2006)

Public [article]  inThe Journal of Forestry > Vol 104 n° 8 (December 2006) . - p. 407-414 Titre : Diameter caps for thinning southwestern ponderosa pine forests: viewpoints, effects and tradeoffs Type de document : Article/Communication Auteurs : Scott R. Abella, Auteur ; Peter Z. Fulé, Auteur ; W. Wallace Covington, Auteur Année de publication : 2006 Article en page(s) : p. 407-414 Note générale : Bibliogr. p .413-414 Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Pinus ponderosa [Termes IFN] gestion des écosystèmes Numéro de notice : A2006-655 Thématique : FORET Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=70659 [article]

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Assessment of Quickbird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation / Nicholas C. Coops in Remote sensing of environment, vol 103 n° 1 (15 July 2006)

Public [article]  inRemote sensing of environment > vol 103 n° 1 (15 July 2006) . - pp 67 - 80 Titre : Assessment of Quickbird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation Type de document : Article/Communication Auteurs : Nicholas C. Coops, Auteur ; M. Johnson, Auteur ; Michael A. Wulder, Auteur ; Joanne C. White, Auteur Année de publication : 2006 Article en page(s) : pp 67 - 80 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Colombie-Britannique (Canada) [Termes descripteurs IGN] dommage matériel [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image Quickbird [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] insecte [Termes descripteurs IGN] Pinus ponderosa [Termes descripteurs IGN] surveillance forestière Résumé : (Auteur) High spatial resolution remotely sensed data has the potential to complement existing forest health programs for both strategic planning over large areas, as well as for detailed and precise identification of tree crowns subject to stress and infestation. The area impacted by the current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia, Canada, has increased 40-fold over the previous 5 years, with approximately 8.5 million ha of forest infested in 2005. As a result of the spatial extent and intensity of the outbreak, new technologies are being assessed to help detect, map, and monitor the damage caused by the beetle, and to inform mitigation of future beetle outbreaks. In this paper, we evaluate the capacity of high spatial resolution QuickBird multi-spectral imagery to detect mountain pine beetle red attack damage. ANOVA testing of individual spectral bands, as well as the Normalized Difference Vegetation Index (NDVI) and a ratio of red to green reflectance (Red–Green Index or RGI), indicated that the RGI was the most successful (p Numéro de notice : A2006-284 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28011 [article]

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Integrating high resolution remote sensing, GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations / C. Bone in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 26 n° 21 (November 2005) . - pp 4809 - 4828 Titre : Integrating high resolution remote sensing, GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations Type de document : Article/Communication Auteurs : C. Bone, Auteur ; Suzana Dragićević, Auteur ; A. Roberts, Auteur Année de publication : 2005 Article en page(s) : pp 4809 - 4828 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] classification floue [Termes descripteurs IGN] Colombie-Britannique (Canada) [Termes descripteurs IGN] forêt [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] insecte [Termes descripteurs IGN] modèle cartographique [Termes descripteurs IGN] Pinus ponderosa [Termes descripteurs IGN] sous ensemble flou [Termes descripteurs IGN] système expert Résumé : (Auteur) The use of fuzzy set theory has become common in remote sensing and geographical information system (GIS) applications to deal with issues surrounding the uncertainty of geospatial datasets. The objective of this study is to develop a model that integrates the concept of fuzzy set theory with remote sensing and GIS in order to produce susceptibility maps of insect infestations in forest landscapes. Fuzzy set theory was applied to information extracted from multiple-year high resolution remote sensing data and integrated in a rasterbased GIS to create a map indicating the spatial variation of insect susceptibility in a landscape. Variable-specific fuzzy membership functions were developed based on expert knowledge and existing data, and integrated through a semantic import model. The results from a case study on mountain pine beetle (Dendroctonus ponderosae Hopkins) illustrate that the model provides a method to successfully estimate areas of varying susceptibility to insect infestation from high resolution remote sensing images. It was concluded that fuzzy sets are an adequate method for dealing with uncertainty in defining susceptibility variables. The susceptibility maps can be utilized for guiding management decisions based on the spatial aspects of insect-host relationships. Numéro de notice : A2005-468 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27604 [article]

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Using Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)

Public [article]  inRemote sensing of environment > vol 91 n° 1 (15/05/2004) . - pp 14 - 26 Titre : Using Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest Type de document : Article/Communication Auteurs : X. Chen, Auteur ; Lee Alexander Vierling, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 14 - 26 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] analyse des mélanges spectraux [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] Dakota du Sud (Etats-Unis) [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] forêt [Termes descripteurs IGN] image Ikonos [Termes descripteurs IGN] image Landsat-ETM+ [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] Pinus ponderosa Résumé : (Auteur) Structural and functional analyses of ecosystems benefit when high accuracy vegetation coverages can be derived over large areas. In this study, we utilize IKONOS, Landsat 7 ETM+, and airborne scanning light detection and ranging (lidar) to quantify coniferous forest and understory grass coverages in a ponderosa pine (Pinus ponderosa) dominated ecosystem in the Black Hills of South Dakota. Linear spectral mixture analyses of IKONOS and ETM+ data were used to isolate spectral endmembers (bare soil, understory grass, and tree/shade) and calculate their subpixel fractional coverages. We then compared these endmember cover estimates to similar cover estimates derived from lidar data and field measures. The IKONOS-derived tree/shade fraction was significantly correlated with the field-measured canopy effective leaf area index (LAIe) (r2 = 0.55, p Numéro de notice : A2004-235 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26762 [article]

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