Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4486
Title: Field spectroscopy for assisting water quality monitoring and assessment in water treatment reservoirs using atmospheric corrected satellite remotely sensed imagery
Authors: Clayton, Chris R I 
Hadjimitsis, Diofantos G. 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Linear regression;Remote sensing;Chl-a;POC;Spectro-radiometric measurements
Issue Date: Feb-2011
Source: Remote Sensing, 2011, vol. 3, no. 2, pp. 362-377
Volume: 3
Issue: 2
Start page: 362
End page: 377
Journal: Remote Sensing 
Abstract: The overall objective of this study was to use field spectro-radiometers for finding possible spectral regions in which chlorophyll-a (Chl-a) and particulate organic carbon(POC) could be identified so as to assist the assessment and monitoring of water quality using satellite remote sensing technology. This paper presents the methodology adopted in this study which is based on the application of linear regression analysis between the mean reflectance values (measured with the GER1500 field spectro-radiometer) across the spectrum and the concentrations of chlorophyll-a (μg/L) and POC (μg/L) acquired simultaneously on the same day and time in the Lower Thames Valley in West London (U.K.) from old campaigns. Each regression model (512 in total) corresponded to a measured wavelength of the GER1500 field spectro-radiometer. The achieved correlations presented as r2 against wavelength, indicate the regions with high correlation values for both water quality variables. Based on the results from this study and by matching the spectral bands of the field spectro-radiometer with those of the Landsat TM satellite sensor (or any other sensor), it has been found that suitable spectral regions for monitoring water quality in water treatment reservoirs are the following: for chlorophyll-a, the spectral region of 0.45–0.52 μm (TM band 1), and for POC, the region 0.52–0.60 μm (TM bands 1 and 2). Then 12 atmospheric corrected Landsat TM/ETM+ band 1 images acquired from 2001 to 2010 were used for validation purposes to retrieve the Chl-a concentrations.
URI: https://hdl.handle.net/20.500.14279/4486
ISSN: 20724292
DOI: 10.3390/rs3020362
Rights: © by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license
Type: Article
Affiliation : University of Southampton 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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