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A spatial model of cognitive distance in cities / Ed Manley in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2316 - 2338 Titre : A spatial model of cognitive distance in cities Type de document : Article/Communication Auteurs : Ed Manley, Auteur ; Gabriele Filomena, Auteur ; Panos Mavros, Auteur Année de publication : 2021 Article en page(s) : pp 2316 - 2338 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cognition [Termes IGN] distance [Termes IGN] espace euclidien [Termes IGN] espace urbain [Termes IGN] modélisation spatiale [Termes IGN] morphologie urbaine [Termes IGN] perception [Termes IGN] positionnement statique [Termes IGN] représentation mentale spatiale [Termes IGN] système d'information urbain Résumé : (auteur) Spatial cognition is fundamental to the behaviour and activity of humans in urban space. Humans perceive their environments with systematic biases and errors, and act upon these perceptions, which in turn form urban patterns of activity. These perceptions are influenced by a multitude of factors, many of them relating to the static urban form. Yet much of geographic analysis ignores the influence of urban form, instead referring most commonly to the Euclidean arrangement of space. In this paper, we propose a novel spatial modelling framework for estimating cognitive distance in urban space. This framework is constructed from a wealth of research describing the effect of environmental factors on distance estimation, and produces a quantitative estimate of the effect based on standard GIS data. Unlike other cost measures, the cognitive distance estimate integrates systematically observed distortions and biases in spatial cognition. As a proof-of-concept, the framework is implemented for 26 cities worldwide using open data, producing a novel comparative measure of ‘cognitive accessibility’. The paper concludes with a discussion of the potential of this approach in analysing and modelling urban systems, and outlines areas for further research. Numéro de notice : A2021-761 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887488 Date de publication en ligne : 19/02/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98790 [article]

A vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)  

Public [article]  inComputers & geosciences > vol 156 (November 2021) Titre : A vector-based method for drainage network analysis based on LiDAR data Type de document : Article/Communication Auteurs : Fangzheng Lyu, Auteur ; Xinlin Ma, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse vectorielle [Termes IGN] Caroline du Nord (Etats-Unis) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] interpolation spatiale [Termes IGN] modèle numérique de surface [Termes IGN] réseau hydrographique [Termes IGN] semis de points Résumé : (auteur) Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. Numéro de notice : A2021-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104892 Date de publication en ligne : 24/07/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98733 [article]

Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 717 - 733 Titre : Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing Type de document : Article/Communication Auteurs : Radhika Ravi, Auteur ; Ayman Habib, Auteur Année de publication : 2021 Article en page(s) : pp 717 - 733 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] alignement des données [Termes IGN] chevauchement [Termes IGN] compensation par moindres carrés [Termes IGN] données lidar [Termes IGN] lidar mobile [Termes IGN] matrice [Termes IGN] matrice de covariance [Termes IGN] modèle de Gauss-Helmert [Termes IGN] modèle de Gauss-Markov [Termes IGN] modèle mathématique [Termes IGN] modélisation 3D [Termes IGN] pondération [Termes IGN] semis de points Résumé : (Auteur) This article proposes a solution to special least squares adjustment (LSA) models with a rank-deficient weight matrix, which are commonly encountered in geomatics. The two sources of rank deficiency in weight matrices are discussed: naturally occurring due to the inherent characteristics of LSA mathematical models and artificially induced to eliminate nuisance parameters from LSA estimation. The physical interpretation of the sources of rank deficiency is demonstrated using a case study to solve the problem of 3D line fitting, which is often encountered in geomatics but has not been addressed fully to date. Finally, some geomatics-related applications—mobile lidar system calibration, point cloud registration, and single-photo resection—are discussed along with respective experimental results, to emphasize the need to assess LSA models and their weight matrices to draw inferences regarding the effective contribution of observations. The discussion and results demonstrate the vast applications of this research in geomatics as well as other engineering domains. Numéro de notice : A2021-675 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00081R3 Date de publication en ligne : 10/01/2021 En ligne : https://doi.org/10.14358/PERS.20-00081R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98861 [article]

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New algorithms for spherical harmonic analysis of area mean values over blocks delineated by equiangular and Gaussian grids / Rong Sun in Journal of geodesy, vol 95 n° 5 (May 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 5 (May 2021) . - n° 47 Titre : New algorithms for spherical harmonic analysis of area mean values over blocks delineated by equiangular and Gaussian grids Type de document : Article/Communication Auteurs : Rong Sun, Auteur Année de publication : 2021 Article en page(s) : n° 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse harmonique [Termes IGN] grille [Termes IGN] matrice [Termes IGN] méthode des moindres carrés [Termes IGN] quadrature [Termes IGN] transformation polynomiale Résumé : (auteur) Spherical harmonic analysis is widely used in all aspects of geoscience. Exact quadrature methods are available for the spherical harmonic analysis of band-limited point values at the grid points of equiangular and Gaussian grids. However, no similarly exact quadrature methods are available for the spherical harmonic analysis of area mean values over the blocks delineated by these grids. In this study, new algorithms appropriate for the exact spherical harmonic analysis of the band-limited area mean values over the blocks delineated by equiangular and Gaussian grids are proposed. For band-limited data, precision that is between that of the least-squares estimation method and of the approximate quadrature methods can be achieved by using the new algorithms. Regarding the computational complexity, fewer operations are needed by the new methods as compared to those needed by the least-squares estimation method and the approximate quadrature methods in the preparation stage when the maximum degree of the spherical harmonic analysis is very large. Simulation experiments are performed to compare the ability to recover the spherical harmonic coefficients by using the least-squares estimation method, the approximate quadrature methods and these new algorithms from aliased data with aliasing components of realistic magnitudes. The results suggest that these new algorithms, with time complexity one order less than that of the least-squares estimation method in the solving stage, perform roughly the same as the least-squares estimation method in recovering spherical harmonic coefficients from the aliased data. Numéro de notice : A2021-488 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01495-8 Date de publication en ligne : 07/04/2021 En ligne : https://doi.org/10.1007/s00190-021-01495-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97507 [article]

Parallel computing for fast spatiotemporal weighted regression / Xiang Que in Computers & geosciences, vol 150 (May 2021)  

Public [article]  inComputers & geosciences > vol 150 (May 2021) . - n° 104723 Titre : Parallel computing for fast spatiotemporal weighted regression Type de document : Article/Communication Auteurs : Xiang Que, Auteur ; Chao Ma, Auteur ; Xiaogang Ma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104723 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] calcul matriciel [Termes IGN] étalonnage de modèle [Termes IGN] modèle de régression [Termes IGN] modélisation spatio-temporelle [Termes IGN] régression géographiquement pondérée [Termes IGN] traitement parallèle Résumé : (auteur) The Spatiotemporal Weighted Regression (STWR) model is an extension of the Geographically Weighted Regression (GWR) model for exploring the heterogeneity of spatiotemporal processes. A key feature of STWR is that it utilizes the data points observed at previous time stages to make better fit and prediction at the latest time stage. Because the temporal bandwidths and a few other parameters need to be optimized in STWR, the model calibration is computationally intensive. In particular, when the data amount is large, the calibration of STWR becomes heavily time-consuming. For example, with 10,000 points in 10 time stages, it takes about 2307 s for a single-core PC to process the calibration of STWR. Both the distance and the weighted matrix in STWR are memory intensive, which may easily cause memory insufficiency as data amount increases. To improve the efficiency of computing, we developed a parallel computing method for STWR by employing the Message Passing Interface (MPI). A cache in the MPI processing approach was proposed for the calibration routine. Also, a matrix splitting strategy was designed to address the problem of memory insufficiency. We named the overall design as Fast STWR (F-STWR). In the experiment, we tested F-STWR in a High-Performance Computing (HPC) environment with a total number of 204,611 observations in 19 years. The results show that F-STWR can significantly improve STWR's capability of processing large-scale spatiotemporal data. Numéro de notice : A2021-300 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.1016/j.cageo.2021.104723 Date de publication en ligne : 05/03/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104723 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97413 [article]

Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

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Study on offshore seabed sediment classification based on particle size parameters using XGBoost algorithm / Fengfan Wang in Computers & geosciences, vol 149 (April 2021)  

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A practical method for calculating reliable integer float estimator in GNSS precise positioning / Xianwen Yu in Survey review, Vol 53 n° 377 (February 2021)  

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Change detection of land use and land cover, using landsat-8 and sentinel-2A images / Mohammed Abdulmohsen Alhedyan (2021)  

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Hyperspectral and multispectral image fusion via graph Laplacian-guided coupled tensor decomposition / Yuanyang Bu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

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Temporal calibration and synchronization of robotic total stations for kinematic multi-sensor-systems / Tomas Thalmann in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

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Local terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

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A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)  

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A convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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A point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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