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Remote Sensing

Monitoring coastal water quality using ground-based and space technology

Municipal beaches in Cyprus will be monitored by integrating satellite remote sensing, wireless sensors deployed on buoys, and field spectroscopy.
17 August 2010, SPIE Newsroom. DOI: 10.1117/2.1201007.002977

Pollution of coastal waters, which affects both ecological processes and public health, can arise from various sources, many of which can be traced back to land-based or sea-based human activities. In Cyprus, the coastal water quality at municipal beaches must fully comply with the water quality sampling criteria of the European Union (e.g., the Blue Flag Program). An important problem for local authorities is the lack of an effective automated system for collecting and processing information from municipal beaches. As a result, pollution control is performed on the basis of thin controls on the spot and periodic sampling.

Monitoring the water quality at a given location consists of in situ measurements or laboratory analysis of water samples. Such techniques, which are considered accurate for a particular sampling point in time and space, are time consuming and expensive. Furthermore, they do not provide synoptic views of the landscape, which are necessary to support management decisions that can effectively control or improve water quality. Not only is the process time- and labor-intensive, but the required number of samples also hinders such implementation.

Integrating a remote sensing technique and seawater sampling is, therefore, more appealing and worth pursuing. Satellite images provide synoptic coverage of the area under investigation (see Figure 1). The use of satellite data for coastal water quality mapping began in the 1970s.1 Despite the variety of applications in which satellite remote sensing has already been used for this purpose, however, further work is needed to develop a complete management and monitoring system for use by local authorities to assess and measure coastal water quality on municipal beaches.

Figure 1. Satellite image of the Paphos coastline, where municipal beaches are under the Blue Flag Program.

Our proposed project aims to design and develop an innovative coastal water quality monitoring and management system. It will be based on the regular, automated collection and processing of data emanating from a network of floating sensor platforms installed on municipal beaches, high- or middle-resolution satellite images, and field spectroscopy measurements. The proposed work includes development and extensive testing of the system according to a carefully planned methodology that involves pioneering research in coastal water quality, in particular that supports the Blue Flag Program for municipal beaches. Wireless sensor networks facilitate the collection of diverse types of data at frequent intervals over large areas, enabling intensive and expansive sampling. Furthermore, real-time data flows allow local authorities to react rapidly to events. The overall approach is to develop regression models in which each water-quality parameter will be retrieved using image, field spectroscopy, and water quality data. Then, data from satellite images and microsensors employed on buoys (like that shown in Figure 2) will be used for systematic cross-validation and monitoring of coastal water quality.

Figure 2. Wireless sensor technology employed on a buoy developed at the Cyprus University of Technology.

In this project, we will focus on collecting and recording available satellite data for use in illustrating the parameters related to water quality. Next, we will preprocess satellite images, applying geometric, radiometric, and atmospheric corrections. Finally, we will test the statistical correlation between in situ measurements of various parameters, such as temperature and turbidity, and image and spectroradiometric data.

Our aim is to identify those parameters that can be detected directly from satellite data and reflectance information in satellite spectral data in each band using regression analysis or multiple linear regression. We also want to determine the spectral signature for recovery information and develop algorithms for calculating the amount of pollution using satellite data.

We used multispectral satellite images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat TM/ETM+, and the Moderate Resolution Imaging Spectroradiometer (MODIS) to begin to address these questions. Spectral signatures at water depths of 0.10, 0.20, 0.50, and 1.00m were obtained using an SVC HR-1024 field spectroradiometer (see Figure 3). Correlating the suspended solids and turbidity with the water reflectance obtained using the spectroradiometer revealed a high correlation with blue and green wavelengths, respectively (r2>0.80). The reflectance values ranged from 1.5% to 6.3% for the period from August 3, 2009 to January 5, 2009 (Landsat TM band 1) without any indication of alerts due to pollution scenarios (reflectance values more than 10–15% in blue wavelengths).

Figure 3. Spectral signature of a municipal beach in Paphos, Cyprus acquired using a field spectroradiometer at different depths.

Continuous surface measurements requiring numerous in situ samplings are very costly because of the need for human labor. An automatic and autonomous sensor system that can be remotely controlled will address this problem and allow real-time analysis of combined satellite and surface data for continuous monitoring of coastal water quality in municipal beaches and other coastal areas over Cyprus. The next step for implementing the proposed integrated system is simultaneous measurement of coastal water reflectance by a spectroradiometer, measurement of water quality parameters by the buoy system, and in situ water sampling during satellite overpasses.

The Remote Sensing Laboratory would like to thank SignalGeneriX Ltd for developing the Wisense® smart data buoy and remote monitoring system

Diofantos Hadjimitsis
Department of Civil Engineering & Geomatics
Remote Sensing Laboratory
Cyprus University of Technology
Lemesos, Cyprus

Diofantos Hadjimitsis is an associate professor and head of the Remote Sensing Laboratory. He has published more than 140 publications in journals and conference proceedings. He has actively participated in the SPIE Remote Sensing Europe conferences for the last six to eight years.

Marinos Hadjimitsis
Department of Civil Engineering & Geomatics
Cyprus University of Technology/Municipality of Paphos
Lemesos/Paphos, Cyprus
Christiana Papoutsa, Athos Agapiou, Kyriakos Themistocleous
Department of Civil Engineering & Geomatics
Cyprus University of Technology
Lemesos, Cyprus