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Mining regional patterns of land use with adaptive adjacent criteria / Xinmeng Tu in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
[article]
Titre : Mining regional patterns of land use with adaptive adjacent criteria Type de document : Article/Communication Auteurs : Xinmeng Tu, Auteur ; Zhenjie Chen, Auteur ; Beibei Wang, Auteur ; changqing Xu, Auteur Année de publication : 2020 Article en page(s) : pp 418 - 431 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] adjacence
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] construction
[Termes IGN] extraction de modèle
[Termes IGN] filtrage spatiotemporel
[Termes IGN] occupation du sol
[Termes IGN] polygone
[Termes IGN] région
[Termes IGN] relation spatiale
[Termes IGN] surface cultivée
[Termes IGN] urbanisation
[Termes IGN] utilisation du sol
[Termes IGN] variogrammeRésumé : (auteur) Land use/cover changes (LULC) are complicated and regionally diverse. When mining regional patterns, the use of a spatial relationship that is determined without considering the spatial correlation among geographical objects can lead to problematic results, e.g. mistakenly treating unrelated objects as adjacent. Additionally, traditional prevalence measures are unstable for uneven datasets such as LULC, wherein some land-use change types show small numbers and uneven quantities, and valuable rules for some land-use categories may be ignored. Therefore, we proposed a regional pattern mining method. First, we developed adaptive adjacent criteria, which can be automatically generated for each specific zone to define adjacency for better spatial-temporal mining. Then, a combinational decision model was built to improve the stability of the prevalence measure, which was used to filter out the insignificant spatial-temporal rules. Furthermore, we proposed two levels of land-use pattern mining, i.e. cluster-level mining and polygon-level mining, to first discover hot-spot areas where similar land-use change has occurred frequently and then to determine the location, frequency, and change time of rules related to different land-use activities. The proposed method was used for mining the dependence of land use and regional patterns on land-use changes. Results show that the proposed method can determine the spatial dependence between the land-use categories, as well as regional patterns of land-use changes. According to our research, the study area, Xinbei District, China, is undergoing land-use change involving rapid urbanization, extensive transportation construction, and losses of farmland. Numéro de notice : A2020-487 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1761452 Date de publication en ligne : 18/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1761452 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95655
in Cartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 418 - 431[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2020051 RAB Revue Centre de documentation En réserve L003 Disponible A novel algorithm to estimate phytoplankton carbon concentration in inland lakes using Sentinel-3 OLCI images / Heng Lyu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
[article]
Titre : A novel algorithm to estimate phytoplankton carbon concentration in inland lakes using Sentinel-3 OLCI images Type de document : Article/Communication Auteurs : Heng Lyu, Auteur ; Zhiqian Yang, Auteur ; Lei Shi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 6512 - 6523 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] changement climatique
[Termes IGN] Chine
[Termes IGN] chlorophylle
[Termes IGN] corrélation
[Termes IGN] image Sentinel-OLCI
[Termes IGN] lac
[Termes IGN] plancton
[Termes IGN] réflectance
[Termes IGN] série temporelle
[Termes IGN] teneur en carboneRésumé : (auteur) Phytoplankton carbon, an important biogeochemical and ecological parameter, plays a critical role in the carbon cycle and in global warming reduction. Estimation of phytoplankton carbon in inland waters on a large scale using remote sensing is useful for understanding, evaluating, and monitoring the carbon dynamics, and, in particular, for determining the spatial–temporal variation of primary production in inland waters. In a correlation analysis of the phytoplankton carbon concentration and water components, the result revealed no significant correlation between the chlorophyll-a concentration and phytoplankton carbon concentration in inland waters. However, the absorption peak height of particles at 675 nm, which is defined as the absorption at 675 nm subtracted by that at 660 nm, was found to be closely correlated with the phytoplankton carbon concentration. Thus, the absorption peak height of particles at 675 nm could be used as an indicator of the phytoplankton carbon concentration. A semianalytical method based on the remote-sensing reflectance in Sentinel-3 Ocean and Land Color Instrument (OLCI) bands 8, 9, and 17 was developed to derive the absorption peak of particles at a wavelength of 675 nm. Finally, an algorithm for estimating the phytoplankton carbon concentration in inland waters using OLCI bands 8, 9, and 17 was constructed. From 2013 to 2018, eight field campaigns were conducted in inland lakes in different seasons, and the optical properties, optically active water components, and phytoplankton carbon concentrations were obtained. An assessment of its accuracy using an independent data set demonstrated that the algorithm performance is acceptable (mean absolute percentage error, 48.6%, and root mean square error, 0.36 mg/L). As a demonstration, the algorithm was successfully applied to map the phytoplankton carbon concentration in Taihu Lake and Chaohu Lake, China, using OLCI images acquired on December 5, 2017, and August 5, 2018 and December 8, 2... Numéro de notice : A2020-531 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2977080 Date de publication en ligne : 12/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2977080 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95714
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 9 (September 2020) . - pp 6512 - 6523[article]Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique / Hao Li in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
[article]
Titre : Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique Type de document : Article/Communication Auteurs : Hao Li, Auteur ; Benjamin Herfort, Auteur ; Wei Huang, Auteur Année de publication : 2020 Article en page(s) : pp 41-51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] carte sanitaire
[Termes IGN] cartographie collaborative
[Termes IGN] données localisées des bénévoles
[Termes IGN] géographie sociale
[Termes IGN] inventaire du bâti
[Termes IGN] Mozambique
[Termes IGN] OpenStreetMap
[Termes IGN] qualité des données
[Termes IGN] TwitterRésumé : (auteur) Accurate and detailed geographical information digitizing human activity patterns plays an essential role in response to natural disasters. Volunteered geographical information, in particular OpenStreetMap (OSM), shows great potential in providing the knowledge of human settlements to support humanitarian aid, while the availability and quality of OSM remains a major concern. The majority of existing works in assessing OSM data quality focus on either extrinsic or intrinsic analysis, which is insufficient to fulfill the humanitarian mapping scenario to a certain degree. This paper aims to explore OSM missing built-up areas from an integrative perspective of social sensing and remote sensing. First, applying hierarchical DBSCAN clustering algorithm, the clusters of geo-tagged tweets are generated as proxies of human active regions. Then a deep learning based model fine-tuned on existing OSM data is proposed to further map the missing built-up areas. Hit by Cyclone Idai and Kenneth in 2019, the Republic of Mozambique is selected as the study area to evaluate the proposed method at a national scale. As a result, 13 OSM missing built-up areas are identified and mapped with an over 90% overall accuracy, being competitive compared to state-of-the-art products, which confirms the effectiveness of the proposed method. Numéro de notice : A2020-350 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.007 Date de publication en ligne : 07/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95233
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 41-51[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Los Angeles as a digital place: The geographies of user‐generated content / Andrea Ballatore in Transactions in GIS, Vol 24 n° 4 (August 2020)
[article]
Titre : Los Angeles as a digital place: The geographies of user‐generated content Type de document : Article/Communication Auteurs : Andrea Ballatore, Auteur ; Stefano de Sabbata, Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] centre urbain
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] distribution spatiale
[Termes IGN] données multisources
[Termes IGN] données socio-économiques
[Termes IGN] exploration de données géographiques
[Termes IGN] Foursquare
[Termes IGN] Los Angeles
[Termes IGN] modèle de régression
[Termes IGN] OpenStreetMap
[Termes IGN] participation du public
[Termes IGN] représentation géographique
[Termes IGN] réseau social
[Termes IGN] réseau social géodépendant
[Termes IGN] TwitterRésumé : (auteur) Online representations of places are becoming pivotal in informing our understanding of urban life. Content production on online platforms is grounded in the geography of their users and their digital infrastructure. These constraints shape place representation, that is, the amount, quality, and type of digital information available in a geographic area. In this article we study the place representation of user‐generated content (UGC) in Los Angeles County, relating the spatial distribution of the data to its geo‐demographic context. Adopting a comparative and multi‐platform approach, this quantitative analysis investigates the spatial relationship between four diverse UGC datasets and their context at the census tract level (about 685,000 geo‐located tweets, 9,700 Wikipedia pages, 4 million OpenStreetMap objects, and 180,000 Foursquare venues). The context includes the ethnicity, age, income, education, and deprivation of residents, as well as public infrastructure. An exploratory spatial analysis and regression‐based models indicate that the four UGC platforms possess distinct geographies of place representation. To a moderate extent, the presence of Twitter, OpenStreetMap, and Foursquare data is influenced by population density, ethnicity, education, and income. However, each platform responds to different socio‐economic factors and clusters emerge in disparate hotspots. Unexpectedly, Twitter data tend to be located in denser, more deprived areas, and the geography of Wikipedia appears peculiar and harder to explain. These trends are compared with previous findings for the area of Greater London. Numéro de notice : A2020-671 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12600 Date de publication en ligne : 02/01/2020 En ligne : https://doi.org/10.1111/tgis.12600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96156
in Transactions in GIS > Vol 24 n° 4 (August 2020) . - 23 p.[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]Reintroduction of the European bison (Bison bonasus) in central-eastern Europe: a case study / Cathlin M. Lord in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)PermalinkBehavior-based location recommendation on location-based social networks / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 24 n° 3 (July 2020)PermalinkExploratory bivariate and multivariate geovisualizations of a social vulnerability index / Georgianna Strode in Cartographic perspectives, n° 95 (July 2020)PermalinkIntegration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkMicro diagrams: visualization of categorical point data from location-based social media / Mathias Gröbe in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)PermalinkAn empirical study on the intra-urban goods movement patterns using logistics big data / Pengxiang Zhao in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkMapping areas of asynchronous‐temporal interaction in animal‐telemetry data / Brendan A. Hoover in Transactions in GIS, Vol 24 n° 3 (June 2020)PermalinkA multi-factor spatial optimization approach for emergency medical facilities in Beijing / Liang Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkPrediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)PermalinkSpatio-temporal evaluation of transport accessibility of the Istanbul metrobus line / Wasim Shoman in Geocarto international, vol 35 n° 6 ([01/05/2020])Permalink