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Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine / Tongxi Hu in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 250 - 261 Titre : Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine Type de document : Article/Communication Auteurs : Tongxi Hu, Auteur ; Elizabeth Myers Toman, Auteur ; Gang Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 250 - 261 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bassin hydrographique [Termes IGN] carte d'occupation du sol [Termes IGN] classification bayesienne [Termes IGN] détection de changement [Termes IGN] estimation bayesienne [Termes IGN] Google Earth Engine [Termes IGN] image Landsat [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Ohio (Etats-Unis) [Termes IGN] précision infrapixellaire [Termes IGN] série temporelle Résumé : (auteur) Large fractions of human-altered lands are working landscapes where people and nature interact to balance social, economic, and ecological needs. Achieving these sustainability goals requires tracking human footprints and landscape disturbance at fine scales over time—an effort facilitated by remote sensing but still under development. Here, we report a satellite time-series analysis approach to detecting fine-scale human disturbances in an Ohio watershed dominated by forests and pastures but with diverse small-scale industrial activities such as hydraulic fracturing (HF) and surface mining. We leveraged Google Earth Engine to stack decades of Landsat images and explored the effectiveness of a fuzzy change detection algorithm called the Bayesian Estimator of Abrupt change, Seasonality, and Trend (BEAST) to capture fine-scale disturbances. BEAST is an ensemble method, capable of estimating changepoints probabilistically and identifying sub-pixel disturbances. We found the algorithm can successfully capture the patterns and timings of small-scale disturbances, such as grazing, agriculture management, coal mining, HF, and right-of-ways for gas and power lines, many of which were not captured in the annual land cover maps from Cropland Data Layers—one of the most widely used classification-based land dynamics products in the US. For example, BEAST could detect the initial HF wellpad construction within 60 days of the registered drilling dates on 88.2% of the sites. The wellpad footprints were small, disturbing only 0.24% of the watershed in area, which was dwarfed by other activities (e.g., right-of-ways of utility transmission lines). Together, these known activities have disturbed 9.7% of the watershed from the year 2000 to 2017 with evergeen forests being the most affected land cover. This study provides empirical evidence on the effectiveness and reliability of BEAST for changepoint detection as well as its capability to detect disturbances from satellite images at sub-pixel levels and also documents the value of Google Earth Engine and satellite time-series imaging for monitoring human activities in complex working landscapes. Numéro de notice : A2021-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.04.008 Date de publication en ligne : 17/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97746 [article]

Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data / Yi Qiang in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2434 - 2450 Titre : Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data Type de document : Article/Communication Auteurs : Yi Qiang, Auteur ; Jinwen Xu, Auteur Année de publication : 2020 Article en page(s) : pp 2434 - 2450 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse de groupement [Termes IGN] données localisées des bénévoles [Termes IGN] étude empirique [Termes IGN] Google Maps [Termes IGN] Ohio (Etats-Unis) [Termes IGN] participation du public [Termes IGN] réseau routier [Termes IGN] résilience écologique [Termes IGN] risque naturel [Termes IGN] trafic routier Résumé : (auteur) Climate change and natural hazards pose great threats to road transport systems which are ‘lifelines’ of human society. However, there is generally a lack of empirical data and approaches for assessing resilience of road networks in real hazard events. This study introduces an empirical approach to evaluate road network resilience using crowdsourced traffic data in Google Maps. Based on the conceptualization of resilience and the Hansen accessibility index, resilience of road network is measured from accumulated accessibility reduction over time during a hazard. The utility of this approach is demonstrated in a case study of the Cleveland metropolitan area (Ohio) in Winter Storm Harper. The results reveal strong spatial variations of the disturbance and recovery rate of road network performance during the hazard. The major findings of the case study are: (1) longer distance travels have higher increasing ratios of travel time during the hazard; (2) communities with low accessibility at the normal condition have lower road network resilience; (3) spatial clusters of low resilience are identified, including communities with low socio-economic capacities. The introduced approach provides ground-truth validation for existing quantitative models and supports disaster management and transportation planning to reduce hazard impacts on road network. Numéro de notice : A2020-691 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1694681 Date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1080/13658816.2019.1694681 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96229 [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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Assessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA / Yongha Park in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 367 - 392 Titre : Assessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA Type de document : Article/Communication Auteurs : Yongha Park, Auteur ; Jerry Mount, Auteur ; Luyu Liu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 367 - 392 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] base de données spatiotemporelles [Termes IGN] Colombus (Ohio) [Termes IGN] diffusion de données [Termes IGN] géolocalisation [Termes IGN] interface web [Termes IGN] mobilité urbaine [Termes IGN] réseau de transport [Termes IGN] temps réel [Termes IGN] trafic routier [Termes IGN] transport public Résumé : (auteur) Public transit vehicles such as buses operate within shared transportation networks subject to dynamic conditions and disruptions such as traffic congestion. The operational delays caused by these conditions can propagate downstream through scheduled transit routes, affecting system performance beyond the initial delay. This paper develops an approach to measuring and assessing vehicle delay propagation in public transit systems. We fuse data on scheduled bus service with real-time vehicle location data to measure the originating, cascading and recovery locations of delay events across space with respect to time. We integrate the resulting patterns to construct stop-specific delay propagation networks. We also analyze the spatiotemporal patterns of propagating delays using parameters such as 1) transit line-based network distance, 2) total propagating delay size, and 3) distance decay. We apply our methodology using publicly available schedule and real-time location data from the Central Ohio Transit Authority (COTA) public bus system in Columbus, Ohio, USA. We find that delay initiation is spatially and temporally uneven, concentrating on specific stops in downtown and specific suburban locations. Core stops play a critical role in propagating delays to a wide range of connected stops, eventually having a disproportional impact on the on-time performance of the bus system. Numéro de notice : A2020-030 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1608997 Date de publication en ligne : 30/04/2019 En ligne : https://doi.org/10.1080/13658816.2019.1608997 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94485 [article]

Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)  

Public [article]  inTransactions in GIS > Vol 23 n° 6 (November 2019) . - pp 1332 - 1351 Titre : Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices Type de document : Article/Communication Auteurs : Gordon A. Cromley, Auteur Année de publication : 2019 Article en page(s) : pp 1332 - 1351 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] coefficient de Gini [Termes IGN] commerce [Termes IGN] courbe de Lorenz [Termes IGN] distribution spatiale [Termes IGN] équipement collectif [Termes IGN] inégalité [Termes IGN] Ohio (Etats-Unis) [Termes IGN] population [Termes IGN] segmentation [Termes IGN] service public [Termes IGN] sociologie [Termes IGN] système d'information géographique Résumé : (auteur) Access to certain types of facilities can promote health and well‐being. When population and facilities are not uniformly distributed across the landscape, inequities in accessibility may occur. Current research into GIS‐based accessibility measures has focused primarily on spatial inequities between different geographic locations but not directly on differences in accessibility between subgroups of the population. The research presented here develops a new method for measuring differential accessibility to facilities between various segments of the population. The method extends concepts and techniques in spatial point pattern analysis that account for the spatial structure of demand and its relationship to supply. In this approach, the traditional Lorenz curve and its associated indices, the Gini coefficient and the dissimilarity index, which are used to measure inequality, are recast in spatial terms for measuring differences in accessibility between population subgroups. An analysis of spatial accessibility to grocery stores in Akron, OH illustrates the value of the spatial Lorenz curve and its associated indices compared to other methods. Numéro de notice : A2019-567 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12577 Date de publication en ligne : 06/10/2019 En ligne : https://onlinelibrary.wiley.com/doi/10.1111/tgis.12577 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94419 [article]

Exploring spatiotemporal clusters based on extended kernel estimation methods / Jay Lee in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

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A parallel algorithm for coverage optimization on multi-core architectures / Ran Wei in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)  

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Development of a vector-based method for coastal bluffline mapping using LiDAR data and a comparison study in the area of lake Erie / Yunjae Choung in Marine geodesy, vol 36 n° 3 (September - November 2013)  

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New perspectives on the use of GPS and GIS to support a highway performance study / D. Tong in Transactions in GIS, vol 13 n° 1 (February 2009)  

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Seasonal sensitivity analysis of impervious surface estimation with satellite imagery / C. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 12 (December 2007)  

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Coverage optimization in continuous space facility siting / Alan T. Murray in International journal of geographical information science IJGIS, vol 21 n° 6-7 (july 2007)  

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Méthodes probabilistes pour la reconstruction de données manquantes / B. Beauzamy (2007)

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Analysis of long-range network RTK during a severe ionospheric storm / Pawel Wielgosz in Journal of geodesy, vol 79 n° 9 (December 2005)  

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Quantitative classification as a tool to show change in an urbanizing watershed / W.B. Clapham in International Journal of Remote Sensing IJRS, vol 26 n° 22 (November 2005)  

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Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery / C. Wu in Remote sensing of environment, vol 93 n° 4 (15/12/2004)  

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