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Use of automated change detection and VGI sources for identifying and validating urban land use change / Ana-Maria Olteanu-Raimond in Remote sensing, vol 12 n° 7 (April 2020)  

Public [article]  inRemote sensing > vol 12 n° 7 (April 2020) . - n° 1186 Titre : Use of automated change detection and VGI sources for identifying and validating urban land use change Type de document : Article/Communication Auteurs : Ana-Maria Olteanu-Raimond , Auteur ; L. See, Auteur ; M. Schultz, Auteur ; Giles M. Foody, Auteur ; M. Riffler, Auteur ; T. Gasber, Auteur ; Laurence Jolivet , Auteur ; Arnaud Le Bris , Auteur ; Yann Méneroux , Auteur ; Lanfa Liu, Auteur ; Marc Poupée , Auteur ; Marie Gombert, Auteur Année de publication : 2020 Projets : Landsense / Raimond, Ana-Maria Article en page(s) : n° 1186 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] carte d'utilisation du sol [Termes IGN] cartographie collaborative [Termes IGN] changement d'utilisation du sol [Termes IGN] détection automatique [Termes IGN] détection de changement [Termes IGN] données localisées des bénévoles [Termes IGN] estimation de précision [Termes IGN] science citoyenne [Termes IGN] zone urbaine Résumé : (Auteur) Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done on a multi-year cycle due to the high costs involved, so changes are only detected when mapping exercises are repeated. Consequently, the information on LULC can quickly become outdated and hence may be incorrect in some areas. In the current era of big data and Earth observation, change detection algorithms can be used to identify changes in urban areas, which can then be used to automatically update LULC databases on a more continuous basis. However, the change detection algorithm must be validated before the changes can be committed to authoritative databases such as those produced by national mapping agencies. This paper outlines a change detection algorithm for identifying construction sites, which represent ongoing changes in LU, developed in the framework of the LandSense project. We then use volunteered geographic information (VGI) captured through the use of mapathons from a range of different groups of contributors to validate these changes. In total, 105 contributors were involved in the mapathons, producing a total of 2778 observations. The 105 contributors were grouped according to six different user-profiles and were analyzed to understand the impact of the experience of the users on the accuracy assessment. Overall, the results show that the change detection algorithm is able to identify changes in residential land use to an adequate level of accuracy (85%) but changes in infrastructure and industrial sites had lower accuracies (57% and 75 %, respectively), requiring further improvements. In terms of user profiles, the experts in LULC from local authorities, researchers in LULC at the French national mapping agency (IGN), and first-year students with a basic knowledge of geographic information systems had the highest overall accuracies (86.2%, 93.2%, and 85.2%, respectively). Differences in how the users approach the task also emerged, e.g., local authorities used knowledge and context to try to identify types of change while those with no knowledge of LULC (i.e., normal citizens) were quicker to choose ‘Unknown’ when the visual interpretation of a class was more difficult. Numéro de notice : A2020-243 Affiliation des auteurs : LASTIG+Ext (2016-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12071186 Date de publication en ligne : 07/04/2020 En ligne : https://doi.org/10.3390/rs12071186 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95217 [article]

PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region / E. Emili in Remote sensing of environment, vol 114 n° 11 (15/11/2010)  

Public [article]  inRemote sensing of environment > vol 114 n° 11 (15/11/2010) . - pp 2485 - 2499 Titre : PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region Type de document : Article/Communication Auteurs : E. Emili, Auteur ; C. Popp, Auteur ; M. Petitta, Auteur ; M. Riffler, Auteur ; et al., Auteur Année de publication : 2010 Article en page(s) : pp 2485 - 2499 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] aérosol [Termes IGN] Alpes [Termes IGN] humidité de l'air [Termes IGN] image MSG-SEVIRI [Termes IGN] image spatiale [Termes IGN] image Terra-MODIS [Termes IGN] particule [Termes IGN] qualité de l'air Résumé : (Auteur) The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ~ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV~ 0.7, rMOD~ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r ~0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas. Numéro de notice : A2010-401 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2010.05.024 En ligne : https://doi.org/10.1016/j.rse.2010.05.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30594 [article]