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University of Leicester
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Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesChange detection of land use and land cover, using landsat-8 and sentinel-2A images / Mohammed Abdulmohsen Alhedyan (2021)
Titre : Change detection of land use and land cover, using landsat-8 and sentinel-2A images Type de document : Thèse/HDR Auteurs : Mohammed Abdulmohsen Alhedyan, Auteur Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2021 Importance : 228 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis submitted for the degree of PhD at the University of LeicesterLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse vectorielle
[Termes IGN] Arabie Saoudite
[Termes IGN] Corine (base de données)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] Royaume-Uni
[Termes IGN] utilisation du solRésumé : (auteur) The main theme of this research is the development of a new hybrid method for change detection of land use and land cover (LULC). LULC change detection is one of most widely used applications of remote sensing. This study used data from two different optical sensors, Landsat-8 images and Sentinel-2A images. Given the newly developed capabilities of these remote sensing satellites, it was necessary to devise appropriate techniques to realise the benefits that they offer. Therefore, three effective change detection methods have been tested, comprehensively analysed, and used to inform the design and development of a new hybrid method of change detection. The studied change detection methods were change vector analysis (CVA), multi-index integrated change analysis (MIICA), and the comprehensive change detection method (CCDM). Case studies were conducted in two regions, Bristol (United Kingdom) and Hail (Saudi Arabia), to provide sufficient variety of inputs to enable the response of more LULC varieties to be recorded. Finally, the Coordination of Information on the Environment (Corine) land cover scheme was used to identify land cover types and LULC changes. In the study area of Bristol, the new hybrid change detection method achieved an overall accuracy of 90% and 0.81 kappa, while the results for the study area of Hail were 74% overall accuracy and 0.40 kappa. The change detection results obtained by the new hybrid method constitute a significant improvement over the implementation of the existing CVA, MIICA and CCDM methods at the two study areas while using Landsat-8 and Sentinel-2A images. Note de contenu : 1- Introduction
2- Literature review
3- Classification system, study areas, data sources and data preparation process
4- Evaluation of existing change detection
5- The hybrid change detection method
6- Discussion
7- ConclusionNuméro de notice : 28466 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Leicester : Geography, Geology, and Environment : 2021 DOI : 10.25392/leicester.data.16988440.v1 En ligne : https://doi.org/10.25392/leicester.data.16988440.v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99094
Titre : Learning digital geographies through geographical artificial intelligence Type de document : Thèse/HDR Auteurs : Pengyuan Liu, Auteur ; Stefano de Sabbata, Directeur de thèse ; Yu-Dong Zhang, Directeur de thèse Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2021 Importance : 199 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy, Geology and EnvironmentLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse socio-économique
[Termes IGN] apprentissage profond
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] croissance urbaine
[Termes IGN] détection de changement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données spatiotemporelles
[Termes IGN] géomatique web
[Termes IGN] intelligence artificielle
[Termes IGN] Londres
[Termes IGN] réseau neuronal de graphes
[Termes IGN] réseau sémantique
[Termes IGN] système d'information urbain
[Termes IGN] zone urbaineIndex. décimale : THESE Thèses et HDR Résumé : (auteur) As the distinction between online and physical spaces rapidly degrades, digital platforms have become an integral component of how people’s everyday experiences are mediated. User-generated content (UGC) shared on such platforms provides insights into how users want to represent their everyday lives, which augments and reinforces our understanding of local communities through time and layers dynamic information across and over the geographic space. Inspired by the development of the newly arisen scientific disciplines within geography: geographical artificial intelligence (GeoAI), this thesis adopts deep learning approaches on graph representations of human dynamics illustrated through geotagged UGC to explore how place representations are augmented and reinforced through users’ spatial experiences by classifying their multimedia activities and identifying the spatial clusters of UGC at the urban scale. Having the place representations described through UGC, this thesis explores how these representations can be used in conjunction with various official spatial statistics to understand and predict the dynamic changes of the socio-economic characteristics of places. The principal contributions of this thesis are: (1) to provide frameworks with higher classification and prediction accuracy but requiring fewer sample data; thus, contributing to an advanced framework to summarise spatial characteristics of places; (2) to show that multimedia content provides rich information regarding places, the use of space, and people’s experience of the landscape; thus, benefiting a better understanding of place representations; (3) to illustrate that the spatial patterns of UGC can be adopted as a valuable proxy to understand urban development and neighbourhood change; (4) to reinforce the concept that Spatial is Special. Spatial processes are commonly spatially autocorrelated. The mainstream of machine learning methods do not explicitly incorporate the spatial or spatio-temporal component to address such a speciality of spatial data. This thesis highlights the importance of explicitly incorporating spatial or spatio-temporal components in geographical analysis models. Note de contenu : 1- Introduction
2- Towards quantitative digital geographies: Concepts, research and implications
3- Data and methods
4- Classification learning through a graph-based semi-supervised approach
5- Location estimation of social media content through a graph-based linkPrediction
6- Urban change modelling with spatial knowledge graphs
7- DiscussionNuméro de notice : 28629 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD Thesis: Geology and Environment: Leicester : 2021 DOI : sans En ligne : https://leicester.figshare.com/articles/thesis/Learning_Digital_Geographies_thro [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99618
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 Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 / Nicholas J. Tate (2010)
Titre : Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 Type de document : Actes de congrès Auteurs : Nicholas J. Tate, Éditeur scientifique ; Peter F. Fisher, Éditeur scientifique Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2010 Autre Editeur : International Spatial Accuracy Research Association ISARA Conférence : Accuracy 2010, 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences 20/07/2010 23/07/2010 Leicester Royaume-Uni OA Proceedings Importance : 436 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Termes IGN] données localisées des bénévoles
[Termes IGN] géostatistique
[Termes IGN] géovisualisation
[Termes IGN] incertitude des données
[Termes IGN] incertitude géométrique
[Termes IGN] incertitude temporelle
[Termes IGN] précision des données
[Termes IGN] propagation d'erreur
[Termes IGN] sous ensemble flou
[Termes IGN] traitement de données localiséesIndex. décimale : CG2010 Actes de congrès en 2010 Note de contenu : 1 - Keynotes
2 - Remote sensing and image interpretation
3 - Fuzzy uncertainty 1
4 - Uncertainty in space and time
5 - Geostatistics 1
6 - ISPRS session
7 - Uncertainty propagation
8 - Land use and land cover
9 - DEM uncertainty 1
10 - Remote sensing
11 - Geoprocessing
12 - Model uncertainty and validation
13 - Vizualisation
14 - Sampling design
15 - Spatio-temporal uncertainty
16 - DEM uncertainty 2
17 - Geostatistics 2
18 - Fuzzy uncertainty 2
19 - DEM uncertainty 3
20 - Remote sensing classification
21 - Environmental quality
22 - Small area concerns
23 - Ecology and forestry
24 - VGI and web-based geoprocessing
25 - Geocoding and adress coding
26 - PostersNuméro de notice : 21370 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes DOI : sans En ligne : http://spatialaccuracy.org/spatial-accuracy-2010/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90097 Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 21370-01 CG2010 Livre Centre de documentation Congrès Disponible Assessing the accuracy of 'crowdsourced' data and its itegration with official spatial data sets / Maythm Al-Bakri (2010)
contenu dans Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 / Nicholas J. Tate (2010)
Titre : Assessing the accuracy of 'crowdsourced' data and its itegration with official spatial data sets Type de document : Article/Communication Auteurs : Maythm Al-Bakri, Auteur ; David Fairbairn, Auteur Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2010 Conférence : Accuracy 2010, 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences 20/07/2010 23/07/2010 Leicester Royaume-Uni OA Proceedings Importance : pp 317 - 320 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] intégration de données
[Termes IGN] précision de localisation
[Termes IGN] précision sémantique
[Termes IGN] production participative
[Termes IGN] qualité des donnéesRésumé : (auteur) A key challenge in supporting effective spatial data integration is the assessment of data quality from different sources. This paper presents a methodology for assessing positional and shape quality from formal data, such as Ordnance Survey (OS) and crowdsourced data , such as OpenStreetMap (OSM) information, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the data sets : results show that the accuracy of OS data is very close to a reference data set, but the positional and shape accuracy of OSM data does not match the reference or the the OS data sets. Numéro de notice : C2010-033 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : sans En ligne : http://spatialaccuracy.org/wp-content/uploads/2021/08/Al-Bakri2010accuracy.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90932
