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An integrated method for DEM simplification with terrain structural features and smooth morphology preserved / Wenhao Yu in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)
[article]
Titre : An integrated method for DEM simplification with terrain structural features and smooth morphology preserved Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Yifan Zhang, Auteur ; Tinghua Ai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 273 - 295 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse structurelle
[Termes IGN] arête
[Termes IGN] carte géomorphologique
[Termes IGN] filtrage statistique
[Termes IGN] ligne caractéristique
[Termes IGN] limite de terrain
[Termes IGN] modèle numérique de surface
[Termes IGN] visualisation multiéchelleRésumé : (auteur) As a key focus of cartography and terrain analysis, the simplification of a digital elevation model (DEM) is used to preserve the pattern features of the terrain surface while suppressing its details over multiple scales. Statistical filtering and structural analysis methods are commonly used for this process. The structural analysis method performs well in identifying terrain structural edges, while it tends to discard the smooth morphology of a terrain surface. In addition, the filter that aims to reduce noise on a surface may over-smooth the terrain structural edges. Therefore, to preserve both the terrain structural edges and smooth morphology, we propose to combine the techniques of statistical filtering and structural analysis. Specifically, all the critical elevation points and structural edges are first detected from the DEM surface by using the structural analysis method. Then, the iterative guided normal filter is used to smooth the generalized DEM with the guidance of the structure of the original surface. After this process, the terrain structure is retained in the smooth surface of the DEM. The experimental results with a real-world dataset show that our method can inherit the merits of both structural analysis and statistical filter in preserving terrain features for multi-scale DEM representations. Numéro de notice : A2021-038 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1772479 Date de publication en ligne : 29/05/2020 En ligne : https://doi.org/10.1080/13658816.2020.1772479 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96747
in International journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 273 - 295[article]Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis / Marco Helbich in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)
[article]
Titre : Spatial eigenvector filtering for spatiotemporal crime mapping and spatial crime analysis Type de document : Article/Communication Auteurs : Marco Helbich, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2015 Article en page(s) : pp 134 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] carte thématique
[Termes IGN] données spatiotemporelles
[Termes IGN] filtrage statistique
[Termes IGN] Houston (Texas)
[Termes IGN] infraction
[Termes IGN] valeur propreRésumé : (auteur) Spatial and spatiotemporal analyses are exceedingly relevant to determine criminogenic factors. The estimation of Poisson and negative binomial models (NBM) is complicated by spatial autocorrelation. Therefore, first, eigenvector spatial filtering (ESF) is introduced as a method for spatiotemporal mapping to uncover time-invariant crime patterns. Second, it is demonstrated how ESF is effectively used in criminology to invalidate model misspecification, i.e., residual spatial autocorrelation, using a nonviolent crime dataset for the metropolitan area of Houston, Texas, over the period 2005–2010. The results suggest that local and regional geography significantly contributes to the explanation of crime patterns. Furthermore, common space-time eigenvectors selected on an annual basis indicate striking spatiotemporal patterns persisting over time. The findings about the driving forces behind Houston’s crime show that linear and nonlinear, spatially filtered, NBMs successfully absorb latent autocorrelation and, therefore, prevent parameter estimation bias. The consideration of a spatial filter also increases the explanatory power of the regressions. It is concluded that ESF can be highly recommended for the integration in spatial and spatiotemporal modeling toolboxes of law enforcement agencies. Numéro de notice : A2015-238 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2014.893839 En ligne : https://doi.org/10.1080/15230406.2014.893839 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76495
in Cartography and Geographic Information Science > Vol 42 n° 2 (April 2015) . - pp 134 - 148[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2015021 RAB Revue Centre de documentation En réserve L003 Disponible Occlusion-based methodology for the classification of Lidar Data / A.F. Habib in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)
[article]
Titre : Occlusion-based methodology for the classification of Lidar Data Type de document : Article/Communication Auteurs : A.F. Habib, Auteur ; Y. Chang, Auteur ; D.C. Lee, Auteur Année de publication : 2009 Article en page(s) : pp 703 - 712 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] angle nadiral
[Termes IGN] changement d'utilisation du sol
[Termes IGN] détection d'objet
[Termes IGN] détection de partie cachée
[Termes IGN] données lidar
[Termes IGN] extraction automatique
[Termes IGN] filtrage statistique
[Termes IGN] interpolation
[Termes IGN] lasergrammétrie
[Termes IGN] modèle numérique de surface
[Termes IGN] relief
[Termes IGN] semis de pointsRésumé : (Auteur) Lidar systems have been widely adopted for the acquisition of dense and accurate topographic data over extended areas. The level of detail and the quality of the collected point cloud motivated the research community to investigate the possibility of automatic object extraction from such data. Prior knowledge of the terrain surface will improve the performance of object detection and extraction procedures. In this paper, a new strategy for automatic terrain extraction from lidar data is presented. The proposed strategy is based on the fact that sudden elevation changes, which usually correspond to non-ground objects, will cause relief displacements in perspective views. The introduced relief displacements will occlude neighboring ground points. To start the process, we generate a digital surface model (DSM) from the irregular lidar points using an interpolation procedure. The presence of sudden-elevation changes and the resulting occlusions can be discerned by sequentially checking the off-nadir angles to the lines of sight connecting the DSM cells and a pre-defined set of synthesized projection centers. Detected occlusions are then used to identify the occluding points, which are hypothesized to be non-ground points. Surface roughness and discontinuities together with inherent noise in the point cloud will lead to some false hypotheses. Therefore, we use a statistical filter to remove these false hypotheses. The performance of the algorithm has been evaluated and verified using both simulated and real lidar datasets with varying levels of complexity. Copyright ASPRS Numéro de notice : A2009-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.6.703 En ligne : https://doi.org/10.14358/PERS.75.6.703 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29892
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 6 (June 2009) . - pp 703 - 712[article]Reconstruction of backscatter and extinction coefficients in Lidar: a stochastic filtering approach / José M. Bioucas-Dias in IEEE Transactions on geoscience and remote sensing, vol 42 n° 2 (February 2004)
[article]
Titre : Reconstruction of backscatter and extinction coefficients in Lidar: a stochastic filtering approach Type de document : Article/Communication Auteurs : José M. Bioucas-Dias, Auteur ; J.M.N. Leitao, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 443 - 456 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] champ aléatoire de Markov
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] données lidar
[Termes IGN] filtrage statistique
[Termes IGN] filtre de Kalman
[Termes IGN] processus stochastiqueRésumé : (Auteur) Reconstruction of the backscatter and extinction coefficients is a crucial step in many quantitative remote sensing applications, such as radar, light detection and ranging (lidar), and sonar. We present a novel stochastic filtering approach for the estimation of the backscatter and extinction coefficients from time-range elastic-backscatter lidar data. The Bayesian perspective is adopted; we take as prior a causal first-order autoregressive Gauss-Markov random field tailored to enforce smoothness on time and range dimensions. By using a reduced-order state-space representation of the prior, we derive a suboptimal stochastic filter that recursively computes the backscatter and extinction coefficients at each range-time inversion cell. The estimator is a kind of adaptive extended Kalman filter, being efficient from the computational point of view. A set of experiments illustrates the effectiveness of the proposed approach, namely its advantage over the classical Klett deterministic approach. Numéro de notice : A2004-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.817216 En ligne : https://doi.org/10.1109/TGRS.2003.817216 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26666
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 2 (February 2004) . - pp 443 - 456[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-04021 RAB Revue Centre de documentation En réserve L003 Disponible Navigation inertielle optimale et filtrage statistique / P. Faurre (1971)
Titre : Navigation inertielle optimale et filtrage statistique Type de document : Monographie Auteurs : P. Faurre, Auteur Editeur : Paris : Dunod Année de publication : 1971 Collection : Méthodes mathématiques de l'informatique Importance : 446 p. Format : 16 x 25 cm Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] accéléromètre
[Termes IGN] calculateur
[Termes IGN] centrale inertielle
[Termes IGN] filtrage statistique
[Termes IGN] filtre de Kalman
[Termes IGN] filtre de Wiener
[Termes IGN] force d'inertie
[Termes IGN] gyroscope
[Termes IGN] navigation inertielle
[Termes IGN] système linéaireIndex. décimale : 30.64 GPS et centrales inertielles Numéro de notice : 48928 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=58893