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Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery / Nicolas David in Remote sensing letters, vol 12 n° 10 (October 2021)  

Public [article]  inRemote sensing letters > vol 12 n° 10 (October 2021) . - pp 970 - 982 Titre : Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery Type de document : Article/Communication Auteurs : Nicolas David , Auteur ; Sébastien Giordano , Auteur ; Clément Mallet , Auteur Année de publication : 2021 Projets : MAESTRIA / Mallet, Clément Article en page(s) : pp 970 - 982 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] chaîne de traitement [Termes IGN] France (administrative) [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] politique agricole commune [Termes IGN] surveillance agricole Résumé : (auteur) In this paper, we propose an operational solution for the yearly classification of crop parcels at national scale (namely France) for Land Parcel Identification System updating, under the Common Agricultural Policy (CAP) umbrella. Our pipeline is based on the ι2 open-source framework and fed with both time series of Sentinel-1 radar and Sentinel-2 optical images, with complementary contributions. Three conceivable scenarios are investigated with two sets of nomenclatures (17 and 43 classes): early, on-line, and late classifications. Experiments performed on 2017 show very satisfactory results (82–97%), locally almost on-par with state-of-the-art deep-based methods. We can conclude our framework offers a strong basis for country-scale operational deployment for 2020+CAP. Numéro de notice : A2021-600 Affiliation des auteurs : UGE-LaSTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/2150704X.2021.1950940 En ligne : https://doi.org/10.1080/2150704X.2021.1950940 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98222 [article]

Assessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, Vol 36 n° 17 ([21/09/2021])  

Public [article]  inGeocarto international > Vol 36 n° 17 [21/09/2021] . - pp 1960 - 1992 Titre : Assessment and prediction of urban growth for a mega-city using CA-Markov model Type de document : Article/Communication Auteurs : Veerendra Yadav, Auteur ; Sanjay Kumar Ghosh, Auteur Année de publication : 2021 Article en page(s) : pp 1960 - 1992 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] classification par maximum de vraisemblance [Termes IGN] coefficient de corrélation [Termes IGN] croissance urbaine [Termes IGN] mégalopole [Termes IGN] modèle de Markov [Termes IGN] modèle de simulation [Termes IGN] OpenStreetMap [Termes IGN] Tamil Nadu (Inde ; état) [Termes IGN] urbanisation Résumé : (auteur) Most of World’s mega-cities are facing high population growth. To accommodate the increased population, new built-up areas are emerging at the periphery or fringe area of cities. New urbanisation has an adverse impact on the existing Land Use Land Cover (LULC). To monitor and analyse the impact of urbanisation, LULC change analysis has become the primary concern for LULC monitoring agencies. In this study, LULC change of Chennai has been assessed during 1981–2011 using temporal Landsat data. All the dataset has been classified using Maximum Likelihood Classifier (MLC). Quantitative change in LULC has been carried out using Pearson’s Correlation Coefficient, Transition Potential Matrix, Land Use Dynamic Degree and MLC. Further, spatio-temporal change analysis has been performed using Post-classification comparison technique. Cellular Automata-Markov (CA-Markov) Model used for LULC prediction for 2021–2051. The urban area of Chennai has increased from 40.74 to 103.52 km2 during 1981–2011. Further, LULC prediction using the CA-Markov model shows that the urban area of Chennai district may increase from 103.52 to 140.79 km2 during 2011–2051. During the period 1981–2051, the prediction model indicates that mostly vegetation and barren land will be converted into urban land class. Numéro de notice : A2021-692 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2019.1690054 date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1690054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98507 [article]

The impact of landscape characteristics on the performance of upscaled maps / Peijun Sun in Geocarto international, Vol 36 n° 17 ([21/09/2021])  

Public [article]  inGeocarto international > Vol 36 n° 17 [21/09/2021] . - pp 1905 - 1922 Titre : The impact of landscape characteristics on the performance of upscaled maps Type de document : Article/Communication Auteurs : Peijun Sun, Auteur ; Russell G. Congalton, Auteur Année de publication : 2021 Article en page(s) : pp 1905 - 1922 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] analyse du paysage [Termes IGN] carte de base [Termes IGN] logiciel de simulation [Termes IGN] mise à l'échelle [Termes IGN] paysage [Termes IGN] précision cartographique Résumé : (auteur) Upscaled maps, as necessary data sources, have drawn much attention to fill data gaps or match the spatial resolution of pre-existing projects. Nevertheless, it remains a challenging task to quantitatively assess the impact of landscape characteristics on the upscaled maps. To simplify the investigation, three characteristics: fragmentation, number of classes and major class impact factor (MCIF), were selected. We utilized SIMMAP to produce categorical maps for generating base maps with different landscape characteristics. The Majority Rule Based algorithm was then used to produce upscaled maps at 11 different spatial resolutions. The findings indicate that the combined effect of landscape patterns greatly impacts upscaling accuracy. This important result should be carefully considered when developing the next generation of upscaling techniques. Overall, extending our understanding of the impacts of landscape characteristics is a critical step forward improving upscaling accuracy and therefore, our use of these maps. Numéro de notice : A2021-693 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1678681 date de publication en ligne : 18/10/2019 En ligne : https://doi.org/10.1080/10106049.2019.1678681 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98511 [article]

Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)  

Public [article]  inComputers & geosciences > vol 155 (October 2021) . - n° 104860 Titre : Landslide susceptibility prediction based on image semantic segmentation Type de document : Article/Communication Auteurs : Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aléa [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] effondrement de terrain [Termes IGN] image captée par drone [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] segmentation sémantique Résumé : (auteur) Numéro de notice : A2021-683 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104860 date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408 [article]

On the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review / Rafael Ramirez Eudave in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 10 (October 2021) . - pp 2047 - 2077 Titre : On the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review Type de document : Article/Communication Auteurs : Rafael Ramirez Eudave, Auteur ; Tiago Miguel Ferreira, Auteur Année de publication : 2021 Article en page(s) : pp 2047 - 2077 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] centre urbain [Termes IGN] CityGML [Termes IGN] codage [Termes IGN] format Industry foudation classes IFC [Termes IGN] géoréférencement [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] monument historique [Termes IGN] prévention des risques [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité Résumé : (auteur) The use of digital representations of physical objects allows to simulate phenomena and predict behaviours. The representativeness of a model is based on the congruency between the code, the survey and the modelling strategies. In terms of physical space, two important approaches are the Geographical Information Systems (GIS) and Building Information Modelling (BIM). GIS approach is intended to code environmental information based on geographical references. BIM approach is intended to code buildings in terms of their components, generating parametric descriptions. For historic buildings, BIM extends to the so-called Historical BIM models (HBIM). Together, these strategies allow coding territorial-scale entities, such as historical centres. An application for these models would be the simulation of risk situations, leading to vulnerability analysis. Despite the existence of GIS-BIM-HBIM integration examples, most of their procedures are designed to fit with a specific case study, which questions the suitability of a general coding framework. This paper presents a vision of state-of-the-art technologies and strategies for coding, surveying and model historical centres, with emphases on the analysis of urban vulnerability and risk. Finally, we propose a general comprehensive framework on the convergences of GIS-BIM-HBIM technologies and successful practices. Numéro de notice : A2021-657 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1844208 date de publication en ligne : 09/11/2020 En ligne : https://doi.org/10.1080/13658816.2020.1844208 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98393 [article]

Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Early detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery / Run Yu in Forest ecology and management, vol 497 (1 October 2021)  

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3D map creation using crowdsourced GNSS data / Terence Lines in Computers, Environment and Urban Systems, vol 89 (September 2021)  

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Automatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

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Combining photogrammetric and bathymetric data to build a 3D model of a canal tunnel / Emmanuel Moisan in Photogrammetric record, Vol 36 n° 175 (September 2021)  

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A deep translation (GAN) based change detection network for optical and SAR remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

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A framework for ecosystem service assessment using GIS interoperability standards / Martin Lacayo in Computers & geosciences, vol 154 (September 2021)  

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Indoor space as the basis for modelling of buildings in a 3D Cadastre / Jernej Tekavec in Survey review, Vol 53 n° 380 (September 2021)  

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Les journées de la Recherche IGN 2021 / Anonyme in Géomatique expert, n° 135 (septembre 2021)

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