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Les eaux de pluie maîtrisées ou en excès / Pierre Clergeot in Géomètre, n° 2173 (octobre 2019)

Public [article]  inGéomètre > n° 2173 (octobre 2019) . - pp 32 - 47 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 descripteurs IGN] aquifère [Termes descripteurs IGN] bassin hydrographique [Termes descripteurs IGN] carte topographique [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] collectivité territoriale [Termes descripteurs IGN] cours d'eau [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] drainage [Termes descripteurs IGN] eau pluviale [Termes descripteurs IGN] écoulement des eaux [Termes descripteurs IGN] gestion de l'eau [Termes descripteurs IGN] inondation [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] réseau d'assainissement [Termes descripteurs IGN] ruissellement [Termes descripteurs IGN] talweg [Termes descripteurs IGN] terminologie [Termes descripteurs IGN] urbanisme [Termes descripteurs IGN] zone humide [Termes descripteurs IGN] zone urbaine Note 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 urbaines Numéro de notice : A2019-487 Nature : Article nature-HAL : ArtSansCL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93685 [article]

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A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy / Yan Zhou in Transactions in GIS, Vol 23 n° 5 (October 2019)  

Public [article]  inTransactions in GIS > Vol 23 n° 5 (October 2019) . - pp 1125 - 1151 Titre : A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy Type de document : Article/Communication Auteurs : Yan Zhou, Auteur ; Yanxi Li, Auteur ; Qing Zhu, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1125 - 1151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] bicyclette [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] gestion prévisionnelle [Termes descripteurs IGN] New York (Etats-Unis ; ville) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] SOLAP [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] Washington D.C. Résumé : (auteur) Bike‐sharing systems have been widely used in major cities across the world. As bike borrowing and return at different stations in different periods are not balanced, the bikes in a bike‐sharing system need to be redistributed frequently to rebalance the system. Therefore, traffic flow forecasting of the bike‐sharing system is an important issue, as this is conducive to achieving rebalancing of the bike system. In this article, we present a new traffic flow prediction approach based on the temporal links in dynamic traffic flow networks. A station clustering algorithm is first introduced to cluster stations into groups. A temporal link prediction method based on the dynamic traffic flow network method (STW+M) is then proposed to predict the traffic flow between stations. In our method, the non‐negative tensor decomposition and time‐series analysis model capture the rich information (temporal variabilities, spatial characteristics, and weather information) of the across‐clusters transition. Then, a temporal link prediction strategy is used to forecast potential links and weights in the traffic flow network by investigating both the network structure and the results of tensor computations. In order to assess the methods proposed in this article, we have used the data of bike‐sharing systems in New York and Washington, DC to conduct bike traffic prediction and the experimental results have shown that our method produces the lowest root mean square error (RMSE) and mean square error (MSE). Compared to four prediction methods from the literature, our RMSE and MSE of the two datasets have been lowered by an average of 2.55 (Washington, DC) and 2.41 (New York) and 3.35 (Washington, DC) and 2.96 (New York), respectively. The results show that the proposed approach improves predictions of traffic flow. Numéro de notice : A2019-551 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12560 date de publication en ligne : 03/07/2019 En ligne : https://doi.org/10.1111/tgis.12560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94201 [article]

Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, sans n° (2019)  

Public [article]  inEuropean journal of remote sensing > sans n° (2019) . - 11 p. Titre : Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale Type de document : Article/Communication Auteurs : Elena Barbierato, Auteur ; Iacopo Bernetti, Auteur ; Irene Capecchi, Auteur ; Claudio Saragosa, Auteur Année de publication : 2019 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] climat urbain [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] flore urbaine [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] Toscane (Italie) Résumé : (auteur) The climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfortable and healthy climate. Due to the predicted global temperature increase, urban climate is likely to become more uncomfortable, especially in summer when an increase in heat stress is expected. Urban forestry has been proposed as one approach for mitigating the human health consequences of increased temperature resulting from climate change. The aims of the current research were to (a) provide a transferable methodology useful for analyzing the effect of urban trees on surface temperature reduction, particularly in public spaces, and (b) provide high-resolution urban mapping for adaptation strategies to climate change based on green space projects. To achieve the established aims, we developed a methodology that uses multisource data: LiDAR data, high-resolution Landsat imagery, global climate model data from CMIP5 (IPPC Fifth Assessment), and data from meteorological stations. The proposed model can be a useful tool for validating the efficiency of design simulations of new green spaces for temperature mitigation. Numéro de notice : A2019-320 Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2019.1646104 date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.1080/22797254.2019.1646104 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93266 [article]

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees / Matthew P. Peters in Ecology and evolution, vol 9 n° 15 (August 2019)  

Public [article]  inEcology and evolution > vol 9 n° 15 (August 2019) . - pp 8876 - 8899 Titre : Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees Type de document : Article/Communication Auteurs : Matthew P. Peters, Auteur ; Louis R. Iverson, Auteur ; Anantha M. Prasad, Auteur ; Stephen N. Matthews, Auteur Année de publication : 2019 Article en page(s) : pp 8876 - 8899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] arbre (flore) [Termes descripteurs IGN] densité [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] placette d'échantillonnage [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Species distribution models (SDMs) provide useful information about potential presence or absence, and environmental conditions suitable for a species; and high‐resolution models across large extents are desirable. A primary feature of SDMs is the underlying spatial resolution, which can be chosen for many reasons, though we propose that a hybrid lattice, in which grid cell sizes vary with the density of forest inventory plots, provides benefits over uniform grids. We examine how the spatial grain size affected overall model performance for the Random Forest‐based SDM, DISTRIB, which was updated with recent forest inventories, climate, and soil data, and used a hybrid lattice derived from inventory densities. Modeled habitat suitability was compared between a uniform grid of 10 × 10 and a hybrid lattice of 10 × 10 and 20 × 20 km grids to assess potential improvements. The resulting DISTRIB‐II models for 125 eastern U.S. tree species provide information on individual habitat suitability that can be mapped and statistically analyzed to understand current and potential changes. Model performance metrics were comparable among the hybrid lattice and 10‐km grids; however, the hybrid lattice models generally had higher overall model reliability scores and were likely more representative of the inventory data. Our efforts to update DISTRIB models with current information aims to produce a more representative depiction of recent conditions by accounting for the spatial density of forest inventory data and using the latest climate data. Additionally, we developed an approach that leverages a hybrid lattice to maximize the spatial information within the models and recommend that similar modeling efforts be used to evaluate the spatial density of response and predictor data and derive a modeling grid that best represents the environment. Numéro de notice : A2019-374 Thématique : FORET Nature : Article DOI : 10.1002/ece3.5445 date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1002/ece3.5445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93415 [article]

High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)  

Public [article]  inJournal of geodesy > vol 93 n°6 (June 2019) . - pp 819 - 835 Titre : High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland Type de document : Article/Communication Auteurs : Karina Wilgan, Auteur ; Alain Geiger, Auteur Année de publication : 2019 Article en page(s) : pp 819 - 835 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] Alpes [Termes descripteurs IGN] collocation par moindres carrés [Termes descripteurs IGN] correction troposphérique [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] précision de l'estimation [Termes descripteurs IGN] prévision météorologique [Termes descripteurs IGN] réfraction [Termes descripteurs IGN] retard troposphérique [Termes descripteurs IGN] retard troposphérique zénithal [Termes descripteurs IGN] Suisse Résumé : (auteur) The tropospheric delay of a microwave signal affects all space geodetic techniques. One possibility of modeling the delay is by introducing tropospheric models from external data sources. In this study, we present high-resolution models of tropospheric total refractivity and zenith total delay (ZTD) for the alpine area in Switzerland. The troposphere models are based on different combinations of data sources, including numerical weather prediction (NWP) model COSMO-1 with high spatial resolution of 1.1 km × 1.1 km, GNSS data from permanent geodetic stations and GPS L1-only data from low-cost permanent stations. The tropospheric parameters are interpolated to the arbitrary locations by the least-squares collocation method using the in-house developed software package COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays). The first goal of this study is to validate the obtained models with the reference radiosonde and GNSS data to show the improvement w.r.t. the previous studies that used lower resolution input data. In case of total refractivity, the profiles reconstructed from COSMO-1 model show the best agreement with the reference radiosonde measurements, with an average bias of 1.1 ppm (0.6% of the total refractivity value along a vertical profile) and standard deviation of 2.6 ppm (1.6%) averaged from the whole profile. The radiosondes are assimilated into COSMO-1 model; thus, a high correlation is expected, and this comparison is not independent. In case of ZTD, the GNSS-based model shows the highest agreement with the reference GNSS data, with an average bias of 0.2 mm (0.01%) and standard deviation of 4.3 mm (0.2%). For COSMO-based model, the agreement is also very high, especially compared to our previous studies with lower resolution NWPs. The average bias is equal to − 2.5 mm (0.1%) with standard deviation of 9.2 mm (0.5%). The second goal of this study is to test the feasibility of calculating high-resolution troposphere models over a limited area from coarser data sets. We calculate the ZTD models with spatial resolution of 20 m for a test area in Matter Valley. We include the information from the low-cost GPS stations (X-Sense), to also assess the performance and future usability of such stations. We validate the models based on three data sources w.r.t. the reference GNSS data. For the station located inside the area of the study, the models have an agreement of few mm with the reference data. For stations located further away from the study area, the agreement for X-Sense is smaller, but the standard deviations of residuals are still below 15 mm. We consider also another factor of evaluating the high-resolution models, i.e., spatial variability of the data. For designing a GNSS network, also for the tropospheric estimates, the height variability of the network may be as important as the horizontal distribution. The GNSS-based models are built from the coarsest network; thus, their variability is the lowest. The variability of X-Sense-based stations is the highest; thus, such data may be suitable for building troposphere models for very high-resolution applications. Numéro de notice : A2019-350 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1203-6 date de publication en ligne : 01/10/2018 En ligne : https://doi.org/10.1007/s00190-018-1203-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93394 [article]

Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])  

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Temporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) / Helge Dietrich in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

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The impact of relative and absolute GNSS positioning strategies on estimated coordinates and ZWD in the framework of meteorological applications / Alessandro Fermi in Applied geomatics, vol 11 n° 1 (March 2019)  

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A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor / Liangke Huang in Journal of geodesy, vol 93 n° 2 (February 2019)  

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Global IWV trends and variability in atmospheric reanalyses and GPS observations / Ana-Claudia Parracho in Atmospheric chemistry and physics, vol 18 n° 22 ([01/11/2018])  

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Multi‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12 / Samiro Khodayar in Quarterly Journal of the Royal Meteorological Society, vol 144 n° 717 (October 2018 Part B)  

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Association rules-based multivariate analysis and visualization of spatiotemporal climate data / Feng Wang in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)  

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A two-stage tropospheric correction model combining data from GNSS and numerical weather model / Jan Douša in GPS solutions, vol 22 n° 3 (July 2018)  

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Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY / Dunya Alraddawi in Atmospheric measurement techniques, vol 11 n° 5 (May 2018)  

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Modeling tropospheric wet delays with national GNSS reference network in China for BeiDou precise point positioning / Fu Zheng in Journal of geodesy, vol 92 n° 5 (May 2018)  

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