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Urban flooding in Britain: an approach to comparing ancient and contemporary flood exposure / T.E. O'Shea in Natural Hazards, Vol 104 n° 1 (October 2020)
[article]
Titre : Urban flooding in Britain: an approach to comparing ancient and contemporary flood exposure Type de document : Article/Communication Auteurs : T.E. O'Shea, Auteur ; J. Lewin, Auteur Année de publication : 2020 Article en page(s) : pp 581 – 591 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse des risques
[Termes IGN] bassin hydrographique
[Termes IGN] croissance urbaine
[Termes IGN] crue
[Termes IGN] données hydrographiques
[Termes IGN] Grande-Bretagne
[Termes IGN] historique des données
[Termes IGN] inondation
[Termes IGN] modèle hydrographique
[Termes IGN] période romaine
[Termes IGN] risque naturel
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineRésumé : (auteur) Using modified UK Environment Agency Flood Estimation Handbook techniques, inundation extent and likely flood hydrographs for 0.1% probability annual return periods are compared for twelve Roman town sites in the UK, both at the present day and for simulated Roman catchment conditions. Eight of the study sites appear to have suffered minimal urban flood liability as occupied in the Roman period. The exceptions were Canterbury, York, Leicester, and Chichester. It is reasonable to expect flood characteristics to have changed subsequently in response to transformations in catchment land use, urban expansion, wetland reclamation, and floodway engineering. However, modelling results suggest limited differences in flood flows attributable to such factors. Greater present-day urban damage liability essentially results from floodplain urban extension. There are also contrasts between sites: those Roman towns lying on floodplains themselves, rather than on slightly elevated terraces (Canterbury, Chichester), are dominated by groundwater regimes with attenuated flood peaks. Taken together, these results suggest some Roman awareness of the actualities of urban flood liability at the time. Site sensitivity has not been carried forward as urban expansion has flourished, especially from the nineteenth century with suburban and industrial expansion. The straightforward mapping approach here suggested should in future take account of multiple century-scale hydroclimatic changes, morphological river channel and floodplain transformations over similar time periods, and on-going improvements to inundation modelling. Numéro de notice : A2020-724 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11069-020-04181-8 Date de publication en ligne : 24/07/2020 En ligne : https://doi.org/10.1007/s11069-020-04181-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96326
in Natural Hazards > Vol 104 n° 1 (October 2020) . - pp 581 – 591[article]A name‐led approach to profile urban places based on geotagged Twitter data / Juntao Lai in Transactions in GIS, Vol 24 n° 4 (August 2020)
[article]
Titre : A name‐led approach to profile urban places based on geotagged Twitter data Type de document : Article/Communication Auteurs : Juntao Lai, Auteur ; Guy Lansley, Auteur ; James Haworth, Auteur ; Tao Cheng, Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] approche participative
[Termes IGN] données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] espace urbain
[Termes IGN] Foursquare
[Termes IGN] Londres
[Termes IGN] point d'intérêt
[Termes IGN] réseau social
[Termes IGN] réseau social géodépendant
[Termes IGN] site urbain
[Termes IGN] toponyme
[Termes IGN] TwitterRésumé : (auteur) Place is a concept that is fundamental to how we orientate and communicate space in our everyday lives. Crowdsourced social media data present a valuable opportunity to develop bottom‐up inferences of places that are integral to social activities and settings. Conventional location‐led approaches use a predefined spatial unit to associate data and space with places, which cannot capture the richness of urban places (i.e., spatial extents and their dynamic functions). This article develops a name‐led framework to overcome these limitations in using social media data to study urban places. The framework first derives place names from georeferenced Twitter data combining text mining and spatial point pattern analysis, then estimates the spatial extents by spatial clustering, and further extracts their dynamic functions with time, which makes up a complete place profile. The framework is tested on a case study in Camden Borough, London and the results are evaluated through comparisons to the Foursquare point of interest data. This name‐led approach enables the shift from space‐based analysis to place‐based analysis of urban space. Numéro de notice : A2020-670 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12599 Date de publication en ligne : 05/12/2019 En ligne : https://doi.org/10.1111/tgis.12599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96155
in Transactions in GIS > Vol 24 n° 4 (August 2020) . - 22 p.[article]What influences the long-term development of mixtures in British forests? / William L. Mason in Forestry, an international journal of forest research, vol 93 n° 4 (July 2020)
[article]
Titre : What influences the long-term development of mixtures in British forests? Type de document : Article/Communication Auteurs : William L. Mason, Auteur ; T. Connolly, Auteur Année de publication : 2020 Article en page(s) : pp 545 - 556 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] Betula pendula
[Termes IGN] composition d'un peuplement forestier
[Termes IGN] croissance des arbres
[Termes IGN] foresterie
[Termes IGN] Grande-Bretagne
[Termes IGN] intensité lumineuse
[Termes IGN] Larix kaempferi
[Termes IGN] ombre
[Termes IGN] peuplement mélangé
[Termes IGN] peuplement pur
[Termes IGN] Picea sitchensis
[Termes IGN] Pinus contorta
[Termes IGN] Pinus sylvestris
[Termes IGN] surface terrière
[Termes IGN] Tsuga heterophylla
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Six experiments were established between 1955 and 1962 in different parts of northern and western Britain which used replicated randomized block designs to compare the performance of two species 50:50 mixtures with pure stands of the component species. The species involved were variously lodgepole pine (Pinus contorta Dougl.), Japanese larch (Larix kaempferi Lamb. Carr.), Scots pine (Pinus sylvestris L.), silver birch (Betula pendula Roth.), Sitka spruce (Picea sitchensis Bong. Carr.) and western hemlock (Tsuga heterophylla Raf. Sarg.). The first four species are light demanding, while Sitka spruce is of intermediate shade tolerance and western hemlock is very shade tolerant: only Scots pine and silver birch are native to Great Britain. In three experiments (Bickley, Ceannacroc, Hambleton), the mixtures were of two light-demanding species, while at the other three sites, the mixture tested contained species of different shade tolerance. The experiments were followed for around 50 years, similar to a full rotation of even-aged conifer stands in Britain. Five experiments showed a tendency for one species to dominate in mixture, possibly reflecting differences in the shade tolerance or other functional traits of the component species. In the three experiments, the basal area of the mixtures at the last assessment was significantly higher than predicted based on the performance of the pure stands (i.e. the mixture ‘overyielded’). In two of these cases, the mixture had had a higher basal area than found in the more productive pure stand indicating ‘transgressive overyielding’. Significant basal area differences were generally more evident at the later assessment date. The exception was in a Scots pine: western hemlock mixture where greater overyielding at the earlier date indicated a nursing (‘facilitation’) effect. In the remaining experiments, the performance of the mixture conformed to predictions from the growth of the component species in pure stands. Taken overall, the results suggest that functional traits can be used to interpret the performance of mixtures but prediction of the outcome will require better understanding of the interplay between species and site characteristics plus the influence of silvicultural interventions. Numéro de notice : A2020-580 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpaa003 Date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1093/forestry/cpaa003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95899
in Forestry, an international journal of forest research > vol 93 n° 4 (July 2020) . - pp 545 - 556[article]Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)
[article]
Titre : Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data Type de document : Article/Communication Auteurs : Rochelle Schneider dos Santos, Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du gradient
[Termes IGN] apprentissage automatique
[Termes IGN] chaleur
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] ilot thermique urbain
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] Londres
[Termes IGN] modèle de régression
[Termes IGN] mortalité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] politique publique
[Termes IGN] Python (langage de programmation)
[Termes IGN] régression linéaire
[Termes IGN] santé
[Termes IGN] station météorologique
[Termes IGN] température au sol
[Termes IGN] température de l'air
[Termes IGN] zone urbaineRésumé : (auteur) Urbanisation generates greater population densities and an increase in anthropogenic heat generation. These factors elevate the urban–rural air temperature (Ta) difference, thus generating the Urban Heat Island (UHI) phenomenon. Ta is used in the fields of public health and epidemiology to quantify deaths attributable to heat in cities around the world: the presence of UHI can exacerbate exposure to high temperatures during summer periods, thereby increasing the risk of heat-related mortality. Measuring and monitoring the spatial patterns of Ta in urban contexts is challenging due to the lack of a good network of weather stations. This study aims to produce a parsimonious model to retrieve maximum Ta (Tmax) at high spatio-temporal resolution using Earth Observation (EO) satellite data. The novelty of this work is twofold: (i) it will produce daily estimations of Tmax for London at 1 km2 during the summertime between 2006 and 2017 using advanced statistical techniques and satellite-derived predictors, and (ii) it will investigate for the first time the predictive power of the gradient boosting algorithm to estimate Tmax for an urban area. In this work, 6 regression models were calibrated with 6 satellite products, 3 geospatial features, and 29 meteorological stations. Stepwise linear regression was applied to create 9 groups of predictors, which were trained and tested on each regression method. This study demonstrates the potential of machine learning algorithms to predict Tmax: the gradient boosting model with a group of five predictors (land surface temperature, Julian day, normalised difference vegetation index, digital elevation model, solar zenith angle) was the regression model with the best performance (R² = 0.68, MAE = 1.60 °C, and RMSE = 2.03 °C). This methodological approach is capable of being replicated in other UK cities, benefiting national heat-related mortality assessments since the data (provided by NASA and the UK Met Office) and programming languages (Python) sources are free and open. This study provides a framework to produce a high spatio-temporal resolution of Tmax, assisting public health researchers to improve the estimation of mortality attributable to high temperatures. In addition, the research contributes to practice and policy-making by enhancing the understanding of the locations where mortality rates may increase due to heat. Therefore, it enables a more informed decision-making process towards the prioritisation of actions to mitigate heat-related mortality amongst the vulnerable population. Numéro de notice : A2020-448 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2020.102066 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102066 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95524
in International journal of applied Earth observation and geoinformation > vol 88 (June 2020) . - 10 p.[article]Street-Frontage-Net: urban image classification using deep convolutional neural networks / Stephen Law in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)
[article]
Titre : Street-Frontage-Net: urban image classification using deep convolutional neural networks Type de document : Article/Communication Auteurs : Stephen Law, Auteur ; Chanuki Illushka Seresinhe, Auteur ; Yao Shen, Auteur Année de publication : 2020 Article en page(s) : pp 681- 707 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] espace public
[Termes IGN] évaluation foncière
[Termes IGN] extraction de données
[Termes IGN] façade
[Termes IGN] habitat urbain
[Termes IGN] image Streetview
[Termes IGN] immobilier (secteur)
[Termes IGN] information géographique
[Termes IGN] Londres
[Termes IGN] matrice de confusion
[Termes IGN] Paris (75)
[Termes IGN] paysage urbain
[Termes IGN] urbanisme
[Termes IGN] vision par ordinateurRésumé : (auteur) Quantifying aspects of urban design on a massive scale is crucial to help develop a deeper understanding of urban designs elements that contribute to the success of a public space. In this study, we further develop the Street-Frontage-Net (SFN), a convolutional neural network (CNN) that can successfully evaluate the quality of street frontage as either being active (frontage containing windows and doors) or blank (frontage containing walls, fences and garages). Small-scale studies have indicated that the more active the frontage, the livelier and safer a street feels. However, collecting the city-level data necessary to evaluate street frontage quality is costly. The SFN model uses a deep CNN to classify the frontage of a street. This study expands on the previous research via five experiments. We find robust results in classifying frontage quality for an out-of-sample test set that achieves an accuracy of up to 92.0%. We also find active frontages in a neighbourhood has a significant link with increased house prices. Lastly, we find that active frontage is associated with more scenicness compared to blank frontage. While further research is needed, the results indicate the great potential for using deep learning methods in geographic information extraction and urban design. Numéro de notice : A2020-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1555832 Date de publication en ligne : 26/12/2018 En ligne : https://doi.org/10.1080/13658816.2018.1555832 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94712
in International journal of geographical information science IJGIS > vol 34 n° 4 (April 2020) . - pp 681- 707[article]Interactive display of surnames distributions in historic and contemporary Great Britain / Justin Van Dijk in Journal of maps, vol 16 n° 1 ([02/01/2020])PermalinkExploring the synergy between Landsat and ASAR towards improving thematic mapping accuracy of optical EO data / Alexander Cass in Applied geomatics, vol 11 n° 3 (September 2019)PermalinkImproving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)PermalinkGeographic space as a living structure for predicting human activities using big data / Bin Jiang in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkInvestigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets / Aelaïg Cournez (2019)PermalinkAerial data acquisition for a digital railway / James Dunthorne in GIM international, vol 32 n° 4 (July - August 2018)PermalinkExploring the sensitivity of coastal inundation modelling to DEM vertical error / Harry West in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkImproving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images / Gabriel Navarro in Estuarine, Coastal and Shelf Science, vol 204 (May 2018)PermalinkA review of the effects of forest management intensity on ecosystem services for northern European temperate forests with a focus on the UK / Louise Sing in Forestry, an international journal of forest research, vol 91 n° 2 (April 2018)PermalinkGraph-based matching of points-of-interest from collaborative geo-datasets / Tessio Novack in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkExtraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkPermalinkPensez à l'échelle du monde pour maîtriser le temps en France et en Grande-Bretagne, 1870-1914 / Isabelle Avila in Cartes & Géomatique, n° 234 (décembre 2017)PermalinkDepicting urban boundaries from a mobility network of spatial interactions : a case study of Great Britain with geo-located Twitter data / Junjun Yin in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkA GIS approach to exploring monetary value on enclosure era property-related maps / Christopher Macdonald Hewitt in Cartographic journal (the), Vol 54 n° 2 (May 2017)PermalinkA method for matching crowd-sourced and authoritative geospatial data / Heshan Du in Transactions in GIS, vol 21 n° 2 (April 2017)PermalinkEtude de l'impact d'un projet de développement sur les propriétés avoisinantes / Sylvain Jourdan (2017)PermalinkIncorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? / Paul Holloway in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkThe impact of land use/land cover scale on modelling urban ecosystem services / Darren R. Grafius in Landscape ecology, vol 31 n° 7 (September 2016)PermalinkUAV monitoring of a largescale environmental project / Alan Roberts in GEO: Geoconnexion international, vol 15 n° 5 (May 2016)Permalink