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Acquisition, orthorectification, and object-based classification of Unmanned Aerial Vehicle (UAV) imagery for rangeland monitoring / A. Laliberte in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 6 (June 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 6 (June 2010) . - pp 661 - 672 Titre : Acquisition, orthorectification, and object-based classification of Unmanned Aerial Vehicle (UAV) imagery for rangeland monitoring Type de document : Article/Communication Auteurs : A. Laliberte, Auteur ; J. Herrick, Auteur ; A. Rango, Auteur ; C. Winters, Auteur Année de publication : 2010 Article en page(s) : pp 661 - 672 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] acquisition d'images [Termes IGN] classification orientée objet [Termes IGN] drone [Termes IGN] Idaho (Etats-Unis) [Termes IGN] image aérienne [Termes IGN] orthorectification [Termes IGN] parcours Résumé : (Auteur) The use of unmanned aerial vehicles (UAVs) for natural resource applications has increased considerably in recent years due to their greater availability, the miniaturization of sensors, and the ability to deploy a UAV relatively quickly and repeatedly at low altitudes. We examine in this paper the potential of using a small UAV for rangeland inventory, assessment and monitoring. Imagery with a ground resolved distance of 8 cm was acquired over a 290 ha site in southwestern Idaho. We developed a semiautomated orthorectification procedure suitable for handling large numbers of small-footprint UAV images. The geometric accuracy of the orthorectified image mosaics ranged from 1.5 m to 2 m. We used object-based hierarchical image analysis to classify imagery of plots measured concurrently on the ground using standard rangeland monitoring procedures. Correlations between imageand ground-based estimates of percent cover resulted in r-squared values ranging from 0.86 to 0.98. Time estimates indicated a greater efficiency for the image-based method compared to ground measurements. The overall classification accuracies for the two image mosaics were 83 percent and 88 percent. Even under the current limitations of operating a UAV in the National Airspace, the results of this study show that UAVs can be used successfully to obtain imagery for rangeland monitoring, and that the remote sensing approach can either complement or replace some ground-based measurements. We discuss details of the UAV mission, image processing and analysis, and accuracy assessment. Numéro de notice : A2010-226 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.6.661 En ligne : https://doi.org/10.14358/PERS.76.6.661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30420 [article]

Support vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery / L. Su in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)  

Public [article]  inRemote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 299 - 311 Titre : Support vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery Type de document : Article/Communication Auteurs : L. Su, Auteur ; M. Chopping, Auteur ; A. Rango, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 299 - 311 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] carte de la végétation [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] désert [Termes IGN] image Terra-MISR [Termes IGN] Nouveau-Mexique (Etats-Unis) [Termes IGN] prairie [Termes IGN] zone aride [Termes IGN] zone semi-aride Résumé : (Auteur) Accurately mapping community types is one of the main challenges for monitoring arid and semi-arid grasslands with remote sensing. The multi-angle approach has been proven useful for mapping vegetation types in desert grassland. The Multi-angle Imaging Spectro-Radiometer (MISR) provides 4 spectral bands and 9 angular reflectance. In this study, 44 classification experiments have been implemented to find the optimal combination of MISR multi-angular data to mine the information carried by MISR data as effectively as possible. These experiments show the following findings: 1) The combination of MISR's 4 spectral bands at nadir and red and near infrared bands in the C, B, and A cameras observing off-nadir can obtain the best vegetation type differentiation at the community level in New Mexico desert grasslands. 2) The k parameter at red band of Modified–Rahman–Pinty–Verstraete (MRPV) model and the structural scattering index (SSI) can bring useful additional information to land cover classification. The information carried by these two parameters, however, is less than that carried by surface anisotropy patterns described by the MRPV model and a linear semi-empirical kernel-driven bidirectional reflectance distribution function model, the RossThin–LiSparseMODIS (RTnLS) model. These experiments prove that: 1) multi-angular reflectance raise overall classification accuracy from 45.8% for nadir-only reflectance to 60.9%. 2) With surface anisotropy patterns derived from MRPV and RTnLS, an overall accuracy of 68.1% can be obtained when maximum likelihood algorithms are used. 3) Support Vector Machine (SVM) algorithms can raise the classification accuracy to 76.7%. This research shows that multi-angular reflectance, surface anisotropy patterns and SVM algorithms can improve desert vegetation type differentiation importantly. Copyright Elsevier Numéro de notice : A2007-056 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.05.023 En ligne : https://doi.org/10.1016/j.rse.2006.05.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28421 [article]

Rangeland runoff curve numbers as determined from Landsat MSS data / A.W. Zevenbergen in International Journal of Remote Sensing IJRS, vol 9 n° 3 (May 1988)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 9 n° 3 (May 1988) . - pp 495 - 502 Titre : Rangeland runoff curve numbers as determined from Landsat MSS data Type de document : Article/Communication Auteurs : A.W. Zevenbergen, Auteur ; A. Rango, Auteur ; J.E. Ritchie, Auteur ; Edwin T. Engman, Auteur ; R.H. Hawkins, Auteur Année de publication : 1988 Article en page(s) : pp 495 - 502 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection [Termes IGN] corrélation [Termes IGN] courbe de niveau [Termes IGN] hydrologie [Termes IGN] image Landsat-MSS [Termes IGN] ligne de partage des eaux [Termes IGN] réflectance Numéro de notice : A1988-109 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431168808954870 En ligne : https://doi.org/10.1080/01431168808954870 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24688 [article]

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080-88031	RAB	Revue	Centre de documentation	En réserve L003	Disponible