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Terme regroupant photographies et images issues de différents capteurs.
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Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment / Longfei Zhou in Urban Forestry & Urban Greening, vol 69 (March 2022)
[article]
Titre : Comparison of UAV-based LiDAR and digital aerial photogrammetry for measuring crown-level canopy height in the urban environment Type de document : Article/Communication Auteurs : Longfei Zhou, Auteur ; Ran Meng, Auteur ; Yiyang Tan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 127489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] arbre urbain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt urbaine
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de terrain
[Termes IGN] structure-from-motionRésumé : (auteur) Spatial information on urban forest canopy height (FCH) is fundamental for urban forest monitoring and assisting urban planning and management. Traditionally, ground-based canopy height measurements are time-consuming and laborious, making it challenging for periodic inventory of urban FCH at crown level. Airborne-light detection and ranging (LiDAR) sensor can efficiently measure crown-level FCH; however, the high cost of airborne-LiDAR data collection over large scales hinders its wide applications at a high temporal resolution. Previous studies have shown that in some cases, the Unmanned Aerial Vehicle (UAV)-digital aerial photogrammetry (DAP) approach (i.e., UAV-based structure from motion algorithm) is equivalent to or even outperform airborne-LiDAR in measuring forest structure, but few studies have evaluated their performances in measuring FCH in more complex urban environment, across non-ground coverage (including both canopy and building coverage) and topographical slope gradients. Also, the contribution of multi-angle measurement technique from UAV-DAP to FCH estimation accuracy has rarely been explored in the urban environment. Here, we compared the performances of UAV-LiDAR and UAV-DAP approaches on measuring thousands of crown-level FCH at different non-ground coverage and topographical slope areas in an urban environment. Specifically, UAV-LiDAR-based spatial measurements of crown-level FCH were used as the reference after ground-based validation (R2 = 0.88, RMSE = 2.36 m). The accuracy of UAV-DAP approach with/without multi-angle measurement in different non-ground coverage and topographical slope areas were then analyzed. The results showed that although the DAP multi-angle-based approach can improve the accuracy of spatial measurement for crown-level FCH in some cases, non-ground coverage (including both canopy and building coverage) was still the main factor affecting the broad applications of DAP approach in measuring urban FCH: at areas where non-ground coverage 0.95, except for the case of flat areas (i.e., topographical slope 0.95, can significantly improve the accuracy of UAV-DAP approach in measuring crown-level FCH (R2 = 0.91, RMSE =1.61 m). Our study thus provides a complete guidance on the usage of cost-effective UAV-DAP approach for measuring crown-level FCH in the urban environment, which will be helpful for precise urban forest management and improving the efficiency of urban environmental planning. Numéro de notice : A2022-318 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127489 Date de publication en ligne : 26/01/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127489 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100424
in Urban Forestry & Urban Greening > vol 69 (March 2022) . - n° 127489[article]Deep-learning-based multispectral image reconstruction from single natural color RGB image - Enhancing UAV-based phenotyping / Jiangsan Zhao in Remote sensing, vol 14 n° 5 (March-1 2022)
[article]
Titre : Deep-learning-based multispectral image reconstruction from single natural color RGB image - Enhancing UAV-based phenotyping Type de document : Article/Communication Auteurs : Jiangsan Zhao, Auteur ; Ajay Kumar, Auteur ; Balaji Naik Banoth, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1272; Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture de précision
[Termes IGN] apprentissage profond
[Termes IGN] erreur absolue
[Termes IGN] image multibande
[Termes IGN] image RVB
[Termes IGN] Inde
[Termes IGN] phénologie
[Termes IGN] reconstruction d'imageRésumé : (auteur) Multispectral images (MSIs) are valuable for precision agriculture due to the extra spectral information acquired compared to natural color RGB (ncRGB) images. In this paper, we thus aim to generate high spatial MSIs through a robust, deep-learning-based reconstruction method using ncRGB images. Using the data from the agronomic research trial for maize and breeding research trial for rice, we first reproduced ncRGB images from MSIs through a rendering model, Model-True to natural color image (Model-TN), which was built using a benchmark hyperspectral image dataset. Subsequently, an MSI reconstruction model, Model-Natural color to Multispectral image (Model-NM), was trained based on prepared ncRGB (ncRGB-Con) images and MSI pairs, ensuring the model can use widely available ncRGB images as input. The integrated loss function of mean relative absolute error (MRAEloss) and spectral information divergence (SIDloss) were most effective during the building of both models, while models using the MRAEloss function were more robust towards variability between growing seasons and species. The reliability of the reconstructed MSIs was demonstrated by high coefficients of determination compared to ground truth values, using the Normalized Difference Vegetation Index (NDVI) as an example. The advantages of using “reconstructed” NDVI over Triangular Greenness Index (TGI), as calculated directly from RGB images, were illustrated by their higher capabilities in differentiating three levels of irrigation treatments on maize plants. This study emphasizes that the performance of MSI reconstruction models could benefit from an optimized loss function and the intermediate step of ncRGB image preparation. The ability of the developed models to reconstruct high-quality MSIs from low-cost ncRGB images will, in particular, promote the application for plant phenotyping in precision agriculture. Numéro de notice : A2022-210 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14051272 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.3390/rs14051272 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100033
in Remote sensing > vol 14 n° 5 (March-1 2022) . - n° 1272;[article]Dynamic linkage between urbanization, electrical power consumption, and suitability analysis using remote sensing and GIS techniques / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)
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Titre : Dynamic linkage between urbanization, electrical power consumption, and suitability analysis using remote sensing and GIS techniques Type de document : Article/Communication Auteurs : Muhammad Nasar Ahmad, Auteur ; Qimin Cheng, Auteur ; Fang Luo, Auteur Année de publication : 2022 Article en page(s) : pp 171 - 179 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] consommation
[Termes IGN] densité de population
[Termes IGN] éclairage public
[Termes IGN] électricité
[Termes IGN] étalement urbain
[Termes IGN] image DMSP-OLS
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] Pakistan
[Termes IGN] prise de vue nocturne
[Termes IGN] urbanisationRésumé : (auteur) This article proposes an estimation method for assessing urban sprawl using multispectral remote sensing data: SNPP-VIIRS, DMSP/OLS, Landsat 5-TM, and Landsat 8-OLI. This study focuses on the impacts of human activities, in terms of increased electrical-power consumption (EPC) due to urbanization. For this purpose, night-time light data are used to measure the EPC growth from 2000 to 2020. We also perform a suitability analysis using geographic information-systems techniques to propose a new urban town in Lahore to mitigate urbanization and EPC increase. We found an overall increase of 33% in urban area and an EPC increase of 21.6% in the last two decades. We also find that the best proposed site for the new urban town is in the northwest of Lahore. Numéro de notice : A2022-201 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00026R3 Date de publication en ligne : 01/03/2022 En ligne : https://doi.org/10.14358/PERS.21-00026R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100004
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 3 (March 2022) . - pp 171 - 179[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2022031 SL Revue Centre de documentation Revues en salle Disponible Estimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds / Jiayuan Lin in Urban Forestry & Urban Greening, vol 69 (March 2022)
[article]
Titre : Estimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds Type de document : Article/Communication Auteurs : Jiayuan Lin, Auteur ; Decao Chen, Auteur ; Wenjian Wu, Auteur ; Xiaohan Liao, Auteur Année de publication : 2022 Article en page(s) : n° 127521 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] allométrie
[Termes IGN] biomasse aérienne
[Termes IGN] Chine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt urbaine
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] semis de points
[Termes IGN] structure-from-motionRésumé : (auteur) Urban forest is a crucial part of urban ecological environment. The accurate estimation of its tree aboveground biomass (AGB) is of significant value to evaluate urban ecological functions and estimate urban forest carbon storage. It has a high accuracy to estimate the forest AGB with field measured canopy structure parameters, but unsuitable for large-scale operations. Limited by low spatial resolution or spectral saturation, the estimated forest AGBs based on various satellite remotely sensed data have relatively low accuracies. In contrast, Unmanned Aerial Vehicle (UAV) remote sensing provides a promising way to accurately estimate the tree AGB of fragmented urban forest. In this study, taking an artificial urban forest in Ma'anxi Wetland Park in Chongqing City, China as an example, we used UAVs equipped with a digital camera and a LiDAR to acquire two point cloud data. One was produced from overlapping images using Structure from Motion (SfM) photogrammetry, and the other was resolved from laser scanned raw data. The dual point clouds were combined to extract individual tree height (H) and canopy radius (Rc), which were then input to the newly established allometric equation with tree H and Rc as predictor variables to obtain the AGBs of all dawn redwood trees in study area. In accuracy assessment, the coefficient of determination (R2) and Root Mean Square Error (RMSE) of extracted H were 0.9341 and 0.59 m; the R2 and RMSE of extracted Rc were 0.9006 and 0.28 m; the R2 and RMSE of estimated AGB were 0.9452 and 17.59 kg. These results proved the feasibility and effectiveness of applying dual-source UAV point cloud data and the new allometric equation on H and Rc to accurate AGB estimation of urban forest trees. Numéro de notice : A2022-319 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127521 Date de publication en ligne : 24/02/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127521 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100425
in Urban Forestry & Urban Greening > vol 69 (March 2022) . - n° 127521[article]Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image / Sinan Kaptan in Geocarto international, vol 37 n° 5 ([01/03/2022])
[article]
Titre : Estimation of uneven-aged forest stand parameters, crown closure and land use/cover using the Landsat 8 OLI satellite image Type de document : Article/Communication Auteurs : Sinan Kaptan, Auteur ; Hasan Aksoy, Auteur Année de publication : 2022 Article en page(s) : pp 1408 - 1425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] correction géométrique
[Termes IGN] forêt inéquienne
[Termes IGN] houppier
[Termes IGN] image Landsat-OLI
[Termes IGN] occupation du sol
[Termes IGN] peuplement forestier
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (Auteur) This study used the Landsat 8 OLI satellite image and the supervised classification method to estimate uneven-aged forest stand parameters and land use/cover. The spatial success of classification was also investigated. The overall success rates and Kappa values of the classification were, respectively, 74.7% and 0.75 for actual structural type, 84.6% and 0.80 for crown closure, and 88.35% and 0.81 for land use class, whereas the spatial success of classification on the forest cover type map was 36.91% for actual structural type, 64.74% for crown closure, and 41.78% for land use/cover class. The results revealed that the Landsat 8 OLI image can be used to identify stand parameters and land use/cover class. However, because the spatial success rates were below 50% for the actual structural type and land use/cover class of the stand types, it is not suitable for use in spatial classification determination for these classes. Numéro de notice : A2022-277 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1765888 Date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.1080/10106049.2020.1765888 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100795
in Geocarto international > vol 37 n° 5 [01/03/2022] . - pp 1408 - 1425[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2022051 RAB Revue Centre de documentation En réserve L003 Disponible Evaluating Sentinel-1A datasets for rice leaf area index estimation based on machine learning regression models / Lamin R. Mansaray in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkEvaluating the 3D integrity of underwater structure from motion workflows / Ian M. Lochhead in Photogrammetric record, vol 37 n° 177 (March 2022)PermalinkExploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China / Zhen Li in Sustainable Cities and Society, vol 78 (March 2022)PermalinkExtraction from high-resolution remote sensing images based on multi-scale segmentation and case-based reasoning / Jun Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)PermalinkFeasibility of mapping radioactive minerals in high background radiation areas using remote sensing techniques / J.O. Ondieki in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)PermalinkFlood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)PermalinkLand surface phenology retrieval through spectral and angular harmonization of Landsat-8, Sentinel-2 and Gaofen-1 data / Jun Lu in Remote sensing, vol 14 n° 5 (March-1 2022)PermalinkLiDAR-based method for analysing landmark visibility to pedestrians in cities: case study in Kraków, Poland / Krystian Pyka in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)PermalinkMonitoring coastal vulnerability by using DEMs based on UAV spatial data / Antonio Minervino Amodio in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)PermalinkMonitoring of phenological stage and yield estimation of sunflower plant using Sentinel-2 satellite images / Omer Gokberk Narin in Geocarto international, vol 37 n° 5 ([01/03/2022])Permalink