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télédétection
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Télédétection aérospatiale Télédétection par satellite Télédétection satellitaire Télédétection spatiale Appareils enregistreurs >> Agriculture de précision Capteurs (technologie) Photogrammétrie aérienne Photographie aérienne >>Terme(s) spécifique(s) : Télédétection en sciences de la Terre Cartographie radar Traitement d'images -- Techniques numériques Images de télédétection Radar à antenne synthétique Radar en sciences de la Terre Reconnaissance aérienne Satellites artificiels en télédétection Satellites de télédétection des ressources terrestres SPOT (satellites de télédétection) Surveillance électronique Télédétection hyperfréquence Télémesure spatiale Thermographie Equiv. LCSH : Remote sensing Domaine(s) : 500; 600 |
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Exploring the addition of airborne Lidar-DEM and derived TPI for urban land cover and land use classification and mapping / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)
[article]
Titre : Exploring the addition of airborne Lidar-DEM and derived TPI for urban land cover and land use classification and mapping Type de document : Article/Communication Auteurs : Clement E. Akumu, Auteur ; Sam Dennis, Auteur Année de publication : 2023 Article en page(s) : pp19 - 26 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte d'occupation du sol
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données topographiques
[Termes IGN] image Landsat-OLI
[Termes IGN] milieu urbain
[Termes IGN] MNS lidar
[Termes IGN] semis de points
[Termes IGN] Tennessee (Etats-Unis)
[Termes IGN] utilisation du solRésumé : (auteur) The classification and mapping accuracy of urban land cover and land use has always been a critical topic and several auxiliary data have been used to improve the classification accuracy. However, to the best of our knowledge, there is limited knowledge of the addition of airborne Light Detection and Ranging (lidar)-Digital Elevation Model (DEM) and Topographic Position Index (TPI) for urban land cover and land use classification and mapping. The aim of this study was to explore the addition of airborne lidar-DEM and derived TPI to reflect data of Landsat Operational Land Imager (OLI) in improving the classification accuracy of urban land cover and land use map- ping. Specifically, this study explored the mapping accuracies of urban land cover and land use classifications derived using: 1) standalone Landsat OLI satellite data; 2) Landsat OLI with acquired airborne lidar-DEM ; 3) Landsat OLI with TPI ; and 4) Landsat OLI with airborne lidar-DEM and derived TPI. The results showed that the addition of airborne lidar-DEM and TPI yielded the best overall urban land cover and land use classification accuracy of about 88%. The findings in this study demonstrated that both lidar-DEM and TPI had a positive impact in improving urban land cover and land use classification. Numéro de notice : A2023-045 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00029R2 Date de publication en ligne : 01/01/2023 En ligne : https://doi.org/10.14358/PERS.21-00029R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102354
in Photogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 1 (January 2023) . - pp19 - 26[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2023011 SL Revue Centre de documentation Revues en salle Disponible Geospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image / Taposh Mollick in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)
[article]
Titre : Geospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image Type de document : Article/Communication Auteurs : Taposh Mollick, Auteur ; MD Golam Azam, Auteur ; Sabrina Karim, Auteur Année de publication : 2023 Article en page(s) : n° 100859 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage automatique
[Termes IGN] Bangladesh
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par nuées dynamiques
[Termes IGN] classification pixellaire
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] occupation du sol
[Termes IGN] rendement agricole
[Termes IGN] segmentation d'image
[Termes IGN] utilisation du solRésumé : (auteur) Bangladesh is primarily an agricultural country where technological advancement in the agricultural sector can ensure the acceleration of economic growth and ensure long-term food security. This research was conducted in the south-western coastal zone of Bangladesh, where rice is the main crop and other crops are also grown. Land use and land cover (LULC) classification using remote sensing techniques such as the use of satellite or unmanned aerial vehicle (UAV) images can forecast the crop yield and can also provide information on weeds, nutrient deficiencies, diseases, etc. to monitor and treat the crops. Depending on the reflectance received by sensors, remotely sensed images store a digital number (DN) for each pixel. Traditionally, these pixel values have been used to separate clusters and classify various objects. However, it frequently generates a lot of discontinuity in a particular land cover, resulting in small objects within a land cover that provide poor image classification output. It is called the salt-and-pepper effect. In order to classify land cover based on texture, shape, and neighbors, Pixel-Based Image Analysis (PBIA) and Object-Based Image Analysis (OBIA) methods use digital image classification algorithms like Maximum Likelihood (ML), K-Nearest Neighbors (KNN), k-means clustering algorithm, etc. to smooth this discontinuity. The authors evaluated the accuracy of both the PBIA and OBIA approaches by classifying the land cover of an agricultural field, taking into consideration the development of UAV technology and enhanced image resolution. For classifying multispectral UAV images, we used the KNN machine learning algorithm for object-based supervised image classification and Maximum Likelihood (ML) classification (parametric) for pixel-based supervised image classification. Whereas, for unsupervised classification using pixels, we used the K-means clustering technique. For image analysis, Near-infrared (NIR), Red (R), Green (G), and Blue (B) bands of a high-resolution ground sampling distance (GSD) 0.0125m UAV image was used in this research work. The study found that OBIA was 21% more accurate than PBIA, indicating 94.9% overall accuracy. In terms of Kappa statistics, OBIA was 27% more accurate than PBIA, indicating Kappa statistics accuracy of 93.4%. It indicates that OBIA provides better classification performance when compared to PBIA for the classification of high-resolution UAV images. This study found that by suggesting OBIA for more accurate identification of types of crops and land cover, which will help crop management, agricultural monitoring, and crop yield forecasting be more effective. Numéro de notice : A2023-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rsase.2022.100859 Date de publication en ligne : 22/11/2022 En ligne : https://doi.org/10.1016/j.rsase.2022.100859 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102224
in Remote Sensing Applications: Society and Environment, RSASE > vol 29 (January 2023) . - n° 100859[article]How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data / Rongfang Lyu in Sustainable Cities and Society, vol 88 (January 2023)
[article]
Titre : How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data Type de document : Article/Communication Auteurs : Rongfang Lyu, Auteur ; Jili Pang, Auteur ; Xiaolei Tian, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104287 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Chine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espace vert
[Termes IGN] hauteur du bâti
[Termes IGN] ilot thermique urbain
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] Leaf Area Index
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] optimisation (mathématiques)
[Termes IGN] paysage urbain
[Termes IGN] plan d'eau
[Termes IGN] planification urbaine
[Termes IGN] réseau bayesien
[Termes IGN] semis de points
[Termes IGN] température au solRésumé : (auteur) The systematical exploration of how two-dimensional (2D) and three-dimensional (3D) features of urban landscapes influence land surface temperature (LST) is still limited. Therefore, we investigated the influence of three main urban landscapes—urban green space, impervious land, and water bodies on LST, with a particular focus on the 3D vegetation metrics of green volume (GV) and leaf area index (LAI). We used Yinchuan City, China, as a case study. We quantified the impacts of various 2D/3D metrics of the three landscape types on LST using a random forest analysis with multiple sources, including Unmanned Aerial Vehicle (UAV) and remote sensing images. We then generated a Bayesian Network (BN) model to identify the optimal configurations for each landscape type. We found that using 11 of the 31 metrics considered, our model could explain 81.8% of the observed variance in LST of Yinchuan City. Among those, water body metrics were the most important, followed by vegetation abundance, impervious land metrics, and landscape pattern of urban green space. The mean classification error of the BN model was only 22.9%. We suggest that this makes the BN model a promising support tool for urban planning with a view to urban heat island mitigation. Our findings also stress the importance of considering both 2D and 3D features when considering urban cooling strategies. Numéro de notice : A2023-007 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.104287 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104287 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102095
in Sustainable Cities and Society > vol 88 (January 2023) . - n° 104287[article]Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)
[article]
Titre : Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography Type de document : Article/Communication Auteurs : Ihor Kozak, Auteur ; Mikhail Popov, Auteur ; Igor Semko, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 127793 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] biomasse aérienne
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] forêt urbaine
[Termes IGN] houppier
[Termes IGN] image hémisphérique
[Termes IGN] Leaf Area Index
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de régression
[Termes IGN] modèle numérique de terrain
[Termes IGN] photographie numérique
[Termes IGN] Pinus sylvestris
[Termes IGN] Pologne
[Termes IGN] semis de points
[Termes IGN] surface terrièreRésumé : (auteur) The article proposes methods for combining Airborne Laser Scanning (ALS) with Digital Hemispherical Photography (DHP) data required by the Urban Forest Biomass (UFB) model to predict the aboveground biomass (AGB) of Scotch pine (Pinus sylvestris L.) in urban forests of Lublin (Poland). The article also demonstrates the potential of ALS and DHP data in urban AGB estimation. ALS and Leaf Area Index (LAI) data were calculated using a voxels-vector approach based on the measurements taken at eight permanent sample plots (PSPs). The research was conducted in 2014 and the prediction was made until 2030. It was found that the determination coefficients (R2) for the Basal Area (BA) of the trees are 0.97, and the BA modeling parameters have a high correlation with those observed in the field (model efficiency (ME) 0.94). 83 % growth trajectory based on the measured BA was appropriately modeled using the UFB model (P > 0.9). The results for AGB show that the degree of fitting and accuracy are greatest for the Monte Carlo (MC) simulation technique based on ALS and DHP data (UBF with ALS and DHP) where R2 = 0.98, RMSE = 2.97 t/ha, MAE = 2.35 t/ha, rRMSE = 1.28 %, which performed better than MC simulation technique without ALS and DHP (UBF without ALS and DHP) where R2 = 0.94, RMSE = 4.58 t/ha, MAE = 3.64 t/ha, rRMSE = 3.29 %. The results indicate that the proposed method based on combining the UFB model, LiDAR and DHP allows us to improve the accuracy of the AGB prediction. Numéro de notice : A2023-023 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127793 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127793 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102246
in Urban Forestry & Urban Greening > vol 79 (January 2023) . - n° 127793[article]In-camera IMU angular data for orthophoto projection in underwater photogrammetry / Erica Nocerino in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 7 (January 2023)
[article]
Titre : In-camera IMU angular data for orthophoto projection in underwater photogrammetry Type de document : Article/Communication Auteurs : Erica Nocerino, Auteur ; Fabio Menna, Auteur Année de publication : 2023 Article en page(s) : n° 100027 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] caméra numérique
[Termes IGN] carte bathymétrique
[Termes IGN] centrale inertielle
[Termes IGN] compensation par faisceaux
[Termes IGN] mesure géodésique
[Termes IGN] orthophotographie
[Termes IGN] photogrammétrie sous-marine
[Termes IGN] positionnement par GNSS
[Termes IGN] redressement différentiel
[Termes IGN] roulis
[Termes IGN] structure-from-motion
[Termes IGN] tangageRésumé : (auteur) Among photogrammetric products, orthophotos are probably the most versatile and widely used in many fields of application. In the last years, coupled with the spread of semi-automated survey and processing approaches based on photogrammetry, orthophotos have become almost a standard for monitoring the underwater environment. If on land the definition of the reference coordinate system and projection plane for the orthophoto generation is trivial, underwater it may represent a challenge. In this paper, we address the issue of defining the vertical direction and resulting horizontal plane (levelling) for the differential ortho rectification. We propose a non-invasive, contactless method based on roll and pitch angular data provided by in-camera IMU sensors and embedded in the Exif metadata of JPEG and raw image files. We show how our approach can be seamlessly integrated into automatic SfM/MVS pipelines, provide the mathematical background, and showcase real-world applications results in an underwater monitoring project. The results illustrate the effectiveness of the proposed method and, for the first time, provide a metric evaluation of the definition of the vertical direction with low-cost sensors enclosed in digital cameras directly underwater. Numéro de notice : A2023-119 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Numéro de périodique DOI : 10.1016/j.ophoto.2022.100027 Date de publication en ligne : 07/12/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102493
in ISPRS Open Journal of Photogrammetry and Remote Sensing > vol 7 (January 2023) . - n° 100027[article]Large-scale individual building extraction from open-source satellite imagery via super-resolution-based instance segmentation approach / Shenglong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)PermalinkMeasuring metro accessibility: An exploratory study of Wuhan based on multi-source urban data / Tao Wu in ISPRS International journal of geo-information, vol 12 n° 1 (January 2023)PermalinkMTMGNN: Multi-time multi-graph neural network for metro passenger flow prediction / Du Yin in Geoinformatica, vol 27 n° 1 (January 2023)PermalinkRemote sensing techniques for water management and climate change monitoring in drought areas: case studies in Egypt and Tunisia / Lifan Ji in European journal of remote sensing, vol 56 n° 1 (2023)PermalinkThe cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)PermalinkInteractive effects of abiotic factors and biotic agents on Scots pine dieback: A multivariate modeling approach in southeast France / Jean Lemaire in Forest ecology and management, vol 526 (December-15 2022)PermalinkCoastal land use and shoreline evolution along the Nador lagoon Coast in Morocco / Khalid El Khalidi in Geocarto international, vol 37 n° 25 ([01/12/2022])PermalinkDecadal surface changes and displacements in Switzerland / Valentin Tertius Bickel in Journal of Geovisualization and Spatial Analysis, vol 6 n° 2 (December 2022)PermalinkEstimating 10-m land surface albedo from Sentinel-2 satellite observations using a direct estimation approach with Google Earth Engine / Xingwen Lin in ISPRS Journal of photogrammetry and remote sensing, vol 194 (December 2022)PermalinkForêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)Permalink