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Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])  

Public [article]  inGeocarto international > vol 35 n° 14 [15/10/2020] . - pp 1511 - 1526 Titre : Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 Type de document : Article/Communication Auteurs : Sisi Yu, Auteur ; ZengXiang Zhang, Auteur ; Fang Liu, Auteur Année de publication : 2020 Article en page(s) : pp 1511 - 1526 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agglomération [Termes IGN] croissance urbaine [Termes IGN] delta de la rivière des perles [Termes IGN] données démographiques [Termes IGN] image DMSP-OLS [Termes IGN] Kouangtoung (Chine) [Termes IGN] prise de vue nocturne [Termes IGN] recensement démographique [Termes IGN] répartition géographique [Termes IGN] série temporelle [Termes IGN] surveillance de l'urbanisation Résumé : (auteur) Although numerous literatures have documented the monitoring of population distributions and dynamics for socio-economic development, environmental protection, and urban planning on different scales, little attention has been paid to long-term and multi-frequency population evolution on urban agglomeration scale, especially in non-census years. Furthermore, although multi models have been applied to population spatialization based on night-time light imagery (NLT) and census data, their accuracy needs to be further improved. Selected the Pearl River Delta (PRD), China as the study area, this work aimed to solve the aforementioned problems by constructing the residential extent extraction index (REEI) and employing the population growth theory and ‘DN density–population density’ model. Results indicated that the proposed approaches were feasible to optimize NTL products and simulate populations in both census (2000, 2010) and non-census (2005) years. Population evolution in the PRD presented distinct differences from space and over time, and mainly driven by socioeconomic development. Numéro de notice : A2020-617 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576778 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95993 [article]

A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1740 - 1764 Titre : A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery Type de document : Article/Communication Auteurs : Bo Yang, Auteur ; Lin Liu, Auteur ; Minxuan Lan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1740 - 1764 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] coefficient de corrélation [Termes IGN] criminalité [Termes IGN] données spatiotemporelles [Termes IGN] géostatistique [Termes IGN] historique des données [Termes IGN] image NPP-VIIRS [Termes IGN] krigeage [Termes IGN] modèle dynamique [Termes IGN] nuit [Termes IGN] Ohio (Etats-Unis) [Termes IGN] prédiction [Termes IGN] prévention des risques [Termes IGN] prise de vue nocturne [Termes IGN] test statistique [Termes IGN] zone urbaine Résumé : (auteur) Accurate crime prediction can help allocate police resources for crime reduction and prevention. There are two popular approaches to predict criminal activities: one is based on historical crime, and the other is based on environmental variables correlated with criminal patterns. Previous research on geo-statistical modeling mainly considered one type of data in space-time domain, and few sought to blend multi-source data. In this research, we proposed a spatio-temporal Cokriging algorithm to integrate historical crime data and urban transitional zones for more accurate crime prediction. Time-series historical crime data were used as the primary variable, while urban transitional zones identified from the VIIRS nightlight imagery were used as the secondary co-variable. The algorithm has been applied to predict weekly-based street crime and hotspots in Cincinnati, Ohio. Statistical tests and Predictive Accuracy Index (PAI) and Predictive Efficiency Index (PEI) tests were used to validate predictions in comparison with those of the control group without using the co-variable. The validation results demonstrate that the proposed algorithm with historical crime data and urban transitional zones increased the correlation coefficient by 5.4% for weekdays and by 12.3% for weekends in statistical tests, and gained higher hit rates measured by PAI/PEI in the hotspots test. Numéro de notice : A2020-475 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1737701 date de publication en ligne : 13/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1737701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95622 [article]

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Learning scene geometry for visual localization in challenging conditions / Nathan Piasco (2019)    

Public Titre : Learning scene geometry for visual localization in challenging conditions Type de document : Article/Communication Auteurs : Nathan Piasco , Auteur ; Désiré Sidibé, Auteur ; Valérie Gouet-Brunet , Auteur ; Cédric Demonceaux, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : PLaTINUM / Gouet-Brunet, Valérie Conférence : ICRA 2019, International Conference on Robotics and Automation 20/05/2019 24/05/2019 Montréal Québec - Canada Proceedings IEEE Importance : pp 9094 - 9100 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] analyse visuelle [Termes IGN] appariement d'images [Termes IGN] carte de profondeur [Termes IGN] descripteur [Termes IGN] géométrie de l'image [Termes IGN] image RVB [Termes IGN] localisation basée vision [Termes IGN] précision de localisation [Termes IGN] prise de vue nocturne [Termes IGN] robotique [Termes IGN] scène urbaine [Termes IGN] variation diurne [Termes IGN] variation saisonnière [Termes IGN] vision par ordinateur Résumé : (auteur) We propose a new approach for outdoor large scale image based localization that can deal with challenging scenarios like cross-season, cross-weather, day/night and longterm localization. The key component of our method is a new learned global image descriptor, that can effectively benefit from scene geometry information during training. At test time, our system is capable of inferring the depth map related to the query image and use it to increase localization accuracy. We are able to increase recall@1 performances by 2.15% on cross-weather and long-term localization scenario and by 4.24% points on a challenging winter/summer localization sequence versus state-of-the-art methods. Our method can also use weakly annotated data to localize night images across a reference dataset of daytime images. Numéro de notice : C2019-002 Affiliation des auteurs : LaSTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICRA.2019.8794221 date de publication en ligne : 12/08/2019 En ligne : http://doi.org/10.1109/ICRA.2019.8794221 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93774

Documents numériques

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Measuring spatial developments in the Czech Republic / Vladimíra Šilhánková in GIM international [en ligne], vol 30 n° 1 (January 2016)

Public [article]  inGIM international [en ligne] > vol 30 n° 1 (January 2016) . - pp 25 - 27 Titre : Measuring spatial developments in the Czech Republic Type de document : Article/Communication Auteurs : Vladimíra Šilhánková, Auteur ; Jan Langr, Auteur ; Michael Pondělíček, Auteur Année de publication : 2016 Article en page(s) : pp 25 - 27 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] développement économique [Termes IGN] image satellite [Termes IGN] prise de vue nocturne [Termes IGN] République Tchèque [Termes IGN] surveillance Résumé : (éditeur) A country's local spatial development can be derived from socio-economic indicators assigned to administrative units. Proper management and monitoring often require statistics at a more detailed level. However, it is difficult if not impossible to sub-aggregate the statistics to smaller areas than administrative units. A reliable alternative is to measure the intensity and extent of night-time illumination and the changes over time. The authors have developed two indicators derived from satellite night-time images for monitoring local spatial developments in the Czech Republic. Numéro de notice : A2016-014 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79346 [article]

Nighttime-lights-derived fossil fuel carbon dioxide emission maps and their limitations / Naizhuo Zhao in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 12 (December 2015) . - pp 935 - 943 Titre : Nighttime-lights-derived fossil fuel carbon dioxide emission maps and their limitations Type de document : Article/Communication Auteurs : Naizhuo Zhao, Auteur ; Eric L. Samson, Auteur ; Nathan A. Currit, Auteur Année de publication : 2015 Article en page(s) : pp 935 - 943 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image numérique [Termes IGN] cartographie des risques [Termes IGN] dioxyde de carbone [Termes IGN] éclairage public [Termes IGN] luminance lumineuse [Termes IGN] pollution lumineuse [Termes IGN] prise de vue nocturne Résumé : (auteur) Brightness of nighttime lights has been used as an indicator for spatial disaggregation of CO2 emission based on an assumed linear relationship between the digital number (DN) values of nighttime light imagery and the amount of CO2 emissions. However, reliability of the linear relationship of these variables has not been thoroughly examined. In this study, we find that the actual overall correlations are exponential rather than linear. More specific analyses showed that the DN values of nighttime light imagery first behaves linearly (from 3 to 50) and then exponentially (from 51 to 63), correlating to the amount of CO2 emissions. Regardless of the use of a linear or piecewise function, some featured limitations are evident as we developed the methodology. Among significant limitations, CO2 emissions were not visualized in unlit areas and a lack of variation existed in regions with the same DN values of nighttime light imagery. Lastly CO2 emissions in urban core areas were grossly under-estimated. Numéro de notice : A2015-993 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80274 [article]

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Orthophotographie nocturne à haute résolution : la nuit, vue du ciel / Eva Frangiamone in Géomatique suisse, vol 112 n° 12 (décembre 2014)

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