2016
DOI: 10.1016/j.ecoleng.2015.09.045
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Ecosystem services and bioremediation of polluted areas

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Cited by 27 publications
(16 citation statements)
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References 59 publications
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“…The factors are non-binary layers [ 47 ]. All raster maps were standardized [ 48 ] and weighted through the ANP technique [ 49 ] and pairwise comparison thanks to the spatial multicriteria evaluation module of ILWIS 3.8. Air component and human health data were not considered.…”
Section: Methodsmentioning
confidence: 99%
“…The factors are non-binary layers [ 47 ]. All raster maps were standardized [ 48 ] and weighted through the ANP technique [ 49 ] and pairwise comparison thanks to the spatial multicriteria evaluation module of ILWIS 3.8. Air component and human health data were not considered.…”
Section: Methodsmentioning
confidence: 99%
“…Six articles from our sample was written on the phytoremediation potential of giant reed. Cervelli, et al [61] investigated bioremediation of polluted areas and analysed poplar and giant reed as possible solutions. Results suggest that both crops may serve as tools for bioremediation of contaminated soils and their use increase the value of ecosystem services.…”
Section: Phytoremediation/waste Managementmentioning
confidence: 99%
“…Constrained areas were deleted and factors area summed. Thus, with the aim of producing homogeneous data, various layers converted into raster maps were standardized in a common scale from 0 to 1, to provide the degree of the answer to a specific identified factor or constraint [49]. Specifically the value 0 was assigned to the worst environmental condition and the value 1 to the best one.…”
Section: Spatial Multicriteria Decision Analysismentioning
confidence: 99%
“…The other classes were sorted out from a Natural Jenks classification (Baz et al 2009), which group data into like classes, minimizing differences within each data class and maximizing differences between classes. The classification has to be considered as a baseline from which to build scenario analysis [49].…”
Section: Spatial Multicriteria Decision Analysismentioning
confidence: 99%
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