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Dasymetric modelling of small-area population distribution using land cover and light emissions data / D.J. Briggs in Remote sensing of environment, vol 108 n° 4 (29 June 2007)  

Public [article]  inRemote sensing of environment > vol 108 n° 4 (29 June 2007) . - pp 451 - 466 Titre : Dasymetric modelling of small-area population distribution using land cover and light emissions data Type de document : Article/Communication Auteurs : D.J. Briggs, Auteur ; J. Gulliver, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 451 - 466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] Corine Land Cover [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] données statistiques [Termes IGN] figuration de la densité [Termes IGN] flux lumineux [Termes IGN] image DMSP-OLS [Termes IGN] image satellite [Termes IGN] intensité lumineuse [Termes IGN] interpolation inversement proportionnelle à la distance [Termes IGN] krigeage [Termes IGN] régression Résumé : (Auteur) Despite the improvements made in census procedures over recent decades, the availability of detailed population data is limited. For many applications, including environmental and health analyses, methods are therefore needed to model population distribution at the small-area level. With the development of GIS and remote sensing techniques, the ability to develop such models has greatly improved. This paper describes a GIS-based approach using remotely sensed land cover and nighttime light emissions data to model population distribution at the land parcel level across the European Union. Light emission data from the DMSP satellites were first resampled and modelled using kriging and inverse distance weighting methods to provide a 200-m resolution light emissions map. This was then matched to CORINE land cover classes across the EU. Regression methods were used to derive models of relationships between census population counts (at NUTS 5 level) and land cover area and light emissions. Models were developed at both national and EU scale, using a range of different modelling strategies. Model performance, as indicated by the regression statistics, was seen to be good, with R2 typically in the order of 0.8–0.9 and SEE ca. 4000 people. In southern countries, especially, incorporation of light emissions data was found to improve model performance considerably compared to models based only on land cover data. More detailed post hoc validation in Great Britain, using independent data on population at census tract (enumeration district and output area) and postcode level, for 1991 and 2001, showed that models gave good predictions of population at the 1 km level (R2 > 0.9), but were less reliable at resolutions below ca. 500 m. Impending enhancements in the available land cover and light emissions data are expected to improve the capability of this modelling approach in the future. Numéro de notice : A2007-300 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.11.020 En ligne : https://doi.org/10.1016/j.rse.2006.11.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28663 [article]

Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example / Edzer J. Pebesma in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 21 n° 5 (may 2007) . - pp 515 - 527 Titre : Interactive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example Type de document : Article/Communication Auteurs : Edzer J. Pebesma, Auteur ; K. de Jong, Auteur ; D.J. Briggs, Auteur Année de publication : 2007 Article en page(s) : pp 515 - 527 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes IGN] analyse comparative [Termes IGN] données spatiotemporelles [Termes IGN] incertitude des données [Termes IGN] méthode de Monte-Carlo [Termes IGN] qualité de l'air [Termes IGN] Union Européenne [Termes IGN] visualisation dynamique Résumé : (Auteur) This paper introduces a method for visually exploring spatio-temporal data or predictions that come as probability density functions, e.g. output of statistical models or Monte Carlo simulations, under different scenarios. For a given moment in time, we can explore the probability dimension by looking at maps with cumulative or exceedance probability while varying the attribute level that is exceeded, or by looking at maps with quantiles while varying the probability value. Scenario comparison is done by arranging the maps in a lattice with each panel reacting identically to legend modification, zooming, panning, or map querying. The method is illustrated by comparing different modelling scenarios for yearly NO2 levels in 2001 across the European Union. Copyright Taylor & Francis Numéro de notice : A2007-134 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810601064009 En ligne : https://doi.org/10.1080/13658810601064009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28497 [article]

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Mapping urban air pollution using GIS: a regression-based approach / D.J. Briggs in International journal of geographical information science IJGIS, vol 11 n° 7 (October 1997)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 11 n° 7 (October 1997) . - pp 699 - 718 Titre : Mapping urban air pollution using GIS: a regression-based approach Type de document : Article/Communication Auteurs : D.J. Briggs, Auteur ; S. Collins, Auteur ; P. Elliott, Auteur ; P. Fischer, Auteur ; et al., Auteur Année de publication : 1997 Article en page(s) : pp 699 - 718 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] Amsterdam (Pays-Bas) [Termes IGN] cartographie thématique [Termes IGN] pollution atmosphérique [Termes IGN] Prague (République tchèque) [Termes IGN] système d'information géographique [Termes IGN] trafic routier Résumé : (Auteur) As part of the EU-funded SAVIAH project, a regression-based methodology for mapping traffic-related air pollution was developped within a GIS environment. Mapping was carried out for NO in Amsterdam, Huddersfield and Prague. A GIS was established with data on monitored air pollution levels, road network, traffic volume, land cover, altitude and other locallly determined features. Numéro de notice : A1997-107 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/136588197242158 En ligne : https://doi.org/10.1080/136588197242158 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=25962 [article]

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