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Interoperable information model for geovisualization and interaction in XR environments / Daeil Seo in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1323 - 1352 Titre : Interoperable information model for geovisualization and interaction in XR environments Type de document : Article/Communication Auteurs : Daeil Seo, Auteur ; Byounghyun Yoo, Auteur Année de publication : 2020 Article en page(s) : pp 1323 - 1352 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] géonavigateur [Termes descripteurs IGN] immersion [Termes descripteurs IGN] interopérabilité [Termes descripteurs IGN] logiciel de navigation [Termes descripteurs IGN] réalité augmentée [Termes descripteurs IGN] réalité mixte [Termes descripteurs IGN] réalité virtuelle [Termes descripteurs IGN] système d'information [Termes descripteurs IGN] toile d'araignée mondiale [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Since the vision of a Digital Earth (DE) was introduced in 1998, geo-browsers seem to have nearly fulfilled this vision. Virtual reality (VR) for visualizing the DE provides an immersive user experience in a mirror world. Location-based augmented reality (AR) browsers have been introduced and provide content according to user and environmental contexts. However, the content models of traditional geo-browsers and AR browsers have very limited interoperability, because they are described in application-specific formats using their domain standards. Each application is vertically integrated from content to application. The Web is an interoperable and open platform, and hundreds of millions of users are already using it to create and share content. To envision DE browsers for cross-reality (XR) environments that concurrently support geovisualization as well as VR, AR, and mixed-reality environments, we propose a DE content model based on Web standards and architecture that provides full interoperability and openness for XR browsers as a first-class citizen of the Web. This is expected to improve the DE content development efficiency by fully using the Web content development environment. Numéro de notice : A2020-304 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1706739 date de publication en ligne : 03/01/2020 En ligne : https://doi.org/10.1080/13658816.2019.1706739 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95146 [article]

Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1451 - 1474 Titre : Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax Type de document : Article/Communication Auteurs : Jose Morales, Auteur ; Alfred Stein, Auteur ; Johannes Flacke, Auteur ; Jaap Zevenbergen, Auteur Année de publication : 2020 Article en page(s) : pp 1451 - 1474 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse de la valeur [Termes descripteurs IGN] analyse syntaxique [Termes descripteurs IGN] cartographie statistique [Termes descripteurs IGN] estimation quantitative [Termes descripteurs IGN] évaluation foncière [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] Guatemala [Termes descripteurs IGN] krigeage [Termes descripteurs IGN] méthode du maximum de vraisemblance (estimation) [Termes descripteurs IGN] modèle conceptuel de données localisées [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] régression [Termes descripteurs IGN] système d'information foncière Résumé : (auteur) Spatial information of land values is fundamental for planners and policy makers. Individual appraisals are costly, explaining the need for predictive modelling. Recent work has investigated using Space Syntax to analyse urban access and explain land values. However, the spatial dependence of urban land markets has not been addressed in such studies. Further, the selection of meaningful variables is commonly conducted under non-spatialized modelling conditions. The objective of this paper is to construct a land value map using a geostatistical approach using Space Syntax and a spatialized variable selection. The methodology is applied in Guatemala City. We used an existing dataset of residential land value appraisals and accessibility metrics. Regression-kriging was used to conduct variable selection and derive a model for spatial prediction. The prediction accuracy is compared with a multivariate regression. The results show that a spatialized variable selection yields a more parsimonious model with higher prediction accuracy. New insights were found on how Space Syntax explains land value variability when also modelling the spatial dependence. Space Syntax can contribute with relevant spatialized information for predictive land value modelling purposes. Finally, the spatial modelling framework facilitates the production of spatial information of land values that is relevant for planning practice. Numéro de notice : A2020-306 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1725014 date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1725014 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95148 [article]

Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata / Yaqian Zhai in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1475 - 1499 Titre : Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata Type de document : Article/Communication Auteurs : Yaqian Zhai, Auteur ; Yao Yao, Auteur ; Qingfeng Guan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1475 - 1499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] aide à la décision [Termes descripteurs IGN] automate cellulaire [Termes descripteurs IGN] changement d'occupation du sol [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] morphologie [Termes descripteurs IGN] parcelle cadastrale [Termes descripteurs IGN] petite échelle [Termes descripteurs IGN] planification urbaine [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] voisinage (topologie) Résumé : (auteur) Vector-based cellular automata (VCA) models have been applied in land use change simulations at fine scales. However, the neighborhood effects of the driving factors are rarely considered in the exploration of the transition suitability of cells, leading to lower simulation accuracy. This study proposes a convolutional neural network (CNN)-VCA model that adopts the CNN to extract the high-level features of the driving factors within a neighborhood of an irregularly shaped cell and discover the relationships between multiple land use changes and driving factors at the neighborhood level. The proposed model was applied to simulate urban land use changes in Shenzhen, China. Compared with several VCA models using other machine learning methods, the proposed CNN-VCA model obtained the highest simulation accuracy (figure-of-merit = 0.361). The results indicated that the CNN-VCA model can effectively uncover the neighborhood effects of multiple driving factors on the developmental potential of land parcels and obtain more details on the morphological characteristics of land parcels. Moreover, the land use patterns of 2020 and 2025 under an ecological control strategy were simulated to provide decision support for urban planning. Numéro de notice : A2020-307 Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1711915 date de publication en ligne : 14/01/2020 En ligne : https://doi.org/10.1080/13658816.2020.1711915 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95149 [article]

Developing shopping and dining walking indices using POIs and remote sensing data / Yingbin Deng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 22 p. Titre : Developing shopping and dining walking indices using POIs and remote sensing data Type de document : Article/Communication Auteurs : Yingbin Deng, Auteur ; Yingwei Yan, Auteur ; Yichun Xie, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] achat [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] distance [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] loisir [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] sport [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] trajet Résumé : (auteur) Walking is one of the most commonly promoted traveling methods and is garnering increasing attention. Many indices/scores have been developed by scholars to measure the walkability in a local community. However, most existing walking indices/scores involve urban planning-oriented, local service-oriented, regional accessibility-oriented, and physical activity-oriented walkability assessments. Since shopping and dining are two major leisure activities in our daily lives, more attention should be given to the shopping or dining-oriented walking environment. Therefore, we developed two additional walking indices that focus on shopping or dining. The point of interest (POI), vegetation coverage, water coverage, distance to bus/subway station, and land surface temperature were employed to construct walking indices based on 50-meter street segments. Then, walking index values were categorized into seven recommendation levels. The field verification illustrates that the proposed walking indices can accurately represent the walking environment for shopping and dining. The results in this study could provide references for citizens seeking to engage in activities of shopping and dining with a good walking environment. Numéro de notice : A2020-310 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060366 date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060366 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95157 [article]

Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data / Sugandh Chauhan in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 138 - 151 Titre : Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data Type de document : Article/Communication Auteurs : Sugandh Chauhan, Auteur ; Roshanak Darvishzadeh, Auteur ; Mirco Boschetti, Auteur ; Andrew Nelson, Auteur Année de publication : 2020 Article en page(s) : pp 138 - 151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] agrégation [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] blé (céréale) [Termes descripteurs IGN] courbure [Termes descripteurs IGN] gestion prévisionnelle [Termes descripteurs IGN] image Radarsat [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] Italie [Termes descripteurs IGN] matrice de confusion [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] surveillance agricole Résumé : (auteur) Crop lodging - the bending of crop stems from their upright position or the failure of root-soil anchorage systems - is a major yield-reducing factor in wheat and causes deterioration of grain quality. The severity of lodging can be measured by a lodging score (LS)- an index calculated from the crop angle of inclination (CAI) and crop lodged area (LA). LS is difficult and time consuming to measure manually meaning that information on lodging occurrence and severity is limited and sparse. Remote sensing-based estimates of LS can provide more timely, synoptic and reliable information on crop lodging across vast areas. This information could improve estimates of crop yield losses, inform insurance loss adjusters and influence management decisions for subsequent seasons. This research - conducted in the 600 ha wheat sown area in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy - evaluated the performance of RADARSAT-2 and Sentinel-1 data to discriminate and classify lodging severity based on field measured LS. We measured temporal crop status characteristics related to lodging (e.g. lodged area, CAI, crop height) and collected relevant meteorological data (wind speed and rainfall) throughout May-June 2018. These field measurements were used to distinguish healthy (He) wheat from lodged wheat with different degrees of lodging severity (moderate, severe and very severe). We acquired multi-incidence angle (FQ8-27° and FQ21-41°) RADARSAT-2 and Sentinel-1 (40°) images and derived multiple metrics from them to discriminate and classify lodging severity. As a part of our data exploration, we performed a correlation analysis between the image-based metrics and LS. Next, a multi-temporal discriminant analysis approach, including a partial least squares (PLS-DA) method, was developed to classify lodging severities. We used the area under the curve-receiver operating characteristics (AUC-ROC) and confusion matrices to evaluate the accuracy of the PLS-DA classification models. Results show that (1) volume scattering components were highly correlated with LS at low incidence angles while double and surface scattering was more prevalent at high incidence angles; (2) lodging severity was best classified using low incidence angle R-FQ8 data (overall accuracy 72%) and (3) the Sentinel-1 data-based classification model was able to correctly identify 60% of the lodging severity cases in the study site. The results from this first study on classifying lodging severity using satellite-based SAR platforms suggests that SAR-based metrics can capture a substantial proportion of the observed variation in lodging severity, which is important in the context of operational crop lodging assessment in particular, and sustainable agriculture in general. Numéro de notice : A2020-276 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.012 date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.012 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95087 [article]

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