Smart monitoring of water quality in Asprokremmos Dam in Paphos, Cyprus using satellite remote sensing and wireless-sensor platform
Journal
Proceedings of SPIE - The international society for optical engineering
Date Issued
2010
DOI
10.1117/12.864824
Abstract
The use of satellite remote sensing for water quality monitoring in inland waters has substantial advantages over the in-situ sampling method since it provides the ability for overall area coverage and also for study and supervision of isolated locations. The development of algorithms for water quality monitoring using satellite data and surface measurements can be widely found in literature. Such algorithms require validation and one of the major problems faced during these attempts was the need for continuous surface measurements requiring numerous in-situ samplings that imply also very high costs due to the need of increased human labour. The development of an automatic and autonomous sensor system able to be remotely controlled, will cover this gap and will allow the real time combined analysis of satellite and surface data for the continuous monitoring of water quality in dams as well as the overall water resources management. Wireless Sensor Networks (WSN) can provide continuous measurements of parameters taken from the field by deploying a lot of wireless sensors to cover a specific geographical area. An innovative, energy-autonomous floating sensor platform (buoy) transferring data via wireless network to a remote central database has been developed for this study which can be applied on all dams in Cyprus. Indeed this project describes the results obtained by an existing running campaign in which in-situ spectroradiometric (GER1500 field spectroradiometer) measurements, water sampling measurements (turbidity), sensor measurements (turbidity) and Landsat TM/ETM+ data have been acquired at the Asprokremmos Dam in Paphos (Cyprus). By applying several regression analyses between reflectance against turbidity for all the spectral bands that correspond to Landsat TM/ETM+ 1-2-3-4, the highest correlation was found for TM band 3 (R 2=0.83)