2013
DOI: 10.1007/s10661-013-3125-3
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River pollution remediation monitored by optical and infrared high-resolution satellite images

Abstract: The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation condi… Show more

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Cited by 9 publications
(5 citation statements)
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“…Although conventional field methods give accurate measurements, they are time-consuming and expensive. Satellite remote sensing is a powerful supportive tool for assessing of spatial and temporal variations in water quality (Giardino, Pepe, Brivio, Ghezzi, & Zilioli, 2001;Sriwongsitanon, Surakit, & Thianpopirug, 2011;Trivero et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…Although conventional field methods give accurate measurements, they are time-consuming and expensive. Satellite remote sensing is a powerful supportive tool for assessing of spatial and temporal variations in water quality (Giardino, Pepe, Brivio, Ghezzi, & Zilioli, 2001;Sriwongsitanon, Surakit, & Thianpopirug, 2011;Trivero et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…We then converted the imagery into Normalized Difference Vegetation Index (NDVI) images (Malone and Foster 2019). NDVI analysis is commonly used in remote sensing studies to determine the health of plants (Trivero et al 2013), and more specifically used in agricultural settings where crop yields and pesticide applications are particularly important (Griffith 2002). The NDVI vegetation categories of “not vegetation” (all values below 0.1), “sparse vegetation” (0.1 to 0.2), “moderate vegetation health” (0.2 to 0.55), and “very healthy vegetation” (0.55 to 1.0) were assigned to each image (Weier and Herring 2000).…”
Section: Methodsmentioning
confidence: 99%
“…back-propagation neural network model) to establish a retrieval model for concentrations of TN & TP on the basis of satellite data (Xiao et al, 2015) Water quality proxy • Assess health of vegetation alongside water bodies as a proxy for water quality, using vegetation indices (e.g. NDVI, EVI) (Trivero et al, 2013) • Identification and mapping of submergent aquatic vegetation using image interpretation and classification techniques (Ackleson and Klemas, 1987;Dogan et al, 2009;Wolter et al, 2005;Yang, 2005) Water Availability Water body area & configuration…”
Section: Biochemical Traits Inc Chlorophyll (Ch) and Water Content Nimentioning
confidence: 99%