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Auteur Ned Horning |
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Mapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles / Ned Horning in Remote sensing in ecology and conservation, vol 6 n° 4 (December 2020)
[article]
Titre : Mapping of land cover with open-source software and ultra-high-resolution imagery acquired with unmanned aerial vehicles Type de document : Article/Communication Auteurs : Ned Horning, Auteur ; Erika Fleishman, Auteur ; Peter J. Ersts, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 487 - 497 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image aérienne
[Termes IGN] image captée par drone
[Termes IGN] Orfeo Tool Box
[Termes IGN] orthoimage
[Termes IGN] R (langage)Résumé : (auteur) The use of unmanned aerial vehicles (UAVs) to map and monitor the environment has increased sharply in the last few years. Many individuals and organizations have purchased consumer-grade UAVs, and commonly acquire aerial photographs to map land cover. The resulting ultra-high-resolution (sub-decimeter-resolution) imagery has high information content, but automating the extraction of this information to create accurate, wall-to-wall land-cover maps is quite difficult. We introduce image-processing workflows that are based on open-source software and can be used to create land-cover maps from ultra-high-resolution aerial imagery. We compared four machine-learning workflows for classifying images. Two workflows were based on random forest algorithms. Of these, one used a pixel-by-pixel approach available in ilastik, and the other used image segments and was implemented with R and the Orfeo ToolBox. The other two workflows used fully connected neural networks and convolutional neural networks implemented with Nenetic. We applied the four workflows to aerial photographs acquired in the Great Basin (western USA) at flying heights of 10 m, 45 m and 90 m above ground level. Our focal cover type was cheatgrass (Bromus tectorum), a non-native invasive grass that changes regional fire dynamics. The most accurate workflow for classifying ultra-high-resolution imagery depends on diverse factors that are influenced by image resolution and land-cover characteristics, such as contrast, landscape patterns and the spectral texture of the land-cover types being classified. For our application, the ilastik workflow yielded the highest overall accuracy (0.82–0.89) as assessed by pixel-based accuracy. Numéro de notice : A2020-853 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1002/rse2.144 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1002/rse2.144 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98682
in Remote sensing in ecology and conservation > vol 6 n° 4 (December 2020) . - pp 487 - 497[article]Determining the rate of forest conversion in Mato-Grosso, Brazil, using Landsat MSS and AVHRR data / R. Nelson in International Journal of Remote Sensing IJRS, vol 8 n° 12 (December 1987)
[article]
Titre : Determining the rate of forest conversion in Mato-Grosso, Brazil, using Landsat MSS and AVHRR data Type de document : Article/Communication Auteurs : R. Nelson, Auteur ; Ned Horning, Auteur ; T.A. Stone, Auteur Année de publication : 1987 Article en page(s) : pp 1767 - 1784 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Advanced Very High Resolution Radiometer
[Termes IGN] analyse de données
[Termes IGN] Brésil
[Termes IGN] forêt
[Termes IGN] image Landsat-MSS
[Termes IGN] thermographieNuméro de notice : A1987-408 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431168708954815 En ligne : https://doi.org/10.1080/01431168708954815 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24471
in International Journal of Remote Sensing IJRS > vol 8 n° 12 (December 1987) . - pp 1767 - 1784[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-87121 RAB Revue Centre de documentation En réserve L003 Disponible Continental land cover assessment using Landsat MSS data / R. Nelson in Remote sensing of environment, vol 21 n° 1 (01/02/1987)
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Titre : Continental land cover assessment using Landsat MSS data Type de document : Article/Communication Auteurs : R. Nelson, Auteur ; D. Case, Auteur ; Ned Horning, Auteur ; V. Anderson, Auteur ; S. Pillai, Auteur Année de publication : 1987 Article en page(s) : pp 61 - 81 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbre (flore)
[Termes IGN] continent
[Termes IGN] Etats-Unis
[Termes IGN] forêt
[Termes IGN] image Landsat-MSS
[Termes IGN] occupation du sol
[Termes IGN] PinophytaNuméro de notice : A1987-078 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/0034-4257(87)90007-1 En ligne : https://doi.org/10.1016/0034-4257(87)90007-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24177
in Remote sensing of environment > vol 21 n° 1 (01/02/1987) . - pp 61 - 81[article]