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ISPRS Int. J. Geo-Inf. 2014, 3(4), 1234-1255; doi:10.3390/ijgi3041234

Improving Inland Water Quality Monitoring through Remote Sensing Techniques

1
Remote Sensing Division, National Institute for Space Research (INPE), Avenida dos Astronautas, 1758, São José dos Campos 12227-010, Brazil
2
Department of Earth Sciences, Indiana University-Purdue University Indianapolis, 723 W. Michigan Street, SL118, Indianapolis, IN 46202, USA
3
Department of Environmental Health, Fairbanks School of Public Health, Indiana University, 714 N. Senate Avenue, EF 206, Indianapolis, IN 46202, USA
*
Author to whom correspondence should be addressed.
Received: 9 June 2014 / Revised: 13 October 2014 / Accepted: 30 October 2014 / Published: 14 November 2014
(This article belongs to the Special Issue Remote Sensing and Geospatial Technologies in Public Health)
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Abstract

Chlorophyll-a (chl-a) levels in lake water could indicate the presence of cyanobacteria, which can be a concern for public health due to their potential to produce toxins. Monitoring of chl-a has been an important practice in aquatic systems, especially in those used for human services, as they imply an increased risk of exposure. Remote sensing technology is being increasingly used to monitor water quality, although its application in cases of small urban lakes is limited by the spatial resolution of the sensors. Lake Thonotosassa, FL, USA, a 3.45-km2 suburban lake with several uses for the local population, is being monitored monthly by traditional methods. We developed an empirical bio-optical algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS) daily surface reflectance product to monitor daily chl-a. We applied the same algorithm to four different periods of the year using 11 years of water quality data. Normalized root mean squared errors were lower during the first (0.27) and second (0.34) trimester and increased during the third (0.54) and fourth (1.85) trimesters of the year. Overall results showed that Earth-observing technologies and, particularly, MODIS products can also be applied to improve environmental health management through water quality monitoring of small lakes. View Full-Text
Keywords: chlorophyll-a; cyanobacteria biomass; empirical algorithms; remote sensing chlorophyll-a; cyanobacteria biomass; empirical algorithms; remote sensing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ogashawara, I.; Moreno-Madriñán, M.J. Improving Inland Water Quality Monitoring through Remote Sensing Techniques. ISPRS Int. J. Geo-Inf. 2014, 3, 1234-1255.

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