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Crowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping / Marta Samulowska in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)
[article]
Titre : Crowdsourcing without data bias: Building a quality assurance system for air pollution symptom mapping Type de document : Article/Communication Auteurs : Marta Samulowska, Auteur ; Szymon Chmielewski, Auteur ; Edwin Raczko, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] assurance qualité
[Termes IGN] carte sanitaire
[Termes IGN] données localisées des bénévoles
[Termes IGN] erreur systématique
[Termes IGN] pollution atmosphérique
[Termes IGN] production participative
[Termes IGN] qualité de l'air
[Termes IGN] qualité des données
[Termes IGN] science citoyenne
[Termes IGN] surveillance sanitaire
[Termes IGN] zone urbaineRésumé : (auteur) Crowdsourcing is one of the spatial data sources, but due to its unstructured form, the quality of noisy crowd judgments is a challenge. In this study, we address the problem of detecting and removing crowdsourced data bias as a prerequisite for better-quality open-data output. This study aims to find the most robust data quality assurance system (QAs). To achieve this goal, we design logic-based QAs variants and test them on the air quality crowdsourcing database. By extending the paradigm of urban air pollution monitoring from particulate matter concentration levels to air-quality-related health symptom load, the study also builds a new perspective for citizen science (CS) air quality monitoring. The method includes the geospatial web (GeoWeb) platform as well as a QAs based on conditional statements. A four-month crowdsourcing campaign resulted in 1823 outdoor reports, with a rejection rate of up to 28%, depending on the applied. The focus of this study was not on digital sensors’ validation but on eliminating logically inconsistent surveys and technologically incorrect objects. As the QAs effectiveness may depend on the location and society structure, that opens up new cross-border opportunities for replication of the research in other geographical conditions. Numéro de notice : A2021-153 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020046 Date de publication en ligne : 22/01/2021 En ligne : https://doi.org/10.3390/ijgi10020046 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97064
in ISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 46[article]Deep traffic light detection by overlaying synthetic context on arbitrary natural images / Jean Pablo Vieira de Mello in Computers and graphics, vol 94 n° 1 (February 2021)
[article]
Titre : Deep traffic light detection by overlaying synthetic context on arbitrary natural images Type de document : Article/Communication Auteurs : Jean Pablo Vieira de Mello, Auteur ; Lucas Tabelini, Auteur ; Rodrigo F. Berriel, Auteur Année de publication : 2021 Article en page(s) : pp 76 - 86 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage profond
[Termes IGN] détection d'objet
[Termes IGN] échantillonnage d'image
[Termes IGN] feu de circulation
[Termes IGN] image à haute résolution
[Termes IGN] navigation autonome
[Termes IGN] signalisation routière
[Termes IGN] trafic routierRésumé : (auteur) Deep neural networks come as an effective solution to many problems associated with autonomous driving. By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights. However, acquiring and annotating real data can be extremely costly in terms of time and effort. In this context, we propose a method to generate artificial traffic-related training data for deep traffic light detectors. This data is generated using basic non-realistic computer graphics to blend fake traffic scenes on top of arbitrary image backgrounds that are not related to the traffic domain. Thus, a large amount of training data can be generated without annotation efforts. Furthermore, it also tackles the intrinsic data imbalance problem in traffic light datasets, caused mainly by the low amount of samples of the yellow state. Experiments show that it is possible to achieve results comparable to those obtained with real training data from the problem domain, yielding an average mAP and an average F1-score which are each nearly 4 p.p. higher than the respective metrics obtained with a real-world reference model. Numéro de notice : A2021-151 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cag.2020.09.012 Date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1016/j.cag.2020.09.012 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97027
in Computers and graphics > vol 94 n° 1 (February 2021) . - pp 76 - 86[article]Estimating the impacts of proximity to public transportation on residential property values: An empirical analysis for Hartford and Stamford areas, Connecticut / Bo Zhang in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)
[article]
Titre : Estimating the impacts of proximity to public transportation on residential property values: An empirical analysis for Hartford and Stamford areas, Connecticut Type de document : Article/Communication Auteurs : Bo Zhang, Auteur ; Weidong Li, Auteur ; Nicholas Lownes, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] analyse de la valeur
[Termes IGN] bien immobilier
[Termes IGN] Connecticut (Etats-Unis)
[Termes IGN] logement
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] régression géographiquement pondérée
[Termes IGN] transport public
[Termes IGN] zone urbaineRésumé : (auteur) Public transit infrastructure may increase residential property values by improving accessibility and reducing commute expenses in urban areas. Prior studies have investigated the impacts of the proximity to public transportation on property values and obtained mixed conclusions. Many of these studies were focused on one transit mode for a single city. In this study, a hedonic pricing model is constructed to investigate the impacts of commuter rail/Bus Rapid Transit (BRT) and bus lines separately in two different areas: the Stamford area (Stamford–Darien–New Canaan) and the Hartford area (Hartford–West Hartford–East Hartford), Connecticut. Comparison of the results from Ordinary Least Square and Geographically Weighted Regression (GWR) indicates that estimation accuracy can be improved by considering local variation. Results from GWR show that impacts of proximity to bus and rail/BRT on property values vary spatially in the Hartford area. Negative impacts of bus stops are found in downtown Hartford and positive impacts in the west and east sides of Hartford. Impacts from rail/BRT are relatively minor compared with bus lines, partly due to the relatively recent launching of the BRT and Hartford rail line. In contrast, most properties in the Stamford area show appreciation towards rail service and depreciation to bus service. This study reveals the roles of different public transit systems in affecting residential property values. It also provides empirical evidence for future transit-oriented development in this region for uplifting the real estate market. Numéro de notice : A2021-154 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020044 Date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.3390/ijgi10020044 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97065
in ISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 44[article]Fully convolutional neural network for impervious surface segmentation in mixed urban environment / Joseph McGlinchy in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)
[article]
Titre : Fully convolutional neural network for impervious surface segmentation in mixed urban environment Type de document : Article/Communication Auteurs : Joseph McGlinchy, Auteur ; Brian Muller, Auteur ; Brian Johnson, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] croissance urbaine
[Termes IGN] Denver
[Termes IGN] exactitude des données
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] milieu urbain
[Termes IGN] segmentation
[Termes IGN] surface imperméableRésumé : (Auteur) The urgency of creating appropriate, high-resolution data products such as impervious cover information has increased as cities face rapid growth as well as climate change and other environmental challenges. This work explores the use of fully convolutional neural networks (FCNNs )—specifically UNet with a ResNet-152 encoder—in mapping impervious surfaces at the pixel level from WorldView-2 in a mixed urban/residential environment. We investigate three-, four-, and eight-band multispectral inputs to the FCNN. Resulting maps are promising in both qualitative and quantitative assessment when compared to automated land use/land cover products. Accuracy was assessed by F1 and average precision (AP) scores, as well as receiver operating characteristic curves, with area under the curve (AUC ) used as an additional accuracy metric. The four-band model shows the highest average test-set accuracies (F1, AP, and AUC of 0.709, 0.82, and 0.807, respectively), with higher AP and AUC than the automated land use/land cover products, indicating the utility of the blue-green-red-infrared channels for the FCNN. Improved performance was seen in residential areas, with worse performance in more densely developed areas. Numéro de notice : A2021-099 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.2.117 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.14358/PERS.87.2.117 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97045
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 2 (February 2021) . - pp 117 - 123[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021021 SL Revue Centre de documentation Revues en salle Disponible Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan / Muhammad Imran in Geocarto international, vol 36 n° 2 ([01/02/2021])
[article]
Titre : Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan Type de document : Article/Communication Auteurs : Muhammad Imran, Auteur ; Yasra Hamid, Auteur ; Abeer Mazher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 197 - 211 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] diptère
[Termes IGN] image Landsat
[Termes IGN] maladie tropicale
[Termes IGN] modélisation spatiale
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Pakistan
[Termes IGN] régression géographiquement pondérée
[Termes IGN] régression logistique
[Termes IGN] risque sanitaire
[Termes IGN] série temporelle
[Termes IGN] zone intertropicale
[Termes IGN] zone urbaineRésumé : (auteur) The study objective is to predict the epidemiological impact of dengue fever arbovirosis in urban tropical areas of Pakistan. To do so, we used the GPS-based data of the Aedes larvae collected during 2014–2015 in Lahore. We developed a Geographically Weighted Logistic Regression (GWLR) model for Geospatially predicting larvae presence or absence in Lahore. Data on rainfall, temperature are included along with time series of the normalized difference vegetation index (NDVI) derived from Landsat imagery. We observed a high spatial variability of the GWLR parameter estimates of these variables in the study area. The GWLR model significantly (R2a = 0.78) explained the presence or absence of Aedes larvae with temperature, rainfall and NDVI variables in South and Southeast of the study area. In the North and North-West, however, GWLR relationships were observed weak in highly populated areas. Interpolating GWLR coefficients generate more accurate maps of Aedes larvae presence or absence. Numéro de notice : A2021-474 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1614100 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1080/10106049.2019.1614100 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96932
in Geocarto international > vol 36 n° 2 [01/02/2021] . - pp 197 - 211[article]A GIS-based system for spatial-temporal availability evaluation of the open spaces used as emergency shelters: The case of Victoria, British Columbia, Canada / Yibing Yao in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)PermalinkA heuristic approach to the generalization of complex building groups in urban villages / Wenhao Yu in Geocarto international, vol 36 n° 2 ([01/02/2021])PermalinkIdentifying 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)PermalinkImproving trajectory estimation using 3D city models and kinematic point clouds / Lucas Lucks in Transactions in GIS, Vol 25 n° 1 (February 2021)PermalinkMitigating urban visual pollution through a multistakeholder spatial decision support system to optimize locational potential of billboards / Khydija Wakil in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)PermalinkMonitoring the spatiotemporal dynamics of urban green space and Its impacts on thermal environment in Shenzhen city from 1978 to 2018 with remote sensing data / Yue Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)PermalinkReclaimed-airport surface-deformation monitoring by improved permanent-scatterer interferometric synthetic-aperture radar: a case study of Shenzhen Bao'an international airport, China / Lu Miao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)PermalinkUrban agglomeration worsens spatial disparities in climate adaptation / Seung-Kyum Kim in Scientific reports, vol 11 (2021)PermalinkGIS-based multicriteria evaluation for earthquake response: a case study of expert opinion in Vancouver, Canada / Blake Byron Walker in Natural Hazards, Vol 105 n° 2 (January 2021)PermalinkAcquisition lasergrammétrique d’ouvrages d’art pour l’interopérabilité BIM-SIG, cas pratique du syndicat mixte "Routes de Guadeloupe" / Sonia Sermanson (2021)Permalink