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Auteur Kevin Tansey |
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Using remote sensing to assess the effect of time of day on the spatial and temporal variation of LST in urban areas / Akram Abdulla (2020)
Titre : Using remote sensing to assess the effect of time of day on the spatial and temporal variation of LST in urban areas Type de document : Thèse/HDR Auteurs : Akram Abdulla, Auteur ; Kevin Tansey, Directeur de thèse ; Kristen Barrett, Directeur de thèse Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2020 Importance : 128 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis submitted for the degree of Doctor of Philosophy at The University of Leicester, School of Geography, Geology and EnvironmentLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données spatiotemporelles
[Termes IGN] ilot thermique urbain
[Termes IGN] image infrarouge
[Termes IGN] image Landsat
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] occupation du sol
[Termes IGN] phénomène climatique extrême
[Termes IGN] température au sol
[Termes IGN] variation diurne
[Termes IGN] variation saisonnière
[Termes IGN] variation temporelle
[Termes IGN] zone urbaineIndex. décimale : THESE Thèses et HDR Résumé : (auteur) This thesis seeks to add to the study of the relationship between land surface temperature (LST) and urban land cover by presenting a method to project Landsat LST data from the satellite overpass time (9:40 am) to a local peak of temperature (estimated to be around 1:15 pm locally), to investigate the impact of the time of image acquisition on modelling the spatial and temporal variations of LST. Additionally, it would also verify the effects of extreme temperature to reach more representative seasonal images.The study uses remote sensing data extracted from Landsat 5 and 8 (30 m resolution) and the Spinning Enhanced Visible and Infrared Imager LST products (SEVIRI 3 km resolution), in addition to LST-based measurements collected from the ground. The study presented a method to convert Landsat images to be estimated during local peaks in LST with an accuracy of: standard error of 1.7°C and an R of 0.82 in comparison with actual ground-based measurements. This allowed an investigation of the effects of time of day on the spatial and temporal variation of LST, where it was found that this factor has clearly affected the relationship between LST and urban land cover. Similarly, the time of day has caused differences in estimating LST change over several years. It is also found that the extreme values of temperature can affect the trend of LST temporal variation, and which can be minimized by using the images in the form of the average of seasonal images for each year rather than images being used in a standalone manner. This study contributes to the improved study of LST by minimizing the uncertainty that can occur because of the angle of the sun and associated factors such as shadows, which has long been a controversial issue among researches due to the lack of appropriate satellite data. Note de contenu : 1- Introduction
2- Literature review
3- Study area
4- Converting Landsat LST data from morning to peak temperatures(9:40 am to 1:15 pm)
5- Assessing the effect of the time of day on the spatial variation of LST
6- Assessment and enhancement of the temporal variation of LST over a time series
7- General Discussion and ConclusionsNuméro de notice : 28304 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Geography, Geology and Environment : University of Leicester : 2020 DOI : sans En ligne : https://doi.org/10.25392/leicester.data.14518848.v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98068 Backscatter coefficient as an attribute for the classification of full-waveform airborne laser scanning data in urban areas / C. Alexander in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)
[article]
Titre : Backscatter coefficient as an attribute for the classification of full-waveform airborne laser scanning data in urban areas Type de document : Article/Communication Auteurs : C. Alexander, Auteur ; Kevin Tansey, Auteur ; J. Kaduk, Auteur ; David A. Holland, Auteur ; Nicholas J. Tate, Auteur Année de publication : 2010 Article en page(s) : pp 423 - 432 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] angle d'incidence
[Termes IGN] classification dirigée
[Termes IGN] classification par arbre de décision
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] données laser
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] milieu urbain
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Airborne laser scanning (ALS) data are increasingly being used for land cover classification. The amplitudes of echoes from targets, available from full-waveform ALS data, have been found to be useful in the classification of land cover. However, the amplitude of an echo is dependent on various factors such as the range and incidence angle, which makes it difficult to develop a classification method which can be applied to full-waveform ALS data from different sites, scanning geometries and sensors. Additional information available from full-waveform ALS data, such as range and echo width, can be used for radiometric calibration, and to derive backscatter cross section. The backscatter cross section of a target is the physical cross sectional area of an idealised isotropic target, which has the same intensity as the selected target. The backscatter coefficient is the backscatter cross section per unit area. In this study, the amplitude, backscatter cross section and backscatter coefficient of echoes from ALS point cloud data collected from two different sites are analysed based on urban land cover classes. The application of decision tree classifiers developed using data from the first study area on the second demonstrates the advantage of using the backscatter coefficient in classification methods, along with spatial attributes. It is shown that the accuracy of classification of the second study area using the backscatter coefficient (kappa coefficient 0.89) is higher than those using the amplitude (kappa coefficient 0.67) or backscatter cross section (kappa coefficient 0.68). This attribute is especially useful for separating road and grass. Numéro de notice : A2010-445 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.05.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.05.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30638
in ISPRS Journal of photogrammetry and remote sensing > vol 65 n° 5 (September - October 2010) . - pp 423 - 432[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2010051 SL Revue Centre de documentation Revues en salle Disponible An algorithm for mapping burnt areas in Australia using SPOT-Vegetation data / D. Stroppiana in IEEE Transactions on geoscience and remote sensing, vol 41 n° 4 (April 2003)
[article]
Titre : An algorithm for mapping burnt areas in Australia using SPOT-Vegetation data Type de document : Article/Communication Auteurs : D. Stroppiana, Auteur ; Kevin Tansey, Auteur ; J.M. Gregoire, Auteur ; J.M.C. Perrira, Auteur Année de publication : 2003 Article en page(s) : pp 907 - 909 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Australie
[Termes IGN] carte thématique
[Termes IGN] classification dirigée
[Termes IGN] image SPOT-Végétation
[Termes IGN] incendie de forêt
[Termes IGN] occupation du sol
[Termes IGN] zone sinistréeRésumé : (auteur) (Auteur) An algorithm has been developed to map burnt areas over the Australian continent using SPOTVEGETATION (VGT) SI satellite images. The algorithm is composed of a set of thresholds applied to each pixel's value of the VGT spectral channels, two spectral indices and their temporal difference. The threshold values have been derived by means of a supervised classification methodology based on the classification and regression trees algorithm. A procedure has also been developed specifically for pre-processing the daily SI images for burnt area mapping purposes. The final product is composed of ten day and monthly burnt area maps over Australia for the full year 2000. Numéro de notice : A2003-183 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.808898 En ligne : https://doi.org/10.1109/TGRS.2003.808898 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77395
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 4 (April 2003) . - pp 907 - 909[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03041 RAB Revue Centre de documentation En réserve L003 Disponible