Descripteur
Documents disponibles dans cette catégorie (7902)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Children’s walking to urban services: an analysis of pedestrian access to social infrastructures and its relationship with land use / Wonjun No in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)
[article]
Titre : Children’s walking to urban services: an analysis of pedestrian access to social infrastructures and its relationship with land use Type de document : Article/Communication Auteurs : Wonjun No, Auteur ; Junyong Choi, Auteur ; Youngchul Kim, Auteur Année de publication : 2023 Article en page(s) : pp 189 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse spatiale
[Termes IGN] enfant
[Termes IGN] matrice
[Termes IGN] milieu urbain
[Termes IGN] navigation pédestre
[Termes IGN] origine - destination
[Termes IGN] Séoul
[Termes IGN] service public
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) The conceptual framework of child-friendly cities guarantees children’s equal access to public urban services. Despite the widespread application of geographical information systems (GISs) and pedestrian network analysis, studies have yet to analyze children’s comprehensive pedestrian access to urban services in a large-scale city. This study demonstrates GIS-based approaches to measuring children’s pedestrian access to urban services using a pedestrian path layer and the spatial layers of social infrastructure locations in Seoul, South Korea. We show the spatial inequities in children’s access to urban services, which depend on the locational characteristics of social infrastructures and the urban development patterns around children. We analyze how children’s access to social infrastructures is differentiated by land use composition. Our statistical analysis finds that low-rise residential areas, consisting of impermeable street patterns, increase children’s walking distance and restrict children from accessing urban services within their walkable area. In addition, there is potential for key infrastructures such as schools and local community centers to promote pedestrian access to urban services for children. Considering pedestrian access at the street level will help pinpoint vulnerable areas with children who have less access overall and maximize the users served within the service areas of infrastructures. Numéro de notice : A2023-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2022.2104455 Date de publication en ligne : 27/07/2022 En ligne : https://doi.org/10.1080/13658816.2022.2104455 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102312
in International journal of geographical information science IJGIS > vol 37 n° 1 (January 2023) . - pp 189 - 214[article]A CNN based approach for the point-light photometric stereo problem / Fotios Logothetis in International journal of computer vision, vol 131 n° 1 (January 2023)
[article]
Titre : A CNN based approach for the point-light photometric stereo problem Type de document : Article/Communication Auteurs : Fotios Logothetis, Auteur ; Roberto Mecca, Auteur ; Ignas Budvytis, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 101 - 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] éclairement lumineux
[Termes IGN] effet de profondeur cinétique
[Termes IGN] intensité lumineuse
[Termes IGN] itération
[Termes IGN] reconstruction 3D
[Termes IGN] réflectivité
[Termes IGN] stéréoscopie
[Termes IGN] vue perspectiveRésumé : (auteur) Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagation and attenuation, perspective viewing geometry and specular light reflection are considered. Many of works tackling Photometric Stereo (PS) problems often relax most of the aforementioned assumptions. Especially they ignore specular reflection and global illumination effects. In this work, we propose a CNN-based approach capable of handling these realistic assumptions by leveraging recent improvements of deep neural networks for far-field Photometric Stereo and adapt them to the point light setup. We achieve this by employing an iterative procedure of point-light PS for shape estimation which has two main steps. Firstly we train a per-pixel CNN to predict surface normals from reflectance samples. Secondly, we compute the depth by integrating the normal field in order to iteratively estimate light directions and attenuation which is used to compensate the input images to compute reflectance samples for the next iteration. Our approach sigificantly outperforms the state-of-the-art on the DiLiGenT real world dataset. Furthermore, in order to measure the performance of our approach for near-field point-light source PS data, we introduce LUCES the first real-world ’dataset for near-fieLd point light soUrCe photomEtric Stereo’ of 14 objects of different materials were the effects of point light sources and perspective viewing are a lot more significant. Our approach also outperforms the competition on this dataset as well. Data and test code are available at the project page. Numéro de notice : A2023-048 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s11263-022-01689-3 Date de publication en ligne : 07/10/2022 En ligne : https://doi.org/10.1007/s11263-022-01689-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102364
in International journal of computer vision > vol 131 n° 1 (January 2023) . - pp 101 - 120[article]A comparative assessment of the statistical methods based on urban population density estimation / Merve Yılmaz in Geocarto international, vol 38 n° 1 ([01/01/2023])
[article]
Titre : A comparative assessment of the statistical methods based on urban population density estimation Type de document : Article/Communication Auteurs : Merve Yılmaz, Auteur Année de publication : 2023 Article en page(s) : n° 2152494 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] planification urbaine
[Termes IGN] population urbaine
[Termes IGN] régression géographiquement pondérée
[Termes IGN] régression multiple
[Termes IGN] TurquieRésumé : (auteur) Population density is important spatial information for addressing the use and access to land resources in cities under the Sustainable Development Goals. This is because the spatial data support appropriate spatial policies at the spatial scale and predicts how much land will be consumed in the future. The study aims to compare and evaluate the regression tools in the context of estimating the population density difference. The three analysis tools used are Random Forest-Based Classification, Multiple Linear Regression, and Geographically Weighted Regression. The sampling area covers cities around Türkiye. Comparative results showed that the two most important descriptive variables in the Random Forest-Based Classification model are the density difference of the new developed area and the connectivity. The three main explanatory variables of the Multiple Linear Regression model are centrality, vehicle ownership, and accessibility. The results of the Multiple Linear Regression model (a non-spatial model) and the Geographically Weighted Regression model (a spatial model), were found to be quite similar. The importance of accessibility and connectivity is more evident in the Multiple Linear Regression model when the Random Forest-Based Classification model highlights the density values in the new development areas. Numéro de notice : A2023-055 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2152494 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.1080/10106049.2022.2152494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102388
in Geocarto international > vol 38 n° 1 [01/01/2023] . - n° 2152494[article]Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data / Thuong V. Tran in GIScience and remote sensing, vol 60 n° 1 (2023)
[article]
Titre : Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data Type de document : Article/Communication Auteurs : Thuong V. Tran, Auteur ; David Bruce, Auteur ; Cho-Ying Huang, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 2163070 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spectrale
[Termes IGN] changement d'occupation du sol
[Termes IGN] image Terra-MODIS
[Termes IGN] indice d'humidité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] parcelle agricole
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] surveillance agricole
[Termes IGN] variation temporelle
[Termes IGN] Viet NamRésumé : (auteur) Using a multivariate drought index that incorporates important environmental variables and is suitable for a specific geographical region is essential to fully understanding the pattern and impacts of drought severity. This study applied feature scaling algorithms to MODIS time-series imagery to develop an integrated Multivariate Drought Index (iMDI). The iMDI incorporates the vegetation condition index (VCI), the temperature condition index (TCI), and the evaporative stress index (ESI). The 54,474 km2 Vietnamese Central Highlands region, which has been significantly affected by drought severity for several decades, was selected as a test site to assess the feasibility of the iMDI. Spearman correlation between the iMDI and other commonly used spectral drought indices (i.e. the Drought Severity Index (DSI–12) and the annual Vegetation Health Index (VHI–12)) and ground-based drought indices (i.e. the Standardized Precipitation Index (SPI–12) and the Reconnaissance Drought Index (RDI–12)) was employed to evaluate performance of the proposed drought index. Pixel-based linear regression together with clustering models of the iMDI time-series was applied to characterize the spatiotemporal pattern of drought from 2001 to 2020. In addition, a persistent area of LULC types (i.e. forests, croplands, and shrubland) during the 2001–2020 period was used to understand drought variation in relation to LULC. Results suggested that the iMDI outperformed the other spectral drought indices (r > 0.6; p Numéro de notice : A2023-042 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2022.2163070 Date de publication en ligne : 03/01/2023 En ligne : https://doi.org/10.1080/15481603.2022.2163070 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102329
in GIScience and remote sensing > vol 60 n° 1 (2023) . - n° 2163070[article]Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis / Haifa Tamiminia in Geocarto international, vol 38 n° inconnu ([01/01/2023])
[article]
Titre : Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis Type de document : Article/Communication Auteurs : Haifa Tamiminia, Auteur ; Bahram Salehi, Auteur ; Masoud Mahdianpari, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse d'image orientée objet
[Termes IGN] biomasse aérienne
[Termes IGN] boosting adapté
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification pixellaire
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Extreme Gradient Machine
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] réserve naturelleRésumé : (auteur) Forest above-ground biomass (AGB) estimation provides valuable information about the carbon cycle. Thus, the overall goal of this paper is to present an approach to enhance the accuracy of the AGB estimation. The main objectives are to: 1) investigate the performance of remote sensing data sources, including airborne light detection and ranging (LiDAR), optical, SAR, and their combination to improve the AGB predictions, 2) examine the capability of tree-based machine learning models, and 3) compare the performance of pixel-based and object-based image analysis (OBIA). To investigate the performance of machine learning models, multiple tree-based algorithms were fitted to predictors derived from airborne LiDAR data, Landsat, Sentinel-2, Sentinel-1, and PALSAR-2/PALSAR SAR data collected within New York’s Adirondack Park. Combining remote sensing data from multiple sources improved the model accuracy (RMSE: 52.14 Mg ha−1 and R2: 0.49). There was no significant difference among gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGBoost) models. In addition, pixel-based and object-based models were compared using the airborne LiDAR-derived AGB raster as a training/testing sample. The OBIA provided the best results with the RMSE of 33.77 Mg ha−1 and R2 of 0.81 for the combination of optical and SAR data in the GBM model. Numéro de notice : A2022-331 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2071475 Date de publication en ligne : 27/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2071475 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100607
in Geocarto international > vol 38 n° inconnu [01/01/2023][article]Establishing a high-precision real-time ZTD model of China with GPS and ERA5 historical data and its application in PPP / Pengfei Xia in GPS solutions, vol 27 n° 1 (January 2023)PermalinkEstimating mangrove above-ground biomass at Maowei Sea, Beibu Gulf of China using machine learning algorithm with Sentinel-1 and Sentinel-2 data / Zhuomei Huang in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkEstimation of lidar-based gridded DEM uncertainty with varying terrain roughness and point density / Luyen K. Bui in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 7 (January 2023)PermalinkField optical clocks and sensitivity to mass anomalies for geoscience applications / Guillaume Lion (2023)PermalinkForest road extraction from orthophoto images by convolutional neural networks / Erhan Çalişkan in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkGeneration of high-resolution orthomosaics from historical aerial photographs using Structure-from-motion and Lidar data / Ji Won Suh in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)PermalinkGeographic-dependent variational parameter estimation: A case study with a 2D ocean temperature model / Zhenyang Du in Journal of Marine Systems, vol 237 (January 2023)PermalinkGeographically masking addresses to study COVID-19 clusters / Walid Houfaf-Khoufaf in Cartography and Geographic Information Science, vol inconnu (2023)PermalinkA geometry-aware attention network for semantic segmentation of MLS point clouds / Jie Wan in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)PermalinkGeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinates / Valerio Marsocci (2023)PermalinkGeospatial-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)PermalinkA hexagon-based method for polygon generalization using morphological operators / Lu Wang in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)PermalinkA hierarchical deformable deep neural network and an aerial image benchmark dataset for surface multiview stereo reconstruction / Jiayi Li in IEEE Transactions on geoscience and remote sensing, vol 61 n° 1 (January 2023)PermalinkA hierarchical multiview registration framework of TLS point clouds based on loop constraint / Hao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)PermalinkHow 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)PermalinkImprovement of 3D LiDAR point cloud classification of urban road environment based on random forest classifier / Mahmoud Mohamed in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkImproving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar / Andrew W. Whelan in Remote sensing of environment, vol 284 (January 2023)PermalinkImproving 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)PermalinkInvestigating the impact of pan sharpening on the accuracy of land cover mapping in Landsat OLI imagery / Komeil Rokni in Geodesy and cartography, vol 49 n° 1 (January 2023)PermalinkLandscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population / Heng Wan in Computers, Environment and Urban Systems, vol 99 (January 2023)Permalink