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Urban growth monitoring using remote sensing and geographic information system: a case study in the Twin Cities metropolitain area, Minnesota / F. Yuan in Geocarto international, vol 25 n° 3 (June 2010)  

Public [article]  inGeocarto international > vol 25 n° 3 (June 2010) . - pp 213 - 230 Titre : Urban growth monitoring using remote sensing and geographic information system: a case study in the Twin Cities metropolitain area, Minnesota Type de document : Article/Communication Auteurs : F. Yuan, Auteur Année de publication : 2010 Article en page(s) : pp 213 - 230 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] croissance urbaine [Termes IGN] image Landsat [Termes IGN] Minneapolis (Minnesota) [Termes IGN] Minnesota (Etats-Unis) [Termes IGN] modèle de Markov [Termes IGN] périphérie urbaine [Termes IGN] prévision [Termes IGN] simulation [Termes IGN] système d'information géographique [Termes IGN] utilisation du sol Résumé : (Auteur) This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary. Numéro de notice : A2010-267 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040903108445 Date de publication en ligne : 10/07/2009 En ligne : https://doi.org/10.1080/10106040903108445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30461 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2010031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Land-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling / F. Yuan in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n°3-4 (February 2008) . - pp 1169 - 1184 Titre : Land-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling Type de document : Article/Communication Auteurs : F. Yuan, Auteur Année de publication : 2008 Article en page(s) : pp 1169 - 1184 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] aménagement du territoire [Termes IGN] analyse diachronique [Termes IGN] apprentissage automatique [Termes IGN] carte d'occupation du sol [Termes IGN] détection de changement [Termes IGN] fusion d'images [Termes IGN] image Quickbird [Termes IGN] impact sur l'environnement [Termes IGN] Minnesota (Etats-Unis) [Termes IGN] photographie aérienne [Termes IGN] planification urbaine [Termes IGN] surface imperméable [Termes IGN] système d'information géographique [Termes IGN] urbanisation Résumé : (Auteur) Land use and land-cover (LULC) data provide essential information for environmental management and planning. This research evaluates the land-cover change dynamics and their effects for the Greater Mankato Area of Minnesota using image classification and Geographic Information Systems (GIS) modelling in high-resolution aerial photography and QuickBird imagery. Results show that from 1971 to 2003, urban impervious surfaces increased from 18.3% to 32.6%, while cropland and grassland decreased from 54.2% to 39.1%. The dramatic urbanization caused evident environmental impacts in terms of runoff and water quality, whereas the annual air pollution removal rate and carbon storage/sequestration remained consistent since urban forests were steady over the 32-year span. The results also indicate that highly accurate land-cover features can be extracted effectively from high-resolution imagery by incorporating both spectral and spatial information, applying an image-fusion technique, and utilizing the hierarchical machine-learning Feature Analyst classifier. This research fills the high-resolution LULC data gap for the Greater Mankato Area. The findings of the study also provide valuable inputs for local decision-makers and urban planners. Copyright Taylor & Francis Numéro de notice : A2008-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701294703 En ligne : https://doi.org/10.1080/01431160701294703 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29003 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-08021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Seasonal sensitivity analysis of impervious surface estimation with satellite imagery / C. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 12 (December 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 12 (December 2007) . - pp 1393 - 1401 Titre : Seasonal sensitivity analysis of impervious surface estimation with satellite imagery Type de document : Article/Communication Auteurs : C. Wu, Auteur ; F. Yuan, Auteur Année de publication : 2007 Article en page(s) : pp 1393 - 1401 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse de sensibilité [Termes IGN] analyse des mélanges spectraux [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-TM [Termes IGN] Ohio (Etats-Unis) [Termes IGN] régression [Termes IGN] surface imperméable [Termes IGN] variation saisonnière Résumé : (Auteur) Numerous approaches have been developed to quantify the distribution of impervious surfaces using remote sensing technologies. Most of these approaches have been applied to data from a single time period, typically in the summer season (June to September). Presently, it is not clear whether there is an optimal time for impervious surface estimation with these methods. In this paper, the seasonal sensitivity of impervious surface estimation is examined. In particular, Landsat TM/ETM+ imagery for four different seasons has been acquired for the environs of Franklin County, Ohio. Two impervious surface estimation methods, spectral mixture analysis and regression modeling, are used to test for seasonal variations. Results indicate that the summer image provides better accuracy with the spectral mixture analysis method, while consistent accuracies are obtained for all four seasons with regression modeling. Copyright ASPRS Numéro de notice : A2007-543 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.12.1393 En ligne : https://doi.org/10.14358/PERS.73.12.1393 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28906 [article]