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Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment / Ömer Ekmekcioğlu in Sustainable Cities and Society, vol 87 (December 2022)  

Public [article]  inSustainable Cities and Society > vol 87 (December 2022) . - n° 104195 Titre : Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment Type de document : Article/Communication Auteurs : Ömer Ekmekcioğlu, Auteur ; Kerim Koc, Auteur ; Ismail Dabanli, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104195 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse multicritère [Termes IGN] changement climatique [Termes IGN] eau [Termes IGN] milieu urbain [Termes IGN] planification urbaine [Termes IGN] pondération [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] résilience écologique [Termes IGN] ressources en eau [Termes IGN] utilisation du sol [Termes IGN] ville durable Résumé : (auteur) This study was undertaken to be a remedy to urban water scarcity phenomena having escalated consequences with the contemporaneous effects of climate change and over-urbanization. Hence, a broad list of mitigation strategies comprising 44 action plans under seven dimensions was assessed depending upon five constraints (i.e., cost-effectiveness, time/effort required, feasibility, primary benefit, and secondary benefits). To realize the overarching aim of this research, the analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) each subjected to the fuzzy set theory were employed. In this regard, the fuzzy AHP was utilized for determining the weights of constraining criteria, while the prioritization of the strategies was performed via the fuzzy TOPSIS. The results revealed that the primary benefit is the most prevailing criterion compared to its counterparts. In addition, procuring organized land use planning and limiting new growth in urban areas was found as the most promising strategy to combat urban water scarcity phenomena. The findings further highlighted the effectiveness of conducting integrated water resource planning against climate change and fostering the use of sustainable materials domestically in not only mitigating urban water scarcity but also increasing the resiliency and sustainability of the urbanized cities. Numéro de notice : A2022-818 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104195 Date de publication en ligne : 21/09/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101985 [article]

Estimation of ionospheric total electron content using GNSS observations derived from a smartphone / Li Xu in GPS solutions, vol 26 n° 4 (October 2022)  

Public [article]  inGPS solutions > vol 26 n° 4 (October 2022) . - n° 138 Titre : Estimation of ionospheric total electron content using GNSS observations derived from a smartphone Type de document : Article/Communication Auteurs : Li Xu, Auteur ; Jiuping Zha, Auteur ; Min Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] modèle ionosphérique [Termes IGN] phase [Termes IGN] pondération [Termes IGN] série de Fourier [Termes IGN] téléphone intelligent [Termes IGN] teneur totale en électrons [Termes IGN] teneur verticale totale en électrons Résumé : (auteur) The global navigation satellite system (GNSS) measurements to determine ionospheric total electron content (TEC) are mainly derived from expensive geodetic-grade receivers, which are not conducive to high-density placement. In this work, we present an analysis of the performance of ionospheric TEC determined by GNSS dual-frequency measurements derived from the smartphone, taking the Xiaomi 8 (XMI8) as an example. First, the ionospheric observable is retrieved from the code and carrier phase data using the carrier-to-code leveling technique and a new carrier-to-noise weighting strategy instead of an elevation weighting strategy, considering the characteristic of the GNSS measurements from smartphones. Then, the absolute ionospheric slant TEC (STEC) values are isolated from the ionospheric observables by modeling with the generalized trigonometric series function. The experimental data, covering over 120 h, were taken from two situations: one is the data collected by the original smartphone antenna; the other is the external geodetic-grade antenna. The TEC data obtained from the collocated geodetic-grade receiver are used as reference data to evaluate the performance of the TEC values from XMI8. Compared to the reference data, the evaluation results show that the ionospheric STEC extraction accuracy can reach total electron content unit (TECU) values of 0.17 and 0.11 under the two different situations in the continuous carrier phase satellite arc without cycle slips. In addition, the VTEC modeling accuracy is above 5 and 2 TECU in the two different situations, respectively. Thus, we concluded that consumer-level GNSS chipsets are highly potential in the future to increase the ionospheric monitoring station density due to their low costs and good data quality. Numéro de notice : A2022-713 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01329-w Date de publication en ligne : 04/09/2022 En ligne : https://doi.org/10.1007/s10291-022-01329-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101591 [article]

Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements / Devendra Shashikant Nagale in Geodesy and Geodynamics, vol 13 n° 5 (September 2022)  

Public [article]  inGeodesy and Geodynamics > vol 13 n° 5 (September 2022) . - pp 445 - 455 Titre : Impact assessment of the seasonal hydrological loading on geodetic movement and seismicity in Nepal Himalaya using GRACE and GNSS measurements Type de document : Article/Communication Auteurs : Devendra Shashikant Nagale, Auteur ; Suresh Kannaujiya, Auteur ; Param K. Gautam, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 445 - 455 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] coefficient de corrélation [Termes IGN] déformation de la croute terrestre [Termes IGN] données GNSS [Termes IGN] données GRACE [Termes IGN] International Terrestrial Reference Frame [Termes IGN] mousson [Termes IGN] Népal [Termes IGN] pondération [Termes IGN] série temporelle [Termes IGN] sismicité [Termes IGN] surcharge hydrologique [Termes IGN] variation saisonnière Résumé : (auteur) The Himalayan terrain is an epitome of ongoing convergence and geodetic deformation where both tectonic and non-tectonic forces prevail. In this study, the Gravity Recovery and Climate Experiment (GRACE) and Global Positioning System (GPS) datasets are used to assess the impact of seasonal loading on deformation with seismicity in Nepal. The recorded GPS data from 21 Global Navigation Satellite System (GNSS) stations during 2017–2020 are processed with respect to ITRF14 and the Indian reference frame, and the Center for Space Research (CSR) mascon RL06 during 2002–2020 is adopted to estimate the terrestrial water storage (TWS) change over the Ganga-Brahmaputra River basin. The results indicate that the hydrological loading effect or TWS change shows high negative, high positive, and moderately positive values in pre-monsoon, co-monsoon, and post-monsoon months, respectively. The detrended GPS data of both horizontal and vertical components correlate with the seasonal TWS change using the Pearson correlation coefficient at each GNSS site. In addition, the correlation coefficient has been interpolated using inverse distance weighting to investigate the regional TWS influence on geodetic displacement. In the north component, the correlation coefficient ranges from −0.6 to 0.6. At the same time, the TWS is positively correlated with geodetic displacement (0.82) in the east component, and the correlation coefficient is negative (−0.69) in the vertical component. The negative correlation signifies an inverse relationship between seasonal TWS variation and geodetic displacements. The strain rate is estimated, which shows higher negative values in pre-monsoon than in post-monsoon. Similarly, the effect of seismicity is 47.90% for pre-monsoon, 15.97% for co-monsoon, and 17.56% for post-monsoon. Thus we can infer that the seismicity decreases with the increase of seasonal hydrological loading. Furthermore, the effect of strain is much higher in pre-monsoon than in post-monsoon since the impact of co-monsoon continues to persist on a small scale in the post-monsoon season. Numéro de notice : A2022-762 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.geog.2022.02.006 Date de publication en ligne : 20/05/2022 En ligne : https://doi.org/10.1016/j.geog.2022.02.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101780 [article]

Can machine learning improve small area population forecasts? A forecast combination approach / Irina Grossman in Computers, Environment and Urban Systems, vol 95 (July 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 95 (July 2022) . - n° 101806 Titre : Can machine learning improve small area population forecasts? A forecast combination approach Type de document : Article/Communication Auteurs : Irina Grossman, Auteur ; Kasun Bandara, Auteur ; Tom Wilson, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101806 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage automatique [Termes IGN] Australie [Termes IGN] démographie [Termes IGN] Extreme Gradient Machine [Termes IGN] infrastructure [Termes IGN] lissage de données [Termes IGN] modèle de simulation [Termes IGN] modèle empirique [Termes IGN] Nouvelle-Zélande [Termes IGN] planification stratégique [Termes IGN] pondération [Termes IGN] série temporelle Résumé : (auteur) Generating accurate small area population forecasts is vital for governments and businesses as it provides better grounds for decision making and strategic planning of future demand for services and infrastructure. Small area population forecasting faces numerous challenges, including complex underlying demographic processes, data sparsity, and short time series due to changing geographic boundaries. In this paper, we propose a novel framework for small area forecasting which combines proven demographic forecasting methods, an exponential smoothing based algorithm, and a machine learning based forecasting technique. The proposed forecasting combination contains four base models commonly used in demographic forecasting, a univariate forecasting model specifically suitable for forecasting yearly data, and a globally trained Light Gradient Boosting Model (LGBM) that exploits the similarities between a collection of population time series. In this study, three forecast combination techniques are investigated to weight the forecasts generated by these base models. We empirically evaluate our method, by preparing small area population forecasts for Australia and New Zealand. The proposed framework is able to achieve competitive results in terms of forecasting accuracy. Moreover, we show that the inclusion of the LGBM model always improves the accuracy of combination models on both datasets, relative to combination models which only include the demographic models. In particular, the results indicate that the proposed combination framework decreases the prevalence of relatively poor forecasts, while improving the reliability of small area population forecasts. Numéro de notice : A2022-374 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101806 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101806 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100621 [article]

Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network / Alex David Singleton in Computers, Environment and Urban Systems, vol 95 (July 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 95 (July 2022) . - n° 101802 Titre : Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network Type de document : Article/Communication Auteurs : Alex David Singleton, Auteur ; Dani Arribas-Bel, Auteur ; John Murray, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101802 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage automatique [Termes IGN] bâtiment [Termes IGN] carte d'occupation du sol [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] Grande-Bretagne [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] morphologie urbaine [Termes IGN] pondération [Termes IGN] processeur graphique Résumé : (auteur) The increased availability of high-resolution multispectral imagery captured by remote sensing platforms provides new opportunities for the characterisation and differentiation of urban context. The discovery of generalized latent representations from such data are however under researched within the social sciences. As such, this paper exploits advances in machine learning to implement a new method of capturing measures of urban context from multispectral satellite imagery at a very small area level through the application of a convolutional autoencoder (CAE). The utility of outputs from the CAE is enhanced through the application of spatial weighting, and the smoothed outputs are then summarised using cluster analysis to generate a typology comprising seven groups describing salient patterns of differentiated urban context. The limits of the technique are discussed with reference to the resolution of the satellite data utilised within the study and the interaction between the geography of the input data and the learned structure. The method is implemented within the context of Great Britain, however, is applicable to any location where similar high resolution multispectral imagery are available. Numéro de notice : A2022-370 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101802 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100606 [article]

Application of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])  

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Adaptive feature weighted fusion nested U-Net with discrete wavelet transform for change detection of high-resolution remote sensing images / Congcong Wang in Remote sensing, vol 13 n° 24 (December-2 2021)  

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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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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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A mean-squared-error condition for weighting ionospheric delays in GNSS baselines / Peter J.G. Teunissen in Journal of geodesy, vol 95 n° 11 (November 2021)  

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Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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Observable quality assessment of broadband very long baseline interferometry system / Ming H. Xu in Journal of geodesy, vol 95 n° 5 (May 2021)  

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Susceptibilité aux glissements de terrain dans la ville d’Al Hoceima et sa périphérie : application de la méthode de la théorie de l’évidence / Taoufik Byou in Geomatica [en ligne], vol 75 n° 1 (Mars 2021)  

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A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping / Zhice Fang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

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Identifying urban growth patterns through land-use/land-cover spatio-temporal metrics: Simulation and analysis / Marta Sapena Moll in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

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