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Geographically masking addresses to study COVID-19 clusters / Walid Houfaf-Khoufaf in Cartography and Geographic Information Science, vol inconnu (2023)  

Public [article]  inCartography and Geographic Information Science > vol inconnu (2023) Titre : Geographically masking addresses to study COVID-19 clusters Type de document : Article/Communication Auteurs : Walid Houfaf-Khoufaf, Auteur ; Guillaume Touya , Auteur Année de publication : 2023 Projets : 1-Pas de projet / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] adresse postale [Termes IGN] anonymisation [Termes IGN] carte sanitaire [Termes IGN] classification barycentrique [Termes IGN] surveillance sanitaire [Termes IGN] traitement de données localisées Résumé : (auteur) The spatio-temporal analysis of cases is a good way an epidemic, and the recent COVID-19 pandemic unfortunately generated a huge amount of data. But analysing this raw data, with for instance the address of the people who contracted COVID-19, raises some privacy issues, and geomasking is necessary to preserve both people privacy and the spatial accuracy required for analysis. This paper proposes dierent geomasking techniques adapted to this COVID-19 data. Methods: Different techniques are adapted from the literature, and tested on a synthetic dataset mimicking the COVID-19 spatio-temporal spreading in Paris and a more rural nearby region. Theses techniques are assessed in terms of k-anonymity and cluster preservation. Results: Three adapted geomasking techniques are proposed: aggregation, bimodal gaussian perturbation, and simulated crowding. All three can be useful in different use cases, but the bimodal gaussian perturbation is the overall best techniques, and the simulated crowding is the most promising one, provided some improvements are introduced to avoid points with a low k-anonymity. Conclusions: It is possible to use geomasking techniques on addresses of people who caught COVID-19, while preserving the important spatial patterns. Numéro de notice : A2023-084 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers RSquare Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.1977709 Date de publication en ligne : 08/10/2021 En ligne : https://doi.org/10.1080/15230406.2021.1977709 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96857 [article]

A machine learning approach for detecting rescue requests from social media / Zheye Wang in ISPRS International journal of geo-information, vol 11 n° 11 (November 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 11 (November 2022) . - n° 570 Titre : A machine learning approach for detecting rescue requests from social media Type de document : Article/Communication Auteurs : Zheye Wang, Auteur ; Nina S.N. Lam, Auteur ; Mingxuan Sun, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 570 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] apprentissage automatique [Termes IGN] code postal [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] données issues des réseaux sociaux [Termes IGN] Etats-Unis [Termes IGN] filtrage d'information [Termes IGN] secours d'urgence [Termes IGN] tempête [Termes IGN] terminologie [Termes IGN] Twitter Résumé : (auteur) Hurricane Harvey in 2017 marked an important transition where many disaster victims used social media rather than the overloaded 911 system to seek rescue. This article presents a machine-learning-based detector of rescue requests from Harvey-related Twitter messages, which differentiates itself from existing ones by accounting for the potential impacts of ZIP codes on both the preparation of training samples and the performance of different machine learning models. We investigate how the outcomes of our ZIP code filtering differ from those of a recent, comparable study in terms of generating training data for machine learning models. Following this, experiments are conducted to test how the existence of ZIP codes would affect the performance of machine learning models by simulating different percentages of ZIP-code-tagged positive samples. The findings show that (1) all machine learning classifiers except K-nearest neighbors and Naïve Bayes achieve state-of-the-art performance in detecting rescue requests from social media; (2) using ZIP code filtering could increase the effectiveness of gathering rescue requests for training machine learning models; (3) machine learning models are better able to identify rescue requests that are associated with ZIP codes. We thereby encourage every rescue-seeking victim to include ZIP codes when posting messages on social media. This study is a useful addition to the literature and can be helpful for first responders to rescue disaster victims more efficiently. Numéro de notice : A2022-846 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11110570 Date de publication en ligne : 16/11/2022 En ligne : https://doi.org/10.3390/ijgi11110570 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102081 [article]

How much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems / Ali Javidaneh in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 27 p. Titre : How much do we learn from addresses? On the syntax, semantics and pragmatics of addressing systems Type de document : Article/Communication Auteurs : Ali Javidaneh, Auteur ; Farid Karimipour, Auteur ; Negar Alinaghi, Auteur Année de publication : 2020 Article en page(s) : 27 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] adresse postale [Termes IGN] appariement d'adresses [Termes IGN] cognition [Termes IGN] géocodage par adresse postale [Termes IGN] modèle orienté agent [Termes IGN] représentation mentale spatiale [Termes IGN] segmentation sémantique [Termes IGN] structure syntaxique Résumé : (auteur) An address is a specification that refers to a unique location on Earth. While there has been a considerable amount of research on the syntactic structure of addressing systems in order to evaluate and improve their quality, aspects of semantics and pragmatics have been less explored. An address is primarily associated by humans to the elements of their spatial mental representations, but may also influence their spatial knowledge and activities through the level of detail it provides. Therefore, it is not only important how addressing components are structured, but it is also of interest to study their meaning as well as the pragmatics in relation to an interpreting agent. This article studies three forms of addresses (i.e., structured as in Austria, semi-formal as in Japan, and descriptive as in Iran) under the principles of semiotics (i.e., through levels of syntax, semantics, and pragmatics). Syntax is discussed through formal definitions of the addressing systems, while semantics and pragmatics are assessed through an agent-based model to explore how they influence spatial knowledge acquisition and growth. Numéro de notice : A2020-302 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050317 Date de publication en ligne : 11/05/2020 En ligne : https://doi.org/10.3390/ijgi9050317 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95142 [article]

Generating vague neighbourhoods through data mining of passive web data / Paul Brindley in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 3-4 (March - April 2018) . - pp 498 - 523 Titre : Generating vague neighbourhoods through data mining of passive web data Type de document : Article/Communication Auteurs : Paul Brindley, Auteur ; James Goulding, Auteur ; M. L. Wilson, Auteur Année de publication : 2018 Article en page(s) : pp 498 - 523 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] adresse postale [Termes IGN] base de données d'adresses [Termes IGN] exploration de données géographiques [Termes IGN] extraction automatique [Termes IGN] limite indéterminée [Termes IGN] recherche d'information géographique [Termes IGN] structure sociale [Termes IGN] voisinage (relation topologique) [Termes IGN] zone urbaine Résumé : (Auteur) Neighbourhoods have been described as ‘the building blocks of public services society’. Their subjective nature, however, and the resulting difficulties in collecting data, means that in many countries there are no officially defined neighbourhoods either in terms of names or boundaries. This has implications not only for policy but also business and social decisions as a whole. With the absence of neighbourhood boundaries many studies resort to using standard administrative units as proxies. Such administrative geographies, however, often have a poor fit with those perceived by residents. Our approach detects these important social boundaries by automatically mining the Web en masse for passively declared neighbourhood data within postal addresses. Focusing on the United Kingdom (UK), this research demonstrates the feasibility of automated extraction of urban neighbourhood names and their subsequent mapping as vague entities. Importantly, and unlike previous work, our process does not require any neighbourhood names to be established a priori. Numéro de notice : A2018-043 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1400549 En ligne : https://doi.org/10.1080/13658816.2017.1400549 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89264 [article]

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Generative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 3 (March 2018) Titre : Generative street addresses from satellite imagery Type de document : Article/Communication Auteurs : İlke Demir, Auteur ; Forest Hughes, Auteur ; Aman Raj, Auteur ; Kaunil Dhruv, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] adresse postale [Termes IGN] apprentissage profond [Termes IGN] extraction du réseau routier [Termes IGN] graphe [Termes IGN] image satellite [Termes IGN] route Résumé : (Auteur) We describe our automatic generative algorithm to create street addresses from satellite images by learning and labeling roads, regions, and address cells. Currently, 75% of the world’s roads lack adequate street addressing systems. Recent geocoding initiatives tend to convert pure latitude and longitude information into a memorable form for unknown areas. However, settlements are identified by streets, and such addressing schemes are not coherent with the road topology. Instead, we propose a generative address design that maps the globe in accordance with streets. Our algorithm starts with extracting roads from satellite imagery by utilizing deep learning. Then, it uniquely labels the regions, roads, and structures using some graph- and proximity-based algorithms. We also extend our addressing scheme to (i) cover inaccessible areas following similar design principles; (ii) be inclusive and flexible for changes on the ground; and (iii) lead as a pioneer for a unified street-based global geodatabase. We present our results on an example of a developed city and multiple undeveloped cities. We also compare productivity on the basis of current ad hoc and new complete addresses. We conclude by contrasting our generative addresses to current industrial and open solutions. Numéro de notice : A2018-095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030084 En ligne : https://doi.org/10.3390/ijgi7030084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89507 [article]

Géomatique et géo-décisionnel appliqués au Référentiel des territoires du département de l’Hérault / Stanislas Cheptou (2017)

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Une adresse normalisée sur toute la France / Pierre Clergeot in Géomètre, n° 2104 (juin 2013)

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Adresses et numéros de parcelles : le décret qui précise / Françoise de Blomac in SIG la lettre, n° 125 (mars 2011)

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Pour une politique nationale de la donnée Adresse / Association française pour l'information géographique (2011) 

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Création d'un référentiel d'adresses des quartiers prioritaires de la politique de la ville à partir de la BD Adresse / I. Nefzi (2010)

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Construction of the planar partition postal code map based on cadastral registration / F. Penninga in Geoinformatica, vol 9 n° 2 (June - August 2005)  

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SIG-LR [SIG-Languedoc-Roussillon] 2004 : une journée très dense ! / Françoise de Blomac in SIG la lettre, n° 57 (mai 2004)

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Les données de référence espace public, adresse et parcelle : analyse et perspectives en matière de réglementation, Volume 1. Mémoire / J.G. Rolland (2004)

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Les données de référence espace public, adresse et parcelle : analyse et perspectives en matière de réglementation, Volume 2. Annexes / J.G. Rolland (2004)

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On the accuracy of TIGER-type geocoded address data in relation to cadastral and census areal units / J.H. Ratcliffe in International journal of geographical information science IJGIS, vol 15 n° 5 (july 2001)  

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