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Ajouter le résultat dans votre panierIssues in Unmanned Aerial Systems (UAS) data collection of complex forest environments / Benjamin T. Fraser in Remote sensing, 10 (2018)
Titre : Issues in Unmanned Aerial Systems (UAS) data collection of complex forest environments Type de document : Imprimé Auteurs : Benjamin T. Fraser ; Russell G. Congalton Année de publication : 2018 Article en page(s) : 908 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Unmanned Aerial Systems (UAS) offer users the ability to capture large amounts of imagery at unprecedented spatial resolutions due to their flexible designs, low costs, automated workflows, and minimal technical knowledge barriers. Their rapid extension into new disciplines promotes the necessity to question and understand the implications of data capture and processing parameter decisions on the respective output completeness. This research provides a culmination of quantitative insight using an eBee Plus, fixed-wing UAS for collecting robust data on complex forest environments. These analyses differentiate from measures of accuracy, which were derived from positional comparison to other data sources, to instead guide applications of comprehensive coverage. Our results demonstrated the impacts of flying height on Structure from Motion (SfM) processing completeness, discrepancies in outputs based on software package choice, and the effects caused by processing parameter settings. For flying heights of 50 m, 100 m, and 120 m above the forest canopy, key quality indicators within the software demonstrated the superior performance of the 100-m flying height. These indicators included, among others, image alignment success, the average number of tie points per image, and planimetric model ground sampling distance. We also compared the output results of two leading SfM software packages: Agisoft PhotoScan and Pix4D Mapper Pro. Agisoft PhotoScan maintained an 11.8% greater image alignment success and a 9.91% finer planimetric model resolution. Lastly, we compared the “high” and “medium” resolution processing workflows in Agisoft PhotoScan. The high-resolution processing setting achieved a 371% increase in point cloud density, with a 3.1% coarser planimetric model resolution, over a considerably longer processing time. As UAS continue to expand their sphere of influence and develop technologically, best-use practices based on aerial photogrammetry principles must remain apparent to achieve optimal results. Lien pérenne : DOI : 10.3390/rs10060908 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151547
in Remote sensing > 10 (2018) . - 908Fraser, Benjamin T., Congalton, Russell G. 2018 Issues in Unmanned Aerial Systems (UAS) data collection of complex forest environments. Remote sensing, 10: 908.Documents numériques
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Article (2018)URL
Titre : Mapping wild leek through the forest canopy using a UAV Type de document : Imprimé Auteurs : Marie-Bé Leduc ; Anders J. Knudby Année de publication : 2018 Article en page(s) : 70 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Wild leek, an endangered plant species of Eastern North America, grows on forest floors and greens up to approximately three weeks before the trees it is typically found under, temporarily allowing it to be observed through the canopy by remote sensing instruments. This paper explores the accuracy with which wild leek can be mapped with a low-flying UAV. Nadir video imagery was obtained using a commercial UAV during the spring of 2017 in Gatineau Park, Quebec. Point clouds were generated from the video frames with the Structure-from-Motion framework, and a multiscale curvature classification was used to separate points on the ground, where wild leek grows, from above-ground points belonging to the forest canopy. Five-cm resolution orthomosaics were created from the ground points, and a threshold value of 0.350 for the green chromatic coordinate (GCC) was applied to delineate wild leek from wood, leaves, and other plants on the forest floor, with an F1-score of 0.69 and 0.76 for two different areas. The GCC index was most effective in delineating bigger patches, and therefore often misclassified patches smaller than 30 cm in diameter. Although short flight times and long data processing times are presently technical challenges to upscaling, the low cost and high accuracy of UAV imagery provides a promising method for monitoring the spatial distribution of this endangered species. Lien pérenne : DOI : 10.3390/rs10010070 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151548
in Remote sensing > 10 (2018) . - 70Leduc, Marie-Bé, Knudby, Anders J. 2018 Mapping wild leek through the forest canopy using a UAV. Remote sensing, 10: 70.Documents numériques
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Titre : Mapping and classification of ecologically sensitive marine habitats using Unmanned Aerial Vehicle (UAV) imagery and Object-Based Image Analysis (OBIA) Type de document : Imprimé Auteurs : Daniele Ventura ; Andrea Bonifazi ; Maria Flavia Gravina ; Andrea Belluscio ; Giandomenico Ardizzone Année de publication : 2018 Article en page(s) : 1331 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Nowadays, emerging technologies, such as long-range transmitters, increasingly miniaturized components for positioning, and enhanced imaging sensors, have led to an upsurge in the availability of new ecological applications for remote sensing based on unmanned aerial vehicles (UAVs), sometimes referred to as “drones”. In fact, structure-from-motion (SfM) photogrammetry coupled with imagery acquired by UAVs offers a rapid and inexpensive tool to produce high-resolution orthomosaics, giving ecologists a new way for responsive, timely, and cost-effective monitoring of ecological processes. Here, we adopted a lightweight quadcopter as an aerial survey tool and object-based image analysis (OBIA) workflow to demonstrate the strength of such methods in producing very high spatial resolution maps of sensitive marine habitats. Therefore, three different coastal environments were mapped using the autonomous flight capability of a lightweight UAV equipped with a fully stabilized consumer-grade RGB digital camera. In particular we investigated a Posidonia oceanica seagrass meadow, a rocky coast with nurseries for juvenile fish, and two sandy areas showing biogenic reefs of Sabelleria alveolata. We adopted, for the first time, UAV-based raster thematic maps of these key coastal habitats, produced after OBIA classification, as a new method for fine-scale, low-cost, and time saving characterization of sensitive marine environments which may lead to a more effective and efficient monitoring and management of natural resources. Lien pérenne : DOI : 10.3390/rs10091331 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151575
in Remote sensing > 10 (2018) . - 1331Ventura, Daniele, Bonifazi, Andrea, Gravina, Maria Flavia, Belluscio, Andrea, Ardizzone, Giandomenico 2018 Mapping and classification of ecologically sensitive marine habitats using Unmanned Aerial Vehicle (UAV) imagery and Object-Based Image Analysis (OBIA). Remote sensing, 10: 1331.Documents numériques
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Titre : Estimation of grassland canopy height and aboveground biomass at the quadrat scale using unmanned aerial vehicle Type de document : Imprimé Auteurs : Huifang Zhang ; Yi Sun ; Li Chang ; Yu Qin ; Jianjun Chen ; Yan Qin ; Jiaxing Du ; Shuhua Yi ; Yingli Wang Année de publication : 2018 Article en page(s) : 851 Catégories : [CBNPMP-Thématique] Télédétection Résumé : Aboveground biomass is a key indicator of a grassland ecosystem. Accurate estimation from remote sensing is important for understanding the response of grasslands to climate change and disturbance at a large scale. However, the precision of remote sensing inversion is limited by a lack in the ground truth and scale mismatch with satellite data. In this study, we first tried to establish a grassland aboveground biomass estimation model at 1 m2 quadrat scale by conducting synchronous experiments of unmanned aerial vehicle (UAV) and field measurement in three different grassland ecosystems. Two flight modes (the new QUADRAT mode and the commonly used MOSAIC mode) were used to generate point clouds for further processing. Canopy height metrics of each quadrat were then calculated using the canopy height model (CHM). Correlation analysis showed that the mean of the canopy height model (CHM_mean) had a significant linear relationship with field height (R2 = 0.90, root mean square error (RMSE) = 19.79 cm, rRMSE = 16.5%, p < 0.001) and a logarithmic relationship with field aboveground biomass (R2 = 0.89, RMSE = 91.48 g/m2, rRMSE = 16.11%, p < 0.001). We concluded our study by conducting a preliminary application of estimation of the aboveground biomass at a plot scale by jointly using UAV and the constructed 1 m2 quadrat scale estimation model. Our results confirmed that UAV could be used to collect large quantities of ground truths and bridge the scales between ground truth and remote sensing pixels, which were helpful in improving the accuracy of remote sensing inversion of grassland aboveground biomass. Lien pérenne : DOI : 10.3390/rs10060851 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=151696
in Remote sensing > 10 (2018) . - 851Zhang, Huifang, Sun, Yi, Chang, Li, Qin, Yu, Chen, Jianjun, Qin, Yan, Du, Jiaxing, Yi, Shuhua, Wang, Yingli 2018 Estimation of grassland canopy height and aboveground biomass at the quadrat scale using unmanned aerial vehicle. Remote sensing, 10: 851.Documents numériques
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Titre : On the use of Unmanned Aerial Systems for environmental monitoring Type de document : Imprimé Auteurs : Salvatore Manfreda ; Matthew F. McCabe ; Pauline E. Miller ; Richard Lucas ; Victor Pajuelo Madrigal ; Giorgos Mallinis ; Eyal Ben-Dor ; David Helman ; Lyndon Estes ; Giuseppe Ciraolo ; Jana Müllerová ; Flavia Tauro ; M. Isabel de Lima ; João Luis Mendes Pedroso de Lima (1959-) ; Antonino Maltese ; Felix Frances ; Kelly Caylor ; Marko Kohv ; Matthew Perks ; Guiomar Ruiz-Pérez ; Zhongbo Su ; Giulia Vico ; Brigitta Toth Année de publication : 2018 Article en page(s) : 641 Catégories : [CBNPMP-Thématique] Télédétection
[CBNPMP-Thématique] Monitoring, suiviRésumé : Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges. Lien pérenne : DOI : 10.3390/rs10040641 Permalink : https://biblio.cbnpmp.fr/index.php?lvl=notice_display&id=152106
in Remote sensing > 10 (2018) . - 641Manfreda, Salvatore, McCabe, Matthew F., Miller, Pauline E., Lucas, Richard, Madrigal, Victor Pajuelo, Mallinis, Giorgos, Ben-Dor, Eyal, Helman, David, Estes, Lyndon, Ciraolo, Giuseppe, Müllerová, Jana, Tauro, Flavia, Lima, M. Isabel de, Lima, João Luis Mendes Pedroso de (1959-), Maltese, Antonino, Frances, Felix, Caylor, Kelly, Kohv, Marko, Perks, Matthew, Ruiz-Pérez, Guiomar, Su, Zhongbo, Vico, Giulia, Toth, Brigitta 2018 On the use of Unmanned Aerial Systems for environmental monitoring. Remote sensing, 10: 641.Documents numériques
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