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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)  

Public [article]  inSustainable Cities and Society > vol 88 (January 2023) . - n° 104287 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 sol Résumé : (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 [article]

Improving 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)  

Public [article]  inRemote sensing of environment > vol 284 (January 2023) . - n° 113362 Titre : Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar Type de document : Article/Communication Auteurs : Andrew W. Whelan, Auteur ; Jeffery B. Cannon, Auteur ; Seth W. Bigelow, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113362 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] diagnostic foliaire [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Géorgie (Etats-Unis) [Termes IGN] modélisation de la forêt [Termes IGN] Pinus palustris [Termes IGN] structure d'un peuplement forestier [Termes IGN] surface forestière [Termes IGN] volume en bois [Termes IGN] voxel Résumé : (auteur) Modeling forest attributes using lidar data has been a useful tool for forest management but the need to correlate lidar to ground-based measurements creates challenges to modeling in diverse forest landscapes. Many lidar models have been based on metrics derived from summarizations of individual lidar returns over sample plot areas, but more recently, metrics based on summarization by volumetric pixel (voxel) have shown promise to better characterize forest structure and distinguish between diverse forest types. Voxel-based metrics may improve characterization of leaf area distribution and horizontal forest structure, which could help create general models of forest attributes applicable in complex landscapes composed of many distinct forest types. We modeled wood volume in longleaf pine woodlands and associated forests to compare how area- and voxel- based lidar metrics predicted wood volume in forest type specific and general predictive models. We created four area-based and six voxel-based metrics to fit models of wood volume using a multiplicative power function. We selected models and compared metric importance using AIC and evaluated model performance using cross-validated mean prediction error. We found that one area-based metric and four voxel-based metrics consistently improved model predictions We suggest that area-based metrics alone may have limitations for characterizing complex forest structure. Area-based summarizes of lidar returns are more heavily influenced by upper canopy returns because lidar returns attenuate below the canopy. By contrast, summarizing lidar returns into a single value per voxel prior to summarization over plots homogenizes point density, giving added weight to sub-canopy returns. Thus voxel-based metrics may be more sensitive to structural variation that may not be adequately captured by area-based metrics alone. This study highlights the potential of voxel-based metrics for characterizing complex forest structure and model generalization capable of accurate forest attribute prediction across diverse forest types. Numéro de notice : A2023-016 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113362 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102150 [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)  

Public [article]  inUrban Forestry & Urban Greening > vol 79 (January 2023) . - n° 127793 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 terrière Résumé : (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 [article]

INS-assisted inter-system biases estimation and inter-system ambiguity resolution in a complex environment / Wenhao Zhao in GPS solutions, vol 27 n° 1 (January 2023)  

Public [article]  inGPS solutions > vol 27 n° 1 (January 2023) . - n° 3 Titre : INS-assisted inter-system biases estimation and inter-system ambiguity resolution in a complex environment Type de document : Article/Communication Auteurs : Wenhao Zhao, Auteur ; Genyou Liu, Auteur ; Ming Gao, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] centrale inertielle [Termes IGN] erreur systématique inter-systèmes [Termes IGN] filtre de Kalman [Termes IGN] positionnement cinématique en temps réel [Termes IGN] résolution d'ambiguïté [Termes IGN] système complexe [Termes IGN] trajet multiple Résumé : (auteur) The inter-system real-time kinematic (RTK) model in which multiple systems choose the same reference satellite uses more observations than the traditional intra-system RTK model; however, it is still difficult to accurately determine the differential inter-system biases (DISB) and inter-system ambiguity in a complex environment. We propose a tightly coupled inter-system RTK/INS model that uses the high-precision position information the inertial navigation system (INS) provides to assist in DISB estimation and inter-system ambiguity resolution. Vehicle experiments on urban roads were designed to verify the effectiveness of the method. The vehicle experiments consisted of a simulated rare satellite environment with a high cutoff elevation angle and a real complex environment with buildings and trees obscuration. A robust Kalman filter strategy is used to combat the effects of multipath and non-line-of-sight signals in real complex environments. The results indicate that with the help of INS, the standard deviation of phase and code DISB is reduced by 11 and 17%, respectively, in the simulated environment and by 33 and 18%, respectively, in the real complex environment. Compared with the intra-system RTK/INS model, inter-system RTK/INS mode 3D positioning root-mean-square error is reduced by 79% in the simulated environment and by 27% in the real complex environment. In the single-epoch mode, the ambiguity success rates of the inter-system RTK/INS model, inter-system RTK model, intra-system RTK/INS model and intra-system RTK model are 89, 74, 69 and 58%, respectively, in the simulated environment, and 68, 41, 64 and 12%, respectively, in the real complex environment. Numéro de notice : A2023-003 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-022-01347-8 Date de publication en ligne : 09/10/2022 En ligne : https://doi.org/10.1007/s10291-022-01347-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101873 [article]

Landscape 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)  

Public [article]  inComputers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101899 Titre : Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population Type de document : Article/Communication Auteurs : Heng Wan, Auteur ; Jim Yoon, Auteur ; Vivek Srikrishnan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte thématique [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] Etats-Unis [Termes IGN] indicateur paysager [Termes IGN] interpolation [Termes IGN] occupation du sol [Termes IGN] paysage [Termes IGN] planification urbaine [Termes IGN] réduction d'échelle Résumé : (auteur) Population downscaling and interpolation methods are required to produce data which correspond to spatial units used in urban planning, demography, and environmental modeling. Population data are typically aggregated at census enumeration units, which can have arbitrary, temporally-evolving boundaries. Previous approaches to imperviousness-based dasymetric mapping ignore cell-level patterning of imperviousness within a spatial unit of prediction, which potentially serve as a strong indicator of population. Landscape metrics derived from imperviousness data offer a promising approach to capture these patterns. In this study, we incorporate landscape metrics derived from impervious cover percentage maps into intelligent dasymetric mapping to downscale population from census tracts to block groups in four states with varying population densities: Connecticut, South Carolina, West Virginia, and New Mexico. We compare the performance of the landscape metrics-based models against two baseline models in all four states across three different time periods. The results show that intelligent dasymetric mapping using landscape metrics generally outperforms the two baseline models. We further compare the performance of landscape metrics as an ancillary source of information for dasymetric mapping against other traditionally-used datasets (e.g., land use, roads, nighttime lights data) in three states (Connecticut, South Carolina, and New Mexico) in 2000. We find that class area, landscape shape index, and number of patches consistently achieve lower error rates than other ancillary datasets in all the three states. Numéro de notice : A2023-013 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101899 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101899 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102130 [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)  

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Linear building pattern recognition in topographical maps combining convex polygon decomposition / Zhiwei Wei in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

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Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami / Riantini Virtriana in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

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Management of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products / Jānis Vuguls in Forests, vol 14 n° 1 (January 2023)  

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Mapping active paddy rice area over monsoon asia using time-series Sentinel-2 images in Google earth engine : a case study over lower gangetic plain / Arabinda Maiti in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

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A method for remote sensing image classification by combining Pixel Neighbourhood Similarity and optimal feature combination / Kaili Zhang in Geocarto international, vol 38 n° 1 ([01/01/2023])  

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Modeling the gravitational effects of ocean tide loading at coastal stations in the China earthquake gravity network based on GOTL software / Chuandong Zhu in Journal of applied geodesy, vol 17 n° 1 (January 2023)  

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MTMGNN: Multi-time multi-graph neural network for metro passenger flow prediction / Du Yin in Geoinformatica, vol 27 n° 1 (January 2023)  

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Multi-information PointNet++ fusion method for DEM construction from airborne LiDAR data / Hong Hu in Geocarto international, vol 38 n° 1 ([01/01/2023])  

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Multipath mitigation for improving GPS narrow-lane uncalibrated phase delay estimation and speeding up PPP ambiguity resolution / Kai Zheng in Measurement, vol 206 (January 2023)  

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A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing / Yali Zhang in GIScience and remote sensing, vol 60 n° 1 (2023)  

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A nonlinear Gauss-Helmert model and its robust solution for seafloor control point positioning / Yingcai Kuang in Marine geodesy, vol 46 n° 1 (January 2023)  

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Precipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation / Minh Ha-Truong in Climate Dynamics, vol 60 n° inconnu (2023)  

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Precise orbit determination for BDS-3 GEO satellites enhanced by intersatellite links / Xiaojie Li in GPS solutions, vol 27 n° 1 (January 2023)  

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Prescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)  

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Production of orthophoto map using mobile photogrammetry and comparative assessment of cost and accuracy with satellite imagery for corridor mapping: a case study in Manesar, Haryana, India / Manuj Dev in Annals of GIS, vol 29 n° 1 (January 2023)  

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Prototype-guided multitask adversarial network for cross-domain LiDAR point clouds semantic segmentation / Zhimin Yuan in IEEE Transactions on geoscience and remote sensing, vol 61 n° 1 (January 2023)  

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Rapid mapping of seismic intensity assessment using ground motion data calculated from early aftershocks selected by GIS spatial analysis / Huaiqun Zhao in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

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A real-time algorithm for continuous navigation in intelligent transportation systems using LiDAR-Gyroscope-Odometer integration / Tarek Hassan in Journal of applied geodesy, vol 17 n° 1 (January 2023)  

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Remote 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)  

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Semi-supervised label propagation for multi-source remote sensing image change detection / Fan Hao in Computers & geosciences, vol 170 (January 2023)  

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Sensing urban soundscapes from street view imagery / Tianhong Zhao in Computers, Environment and Urban Systems, vol 99 (January 2023)  

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A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band / Xinjie Liu in Remote sensing of environment, vol 284 (January 2023)  

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Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)  

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Solid waste mapping based on very high resolution remote sensing imagery and a novel deep learning approach / Bowen Niu in Geocarto international, vol 38 n° 1 ([01/01/2023])  

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Spatial distribution analysis of seismic activity based on GMI, LMI, and LISA in China / Ziyi Cao in Open geosciences, vol 14 n° 1 (January 2023)  

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Spatiotemporal accuracy evaluation and errors analysis of global VTEC maps using a simulation technique / Jian Lin in GPS solutions, vol 27 n° 1 (January 2023)  

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Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)  

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The 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)  

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Tree height-growth trajectory estimation using uni-temporal UAV laser scanning data and deep learning / Stefano Puliti in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)  

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Tree position estimation from TLS data using hough transform and robust least-squares circle fitting / Maja Michałowska in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)  

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Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data / Ying Quan in GIScience and remote sensing, vol 60 n° 1 (2023)  

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UAV DTM acquisition in a forested area – comparison of low-cost photogrammetry (DJI Zenmuse P1) and LiDAR solutions (DJI Zenmuse L1) / Martin Štroner in European journal of remote sensing, vol 56 n° 1 (2023)  

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Understanding public perspectives on fracking in the United States using social media big data / Xi Gong in Annals of GIS, vol 29 n° 1 (January 2023)  

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Wavelet-like denoising of GNSS data through machine learning. Application to the time series of the Campi Flegrei volcanic area (Southern Italy) / Rolando Carbonari in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

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Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models / Saadia Sultan Wahlaa in Geocarto international, vol 37 n° 27 ([20/12/2022])  

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Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery / Yuxin Wang in Science of the total environment, vol 853 (December 2022)  

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Consistency assessment of multi-date PlanetScope imagery for seagrass percent cover mapping in different seagrass meadows / Pramaditya Wicaksono in Geocarto international, vol 37 n° 27 ([20/12/2022])  

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Eco-environment and coupling coordination and quantification of urbanization in Yangtze River delta considering spatial non-stationarity / Yaqiu Zhang in Geocarto international, vol 37 n° 27 ([20/12/2022])  

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Geospatial modelling of overlapping habitats for identification of tiger corridor networks in the Terai Arc landscape of India / Nupur Rautela in Geocarto international, vol 37 n° 27 ([20/12/2022])  

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Interactive 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)  

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Above ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy / Mauro Maesano in iForest, biogeosciences and forestry, vol 15 n° 6 (December 2022)  

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Assessment of camera focal length influence on canopy reconstruction quality / Martin Denter in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)  

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Automatic registration method of multi-source point clouds based on building facades matching in urban scenes / Yumin Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 12 (December 2022)  

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Automatic registration of point cloud and panoramic images in urban scenes based on pole matching / Yuan Wang in International journal of applied Earth observation and geoinformation, vol 115 (December 2022)  

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