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Acquisition, orthorectification, and object-based classification of Unmanned Aerial Vehicle (UAV) imagery for rangeland monitoring / Andrea S. Laliberte in Photogrammetric engineering and remote sensing, 76 (2010) 

Public Citation [article]  inPhotogrammetric engineering and remote sensing > 76 (2010) . - 661-672 Titre : Acquisition, orthorectification, and object-based classification of Unmanned Aerial Vehicle (UAV) imagery for rangeland monitoring Type de document : Imprimé Auteurs : Andrea S. Laliberte ; Jeffrey E. Herrick ; Albert Rango ; Craig Winters Année de publication : 2010 Article en page(s) : 661-672 Catégories : [CBNPMP-Thématique] Télédétection Résumé : 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 semi-automated 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 image-and 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. Lien pérenne : DOI : 10.14358/PERS.76.6.661 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151513 Laliberte, Andrea S., Herrick, Jeffrey E., Rango, Albert, Winters, Craig 2010 Acquisition, orthorectification, and object-based classification of Unmanned Aerial Vehicle (UAV) imagery for rangeland monitoring. Photogrammetric engineering and remote sensing, 76: 661-672.

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Application of UAV-based methodology for census of an endangered plant species in a fragile habitat / Kody Rominger in Remote sensing, 11 (2019) 

Public Citation [article]  inRemote sensing > 11 (2019) . - 719 Titre : Application of UAV-based methodology for census of an endangered plant species in a fragile habitat Type de document : Imprimé Auteurs : Kody Rominger ; Susan E. Meyer Année de publication : 2019 Article en page(s) : 719 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Accurate census is essential for endangered plant management, yet lack of resources may make complete on-the-ground census difficult to achieve. Accessibility, especially for species in fragile habitats, is an added constraint. We examined the feasibility of using UAV (unmanned aerial vehicle, drone)-based imagery for census of an endangered plant species, Arctomecon humilis (dwarf bear-poppy), an herbaceous perennial gypsophile endemic of the Mojave Desert, USA. Using UAV technology, we captured imagery at both 50-m altitude (census) and 15-m altitude (validation) at two populations, White Dome (325 ha) and Red Bluffs (166 ha). The imagery was processed into orthomosaics that averaged 2.32 cm ground sampling distance (GSD) for 50-m imagery and 0.73 cm GSD for 15-m imagery. Putative poppy plants were marked in the 50-m imagery according to predefined criteria. We then used the 15-m imagery from each area to verify the identification accuracy of marked plants. Visual evaluation of the 50-m imagery resulted in errors of both commission and omission, mainly caused by failure to accurately identify or detect small poppies (<10 cm diameter). Higher-resolution 30-m altitude imagery (1.19 cm GSD) greatly reduced errors of commission. Habitat classification demonstrated that poppy density variation was closely tied to soil surface color. This study showed that drone imagery can potentially be used to census rare plant species with distinctive morphology in open habitats and understand their spatial distribution. Lien pérenne : DOI : 10.3390/rs11060719 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151549 Rominger, Kody, Meyer, Susan E. 2019 Application of UAV-based methodology for census of an endangered plant species in a fragile habitat. Remote sensing, 11: 719.

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Application de photogrammétrie par drone et analyses d'images satellitaires pour l'étude de la végétation des marges proglaciaires / Nicolas Rouyer (2021) 

Public Citation Titre : Application de photogrammétrie par drone et analyses d'images satellitaires pour l'étude de la végétation des marges proglaciaires Type de document : Électronique Auteurs : Nicolas Rouyer Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques (ENSG) Année de publication : 2021 Importance : 57 p. Langues : Français (fre) Catégories : [CBNPMP-Thématique] Télédétection [CBNPMP-Géographique] Alpes Résumé : Dans toutes les régions montagneuses du monde, les glaciers reculent et des terres libres de glace émergent. Ces nouvelles surfaces, principalement situées au-dessus de la limite de la forêt dans les Alpes, représentent une opportunité pour la colonisation des végétaux. Ces zones libérées dite proglaciaire, où les conditions environnementales sont parmi les plus dures pour la végétation, sont encore très peu étudiées. Les techniques de télédétection deviennent de plus en plus importantes dans la recherche et les travaux scientifiques sur les risques naturels. Elles peuvent être utilisées pour documenter avec précision les changements dans les paysages de hautes montagnes. La combinaison de la télédétection avec de l’imagerie drone multispectrale à très haute résolution spatiale peut permettre de détecter et d’étudier les écosystèmes alpins qui s’y développent. L’objectif principal de ce stage est d’appliquer et d’optimiser la méthodologie d’acquisition par drone sur les zones alpines dans le but de générer des orthoimages à très haute résolution spatiale, puis de commencer à évaluer le potentiel de la télédétection pour l’observation de la végétation se développant sur les marges proglaciaires. Les nombreuses données ainsi récoltées et traitées par photogrammétrie sur différents sites sont une ressource considérable qui projette d'être étudiée et approfondie dans les prochaines années. Note de contenu : Mémoire de Master 1 Géomatique Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=148529 Rouyer, Nicolas , 2021. Application de photogrammétrie par drone et analyses d'images satellitaires pour l'étude de la végétation des marges proglaciaires. Ecole nationale des sciences géographiques (ENSG), Champs-sur-Marne. 57 pp.

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Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles / Stephan Getzin in Methods in ecology and evolution, 3 (2012) 

Public Citation [article]  inMethods in ecology and evolution > 3 (2012) . - 397-404 Titre : Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles Type de document : Imprimé Auteurs : Stephan Getzin ; Kerstin Wiegand ; Ingo Schöning Année de publication : 2012 Article en page(s) : 397-404 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Structural diversity and niche differences within habitats are important for stabilizing species coexistence. However, land-use change leading to environmental homogenization is a major cause for the dramatic decline of biodiversity under global change. The difficulty in assessing large-scale biodiversity losses urgently requires new technological advances to evaluate land-use impact on diversity timely and efficiently across space. While cost-effective aerial images have been suggested for potential biodiversity assessments in forests, correlation of canopy object variables such as gaps with plant or animal diversity has so far not been demonstrated using these images. Here, we show that aerial images of canopy gaps can be used to assess floristic biodiversity of the forest understorey. This approach is made possible because we employed cutting-edge unmanned aerial vehicles and very high-resolution images (7 cm pixel−1) of the canopy properties. We demonstrate that detailed, spatially implicit information on gap shape metrics is sufficient to reveal strong dependency between disturbance patterns and plant diversity (R2 up to 0·74). This is feasible because opposing disturbance patterns such as aggregated and dispersed tree retention directly correspond to different functional and dispersal traits of species and ultimately to different species diversities. Our findings can be used as a coarse-filter approach to conservation in forests wherever light strongly limits regeneration and biodiversity. Lien pérenne : DOI : 10.1111/j.2041-210X.2011.00158.x Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151520 Getzin, Stephan, Wiegand, Kerstin, Schöning, Ingo 2012 Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles. Methods in ecology and evolution, 3: 397-404.

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Biomass prediction of heterogeneous temperate grasslands using an sfm approach based on UAV imaging / Esther Grüner in Agronomy, 9 (2019) 

Public Citation [article]  inAgronomy > 9 (2019) . - 54 Titre : Biomass prediction of heterogeneous temperate grasslands using an sfm approach based on UAV imaging Type de document : Imprimé Auteurs : Esther Grüner ; Thomas Astor ; Michael Wachendorf Année de publication : 2019 Article en page(s) : 54 Langues : Français (fre) Catégories : [CBNPMP-Thématique] Télédétection Résumé : An early and precise yield estimation in intensive managed grassland is mandatory for economic management decisions. RGB (red, green, blue) cameras attached on an unmanned aerial vehicle (UAV) represent a promising non-destructive technology for the assessment of crop traits especially in large and remote areas. Photogrammetric structure from motion (SfM) processing of the UAV-based images into point clouds can be used to generate 3D spatial information about the canopy height (CH). The aim of this study was the development of prediction models for dry matter yield (DMY) in temperate grassland based on CH data generated by UAV RGB imagingover a whole growing season including four cuts. The multi-temporal study compared the remote sensing technique with two conventional methods, i.e., destructive biomass sampling and ruler height measurements in two legume-grass mixtures with red clover (Trifolium pratense L.) and lucerne (Medicago sativa L.) in combination with Italian ryegrass (Lolium multiflorum Lam.). To cover the full range of legume contribution occurring in a practical grassland, pure stands of legumes and grasses contained in each mixture were also investigated. The results showed, that yield prediction by SfM-based UAV RGB imaging provided similar accuracies across all treatments (R2 = 0.59–0.81) as the ruler height measurements (R2 = 0.58–0.78). Furthermore, results of yield prediction by UAV RGB imaging demonstrated an improved robustness when an increased CH variability occurred due to extreme weather conditions. It became apparent that morphological characteristics of clover-based canopies (R2 = 0.75) allow a better remotely sensed prediction of total annual yield than for lucerne-grass mixtures (R2 = 0.64), and that these crop-specific models cannot be easily transferred to other grassland types. Lien pérenne : DOI : 10.3390/agronomy9020054 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151689 Grüner, Esther, Astor, Thomas, Wachendorf, Michael 2019 Biomass prediction of heterogeneous temperate grasslands using an sfm approach based on UAV imaging. Agronomy, 9: 54.

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Capacités et limites de la télédétection pour cartographier les habitats naturels / Samuel Alleaume (2013) 

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Cartographie des habitats du Phragmite aquatique (Acrocephalus paludicola) (Août 2017) sur la zone Natura 2000 des marais de l’Erdre (FR5200624) / Franck Latraube (2017) 

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Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis / Jana Müllerová in Ecological indicators, 131 (2021) 

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Comment utiliser la télédétection / Gustave Coste in Espaces naturels, 49 (2015)

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Un drone pour détecter et délimiter les zones humides : une réalité imminente ? / Florentin Madrolles in Revue forestière française, 65 (6) (12/2013) 

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Drone systems and applications (2022-)  

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Drones for conservation in protected areas: present and future / Jesús Jiménez López in Drones, 3 (2019) 

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Efficient drone-based rare plant monitoring using a species distribution model and ai-based object detection / William Reckling in Drones, 5 (2021) 

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Elaboration d'indicateurs à partir de données d'observation de la terre pour l'évaluation et le suivi des habitats naturels : application au site Natura 2000 du Causse Noir / École supérieure d'agriculture de Purpan (ESAP) (Toulouse) (2005)

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Estimating rangeland forage production using remote sensing data from a small unmanned aerial system (sUAS) and planetscope satellite / Han Liu in Remote sensing, 11 (2019) 

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