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Urban growth analysis and simulations using cellular automata and geo-informatics: comparison between Almaty and Astana in Kazakhstan / Aigerim Ilyassova in Geocarto international, vol 36 n° 5 ([15/03/2021])  

Public [article]  inGeocarto international > vol 36 n° 5 [15/03/2021] . - pp 520 - 539 Titre : Urban growth analysis and simulations using cellular automata and geo-informatics: comparison between Almaty and Astana in Kazakhstan Type de document : Article/Communication Auteurs : Aigerim Ilyassova, Auteur ; Lakshmi Kantakumar, Auteur ; Doreen S. Boyd, Auteur Année de publication : 2021 Article en page(s) : pp 520 - 539 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] croissance urbaine [Termes IGN] dynamique spatiale [Termes IGN] étalement urbain [Termes IGN] image Landsat [Termes IGN] Kazakhstan [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] planification urbaine [Termes IGN] simulation spatiale [Termes IGN] système d'information géographique Résumé : (auteur) In this research, the SLEUTH urban growth model is calibrated and validated for the first time to post Soviet Union cities. The aim of the study is to monitor, assess, simulate and compare the spatiotemporal urban growth dynamics and spatial patterns of the two largest cities Almaty and Astana using free remote sensing data. The urban expansion metrics and SLEUTH model are used to assess the urban growth dynamics. Though the capital has been moved to Astana from Almaty in 1998, Almaty is still developing faster than Astana. The urban growth simulation results from SLEUTH show Astana will surpass the urban growth of Almaty to emerge as the largest city in Kazakhstan by 2030. Astana may experience more leapfrog and ribbon developments. In Almaty, the urban growth may likely to take place in north and north-west parts. Numéro de notice : A2021-251 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1618923 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1618923 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97273 [article]

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Increasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data / Giles M. Foody 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 : Increasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data Type de document : Article/Communication Auteurs : Giles M. Foody, Auteur ; Linda M. See, Auteur ; Steffen Fritz, Auteur ; Inian Moorthy, Auteur ; Christoph Perger, Auteur ; Christian Schill, Auteur ; Doreen S. Boyd, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] cartographie collaborative [Termes IGN] données localisées des bénévoles [Termes IGN] modèle de classe latente [Termes IGN] occupation du sol [Termes IGN] pondération [Termes IGN] précision de la classification Résumé : (Auteur) Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling. Numéro de notice : A2018-093 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030080 Date de publication en ligne : 25/02/2018 En ligne : https://doi.org/10.3390/ijgi7030080 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89505 [article]

Integrating user needs on misclassification error sensitivity into image segmentation quality assessment / Hugo Costa in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 6 (June 2015) . - pp 451 - 459 Titre : Integrating user needs on misclassification error sensitivity into image segmentation quality assessment Type de document : Article/Communication Auteurs : Hugo Costa, Auteur ; Giles M. Foody, Auteur ; Doreen S. Boyd, Auteur Année de publication : 2015 Article en page(s) : pp 451 - 459 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des besoins [Termes IGN] classification dirigée [Termes IGN] connaissance thématique [Termes IGN] objet géographique [Termes IGN] occupation du sol [Termes IGN] segmentation d'image [Termes IGN] similitude [Termes IGN] utilisateur Résumé : (auteur) Commonly the assessment of the quality of image segmentations used in object-based land cover classification uses the geometric match between the derived segmentation and a reference dataset. This paper argues that a more appropriate assessment of a segmentation is to also consider the thematic content of the objects generated. This allows the assessment to be tailored to the needs of the specific user. A new method for image segmentation quality assessment is described, which combines a traditional geometric-only method with the thematic similarity index (TSI), a metric that expresses the degree of thematic quality of objects from a user’s perspective. The perspectives of two users (a wolf researcher and a general user of land cover information) were adopted in a case study to demonstrate the new method. The results show that the new method allowed the production of more accurate land cover classifications for the two users than the use of the geometric-only approach Numéro de notice : A2015-976 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.6.451 En ligne : https://doi.org/10.14358/PERS.81.6.451 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80059 [article]

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Updating topographic mapping in Great Britain using imagery from high-resolution satellite sensors / David A. Holland in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 3 (May 2006)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 60 n° 3 (May 2006) . - pp 212 - 223 Titre : Updating topographic mapping in Great Britain using imagery from high-resolution satellite sensors Type de document : Article/Communication Auteurs : David A. Holland, Auteur ; Doreen S. Boyd, Auteur ; P. Marshall, Auteur Année de publication : 2006 Article en page(s) : pp 212 - 223 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] caméra numérique [Termes IGN] détection de changement [Termes IGN] Grande-Bretagne [Termes IGN] image à haute résolution [Termes IGN] mise à jour cartographique [Termes IGN] organisme cartographique national Résumé : (Auteur) Topographic mapping from remotely sensed imagery is carried out all over the world, using data from an ever-growing number of sensors. Traditional film cameras are gradually being replaced by digital cameras and scanners, but most topographic mapping still relies on sensors based on airborne platforms. This paper examines the potential of high resolution satellite sensor imagery for the updating of topographic mapping, from the perspective of a national mapping agency. After a review of satellites capable of being used for this purpose, several examples of mapping projects are presented. The paper ends with a look to the future, and asks whether satellite imagery can ever replace airborne (digital or analogue) photography for the makers of maps. It is concluded that high resolution satellite sensor imagery does have a role to play in the update of topographic mapping, especially in the detection of change. Copyright ISPRS Numéro de notice : A2006-231 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.02.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27958 [article]

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