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Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])
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Titre : Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques Type de document : Article/Communication Auteurs : Saman Javadi, Auteur ; Seied Mehdy Hashemy Shahdany, Auteur ; Hashemy Shahdany, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1160-1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] aquifère
[Termes IGN] arsenic
[Termes IGN] cartographie des risques
[Termes IGN] contamination
[Termes IGN] eau souterraine
[Termes IGN] Iran
[Termes IGN] logique floue
[Termes IGN] nitrate
[Termes IGN] pollution des eaux
[Termes IGN] vulnérabilitéRésumé : (auteur) This study proposes a new approach to establish a multi-parameter risk mapping method by employing the K-Means clustering technique. Accordingly, spatial assessment of arsenic (As), nitrate (NO3) and total dissolved solids (TDS) were carried out based on the type of land use to estimate contamination potential in an aquifer. Since risk mapping is always associated with the occurrence probability of a phenomenon, pollution occurrence probability was then obtained using the fuzzy C-means clustering. The results reveal that NO3 and As contamination levels increase from the first cluster (C1), covers 22.3% of the aquifer, to C5 encompassing 35.1% of the aquifer devoted to extensive industrial and agricultural activities. Fuzzy clustering results show that the pollution occurrence probability in each aquifer cell varied from less than 30 to more than 90%. Moreover, the results show, industrial and agricultural land uses cover about 70% of the areas with high risk of contamination. Numéro de notice : A2022-396 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778099 Date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100690
in Geocarto international > vol 37 n° 4 [15/02/2022] . - pp 1160-1182[article]Possibilities for assessment and geovisualization of spatial and temporal water quality data using a webGIS application / Daniel Balla in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)
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Titre : Possibilities for assessment and geovisualization of spatial and temporal water quality data using a webGIS application Type de document : Article/Communication Auteurs : Daniel Balla, Auteur ; Marianna Zichar, Auteur ; Emoke Kiss, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] contamination
[Termes IGN] données spatiotemporelles
[Termes IGN] épidémie
[Termes IGN] évaluation
[Termes IGN] maladie infectieuse
[Termes IGN] outil d'aide à la décision
[Termes IGN] pollution des eaux
[Termes IGN] qualité des eaux
[Termes IGN] WebSIG
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) The provision of webGIS-based water quality data services has become a priority area for both the public and administrative sectors in the context of the pandemic emergency associated with the global spread of COVID-19. Current geographic, monitoring and decision supporting systems, typically based on web-based geospatial information, greatly facilitate the sharing of spatial and temporal data from environmental databases and real-time analyses. In the present study, different water quality indices are determined, compared and geovisualized, during which the changes in the quality of the shallow groundwater resources of a settlement are examined in the period (2011–2019) in an eastern Hungarian settlement. Another objective of the research is to determine three water quality indices (Water Quality Index, CCME Water Quality Index, Contamination degree) and categorize water samples based on the same input spatial and temporal data using self-developed freely available geovisualization tools. Groundwater quality was assessed by using different water quality indices. Significant pollution of the groundwater in the time period before the installation of a sewage network was shown. Regarding water quality, significant positive changes were shown based on all three water quality indices in the years after installing a sewage network (2015–2019). The presence of pollution apart from the positive changes suggests that the purification processes will last for a long time. Numéro de notice : A2022-170 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11020108 En ligne : https://doi.org/10.3390/ijgi11020108 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99799
in ISPRS International journal of geo-information > vol 11 n° 2 (February 2022) . - n° 108[article]Visual analysis of geospatial multivariate data for investigating radioactive deposition processes / Shigeo Takahashi in The Visual Computer, vol 37 n° 12 (December 2021)
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Titre : Visual analysis of geospatial multivariate data for investigating radioactive deposition processes Type de document : Article/Communication Auteurs : Shigeo Takahashi, Auteur ; Daisuke Sakurai, Auteur ; Miyuki Sasaki, Auteur ; Hiroko N. Miyamura, Auteur ; Yukihisa Sanada, Auteur Année de publication : 2021 Article en page(s) : pp 3039 - 3050 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] accident nucléaire
[Termes IGN] analyse géovisuelle
[Termes IGN] analyse multicritère
[Termes IGN] analyse multivariée
[Termes IGN] contamination
[Termes IGN] Japon
[Termes IGN] pollution atmosphérique
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) The Fukushima nuclear accident of 2011 raised awareness of the importance of radioactive deposition processes, especially for proposing aerosol measures against possible air pollution. However, identifying these types of processes is often difficult due to complicated terrains. This paper presents an application study for identifying radioactive deposition processes by taking advantage of visual interaction with topographic data. The idea is to visually investigate the correspondence of the spatial positions to the air dose rate along with relevant attributes. This is accomplished by composing scatterplots of pairwise attributes, onto which we project terrain areas to interactively find specific patterns of such attributes. We applied our approach to the analysis of air dose rate distribution data around the Fukushima nuclear plant after the accident. Our visualization technique clearly distinguished contamination areas derived from different deposition processes and thus is useful for elucidation of the deposition process. Numéro de notice : A2021-906 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s00371-021-02248-6 Date de publication en ligne : 20/07/2021 En ligne : https://doi.org/10.1007/s00371-021-02248-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99314
in The Visual Computer > vol 37 n° 12 (December 2021) . - pp 3039 - 3050[article]A web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)
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Titre : A web-based spatial decision support system for monitoring the risk of water contamination in private wells Type de document : Article/Communication Auteurs : Yu Lan, Auteur ; Wenwu Tang, Auteur ; Samantha Dye, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 293 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] arsenic
[Termes IGN] base de données localisées
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] contamination
[Termes IGN] eau souterraine
[Termes IGN] interpolation spatiale
[Termes IGN] krigeage
[Termes IGN] pollution des eaux
[Termes IGN] prévention des risques
[Termes IGN] puits
[Termes IGN] santé
[Termes IGN] surveillance sanitaire
[Termes IGN] système d'aide à la décision
[Termes IGN] système d'information géographique
[Termes IGN] WebSIGRésumé : (auteur) Long-term exposure to contaminated water can cause health effects, such as cancer. Accurate spatial prediction of inorganic compounds (e.g. arsenic) and pathogens in groundwater is critical for water supply management. Ideally, environmental health agencies would have access to an early warning system to alert well owners of risks of such contamination. The estimation and dissemination of these risks can be facilitated by the combination of Geographic Information Systems and spatial analysis capabilities – i.e., spatial decision support system (SDSS). However, the use of SDSS, especially web-based SDSS, is rare for spatially explicit studies of drinking water quality of private wells. In this study, we introduce the interactive Well Water Risk Estimation(iWWRE), a web-based SDSS to facilitate the monitoring of water contamination in private wells across Gaston County, North Carolina (US). Our system implements geoprocessing web services and generates dynamic spatial analysis results based on a database of private wells. Environmental health scientists using our system can conduct fine-grained spatial interpolation on 1) a particular type of contaminant such as arsenic, 2) on various subsets through a temporal query. Visuals consist of an estimation map, cross validation information, Kriging variance and contour lines that delineate areas with maximum contaminant levels (MCL), as set by the US Environmental Protection Agency (EPA). Our web-based SDSS was developed jointly with environmental health specialists who found it particularly critical for the monitoring of local contamination trends, and a useful tool to reach out to private well users in highly elevated contaminated areas. Numéro de notice : A2020-583 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1798508 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1080/19475683.2020.1798508 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95905
in Annals of GIS > vol 26 n° 3 (July 2020) . - pp 293 - 309[article]Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils / Haein Shin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)
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Titre : Spectral Interference of Heavy Metal Contamination on Spectral Signals of Moisture Content for Heavy Metal Contaminated Soils Type de document : Article/Communication Auteurs : Haein Shin, Auteur ; Jaehyung Yu, Auteur ; Lei Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2266 - 2275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arsenic
[Termes IGN] bande spectrale
[Termes IGN] bruit blanc
[Termes IGN] contamination
[Termes IGN] cuivre
[Termes IGN] dégradation du signal
[Termes IGN] échantillonnage
[Termes IGN] humidité du sol
[Termes IGN] interférence
[Termes IGN] métal lourd
[Termes IGN] modèle de régression
[Termes IGN] plomb
[Termes IGN] pollution des sols
[Termes IGN] signature spectraleRésumé : (auteur) This article examined the spectral interference by heavy metal on the spectral signal of moisture content of heavy metal contaminated soils. Soil samples were collected from an abandoned mine area, and the chemical analysis revealed extremely high contamination amount of copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and lead (Pb). The mineralogical analysis showed that the spectral signature of the heavy metal contaminated soils was manifested by secondary minerals. Water content suppressed the spectral reflectance of the soil samples but increased the absorption depths. Although a regression model can predict moisture content using the magnitude of the water absorption feature, the accuracy was much lower when the heavy metal concentration was extremely high. It indicates that geochemical reactions between the heavy metal cation and iron oxide/clay minerals may have affected the spectral responses of the contaminated soils at the water absorption bands. Our model also showed that there was a shift of the absorption features of moisture content if the heavy metal contamination level went up. Unlike normal soils, the absorption features of clay minerals and ferric iron were not able to accurately predict moisture in highly contaminated soils. Given the fact that the spectral bands selected in this article were associated with water absorption, the findings from this article may only be useful to a drone-based low-altitude remote sensing of soil moisture content. Numéro de notice : A2020-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946297 Date de publication en ligne : 31/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2946297 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94860
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 4 (April 2020) . - pp 2266 - 2275[article]Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)
PermalinkImpact of signal contamination on the adaptive detection performance of local hyperspectral anomalies / Stefania Matteoli in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)
PermalinkModelling the Zn emissions from roofing materials at Créteil city scale - Defining a methodology / Emna Sellami-Kaaniche (2012)
PermalinkA GIS-based approach in support of an assessment of food safety risks / L. Beni in Transactions in GIS, vol 15 n° 3 (July 2011)
PermalinkOptimization of mobile radioactivity monitoring networks / Gerard B.M. Heuvelink in International journal of geographical information science IJGIS, vol 24 n°3-4 (march 2010)
PermalinkGIS, multi-criteria and multi-factor spatial analysis for the probability assessment of the existence of illegal landfills / G. Biotto in International journal of geographical information science IJGIS, vol 23 n°9-10 (september 2009)
PermalinkSensitivity analysis of spatial models / Linda Lilburne in International journal of geographical information science IJGIS, vol 23 n° 1-2 (january 2009)
PermalinkPatterns in soil quality: Natural geochemical variability versus anthropogenic impact in soils of Zeeland, The Netherlands / P.F.M. Van Gaans in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)
PermalinkPermalinkClassification of contamination in salt marsh plant using hyperspectral reflectance / M.D. Wilson in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)
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