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Development of a single-wavelength airborne bathymetric LiDAR: System design and data processing / Kai Guo in ISPRS Journal of photogrammetry and remote sensing, vol 185 (March 2022)
[article]
Titre : Development of a single-wavelength airborne bathymetric LiDAR: System design and data processing Type de document : Article/Communication Auteurs : Kai Guo, Auteur ; Qingquan Li, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 62 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] forme d'onde pleine
[Termes IGN] Hainan (Chine)
[Termes IGN] lever bathymétrique
[Termes IGN] lidar bathymétrique
[Termes IGN] semis de points
[Termes IGN] signal lidar
[Termes IGN] traitement de donnéesRésumé : (auteur) Airborne laser bathymetry (ALB) is employed to measure shallow depth water by using a high sampling rate and point density. Thus, the problems of using traditional detection methods in inaccessible areas can be avoided. This study focuses on practical solutions for receiving echo signals, identifying target echoes, and integrating land and underwater terrain point cloud data in coastal environments. Optimization of the system design and its data processing scheme is undertaken to improve the performance of the receiving system based on a single-band ALB system developed by the authors at Shenzhen University. A flight experiment over eastern Hainan Island was conducted, during which the effectiveness of the proposed strategy was verified. Finally, the technical characteristics of the self-developed system are summarized to provide a reliable reference source for the subsequent industrialization and production of related marine light detection and ranging (LiDAR) laser systems. Numéro de notice : A2022-134 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.011 Date de publication en ligne : 29/01/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99730
in ISPRS Journal of photogrammetry and remote sensing > vol 185 (March 2022) . - pp 62 - 84[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022031 SL Revue Centre de documentation Revues en salle Disponible 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)
[article]
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 Early warning of COVID-19 hotspots using human mobility and web search query data / Takahiro Yabe in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Early warning of COVID-19 hotspots using human mobility and web search query data Type de document : Article/Communication Auteurs : Takahiro Yabe, Auteur ; Kota Tsubouchi, Auteur ; Yoshihide Sekimoto, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101747 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aide à la localisation
[Termes IGN] analyse de données
[Termes IGN] analyse de groupement
[Termes IGN] épidémie
[Termes IGN] exploration de données
[Termes IGN] maladie virale
[Termes IGN] mobilité urbaine
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] requête spatiale
[Termes IGN] ressources web
[Termes IGN] surveillance sanitaire
[Termes IGN] Tokyo (Japon)Résumé : (auteur) COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical interventions (e.g., lockdowns) through population density analysis. However, predicting the locations of potential outbreak occurrence is difficult using mobility data alone. Meanwhile, web search queries have been shown to be good predictors of the disease spread. In this study, we utilize a unique dataset of human mobility trajectories (GPS traces) and web search queries with common user identifiers (> 450 K users), to predict COVID-19 hotspot locations beforehand. More specifically, web search query analysis is conducted to identify users with high risk of COVID-19 contraction, and social contact analysis was further performed on the mobility patterns of these users to quantify the risk of an outbreak. Our approach is empirically tested using data collected from users in Tokyo, Japan. We show that by integrating COVID-19 related web search query analytics with social contact networks, we are able to predict COVID-19 hotspot locations 1–2 weeks beforehand, compared to just using social contact indexes or web search data analysis. This study proposes a novel method that can be used in early warning systems for disease outbreak hotspots, which can assist government agencies to prepare effective strategies to prevent further disease spread. Human mobility data and web search query data linked with common IDs are used to predict COVID-19 outbreaks. High risk social contact index captures both the contact density and COVID-19 contraction risks of individuals. Real world data was collected from 200 K individual users in Tokyo during the COVID-19 pandemic. Experiments showed that the index can be used for microscopic outbreak early warning. Numéro de notice : A2022-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101747 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101747 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99637
in Computers, Environment and Urban Systems > vol 92 (March 2022) . - n° 101747[article]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 the height datum geopotential value of Hong Kong using the combined Global Geopotential Models and GNSS/levelling data / Panpan Zhang in Survey review, vol 54 n° 383 (March 2022)
[article]
Titre : Estimation of the height datum geopotential value of Hong Kong using the combined Global Geopotential Models and GNSS/levelling data Type de document : Article/Communication Auteurs : Panpan Zhang, Auteur ; Lifeng Bao, Auteur ; Dongmei Guo, Auteur Année de publication : 2022 Article en page(s) : pp 106 - 116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] données GNSS
[Termes IGN] données GOCE
[Termes IGN] données GRACE
[Termes IGN] données topographiques
[Termes IGN] Earth Gravity Model 2008
[Termes IGN] géoïde altimétrique
[Termes IGN] Hong-Kong
[Termes IGN] MNS SRTM
[Termes IGN] modèle de géopotentiel local
[Termes IGN] nivellement
[Termes IGN] système de référence altimétriqueRésumé : (auteur) The advent of the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Exploration (GOCE) has changed the global contribution in the determination of high-accuracy global geopotential models (GGMs). In this paper, a spectral expansion method is used to determine the combined GGMs, using the high-resolution EGM2008 model and residual terrain model (RTM) to effectively bridge the spectral gap between the satellite and terrestrial data. The accuracy of the combined GGMs shows improvement compared with GOCE/GRACE-based GGMs and EGM2008 in determining the geopotential of the Hong Kong Principal Datum (HKPD). As a result of the DIR_R5/EGM2008/RTM model and GNSS/levelling, the geopotential value of HKPD is estimated to be 62,636,860.52 m2s−2 with respect to the global geoid W0 = 62,636,853.4 m2s−2. Therefore, the vertical offset between the HKPD and global geoid is about −72.8 cm, which means that the HKPD is 72.8 cm below the global height datum. Numéro de notice : A2022-238 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2021.1884794 Date de publication en ligne : 17/02/2021 En ligne : https://doi.org/10.1080/00396265.2021.1884794 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100162
in Survey review > vol 54 n° 383 (March 2022) . - pp 106 - 116[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])PermalinkEvaluating 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])PermalinkEvaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China / Longfei Xie in Canadian Journal of Forest Research, Vol 52 n° 3 (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)PermalinkFlood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)PermalinkGIS-based employment availabilities by mode of transport in Kuwait / S. Alkheder in Applied geomatics, vol 14 n° 1 (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])PermalinkUltrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach / Linyuan Li in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)PermalinkUnderstanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea / Yang Xu in Computers, Environment and Urban Systems, vol 92 (March 2022)PermalinkUsing street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)PermalinkAboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkMulti-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkMulti-species individual tree segmentation and identification based on improved mask R-CNN and UAV imagery in mixed forests / Chong Zhang in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkSimulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkSimulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model / Hasan Aksoy in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkAnalysis of factors affecting adoption of volunteered geographic information in the context of national spatial data infrastructure / Munir Ahmad in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)PermalinkAnalysis of spatio-temporal changes in forest biomass in China / Weiyi Xu in Journal of Forestry Research, vol 33 n° 1 (February 2022)PermalinkApplication of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkBuilding footprint extraction in Yangon city from monocular optical satellite image using deep learning / Hein Thura Aung in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkA combination of convolutional and graph neural networks for regularized road surface extraction / Jingjing Yan in IEEE Transactions on geoscience and remote sensing, vol 60 n° 2 (February 2022)Permalink