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Partitions of normalised multiple regression equations for datum transformations / Andrew Carey Ruffhead in Boletim de Ciências Geodésicas, vol 28 n° 1 ([01/03/2022])
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Titre : Partitions of normalised multiple regression equations for datum transformations Type de document : Article/Communication Auteurs : Andrew Carey Ruffhead, Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] Australie occidentale (Australie)
[Termes IGN] Grande-Bretagne
[Termes IGN] régression multiple
[Termes IGN] Slovénie
[Termes IGN] transformation de coordonnéesRésumé : (auteur) Multiple regression equations (MREs) provide an empirical direct method of transforming coordinates between geodetic datums. Since they offer a means of modelling distortions, they are capable of a more accurate fit to datum-shift datasets than more basic direct methods. MRE models of datum shifts traditionally consist of polynomials based on relative latitude and longitude. However, the limited availability of low-power terms often leads to high-power terms being included, and these are a potential cause of instability. This paper introduces three variations based on simple partitions and 2 or 4 smoothly conjoined polynomials. The new types are North/South, East/West and Four-Quadrant. They increase the availability of low-order terms, enabling distortions to be modelled with fewer side effects. Case studies in Great Britain, Slovenia and Western Australia provide examples of partitioned MREs that are more accurate than conventional MREs with the same number of terms. Numéro de notice : A2022-684 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans En ligne : https://revistas.ufpr.br/bcg/article/view/86199/46467 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101548
in Boletim de Ciências Geodésicas > vol 28 n° 1 [01/03/2022][article]Probabilistic unsupervised classification for large-scale analysis of spectral imaging data / Emmanuel Paradis in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)
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Titre : Probabilistic unsupervised classification for large-scale analysis of spectral imaging data Type de document : Article/Communication Auteurs : Emmanuel Paradis, Auteur Année de publication : 2022 Article en page(s) : n° 102675 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] analyse spectrale
[Termes IGN] classification barycentrique
[Termes IGN] classification ISODATA
[Termes IGN] classification non dirigée
[Termes IGN] classification par nuées dynamiques
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] entropie
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] Matlab
[Termes IGN] occupation du solRésumé : (auteur) Land cover classification of remote sensing data is a fundamental tool to study changes in the environment such as deforestation or wildfires. A current challenge is to quantify land cover changes with real-time, large-scale data from modern hyper- or multispectral sensors. A range of methods are available for this task, several of them being based on the k-means classification method which is efficient when classes of land cover are well separated. Here a new algorithm, called probabilistic k-means, is presented to solve some of the limitations of the standard k-means. It is shown that the new algorithm performs better than the standard k-means when the data are noisy. If the number of land cover classes is unknown, an entropy-based criterion can be used to select the best number of classes. The proposed new algorithm is implemented in a combination of R and C computer codes which is particularly efficient with large data sets: a whole image with more than 3 million pixels and covering more than 10,000 km2 can be analysed in a few minutes. Four applications with hyperspectral and multispectral data are presented. For the data sets with ground truth data, the overall accuracy of the probabilistic k-means was substantially improved compared to the standard k-means. One of these data sets includes more than 120 million pixels, demonstrating the scalability of the proposed approach. These developments open new perspectives for the large scale analysis of remote sensing data. All computer code are available in an open-source package called sentinel. Numéro de notice : A2022-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102675 Date de publication en ligne : 06/01/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102675 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99954
in International journal of applied Earth observation and geoinformation > vol 107 (March 2022) . - n° 102675[article]ReBankment : un algorithme pour déplacer les talus sur les cartes par moindres carrés / Guillaume Touya in Cartes & Géomatique, n° 247-248 (mars-juin 2022)
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Titre : ReBankment : un algorithme pour déplacer les talus sur les cartes par moindres carrés Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat
, Auteur
Année de publication : 2022 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Article en page(s) : pp 81 - 94 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Termes IGN] 1:25.000
[Termes IGN] algorithme de généralisation
[Termes IGN] carte topographique
[Termes IGN] déplacement d'objet géographique
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] implémentation (informatique)
[Termes IGN] jeu de données localisées
[Termes IGN] méthode des moindres carrés
[Termes IGN] optimisation spatiale
[Termes IGN] talus
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Même si les progrès récents en automatisation de la généralisation cartographique aident les agences de cartographie nationales à produire leurs cartes topographiques à différentes échelles de plus en plus rapidement, il existe encore des opérations de généralisation que nous ne savons pas automatiser correctement. Par exemple, les talus sont fréquemment représentés par un symbole linéaire avec des barbules représentant le sens de la pente du talus. Ce type de symbole prend de la place et nécessite d'être éloigné des symboles de routes notamment. Cet article propose un algorithme, appelé ReBankment, qui permet de déplacer automatiquement les lignes de talus. L'algorithme utilise une triangulation pour identifier les voisinages entre objets de la carte, puis une optimisation par moindres carrés de la position des points de la ligne de talus, ce qui permet un déplacement sans modifier la forme initiale de la ligne. L'article propose également des moyens pour traiter les cas complexes et les jeux de données massifs. L'algorithme est testé sur des données réelles de l'IGN France pour la généralisation de la carte au 1:25.000 Numéro de notice : A2022-800 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101903
in Cartes & Géomatique > n° 247-248 (mars-juin 2022) . - pp 81 - 94[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 021-2022011 SL Revue Centre de documentation Revues en salle Disponible ReBankment: displacing embankment lines from roads and rivers with a least squares adjustment / Guillaume Touya in International journal of cartography, vol 8 n° 1 (March 2022)
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Titre : ReBankment: displacing embankment lines from roads and rivers with a least squares adjustment Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Imran Lokhat
, Auteur
Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : pp 37 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation
[Termes IGN] compensation par moindres carrés
[Termes IGN] données topographiques
[Termes IGN] talus
[Vedettes matières IGN] GénéralisationRésumé : (auteur) While the recent progress on automated generalisation helped National Mapping Agencies to derive topographic maps more and more quickly, there are still practical cartographic issues that require attention. For instance, embankments are represented with line symbols showing the slope of the embankment. This paper proposes an automated algorithm called ReBankment that displaces the embankment lines from the roads and rivers that overlap the embankment symbol. ReBankment is based on a triangulation to identify neighbourhoods, and on a least squares adjustment to displace and distort the embankment line while preserving its shape. This paper also proposes how to handle complex cases and scaling issues. ReBankment is tested on real data from a 1:25k scale topographic map. Numéro de notice : A2022-006 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2021.1972787 Date de publication en ligne : 18/10/2021 En ligne : https://doi.org/10.1080/23729333.2021.1972787 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98838
in International journal of cartography > vol 8 n° 1 (March 2022) . - pp 37 - 53[article]Road network generalization method constrained by residential areas / Zheng Lyu in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)
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Titre : Road network generalization method constrained by residential areas Type de document : Article/Communication Auteurs : Zheng Lyu, Auteur ; Qun Sun, Auteur ; Jingzhen Ma, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] 1:50.000
[Termes IGN] carte routière
[Termes IGN] connexité (topologie)
[Termes IGN] corrélation
[Termes IGN] programmation par contraintes
[Termes IGN] quartier
[Termes IGN] réseau routier
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone (aménagement du territoire)
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Residential areas and road networks have a strong geographical correlation. The development of a single geographical feature could destroy the geographical correlation. It is necessary to establish collaborative generalization models suitable for multiple features. However, existing road network generalization methods for mapping purposes do not fully consider residential areas. Compared with road networks, residential areas have a higher priority in cartographic generalization. In this regard, this study proposes a road network generalization method constrained by residential areas. First, the roads and settlements obtained from clustering residential areas were classified. Next, the importance of the settlements was evaluated and certain settlements were selected as the control features. Subsequently, a geographical network with the settlements as the nodes was built, and the traffic paths between adjacent settlements were searched. Finally, redundant paths between the settlements were simplified, and the visual continuity and topological connectivity were checked. The data of a 1:50,000 road network and residential areas were used as the experimental data. The experimental results demonstrated that the proposed method preserves the overall structure and relative density characteristics of the road network, as well as the geographical correlation between the road network and residential areas. Numéro de notice : A2022-184 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11030159 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.3390/ijgi11030159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99890
in ISPRS International journal of geo-information > vol 11 n° 3 (March 2022) . - n° 159[article]A search step optimization in an ambiguity function-based GNSS precise positioning / Sławomir Cellmer in Survey review, vol 54 n° 383 (March 2022)
PermalinkSimultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 / Nima Pahlevan in Remote sensing of environment, vol 270 (March 2022)
PermalinkTowards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) / Langning Huo in Remote sensing of environment, vol 270 (March 2022)
PermalinkTraffic sign three-dimensional reconstruction based on point clouds and panoramic images / Minye Wang in Photogrammetric record, vol 37 n° 177 (March 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 geodetic signature of large aquifer systems: Example of the Ozark plateaus in central United States / Stacy Larochelle in Journal of geophysical research : Solid Earth, vol 127 n° 3 (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)
PermalinkVisual vs internal attention mechanisms in deep neural networks for image classification and object detection / Abraham Montoya Obeso in Pattern recognition, vol 123 (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])
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