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The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)
[article]
Titre : The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) Type de document : Article/Communication Auteurs : Muhammad Amir Siddique, Auteur ; Yu Wang, Auteur ; Ninghan Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] champ aléatoire de Markov
[Termes IGN] changement d'occupation du sol
[Termes IGN] changement d'utilisation du sol
[Termes IGN] classification et arbre de régression
[Termes IGN] coefficient de corrélation
[Termes IGN] écosystème urbain
[Termes IGN] flore urbaine
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle de simulation
[Termes IGN] Pékin (Chine)
[Termes IGN] planification urbaine
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] urbanisationRésumé : (auteur) The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km2 (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km2 (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km2 (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots. Numéro de notice : A2021-860 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13224697 Date de publication en ligne : 20/11/2021 En ligne : https://doi.org/10.3390/rs13224697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99074
in Remote sensing > vol 13 n° 22 (November-2 2021) . - n° 4697[article]A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)
[article]
Titre : A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area Type de document : Article/Communication Auteurs : Myung-Jin Jun, Auteur Année de publication : 2021 Article en page(s) : pp 2149 - 2167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] arbre de décision
[Termes IGN] changement d'utilisation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Extreme Gradient Machine
[Termes IGN] modèle de simulation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] Séoul
[Termes IGN] zone urbaineRésumé : (auteur) This study compares the performance of gradient boosting decision tree (GBDT), artificial neural networks (ANNs), and random forests (RF) methods in LUC modeling in the Seoul metropolitan area. The results of this study showed that GBDT and RF have higher predictive power than ANN, indicating that tree-based ensemble methods are an effective technique for LUC prediction. Along with the outstanding predictive performance, the DT-based ensemble models provide insights for understanding which factors drive LUCs in complex urban dynamics with the relative importance and nonlinear marginal effects of predictor variables. The GBDT results indicate that distance to the existing residential site has the highest contribution to urban land use conversion (30.4% of the relative importance), while other significant predictor variables were proximity to industrial and public sites (combined 32.3% of relative importance). New residential development is likely to be adjacent to existing residential sites, but nonresidential development occurs at a distance (about 600 m) from such sites. The distance to the central business district (CBD) had increasing marginal effects on residential land use conversion, while no significant pattern was found for nonresidential land use conversion, indicating that Seoul has experienced more population suburbanization than employment decentralization. Numéro de notice : A2021-756 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887490 Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887490 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98771
in International journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2149 - 2167[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2021111 SL Revue Centre de documentation Revues en salle Disponible Evaluation of global ocean tide models based on tidal gravity observations in China / Hongbo Tan in Geodesy and Geodynamics, vol 12 n° 6 (November 2021)
[article]
Titre : Evaluation of global ocean tide models based on tidal gravity observations in China Type de document : Article/Communication Auteurs : Hongbo Tan, Auteur ; Olivier Francis, Auteur ; Guiju Wu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 451 - 458 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Chine
[Termes IGN] effet de charge
[Termes IGN] marée océanique
[Termes IGN] modèle océanographique
[Termes IGN] surcharge océaniqueRésumé : (auteur) Previous studies show that the calculated loading effects from global ocean tide models do not match actual measurements of gravity attraction and loading effects in Southeast Asia. In this paper, taking advantage of a unique network of gravity tidal stations all over the Chinese mainland, we compare the observed and modeled tidal loading effects on the basis of the most recent global ocean tide models. The results show that the average efficiencies of the ocean tidal loading correction for O1, K1, M2 are 77%, 73% and 59%, respectively. The loading correction efficiencies using recent ocean tidal models are better than the 40 years old Schwiderskis model at coastal stations, but relative worse at stations far from ocean. Numéro de notice : A2021-885 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.geog.2021.08.001 Date de publication en ligne : 13/08/2021 En ligne : https://doi.org/10.1016/j.geog.2021.08.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99208
in Geodesy and Geodynamics > vol 12 n° 6 (November 2021) . - pp 451 - 458[article]Evaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China / Shifa Chen in Natural Hazards, vol 109 n° 2 (November 2021)
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Titre : Evaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China Type de document : Article/Communication Auteurs : Shifa Chen, Auteur ; Wen Liu, Auteur ; Yonghui Bai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1603 - 1628 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] ArcGIS
[Termes IGN] bassin hydrographique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] combinaison linéaire ponderée
[Termes IGN] entropie
[Termes IGN] érosion hydrique
[Termes IGN] modèle numérique de surface
[Termes IGN] pondération
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] risque naturelRésumé : (auteur) Soil erosion is a type of land degradation caused by the interactive interaction of numerous factors, such as natural and socioeconomic conditions of a particular watershed. In this study, a comprehensive integrated methodology was used to evaluate the water erosion hazard in the Zhuxi watershed in Southern China, which is greatly affected by eroded soil. Ten indicators were selected, and a thematic layer map was generated for each indicator using Geographic Information System (GIS). The weight of each evaluation indicator was determined by combining analytic hierarchy process (AHP) with entropy method. Results show that the east and west sections of the Zhuxi watershed have very low and low grades of soil erosion hazards, respectively, and the middle part has the highest hazard. More than 60% of the area has high erosion hazard (moderate to very high). The intensity of soil erosion is lower than its hazard level, especially in high-grade hazard. The obtained results for erosion hazard level can be used to develop conservation strategies for the Zhuxi watershed. This study evaluates soil erosion hazard and offers reference for soil erosion control. Numéro de notice : A2021-851 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-021-04891-7 Date de publication en ligne : 05/07/2021 En ligne : https://doi.org/10.1007/s11069-021-04891-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99036
in Natural Hazards > vol 109 n° 2 (November 2021) . - pp 1603 - 1628[article]Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China / Dongmei Guo in Survey review, Vol 53 n° 381 (November 2021)
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Titre : Geoid determination through the combined least-squares adjustment of GNSS/levelling/gravity networks – a case study in Linyi, China Type de document : Article/Communication Auteurs : Dongmei Guo, Auteur ; Zhixin Xue, Auteur Année de publication : 2021 Article en page(s) : pp 504 - 512 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] analyse de variance
[Termes IGN] Chine
[Termes IGN] compensation par moindres carrés
[Termes IGN] données GNSS
[Termes IGN] géoïde altimétrique
[Termes IGN] géoïde local
[Termes IGN] levé gravimétrique
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle stochastique
[Termes IGN] pondération
[Termes IGN] réseau de nivellement
[Termes IGN] réseau gravimétriqueRésumé : (Auteur) A detailed discussion of the adjustment problems used to combine GNSS/levelling/gravity network data is provided in this paper. The two primary problems inherent to heterogeneous data networks, namely, parametric models that describe the datums and systematic distortions among the available data sets and stochastic models that describe the observational residuals, are described. For parametric models, a relationship between the transformation parameters and the effects of datums and systematic distortions inherent among different height data types is established based on a least squares criterion. For stochastic models, the stochastic errors in GNSS/levelling/gravity data are evaluated, and a Helmert variance component estimation approach is introduced to refine weighting models. Finally, the proposed model is applied to determine the hybrid geoid in Linyi, China. The numerical results validate the capability and effectiveness of the proposed combined adjustment technique for hybrid geoid computations, revealing an achievable external accuracy of ±1.22 cm compared with GNSS/levelling measurements, which can be increased by 0.44 cm compared with classic adjustments of GNSS/levelling/geoid height data. Numéro de notice : A2021-913 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1842642 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/00396265.2020.1842642 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99316
in Survey review > Vol 53 n° 381 (November 2021) . - pp 504 - 512[article]Identifying surface urban heat island drivers and their spatial heterogeneity in China’s 281 cities: An empirical study based on multiscale geographically weighted regression / Lu Niu in Remote sensing, vol 13 n° 21 (November-1 2021)PermalinkLand subsidence in Beijing’s sub-administrative center and its relationship with urban expansion inferred from Sentinel-1/2 observations / Jin Cao in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])PermalinkMulti-sensor aboveground biomass estimation in the broadleaved hyrcanian forest of Iran / Ghasem Ronoud in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])PermalinkMultiscale geographically and temporally weighted regression with a unilateral temporal weighting scheme and its application in the analysis of spatiotemporal characteristics of house prices in Beijing / Zhi Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkA novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lan Xun in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)PermalinkPersistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images / Hari Shankar in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)PermalinkPoint-of-interest (POI) data validation methods: An urban case study / Lih Wei Yeow in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkSemi-automatic extraction of rural roads under the constraint of combined geometric and texture features / Hai Tan in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkTime-series analysis of geodetic reference frame aligned to International Terrestrial Reference Frame / Tae-Suk Bae in Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, vol 39 n° 5 ([01/11/2021])PermalinkA topic model based framework for identifying the distribution of demand for relief supplies using social media data / Ting Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkExploring fuzzy local spatial information algorithms for remote sensing image classification / Anjali Madhu in Remote sensing, vol 13 n° 20 (October-2 2021)PermalinkSuperpixel-based regional-scale grassland community classification using genetic programming with Sentinel-1 SAR and Sentinel-2 multispectral images / Zhenjiang Wu in Remote sensing, vol 13 n° 20 (October-2 2021)PermalinkAnalyzing routes in Ottoman Greater Syria using historical GIS: The 1849 Saida map / Motti Zohar in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkBi- and three-dimensional urban change detection using sentinel-1 SAR temporal series / Meiqin Che in Geoinformatica, vol 25 n° 4 (October 2021)PermalinkComplexity-based matching between image resolution and map scale for multiscale image-map generation / Qian Peng in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)PermalinkEarly detection of pine wilt disease using deep learning algorithms and UAV-based multispectral imagery / Run Yu in Forest ecology and management, vol 497 (October-1 2021)PermalinkField scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques / Rajkumar Dhakar in Geocarto international, vol 36 n° 18 ([01/10/2021])PermalinkFlood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model / Gaurav Talukdar in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkInvestigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkJoint inversion of ground gravity data and satellite gravity gradients between Nepal and Bhutan: New insights on structural and seismic segmentation of the Himalayan arc / Rodolphe Cattin in Physics and chemistry of the Earth (A/B/C), vol 123 (October 2021)Permalink