KotchiBrazeauTurgeonEtAl2015

Référence

Kotchi, S.O., Brazeau, S., Turgeon, P., Pelcat, Y., Legare, J., Lavigne, M.-P., Essono, F.N., Fournier, R.A. and Michel, P. (2015) Evaluation of Earth Observation Systems for Estimating Environmental Determinants of Microbial Contamination in Recreational Waters. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(7):3730-3741. (Scopus )

Résumé

Public health risks related to the microbial contamination of recreational waters are increased by global environmental change. Intensification of agriculture, urban sprawl, and climate change are some of the changes which can lead to favorable conditions for the emergence of waterborne diseases. Earth observation (EO) images have several advantages for the characterization and monitoring of environmental determinants that could be associated with the risk of microbial contamination of recreational waters in vast territories like Canada. There are a large number of EO systems characterized by different spatial, temporal, spectral, and radiometric resolutions. Also, they have different levels of accessibility. In this study, we compared several EO systems for the estimation of environmental determinants to assess their usefulness and their added value in monitoring programs of recreational waters. Satellite images from EO systems WorldView-2, GeoEye-1, SPOT-5/HRG, Landsat-5/TM, Envisat/MERIS, Terra/MODIS, NOAA/AVHRR, and Radarsat-2 were acquired in 2010 and 2011 in southern Quebec, Canada. A supervised classification of these images with a maximum likelihood algorithm was used to estimate five key environmental determinants (agricultural land, impervious surfaces, water, forest, and wetlands) within the area of influence of 78 beaches. Logistic regression models were developed to establish the relationship between fecal contamination of beaches and environmental determinants derived from satellite images. The power prediction of these models and criteria such as accuracy of classified images, the ability of the sensor to detect environmental determinants in the area of influence of beaches, the correlation between the estimated environmental determinants in the area of influence by the sensor with those estimated by very high spatial resolution reference sensors (WorldView-2 and GeoEye-1), and general criteria of accessibility (cost of the images, imaging swath, satellite revisit interval, hours of work, and expertise and material required to process the images) were used to evaluate the EO systems. The logistic regression model establishing the relationship between environmental determinants from Landsat-5/TM images and the level of fecal contamination of beaches is the one which performs best. These images are also those that best meet all of the evaluation criteria. This study showed that environmental determinants like agricultural lands and impervious surfaces present in the area of influence of beaches are those which contribute the most to the microbial contamination of beaches. Our study demonstrated the utility and the added value that EO images could bring to programs monitoring the microbial contamination of recreational waters. © 2008-2012 IEEE.

Format EndNote

Vous pouvez importer cette référence dans EndNote.

Format BibTeX-CSV

Vous pouvez importer cette référence en format BibTeX-CSV.

Format BibTeX

Vous pouvez copier l'entrée BibTeX de cette référence ci-bas, ou l'importer directement dans un logiciel tel que JabRef .

@ARTICLE { KotchiBrazeauTurgeonEtAl2015,
    AUTHOR = { Kotchi, S.O. and Brazeau, S. and Turgeon, P. and Pelcat, Y. and Legare, J. and Lavigne, M.-P. and Essono, F.N. and Fournier, R.A. and Michel, P. },
    TITLE = { Evaluation of Earth Observation Systems for Estimating Environmental Determinants of Microbial Contamination in Recreational Waters },
    JOURNAL = { IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing },
    YEAR = { 2015 },
    VOLUME = { 8 },
    PAGES = { 3730-3741 },
    NUMBER = { 7 },
    NOTE = { cited By 0 },
    ABSTRACT = { Public health risks related to the microbial contamination of recreational waters are increased by global environmental change. Intensification of agriculture, urban sprawl, and climate change are some of the changes which can lead to favorable conditions for the emergence of waterborne diseases. Earth observation (EO) images have several advantages for the characterization and monitoring of environmental determinants that could be associated with the risk of microbial contamination of recreational waters in vast territories like Canada. There are a large number of EO systems characterized by different spatial, temporal, spectral, and radiometric resolutions. Also, they have different levels of accessibility. In this study, we compared several EO systems for the estimation of environmental determinants to assess their usefulness and their added value in monitoring programs of recreational waters. Satellite images from EO systems WorldView-2, GeoEye-1, SPOT-5/HRG, Landsat-5/TM, Envisat/MERIS, Terra/MODIS, NOAA/AVHRR, and Radarsat-2 were acquired in 2010 and 2011 in southern Quebec, Canada. A supervised classification of these images with a maximum likelihood algorithm was used to estimate five key environmental determinants (agricultural land, impervious surfaces, water, forest, and wetlands) within the area of influence of 78 beaches. Logistic regression models were developed to establish the relationship between fecal contamination of beaches and environmental determinants derived from satellite images. The power prediction of these models and criteria such as accuracy of classified images, the ability of the sensor to detect environmental determinants in the area of influence of beaches, the correlation between the estimated environmental determinants in the area of influence by the sensor with those estimated by very high spatial resolution reference sensors (WorldView-2 and GeoEye-1), and general criteria of accessibility (cost of the images, imaging swath, satellite revisit interval, hours of work, and expertise and material required to process the images) were used to evaluate the EO systems. The logistic regression model establishing the relationship between environmental determinants from Landsat-5/TM images and the level of fecal contamination of beaches is the one which performs best. These images are also those that best meet all of the evaluation criteria. This study showed that environmental determinants like agricultural lands and impervious surfaces present in the area of influence of beaches are those which contribute the most to the microbial contamination of beaches. Our study demonstrated the utility and the added value that EO images could bring to programs monitoring the microbial contamination of recreational waters. © 2008-2012 IEEE. },
    ART_NUMBER = { 7112079 },
    AUTHOR_KEYWORDS = { Environmental determinants; epidemiology; image classification; microbial contamination; optical imaging; radar imaging; remote sensing; water pollution },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1109/JSTARS.2015.2426138 },
    KEYWORDS = { Agriculture; Beaches; Climate change; Contamination; Epidemiology; Geodetic satellites; Health risks; Maximum likelihood; Maximum likelihood estimation; Observatories; Pollution detection; Public risks; Radar imaging; Regression analysis; Remote sensing; Satellite imagery; Satellites; Space-based radar; Transportation; Water pollution, Environmental determinants; Global environmental change; Logistic Regression modeling; Logistic regression models; Maximum likelihood algorithm; Microbial contamination; Optical imaging; Very high spatial resolutions, Image classification, beach; environmental impact; EOS; epidemiology; global change; health risk; image classification; marine pollution; microbiology; pollution monitoring; radar imagery; recreational management; water pollution, Canada; Quebec [Canada] },
    SOURCE = { Scopus },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84939486312&partnerID=40&md5=525c91fb0f6efb8f929dcfb4e3f38187 },
}

********************************************************** ***************** Facebook Twitter *********************** **********************************************************

Abonnez-vous à
l'Infolettre du CEF!

********************************************************** ************* Colloque **************************** **********************************************************

1er au 3 mai 2019
UQAC

********************************************************** ************* R à Québec 2019**************************** **********************************************************

********************************************************** ********************* Traits **************************** **********************************************************

********************************************************** ************* Écoles d'été et formation **************************** **********************************************************

Écoles d'été et formations

Cours intensif sur l'analyse des pistes 
6-10 mai 2019, Université de Sherbrooke
Cours intensif : Taxonomie et méthodes d’échantillonnage en tourbières 
6-17 mai 2019, Université Laval
Dendrochronological Fieldweek 2019 
16-21 mai 2019, Station FERLD
Traits Fonctionnels des Organismes - École thématique internationale
19-24 mai 2019, Porquerolles, France
Cours aux cycles supérieurs: Terrain avancé en géographie 
10-15 juin 2019, FERLD, Abitibi-Témiscamingue
École d'été « Drones et télédétection environnementale » 
13-14 juin 2019, Sherbrooke
Ecole d'été en Biologie et Ecologie intégratives 
6-12 juillet 2019, Pyrénées françaises
École d'été en modélisation de la biodiversité 
19-23 août 2019, Orford
Cours aux cycles supérieurs: Aménagement des écosystèmes forestiers 
19-30 août 2019, Station FERLD

********************************************************** ***************** Pub - Carapace ****************** **********************************************************

********************************************************** ***************** Pub - Budworm ****************** **********************************************************

********************************************************** ***************** Pub - Colibri **************************** **********************************************************

********************************************************** ********** Pub 6 - Au coeur de l'arbre *********** **********************************************************

...Une exposition
virtuelle sur l'arbre!

********************************************************** ***************** Boîte à trucs *************** **********************************************************

CEF-Référence
La référence vedette !

Jérémie Alluard (2016) Les statistiques au moments de la rédaction 

  • Ce document a pour but de guider les étudiants à intégrer de manière appropriée une analyse statistique dans leur rapport de recherche.

Voir les autres...