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Binary space partitioning visibility tree for polygonal and environment light rendering / Hiroki Okuno in The Visual Computer, vol 37 n° 9 - 11 (September 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 9 - 11 (September 2021) . - pp 2499 - 2511 Titre : Binary space partitioning visibility tree for polygonal and environment light rendering Type de document : Article/Communication Auteurs : Hiroki Okuno, Auteur ; Kei Iwasaki, Auteur Année de publication : 2021 Article en page(s) : pp 2499 - 2511 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arbre BSP [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] éclairage [Termes IGN] éclairement lumineux [Termes IGN] équation intégrale [Termes IGN] intensité lumineuse [Termes IGN] ombre [Termes IGN] polygone [Termes IGN] réflectance [Termes IGN] visibilité (optique) Résumé : (auteur) In this paper, we present a geometric approach to render shadows for physically based materials under polygonal light sources. Direct illumination calculation from a polygonal light source involves the triple product integral of the lighting, the bidirectional reflectance distribution function (BRDF), and the visibility function over the polygonal domain, which is computation intensive. To achieve real-time performance, work on polygonal light shading exploits analytical solutions of boundary integrals along the edges of the polygonal light at the cost of lacking shadowing effects. We introduce a hierarchical representation for the precomputed visibility function to retain the merits of closed-form solutions for boundary integrals. Our method subdivides the polygonal light into a set of polygons visible from a point to be shaded. Experimental results show that our method can render complex shadows with a GGX microfacet BRDF from polygonal light sources at interactive frame rates. In addition, our visibility representation can be easily incorporated into environment lighting. Numéro de notice : A2021-644 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-021-02181-8 Date de publication en ligne : 14/06/2021 En ligne : https://doi.org/10.1007/s00371-021-02181-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98345 [article]

A new small area estimation algorithm to balance between statistical precision and scale / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 97 (May 2021)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 97 (May 2021) . - n° 102303 Titre : A new small area estimation algorithm to balance between statistical precision and scale Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Jean-Pierre Renaud , Auteur ; Ankit Sagar , Auteur ; Olivier Bouriaud , Auteur Année de publication : 2021 Projets : LUE / Université de Lorraine, DIABOLO / Packalen, Tuula, ARBRE/CHM-era / Jolly, Anne Article en page(s) : n° 102303 Note générale : bibliographie This research was funded by The French Environmental Management Agency (ADEME), grant number 16-60-C0007. The methods and algorithms for processing photogrammetric data were supported by DIABOLO project from the European Union’s Horizon 2020 research and innovation program under grant agreement No 633464, as well as CHM-ERA project from the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Ankit Sagar received the financial support of the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE, through the project Impact DeepSurf. Langues : Anglais (eng) Descripteur : [Termes IGN] arbre BSP [Termes IGN] capital sur pied [Termes IGN] données auxiliaires [Termes IGN] données de terrain [Termes IGN] estimation bayesienne [Termes IGN] inventaire forestier national (données France) [Termes IGN] réduction d'échelle [Termes IGN] seuillage [Termes IGN] surface terrière [Vedettes matières IGN] Sylviculture Résumé : (auteur) Combining national forest inventory (NFI) data with auxiliary information allows downscaling and improving the precision of NFI estimates for small domains, where normally too few field plots are available to produce reliable estimates. In most situations, small domains represent administrative units that could greatly vary in size and forested area. In small and poorly sampled domains, the precision of estimates often drop below expected standards. To tackle this issue, we introduce a downscaling algorithm generating the smallest possible groups of domains satisfying prescribed sampling density and estimation error. The binary space partitioning algorithm recursively divides the population of domains in two groups while the prescribed precision conditions are fulfilled. The algorithm was tested on two major forest attributes (i.e. growing stock and basal area) in an area of 7,500 km2 dominated by hardwood forests in the centre of France. The estimation domains consisted in 157 municipalities. The field data included 819 NFI plots surveyed during a 5 years period. The auxiliary data consisted in 48 metrics derived from a forest map, photogrammetric models and Landsat images. A model-assisted framework was used for estimation. For each forest attribute, the best model was selected using a best-subset approach using a Bayesian Information Criteria. The retained models explained 58% and 41% of the observed variance for the growing stocks and basal areas respectively. The performance of the algorithm was evaluated using a minimum of 3 NFI points per domain and estimation errors varying from 10 to 50%. For a target estimation error set to 10%, the algorithm led to a limited number of estimation domains ( The algorithm provides a flexible estimation framework for small area estimation. The key advantages of the approach are relying on its capacity to produce estimations based on a preselected precision threshold and to produce results over the whole area of interest, avoiding areas without any estimates. The algorithm could also be used on any kind of polygon layers (not only administrative ones), provided that the field sampling design enable estimation. This makes the proposed algorithm a convenient tool notably for decision makers and forest managers. Numéro de notice : A2021-067 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2021.102303 Date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.jag.2021.102303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96992 [article]

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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 2994 - 3006 Titre : A point cloud feature regularization method by fusing judge criterion of field force Type de document : Article/Communication Auteurs : Xijiang Chen, Auteur ; Qing Liu, Auteur ; Kegen Yu, Auteur Année de publication : 2020 Article en page(s) : pp 2994 - 3006 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse vectorielle [Termes IGN] arbre BSP [Termes IGN] détection de contours [Termes IGN] échantillonnage [Termes IGN] extraction de traits caractéristiques [Termes IGN] matrice de covariance [Termes IGN] modèle numérique de surface [Termes IGN] modélisation du bâti [Termes IGN] niveau de gris (image) [Termes IGN] plus proche voisin, algorithme du [Termes IGN] reconstruction d'objet [Termes IGN] semis de points [Termes IGN] spline cubique [Termes IGN] traitement d'image [Termes IGN] transformation de Hough [Termes IGN] Wuhan (Chine) Résumé : (auteur) Point cloud boundary is an important part of the surface model. The traditional feature extraction method has slow speed and low efficiency and only achieves the boundary feature points. Hence, the point cloud feature regularization is proposed to obtain the boundary lines based on the fast extraction of feature points in this article. First, an improved $k$ - $d$ tree method is used to search the $k$ neighbors of sampling point. Then, the sampling point and its $k$ neighbors are used as the reference points set to fit a microcut plane and project to the plane. The local coordinate system is established on the microcut plane to convert 3-D into 2-D. The boundary feature points are identified by judging criterion of field force and then are sorted and connected according to the vector deflected angle and distance. Finally, the boundary lines are smoothed by the improved cubic B-spline fitting method. Experiments show that the proposed method can extract the boundary feature points quickly and efficiently, and the mean error of boundary lines is 0.0674 mm and the standard deviation is 0.0346 mm, which has high precision. This proposed method was also successfully applied to feature extraction and boundary fitting of Xinyi teaching building of the Wuhan University of Technology. Numéro de notice : A2020-230 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946326 Date de publication en ligne : 16/12/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2946326 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94968 [article]

Fast computation of distances in a tree / Marc Pierrot-Deseilligny (2020)    

Public Titre : Fast computation of distances in a tree Titre original : Calcul rapide de distances dans un arbre Type de document : Article/Communication Auteurs : Marc Pierrot-Deseilligny , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2020 Importance : 8 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Algorithmique [Termes IGN] arbre (mathématique) [Termes IGN] distance (mathématique) Résumé : (Auteur) Computation of distances between two submits of a tree is an operation that occurs in some pattern recognition problem. When this operation has to be done thousands of times on millions of trees, the linear standard algorithms in OpN q for each pair may be a bottleneck to the global computation. This note present recursive spliting method with a complexity of OplogpN qq on each pair in worst case, and Op1q in average on all pair, once a pre-computation OpN logpN qq has been done on the whole tree. A commented C++ implementation is published as a companion to this note. Numéro de notice : P2020-004 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Preprint nature-HAL : Préprint DOI : sans Date de publication en ligne : 05/05/2020 En ligne : https://hal.science/hal-02563859 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95036

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Spatial data management in apache spark: the GeoSpark perspective and beyond / Jia Yu in Geoinformatica, vol 23 n° 1 (January 2019)  

Public [article]  inGeoinformatica > vol 23 n° 1 (January 2019) . - pp 37 - 78 Titre : Spatial data management in apache spark: the GeoSpark perspective and beyond Type de document : Article/Communication Auteurs : Jia Yu, Auteur ; Zongsi Zhang, Auteur ; Mohamed Sarwat, Auteur Année de publication : 2019 Article en page(s) : pp 37 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse comparative [Termes IGN] Apache (serveur) [Termes IGN] arbre k-d [Termes IGN] arbre quadratique [Termes IGN] arbre-R [Termes IGN] données massives [Termes IGN] Hadoop [Termes IGN] index spatial [Termes IGN] performance [Termes IGN] Spark [Termes IGN] traitement réparti Résumé : (auteur) The paper presents the details of designing and developing GeoSpark, which extends the core engine of Apache Spark and SparkSQL to support spatial data types, indexes, and geometrical operations at scale. The paper also gives a detailed analysis of the technical challenges and opportunities of extending Apache Spark to support state-of-the-art spatial data partitioning techniques: uniform grid, R-tree, Quad-Tree, and KDB-Tree. The paper also shows how building local spatial indexes, e.g., R-Tree or Quad-Tree, on each Spark data partition can speed up the local computation and hence decrease the overall runtime of the spatial analytics program. Furthermore, the paper introduces a comprehensive experiment analysis that surveys and experimentally evaluates the performance of running de-facto spatial operations like spatial range, spatial K-Nearest Neighbors (KNN), and spatial join queries in the Apache Spark ecosystem. Extensive experiments on real spatial datasets show that GeoSpark achieves up to two orders of magnitude faster run time performance than existing Hadoop-based systems and up to an order of magnitude faster performance than Spark-based systems. Numéro de notice : A2019-225 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-0330-9 Date de publication en ligne : 22/10/2018 En ligne : http://dx.doi.org/10.1007/s10707-018-0330-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92621 [article]

A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks / Shaohua Wang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

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Space-time tree ensemble for action recognition and localization / Shugao Ma in International journal of computer vision, vol 126 n° 2-4 (April 2018)  

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A spatio-temporal index for aerial full waveform laser scanning data / Debra F. Laefer in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

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Nouvelle méthode en cascade pour la classification hiérarchique multi-temporelle ou multi-capteur d'images satellitaires haute résolution / Ihsen Hedhli in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)  

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Manuel d'analyse spatiale / Vincent Loonis (2018)    

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Etude et méthodes d'intégration et d'interaction de données 3D complexes type "nuages de points" vers un web SIG / Victor Lambert (2017) 

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The D-FCM partitioned D-BSP tree for massive point cloud data access and rendering / Yi Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)  

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Morphing linear features based on their entire structures / Min Deng in Transactions in GIS, vol 19 n° 5 (October 2015)  

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Street environment change detection from mobile laser scanning point clouds / Wen Xiao in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)  

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The TM-RTree: an index on generic moving objects for range queries / Jianqiu Xu in Geoinformatica, vol 19 n° 3 (July - September 2015)  

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