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Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees / Matthew P. Peters in Ecology and evolution, vol 9 n° 15 (August 2019)  

Public [article]  inEcology and evolution > vol 9 n° 15 (August 2019) . - pp 8876 - 8899 Titre : Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees Type de document : Article/Communication Auteurs : Matthew P. Peters, Auteur ; Louis R. Iverson, Auteur ; Anantha M. Prasad, Auteur ; Stephen N. Matthews, Auteur Année de publication : 2019 Article en page(s) : pp 8876 - 8899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore) [Termes IGN] densité [Termes IGN] distribution spatiale [Termes IGN] données météorologiques [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle mathématique [Termes IGN] placette d'échantillonnage [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Species distribution models (SDMs) provide useful information about potential presence or absence, and environmental conditions suitable for a species; and high‐resolution models across large extents are desirable. A primary feature of SDMs is the underlying spatial resolution, which can be chosen for many reasons, though we propose that a hybrid lattice, in which grid cell sizes vary with the density of forest inventory plots, provides benefits over uniform grids. We examine how the spatial grain size affected overall model performance for the Random Forest‐based SDM, DISTRIB, which was updated with recent forest inventories, climate, and soil data, and used a hybrid lattice derived from inventory densities. Modeled habitat suitability was compared between a uniform grid of 10 × 10 and a hybrid lattice of 10 × 10 and 20 × 20 km grids to assess potential improvements. The resulting DISTRIB‐II models for 125 eastern U.S. tree species provide information on individual habitat suitability that can be mapped and statistically analyzed to understand current and potential changes. Model performance metrics were comparable among the hybrid lattice and 10‐km grids; however, the hybrid lattice models generally had higher overall model reliability scores and were likely more representative of the inventory data. Our efforts to update DISTRIB models with current information aims to produce a more representative depiction of recent conditions by accounting for the spatial density of forest inventory data and using the latest climate data. Additionally, we developed an approach that leverages a hybrid lattice to maximize the spatial information within the models and recommend that similar modeling efforts be used to evaluate the spatial density of response and predictor data and derive a modeling grid that best represents the environment. Numéro de notice : A2019-374 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1002/ece3.5445 Date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1002/ece3.5445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93415 [article]

A technique for extrapolating and validating forest cover across large region : calibrating AVHRR data with TM data / Louis R. Iverson in International Journal of Remote Sensing IJRS, vol 10 n° 11 (November 1989)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 10 n° 11 (November 1989) . - pp 1805 - 1812 Titre : A technique for extrapolating and validating forest cover across large region : calibrating AVHRR data with TM data Type de document : Article/Communication Auteurs : Louis R. Iverson, Auteur ; E.A. Cook, Auteur ; R.L. Graham, Auteur Année de publication : 1989 Article en page(s) : pp 1805 - 1812 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] couvert végétal [Termes IGN] étalonnage des données [Termes IGN] forêt [Termes IGN] Illinois (Etats-Unis) [Termes IGN] image Landsat-TM [Termes IGN] image NOAA-AVHRR Numéro de notice : A1989-388 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431168908904011 En ligne : https://doi.org/10.1080/01431168908904011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=25347 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-89101	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Estimating forest productivity with Thematic Mapper and biogeographical data / E.A. Cook in Remote sensing of environment, vol 28 n° 1 (April - June 1989)  

Public [article]  inRemote sensing of environment > vol 28 n° 1 (April - June 1989) . - pp 131 - 141 Titre : Estimating forest productivity with Thematic Mapper and biogeographical data Type de document : Article/Communication Auteurs : E.A. Cook, Auteur ; Louis R. Iverson, Auteur ; R.L. Graham, Auteur Année de publication : 1989 Article en page(s) : pp 131 - 141 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande infrarouge [Termes IGN] bande visible [Termes IGN] biogéographie [Termes IGN] classification [Termes IGN] corrélation [Termes IGN] écosystème [Termes IGN] forêt [Termes IGN] Illinois (Etats-Unis) [Termes IGN] image Landsat-TM [Termes IGN] New York (Etats-Unis ; état) [Termes IGN] productivité [Termes IGN] sylviculture [Termes IGN] système d'information géographique [Termes IGN] Tennessee (Etats-Unis) [Termes IGN] thermographie Numéro de notice : A1989-330 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/0034-4257(89)90111-9 En ligne : https://doi.org/10.1016/0034-4257(89)90111-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=25289 [article]