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Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)
[article]
Titre : Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax Type de document : Article/Communication Auteurs : Jose Morales, Auteur ; Alfred Stein, Auteur ; Johannes Flacke, Auteur ; Jaap Zevenbergen, Auteur Année de publication : 2020 Article en page(s) : pp 1451 - 1474 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de la valeur
[Termes IGN] analyse syntaxique
[Termes IGN] cartographie statistique
[Termes IGN] estimation quantitative
[Termes IGN] évaluation foncière
[Termes IGN] géostatistique
[Termes IGN] Guatemala
[Termes IGN] krigeage
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] modèle de simulation
[Termes IGN] régression
[Termes IGN] système d'information foncièreRésumé : (auteur) Spatial information of land values is fundamental for planners and policy makers. Individual appraisals are costly, explaining the need for predictive modelling. Recent work has investigated using Space Syntax to analyse urban access and explain land values. However, the spatial dependence of urban land markets has not been addressed in such studies. Further, the selection of meaningful variables is commonly conducted under non-spatialized modelling conditions. The objective of this paper is to construct a land value map using a geostatistical approach using Space Syntax and a spatialized variable selection. The methodology is applied in Guatemala City. We used an existing dataset of residential land value appraisals and accessibility metrics. Regression-kriging was used to conduct variable selection and derive a model for spatial prediction. The prediction accuracy is compared with a multivariate regression. The results show that a spatialized variable selection yields a more parsimonious model with higher prediction accuracy. New insights were found on how Space Syntax explains land value variability when also modelling the spatial dependence. Space Syntax can contribute with relevant spatialized information for predictive land value modelling purposes. Finally, the spatial modelling framework facilitates the production of spatial information of land values that is relevant for planning practice. Numéro de notice : A2020-306 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1725014 Date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1725014 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95148
in International journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1451 - 1474[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2020071 RAB Revue Centre de documentation En réserve L003 Disponible Prognostic evaluation of the impact of restricted horizon visibility on the accuracy of position (coordinates) obtained with GNSS based on empirical data / Oleksandr Yanchuk in Geodesy and cartography, vol 46 n° 2 (July 2020)
[article]
Titre : Prognostic evaluation of the impact of restricted horizon visibility on the accuracy of position (coordinates) obtained with GNSS based on empirical data Type de document : Article/Communication Auteurs : Oleksandr Yanchuk, Auteur ; Roman Shulgan, Auteur Année de publication : 2020 Article en page(s) : pp 67 - 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] erreur moyenne quadratique
[Termes IGN] ligne de base
[Termes IGN] récepteur GNSS
[Termes IGN] régressionRésumé : (auteur) In this research, the practical check of regression equation to calculate the prognostic root mean square error (RMSE) of the final point position of the base line in relation to the initial one has been executed. For the investigation, experimental data from three satellite receivers within two days on 5 points have been used. According to the received results, the regression equation to calculate the RMSE of spatial, planned and height position of the final point of the base line in relation to the initial value has been made. These equations allow executing the prognostic evaluation of accuracy for conducting satellite calculations based on data about available obstacles. The dependencies received for the duration of observations sessions for 1 hour, the vectors with the length of 4 km, and the coefficient value of openness from 5.17 to 10.31 have been presented. Numéro de notice : A2020-780 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3846/gac.2020.11191 Date de publication en ligne : 09/07/2020 En ligne : https://doi.org/10.3846/gac.2020.11191 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96474
in Geodesy and cartography > vol 46 n° 2 (July 2020) . - pp 67 - 74[article]A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)
[article]
Titre : A robust total Kalman filter algorithm with numerical evaluation Type de document : Article/Communication Auteurs : Sida Li, Auteur ; Lintao Liu, Auteur ; Zhiping Liu, Auteur ; Guocheng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 309 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] filtre de Kalman
[Termes IGN] matrice
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] modèle d'erreur
[Termes IGN] précision du positionnement
[Termes IGN] valeur aberranteRésumé : (auteur) In this study, the observation model of Kalman Filter (KF) is extended to an errors-in-variables (EIV) model because the observations may exist in the design matrix of the observation model. Then, a robust total least squares method (RTLS) is introduced into the KF, and a robust total Kalman filter (RTKF) algorithm is derived. The RTKF is a simple, flexible and effective algorithm. It is simple because its computational formulae are similar to the computational formulae of a standard KF; it is flexible because it can be used in a wide range of applications; it is effective because the influence of outliers on estimated results is weakened. Finally, the simulated example of the indoor location and the empirical example of pseudorange differential positioning are used to demonstrate the performance of the RTKF algorithm. The results prove the validity, robustness, and reliability of the RTKF in dealing with the outliers that exist in both observation vector and design matrix of the EIV model. Furthermore, the results of the empirical example show that the RTKF improves the precision of a pseudorange differential positioning compared with KF and robust Kalman filter (RKF) algorithms regardless the observation model has outliers or not in this empirical example. Numéro de notice : A2020-457 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563392 Date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563392 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95556
in Survey review > vol 52 n° 373 (July 2020) . - pp 309 - 316[article]Roles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
[article]
Titre : Roles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects Type de document : Article/Communication Auteurs : Jike Chen, Auteur ; Shuanggen Jin, Auteur ; Peijun Du, Auteur Année de publication : 2020 Article en page(s) : n° 102060 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre urbain
[Termes IGN] canopée
[Termes IGN] carte de la végétation
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle numérique de terrain
[Termes IGN] Nankin (Kiangsou)
[Termes IGN] occupation du sol
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] température au solRésumé : (auteur) The urban heat island (UHI) is increasingly recognized as a serious, worldwide problem because of urbanization and climate change. Urban vegetation is capable of alleviating UHI and improving urban environment by shading together with evapotranspiration. While the impacts of abundance and spatial configuration of vegetation on land surface temperature (LST) have been widely examined, very little attention has been paid to the role of vertical structure of vegetation in regulating LST. In this study, we investigated the relationships between horizontal/vertical structure characteristics of urban tree canopy and LST as well as diurnal divergence in Nanjing City, China, with the help of high resolution vegetation map, Light Detection and Ranging (LiDAR) data and various statistical analysis methods. The results indicated that composition, configuration and vertical structure of tree canopy were all significantly related to both daytime LST and nighttime LST. Tree canopy showed stronger influence on LST during the day than at night. Note that the contribution of composition of tree canopy to explaining spatial heterogeneity of LST, regardless of day and night, was the highest, followed by vertical structure and configuration. Combining composition, configuration and vertical structure of tree canopy can take advantage of their respective advantages, and best explain variation in both daytime LST and nighttime LST. As for the independent importance of factors affecting spatial variation of LST, percent cover of tree canopy (PLAND), mean tree canopy height (TH_Mean), amplitude of tree canopy height (TA) and patch cohesion index (COHESION) were the most influential during the day, while the most important variables were PLAND, maximum height of tree canopy (TH_Max), variance of tree canopy height (TH_SD) and COHESION at night. This research extends our understanding of the impacts of urban trees on the UHI effect from the horizontal to three-dimensional space. In addition, it may offer sustainable and effective strategies for urban designers and planners to cope with increasing temperature. Numéro de notice : A2020-715 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102060 Date de publication en ligne : 25/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102060 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96285
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102060[article]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]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)PermalinkCounting of grapevine berries in images via semantic segmentation using convolutional neural networks / Laura Zabawa in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkDiscriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data / Sugandh Chauhan in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkEnsemble learning for hyperspectral image classification using tangent collaborative representation / Hongjun Su in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkEstimating 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)PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)PermalinkModelling housing rents using spatial autoregressive geographically weighted regression: a case study in cracow, Poland / Mateusz Tomal in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkWheat leaf area index retrieval using RISAT-1 hybrid polarized SAR data / Thota Sivasankar in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkAn integrated approach to registration and fusion of hyperspectral and multispectral images / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 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)Permalink