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A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques / Olutoyin Adeola Fashae in Geocarto international, vol 35 n° 9 ([01/07/2020])
[article]
Titre : A simple distributed water balance model for an urbanized river basin using remote sensing and GIS techniques Type de document : Article/Communication Auteurs : Olutoyin Adeola Fashae, Auteur ; Rotimi Oluseyi Obateru, Auteur ; Adeyemi Oludap Olusola, Auteur Année de publication : 2020 Article en page(s) : pp 954 - 975 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique subsaharienne
[Termes IGN] ArcGIS
[Termes IGN] bassin hydrographique
[Termes IGN] bilan hydrique
[Termes IGN] classification dirigée
[Termes IGN] image Landsat
[Termes IGN] modèle numérique de surface
[Termes IGN] planification urbaine
[Termes IGN] série temporelle
[Termes IGN] stress hydrique
[Termes IGN] système d'information géographique
[Termes IGN] télédétection
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineRésumé : (auteur) Across most urban centres, adequate supply of water becomes essential for the urban poor. Attempts at ensuring water availability has been formulated using standard water models. This study developed a water balance model using Remote Sensing and GIS techniques during periods of water surplus and deficit across pre-millennium (1996 – 2000) and the post-millennium (2010 – 2014) periods within an urbanized Sub-Saharan city. Digital Elevation Model of the basin was prepared to generate flow direction and to delimit the watershed using ArcHydro tools in ArcGIS 10.3. Supervised classification was used to delineate the landuse classes from Landsat imageries. The result revealed that 1996, 1997, 1998, 2000, 2010 and 2013 were periods of water deficit, while 1999, 2011, 2012 and 2014 were periods of water surplus. This study affirmed the need to reactivate institutional frameworks that are responsible for assessment, conservation, management and planning of water resources for sustainable utilization. Numéro de notice : A2020-399 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1557261 Date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2018.1557261 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95435
in Geocarto international > vol 35 n° 9 [01/07/2020] . - pp 954 - 975[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020091 RAB Revue Centre de documentation En réserve L003 Disponible Spatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships / Chao Song in Annals of GIS, vol 26 n° 3 (July 2020)
[article]
Titre : Spatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships Type de document : Article/Communication Auteurs : Chao Song, Auteur ; Xun Shi, Auteur ; Jinfeng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 277 - 291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Chine
[Termes IGN] données socio-économiques
[Termes IGN] estimation bayesienne
[Termes IGN] géostatistique
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] régression
[Termes IGN] régression géographiquement pondérée
[Termes IGN] santé
[Termes IGN] série temporelleRésumé : (auteur) Local regression has an advantage over global regression by allowing coefficients that qualify variables relationships being heterogeneous, where such varying regression relationships are nonstationarity. Spatiotemporally Varying Coefficients (STVC) model is the first Bayesian-based local spatiotemporal regression approach, intending to simultaneously detect spatial and temporal nonstationarity for heterogeneous response-covariate variables relationships, through separately estimating posterior local-scale coefficients over different space areas and time frames. In this paper, we first presented a general Bayesian STVC modelling paradigm as a specification guide to show its commonality in broader geospatial research. Then, we employed it to solve a real-world issue concerning spatiotemporal healthcare-socioeconomic relations, for which we derived data of county-level hospital beds number per capita, as well as data of related socioeconomic factors in northeast China during 2002–2011. Results showed that the STVC model surpassed all the other comparative regressions, in terms of both Bayesian model fitness and predictive ability. Globally, resident savings, financial institutions loans, GDP, and primary industry were identified as key socioeconomic conditions affecting healthcare resources in Northeast China. Temporally, with Time-Coefficients (TC) plots, we found that after 2011, GDP and primary industry would further help improve the overall healthcare level of northeast China. Spatially, with Space-Coefficients (SC) maps, we could directly identify the relative contribution of four socioeconomic covariates’ impacts on healthcare within each administrative county. Bayesian STVC model is an essential development and extension of the local regression family for exploring the spatiotemporal heterogeneous variables relationships, especially under Bayesian statistics, as well as GIScience and spatial statistics. Numéro de notice : A2020-582 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1782469 Date de publication en ligne : 08/08/2020 En ligne : https://doi.org/10.1080/19475683.2020.1782469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95904
in Annals of GIS > vol 26 n° 3 (July 2020) . - pp 277 - 291[article]Temporal and spatial variations of monsoonal upwelling along the South West and East coasts of India / Shailee Patel in Marine geodesy, Vol 43 n° 4 (July 2020)
[article]
Titre : Temporal and spatial variations of monsoonal upwelling along the South West and East coasts of India Type de document : Article/Communication Auteurs : Shailee Patel, Auteur ; Manisha Vithalpura, Auteur ; Subrat Kumar Mallick, Auteur ; Smitha Ratheesh, Auteur Année de publication : 2020 Article en page(s) : pp 414 - 432 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] aménagement du littoral
[Termes IGN] changement climatique
[Termes IGN] Inde
[Termes IGN] mousson
[Termes IGN] série temporelle
[Termes IGN] ventRésumé : (Auteur) The implicit/explicit impact of global warming or the anthropogenic climate change on the coastal upwelling processes affects the marine ecosystem significantly and continuous monitoring of the coastal upwelling along the coastal regions is essential. The Ekman transport due to alongshore winds and Ekman pumping due to wind stress curl play important roles on the coastal upwelling, especially along the southern part of Indian peninsula. Upwelling Indexes based on wind and SST are computed in the study to demarcate the upwelling features along the coasts. Since upwelling leaves its trail on surface features, long time series of satellite-derived wind, Sea Surface Temperature (SST), Sea level anomaly (SLA) and Surface Chlorophyll-a concentration (Chl-a) are analyzed to understand the upwelling along the coastal regions of south India. The present study reveals a decrease in the intensity of upwelling along the western coast and a slight increase all along the eastern coast of southern India during summer monsoon. Numéro de notice : A2020-250 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2019.1703061 Date de publication en ligne : 19/12/2019 En ligne : https://doi.org/10.1080/01490419.2019.1703061 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95375
in Marine geodesy > Vol 43 n° 4 (July 2020) . - pp 414 - 432[article]An 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)
[article]
Titre : An empirical study on the intra-urban goods movement patterns using logistics big data Type de document : Article/Communication Auteurs : Pengxiang Zhao, Auteur ; Wenzhong Shi, Auteur ; Tao Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1089 - 1116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] analyse systémique
[Termes IGN] fret
[Termes IGN] gestion urbaine
[Termes IGN] Hong-Kong
[Termes IGN] interaction spatiale
[Termes IGN] logistique
[Termes IGN] objet mobile
[Termes IGN] origine - destination
[Termes IGN] plan de déplacement urbain
[Termes IGN] réseau de transport
[Termes IGN] série temporelle
[Termes IGN] trafic urbainRésumé : (auteur) Movement patterns of intra-urban goods/things and the ways they differ from human mobility and traffic flow patterns have seldom been explored due to data access and methodological limitations, especially from systemic and long timescale perspectives. However, urban logistics big data are increasingly available, enabling unprecedented spatial and temporal resolutions to this issue. This research proposes an analytical framework for exploring intra-urban goods movement patterns by integrating spatial analysis, network analysis and spatial interaction analysis. Using daily urban logistics big data (over 10 million orders) provided by the largest online logistics company in Hong Kong (GoGoVan) from 2014 to 2016, we analyzed two spatial characteristics (displacement and direction) of urban goods movement. Results showed that the distribution of goods displaceFower law or exponential distribution of human mobility trends. The origin–destination flows of goods were used to build a spatially embedded network, revealing that Hong Kong became increasingly connected through intra-urban freight movement. Finally, spatial interaction characteristics were revealed using a fitting gravity model. Distance lacked substantial influence on the spatial interaction of goods movement. These findings have policy implications to intra-urban logistics and urban transport planning. Numéro de notice : A2020-268 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1520236 Date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/13658816.2018.1520236 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95039
in International journal of geographical information science IJGIS > vol 34 n° 6 (June 2020) . - pp 1089 - 1116[article]An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)
[article]
Titre : An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis Type de document : Article/Communication Auteurs : Lei Zhou, Auteur ; Siyu Wang, Auteur ; Mingyi Du, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] changement climatique
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] couvert végétal
[Termes IGN] désert
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] image Landsat
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (auteur) The combined study of vegetation coverage (VC) and land use change provides important scientific guidance for the restoration and protection of arid regions. Taking Hongjian Nur (HJN) Lake in the desert region as a case study, the VC of this area was calculated using a normalized difference vegetation index (NDVI), which is based on a mixed pixel decomposition method. A grey forecasting model (GM) (1, 1) was used to predict future VC. The driving factors of VC and land use change were analyzed. The results indicate that the average VC of the whole watershed showed a gradual increase from 0.29 to 0.49 during 2000–2017. The prediction results of the GM VC showed that the greening trend is projected to continue until 2027. The area of farmland in the watershed increased significantly and its area was mainly converted from unused land, grassland, and forest. The reason for increased VC may be that the combination of the exploitation of unused land and climate change, which is contrary to the country’s sustainable development goals (SDG; goal 15). Therefore, the particularities of the local ecological environment in China’s desert area needs to be considered in the development of ecological engineering projects. Numéro de notice : A2020-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060364 Date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060364 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95163
in ISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 24 p.[article]Coastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)PermalinkImproved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkMonitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science, Vol 77 n° 2 (June 2020)PermalinkValidation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz / Ana Aldarias in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkHomogenizing GPS integrated water vapor time series: Benchmarking break detection methods on synthetic data sets / Roeland Van Malderen in Earth and space science, vol 7 n° 5 (May 2020)PermalinkSelf-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors / Boris Kargoll in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkAccounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities / Clément Benoist in Journal of geodynamics, vol 135 (April 2020)PermalinkAntenna phase center correction differences from robot and chamber calibrations: the case study LEIAR25 / Grzegorz Krzan in GPS solutions, vol 24 n° 2 (April 2020)PermalinkAssessment of geocenter motion estimates from the IGS second reprocessing / Yifang Ma in GPS solutions, vol 24 n° 2 (April 2020)PermalinkComparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series / Zhao Li in Journal of geodesy, vol 94 n°4 (April 2020)PermalinkImproving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series / Maylis Lopes in Methods in ecology and evolution, vol 11 n° 4 (April 2020)PermalinkSpatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkTemporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)PermalinkWavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data / Niraj Priyadarshi in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkEvaluation of the high-rate GNSS-PPP method for vertical structural motion / Mosbeh R. Kaloop in Survey review, vol 52 n° 371 (March 2020)PermalinkRecent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkA sequential Monte Carlo framework for noise filtering in InSAR time series / Mehdi Khaki in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkSmoothing and predicting celestial pole offsets using a Kalman filter and smoother / Jolanta Nastula in Journal of geodesy, Vol 94 n°3 (March 2020)PermalinkSpectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkA breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals / Olivier Bock in Statistics and Computing, vol 29 n° 1 (February 2020)PermalinkEstimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)PermalinkMapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkMODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n° 1 (2020)PermalinkPrediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)PermalinkAdvanced GNSS tropospheric products for monitoring severe weather events and climate, ch. 5. Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) / Olivier Bock (2020)PermalinkAnalyse des surcharges hydrologiques observées par géodésie spatiale avec l’outil Multi Singular Spectrum Analysis / Louis Bonhomme (2020)PermalinkApplication of geographic Information system and remote sensing in multiple criteria analysis to identify priority areas for biodiversity conservation in Vietnam / Xuan Dinh Vu (2020)PermalinkCaractérisation de la contribution des charges hydrologiques, atmosphériques et océaniques aux séries temporelles de position GNSS : analyse comparée des modèles de charge et de mouvement du géocentre / Elie-Alban Lescout (2020)PermalinkCartographie des essences forestières à partir de séries temporelles d’images satellitaires à hautes résolutions : stabilité des prédictions, autocorrélation spatiale et cohérence avec la phénologie observée in situ / Nicolas Karasiak (2020)PermalinkClassification of time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne (2020)PermalinkDétermination conjointe des inondations et du type d’eau au moyen de l’imagerie multi-spectrale / Sabrine Amzil (2020)PermalinkDevelopment of new homogenisation methods for GNSS atmospheric data. Application to the analysis of climate trends and variability / Annarosa Quarello (2020)PermalinkDéveloppement d’outils ad-hoc open source pour des applications Web cartographiques / Bruno Verchère (2020)PermalinkÉtude de la vapeur d’eau atmosphérique à partir de données GNSS dans le bassin sud-ouest de l’océan Indien et applications à l’étude du climat et des cyclones tropicaux / Edouard Lees (2020)PermalinkEtudes des dynamiques spatiales d’évolution de l’occupation et de l’utilisation des sols dans la fenêtre lacustre camerounaise du lac Tchad et son arrière-pays à partir des grandes sécheresses sahéliennes de 1970 / Paul Gérard Gbetkom (2020)PermalinkInversion de données PolSAR en bande P pour l'estimation de la biomasse forestière / Colette Gelas (2020)PermalinkLightweight temporal self-attention for classifying satellite images time series / Vivien Sainte Fare Garnot (2020)PermalinkPermalinkPermalinkA new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)PermalinkOn the joint exploitation of optical and SAR satellite imagery for grassland monitoring / Anatol Garioud (2020)PermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)PermalinkSatellite image time series classification with pixel-set encoders and temporal self-attention / Vivien Sainte Fare Garnot (2020)PermalinkSemi-kinematic geodetic reference frame based on the ITRF2014 for Malaysia / M. Azhari in Journal of geodetic science, vol 10 n° 1 (January 2020)Permalink