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From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping / Tian Lan in Journal of Geovisualization and Spatial Analysis, vol 6 n° 2 (December 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 2 (December 2022) . - n° 22 Titre : From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping Type de document : Article/Communication Auteurs : Tian Lan, Auteur ; Oliver O'Brien, Auteur ; James Cheshire, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] carte interactive [Termes IGN] cartographie sensible [Termes IGN] culture [Termes IGN] données démographiques [Termes IGN] données socio-économiques [Termes IGN] impact social [Termes IGN] récit [Termes IGN] Royaume-Uni [Termes IGN] sciences sociales [Termes IGN] web mapping Mots-clés libres : narrative mapping Résumé : (auteur) Modern web mapping techniques have enhanced the storytelling capability of cartography. In this paper, we present our recent development of a web mapping facility that can be used to extract interesting stories and unique insights from a diverse range of socio-economic and demographic variables and indicators, derived from a variety of datasets. We then use three curated narratives to show that online maps are effective ways of interactive storytelling and visualisation, which allow users to tailor their own story maps. We discuss the reasons for the revival of the recent attention to narrative mapping and conclude that our interactive web mapping facility powered by data assets can be employed as an accessible and powerful toolkit, to identify geographic patterns of various social and economic phenomena by social scientists, journalists, policymakers, and the public. Numéro de notice : A2022-541 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-022-00117-x Date de publication en ligne : 16/06/2022 En ligne : https://doi.org/10.1007/s41651-022-00117-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101105 [article]

PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna / Xingxing Li in Journal of geodesy, vol 96 n° 10 (October 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 10 (October 2022) . - n° 65 Titre : PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Hao Wang, Auteur ; Xin Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 65 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Androïd [Termes IGN] antenne [Termes IGN] données GNSS [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement ponctuel précis [Termes IGN] précision du positionnement [Termes IGN] rapport signal sur bruit [Termes IGN] résolution d'ambiguïté [Termes IGN] téléphone intelligent Résumé : (auteur) The release of GNSS raw measurement acquisition privileges on Google Android makes high-precision positioning on the low-cost smart devices possible. However, influenced by the inner linearly polarized antenna, the pseudorange and carrier phase noises of the smart device are much larger than those of the geodetic receiver. As a result, only meter-level positioning accuracy can be obtained based on the smart device’s original antenna. With the external survey-grade antenna enhancing, positioning accuracy of decimeter-level to centimeter-level can be obtained, but it still takes tens of minutes to converge and fix the ambiguity. However, a PPP-RTK method is proposed to achieve rapid integer ambiguity resolution (AR) with the regional atmospheric augmentation. In this contribution, an uncombined PPP-RTK model is developed using Android GNSS raw measurements with an external antenna, after carefully considering the coexistence of single- and dual-frequency signals on smart devices. A low-cost helical antenna is employed to enhance the Android GNSS data as it is capable to provide observation data of comparable quality with the survey-grade antenna and has several advantages of low weight, low-power consumption, and portability. Moreover, a series of quality control methods in the data preprocessing and ambiguity resolution are proposed for smartphone-based PPP-RTK to enhance the positioning results. To validate the proposed method, several experiments are carried out using raw measurements of Xiaomi Mi8 with an external low-cost helical antenna. The result shows that the ambiguity fixed solution can be obtained within 3 min in both static and kinematic scenarios. After the ambiguity resolution, centimeter-level positioning accuracy of (1.7, 2.1, 4.1) cm and (7.2, 4.5, 8.1) cm for the east, north, and up components can be achieved in static and kinematic scenarios, respectively. Numéro de notice : A2022-735 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01661-6 Date de publication en ligne : 27/09/2022 En ligne : https://doi.org/10.1007/s00190-022-01661-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101706 [article]

A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])  

Public [article]  inGeocarto international > vol 37 n° 20 [20/09/2022] . - pp 5832 - 5850 Titre : A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers Type de document : Article/Communication Auteurs : Qasim Khan, Auteur ; Muhammad Usman Liaqat, Auteur ; Mohamed Mostafa Mohamed, Auteur Année de publication : 2022 Article en page(s) : pp 5832 - 5850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage automatique [Termes IGN] aquifère [Termes IGN] ArcGIS [Termes IGN] classification bayesienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] eau souterraine [Termes IGN] Emirats Arabes Unis [Termes IGN] estimation par noyau [Termes IGN] nitrate [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité Résumé : (auteur) Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This study proposes a novel method of mapping groundwater vulnerability using machine learning algorithms. In this study, point extraction method was used to extract point values from a grid of 646 points of seven raster layer in the Al Khatim study area of United Arab Emirates. These extracted values were classified based on nitrate concentration threshold of 50 mg/L into two classes. Machine learning models were developed, using depth to water (D), recharge (R), aquifer media (A), soil media (S), topography (T), vadose zone (I) and hydraulic conductivity (C), on the basis of nitrate class. Classified ‘groundwater vulnerability class values’ were trained using 10-fold cross-validation, using four machine learning models which were Random Forest, Support Vector Machine, Naïve Bayes and C4. 5. Accuracy showed the model developed by Random Forest gained highest accuracy of 93%. Four groundwater vulnerability maps were developed from machine learning classifiers and was compared with base method of DRASTIC index. The efficiency, accuracy and validity of machine learning based models were evaluated based on Receiver Operating Characteristics (ROC) curve and Precision-Recall curve (PRC). The results proved that machine learning is an efficient tool to access, analyze and map groundwater vulnerability. Numéro de notice : A2022-716 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1923833 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1923833 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101641 [article]

Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 191 (September 2022) . - pp 277 - 289 Titre : Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine Type de document : Article/Communication Auteurs : Luis Carrasco, Auteur ; Go Fujita, Auteur ; Kensuke Kito, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 277 - 289 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] cartographie historique [Termes IGN] détection de changement [Termes IGN] Google Earth [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-TM [Termes IGN] indice de végétation [Termes IGN] Japon [Termes IGN] phénologie [Termes IGN] photographie aérienne [Termes IGN] réflectance de surface [Termes IGN] rizière [Termes IGN] signature spectrale Résumé : (auteur) Mapping the expansion or reduction of rice fields is fundamental for food and water security, greenhouse gas emission accounting, and environmental management. The historical mapping of rice fields with satellite images is challenging because of the limited availability of remote sensing and training data from past decades. The use of phenology-based algorithms has been proposed for mapping rice fields because they can take advantage of rice fields’ characteristic spectral signature during the transplanting phase and do not need training data. However, in order to employ phenology-based algorithms effectively for the historical rice mapping of large areas, we need to incorporate automatized methods able to deal with non-usable data (e.g., cloud cover) and with spatial inconsistencies in the number of available images for each pixel. Here we propose the combination of a pixel-based, phenological algorithm with the temporal aggregation of all available Landsat images to produce national level historical maps of rice fields in Japan from the 1980s onwards. We used temporally aggregated metrics (median, percentiles, etc.), derived from spectral indices of a large number of images within the Google Earth Engine, to minimize the issue of inconsistent image availability and reduce the effects of outliers in phenology-based algorithms. We produced seven rice field maps, for the periods 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, 2010–14, and 2015–19. The overall map accuracies ranged from 83% to 95% when validated with visually interpreted aerial photography. We detected a 23% decrease in the area of rice fields at a country level, although the changes varied greatly among prefectures. Here we present the first freely available historical rice field maps of Japan from the 1980s onwards, together with the source code, and a web application that enables the exploration of the maps and data relating to the derived rice field area changes. The application of temporal aggregation is promising for dealing with the gap-filling of large amounts of satellite data, reducing the issue of data outliers and providing an effective use of the historical Landsat archive for phenology-based crop detection algorithms. Our maps could greatly help researchers, conservationists and policymakers studying the drivers and consequences of rice field changes, and our methods could be extrapolated to map rice fields at large scales in other regions of the world. Numéro de notice : A2022-665 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.07.018 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.07.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101527 [article]

Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? / Paul Courbon in XYZ, n° 172 (septembre 2022)

Public [article]  inXYZ > n° 172 (septembre 2022) . - pp 27 - 30 Titre : Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? Type de document : Article/Communication Auteurs : Paul Courbon, Auteur ; Dominique Foubert, Auteur Année de publication : 2022 Article en page(s) : pp 27 - 30 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] BD Topo [Termes IGN] carte Top 25 [Termes IGN] carte topographique [Termes IGN] courbe de niveau [Termes IGN] falaise [Termes IGN] géoportail [Termes IGN] représentation cartographique [Termes IGN] rocher [Termes IGN] visualisation cartographique Résumé : (Auteur) La rédaction de XYZ est alertée par Paul Courbon, l'un de nos auteurs, sur le rendu des zones rocheuses sur les nouvelles cartes IGN. Il compare les anciennes cartes au 1/25 000 et les nouvelles, que l’on peut également visualiser sur le Géoportail. Excès d’automatisation du dessin, mauvais choix dans les méthodes de restitution, économie des moyens en personnels, Paul essaie de comprendre pourquoi il ne retrouve plus les falaises d’antan, leurs courbes de niveau et leurs ombrages. Sollicité, Dominique Foubert, ancien topographe du service de la cartographie à l’IGN, nous déroule des pistes de réflexion liées à l’historique de la production des cartes. Effectivement, grâce à l’appui de Christophe Pécot, les souvenirs se précisent et Dominique nous explique “pourquoi et comment” on en est arrivé là. Numéro de notice : A2022-673 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Date de publication en ligne : 01/09/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101637 [article]

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