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A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding / Mohammad Khalid Hossain in Computers, Environment and Urban Systems, vol 79 (January 2020)
[article]
Titre : A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding Type de document : Article/Communication Auteurs : Mohammad Khalid Hossain, Auteur ; Qingmin Meng, Auteur Année de publication : 2020 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Alabama (Etats-Unis)
[Termes IGN] aléa
[Termes IGN] approche hiérarchique
[Termes IGN] cartographie des risques
[Termes IGN] catastrophe naturelle
[Termes IGN] données socio-économiques
[Termes IGN] ethnographie
[Termes IGN] inondation
[Termes IGN] risque naturel
[Termes IGN] système d'information géographique
[Termes IGN] vulnérabilité
[Termes IGN] zone inondable
[Termes IGN] zone urbaineRésumé : (Auteur) About 30% of the total global economic loss inflicted by natural hazards is caused by flooding. Among them, the most serious situation is urban flooding. Urban impervious surface enhances storm runoff and overwhelms the drainage capacity of the storm sewer system, while the urban socioeconomic characteristics most often exacerbate them even more vulnerable to urban flooding impacts. Currently, there is still a significant knowledge gap of comparable assessment and understanding of minority's and non-minority's vulnerability. Therefore, this study designs a quantitative thematic mapping method–location quotient (LQ), using Birmingham, Alabama, USA as the study area. Urban residents' vulnerability to flooding is then analyzed demographically using LQ with census data. Comparing with the widely used social vulnerability index (SVI), LQ is more robust, which not only provides more detailed measurements of both the minority's and the White's vulnerability, but also shows a direct comparison for all populations with finer information about their potential spatial risk assessment. Although SVI showed the Shades Creek is the most vulnerable area with a SVI value above 0.75, only 228 Hispanic people and 2290 African-American live there that is not a significant aggregation of minorities in Birmingham; however, a total White population 12,872 is identified by LQ with a significant aggregation in the Shades Creek. Overall, LQ suggests that the White populations are highly and significantly concentrated in the flood areas, while SVI never considered the White as vulnerable. LQ further indicates that the concentration of minorities (i.e., 88,895) and vulnerable houses (i.e., 26,235) are much higher compared to the numbers of the minorities and houses indicated by SVI, which are only 11,772 and 8323, respectively. The LQ based thematic mapping, as a promising method for vulnerability assessment of urban hazards and risks, can make a significant contribution to hazard management efforts to reduce urban vulnerability and hence enhance urban resilience to hazards in the future. Numéro de notice : A2020-002 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101417 Date de publication en ligne : 14/09/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101417 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93621
in Computers, Environment and Urban Systems > vol 79 (January 2020)[article]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 Very high resolution land cover mapping of urban areas at global scale with convolutional neural network / Thomas Tilak (2020)
Titre : Very high resolution land cover mapping of urban areas at global scale with convolutional neural network Type de document : Article/Communication Auteurs : Thomas Tilak , Auteur ; Arnaud Braun , Auteur ; David Chandler , Auteur ; Nicolas David , Auteur ; Sylvain Galopin , Auteur ; Amélie Lombard, Auteur ; Camille Parisel , Auteur ; Camille Parisel , Auteur ; Matthieu Porte , Auteur ; Marjorie Robert, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2020 Autre Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B3 Projets : 1-Pas de projet / Conférence : ISPRS 2020, Commission 3, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Archives Commission 3 Importance : 8 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] BD Alti
[Termes IGN] carte d'occupation du sol
[Termes IGN] chaîne de production
[Termes IGN] chaîne de traitement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] corrélation croisée maximale
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] Gironde (33)
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image multibande
[Termes IGN] modèle numérique de surface
[Termes IGN] segmentation sémantique
[Termes IGN] vectorisation
[Termes IGN] zone d'intérêt
[Termes IGN] zone urbaineRésumé : (auteur) This paper describes a methodology to produce a 7-classes land cover map of urban areas from very high resolution images and limited noisy labeled data. The objective is to make a segmentation map of a large area (a french department) with the following classes: asphalt, bare soil, building, grassland, mineral material (permeable artificialized areas), forest and water from 20cm aerial images and Digital Height Model. We created a training dataset on a few areas of interest aggregating databases, semi-automatic classification, and manual annotation to get a complete ground truth in each class. A comparative study of different encoder-decoder architectures (U-Net, U-Net with Resnet encoders, Deeplab v3+) is presented with different loss functions. The final product is a highly valuable land cover map computed from model predictions stitched together, binarized, and refined before vectorization. Numéro de notice : C2020-038 Affiliation des auteurs : IGN+Ext (2020- ) Autre URL associée : vers ArXiv Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B3-2020-201-2020 Date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-201-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95079 Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images / Cheolhee Yoo in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
[article]
Titre : Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images Type de document : Article/Communication Auteurs : Cheolhee Yoo, Auteur ; Daehyeon Han, Auteur ; Jungho Im, Auteur ; Benjamin Bechtel, Auteur Année de publication : 2019 Article en page(s) : pp 155 - 170 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] Chicago (Illinois)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] climat urbain
[Termes IGN] Hong-Kong
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-8
[Termes IGN] Madrid (Espagne)
[Termes IGN] Rome
[Termes IGN] World Urban Database and Access Portal Tools
[Termes IGN] zone urbaine denseRésumé : (Auteur) The Local Climate Zone (LCZ) scheme is a classification system providing a standardization framework to present the characteristics of urban forms and functions, especially for urban heat island (UHI) research. Landsat-based 100 m resolution LCZ maps have been classified by the World Urban Database and Portal Tool (WUDAPT) method using a random forest (RF) machine learning classifier. Some studies have proposed modified RF and convolutional neural network (CNN) approaches. This study aims to compare CNN with an RF classifier for LCZ mapping in great detail. We designed five schemes (three RF-based schemes (S1–S3) and two CNN-based ones (S4–S5)), which consist of various combinations of input features from bitemporal Landsat 8 data over four global mega cities: Rome, Hong Kong, Madrid, and Chicago. Among the five schemes, the CNN-based one with the incorporation of a larger neighborhood information showed the best classification performance. When compared to the WUDAPT workflow, the overall accuracies for entire land cover classes (OA) and for urban LCZ types (i.e., LCZ1-10; OAurb) increased by about 6–8% and 10–13%, respectively, for the four cities. The transferability of LCZ models for the four cities were evaluated, showing that CNN consistently resulted in higher accuracy (increased by about 7–18% and 18–29% for OA and OAurb, respectively) than RF. This study revealed that the CNN classifier classified particularly well for the specific LCZ classes in which buildings were mixed with trees or buildings or plants were sparsely distributed. The research findings can provide a basis for guidance of future LCZ classification using deep learning. Numéro de notice : A2019-495 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.09.009 Date de publication en ligne : 19/09/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.09.009 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93728
in ISPRS Journal of photogrammetry and remote sensing > vol 157 (November 2019) . - pp 155 - 170[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019111 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019113 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019112 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Les eaux de pluie maîtrisées ou en excès / Pierre Clergeot in Géomètre, n° 2173 (octobre 2019)
[article]
Titre : Les eaux de pluie maîtrisées ou en excès Type de document : Article/Communication Auteurs : Pierre Clergeot, Auteur Année de publication : 2019 Article en page(s) : pp 32 - 47 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Hydrologie
[Termes IGN] aquifère
[Termes IGN] bassin hydrographique
[Termes IGN] carte topographique
[Termes IGN] changement climatique
[Termes IGN] collectivité territoriale
[Termes IGN] cours d'eau
[Termes IGN] données météorologiques
[Termes IGN] drainage
[Termes IGN] eau pluviale
[Termes IGN] écoulement des eaux
[Termes IGN] gestion de l'eau
[Termes IGN] inondation
[Termes IGN] précipitation
[Termes IGN] prévention des risques
[Termes IGN] réseau d'assainissement
[Termes IGN] ruissellement
[Termes IGN] talweg
[Termes IGN] terminologie
[Termes IGN] urbanisme
[Termes IGN] zone humide
[Termes IGN] zone urbaineNote de contenu : - Connaître le relief pour faire face
- Eaux pluviales et eaux de ruissellement
- La maîtrise des risques dus au ruissellement
- Les pluies intenses et la mesure des précipitations
- La hiérarchie des pluies,un vocabulaire à préciser
- Les bassins versants et les eaux de ruissellement
- Le service public administratif de gestion des eaux pluviales urbainesNuméro de notice : A2019-487 Affiliation des auteurs : non IGN Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93685
in Géomètre > n° 2173 (octobre 2019) . - pp 32 - 47[article]Réservation
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