Integration of micro-sensor technology and remote sensing for monitoring coastal water quality in a municipal beach and other areas in Cyprus Hadjimitsis G. Diofantos a*, Hadjimitsis G. Marinos a,b, Themistocleous Kyriacos a and Agapiou Athos a a Cyprus University of Technology, Department of Civil Engineering and Geomatics-Remote Sensing Laboratory, Limassol b Municipality of Paphos-Cyprus. *Corresponding author: E-mail:
[email protected], Tel +357 25002548, Fax: +357 25002661 ABSTRACT The proposed project has as main objective the monitoring of coastal waters using satellite remote sensing and wireless sensor technology employed on a buoy with emphasis firstly in municipal beaches and further to areas that a systematic sampling is required. Satellite remote sensing has the advantage of using remote sensing data to assess the quality of water bodies has proven to be successful not only in inland waters but to coastal water areas as shown by several others conducted studies. Reflectance signature of municipal coastal water is monitored using a GER 1500 field spectroradiometer. Simultaneous measurements of turbidity, temperature have been acquired. Cross-validation of measurements of water quality both from micro-sensor and remote sensing are planned to be undertaken. An overall methodology that integrates both micro-sensor technology and satellite remote sensing is presented. Keywords: water quality, remote sensing, micro-sensor, monitoring, municipal beaches
1. INTRODUCTION Pollution of coastal water affects both ecological processes and public health. So it is important to monitor water quality and prevent any sea pollution. Pollution of coastal waters may arise from various sources where many of these impacts can be traced back to land-based human activities or sea-activities. Cyprus is an island with areas of high level at sea biodiversity and also with large areas with major threats from sea pollution (see Figure 1), has an imperative need to design and implement new comprehensive system coverage and continuous monitoring of coastal waters. Such a system can help to monitor pollution, and immediately respond to such occurrences. The main objective of the proposed project is the monitoring of coastal waters using satellite remote sensing and Wireless Sensor Technology with emphasis on municipal beaches and on areas where systematic sampling is required, such as areas in the vicinity of desalination plants, ports or other point sources of pollution. Moreover, water samples will be taken to link some parameters with satellite and terrestrial means. In-situ measurements of physicochemical parameters (water temperature, turbidity, dissolved oxygen, pH, salinity, electrical conductivity and suspended particulate matter-suspended solids) will be taken. As well, laboratory determination of quality parameters - nutrients (total phosphorus, reactant dissolved phosphorus, total nitrogen, nitrate and nitrite, ammonium chlorophyll-a, BOD, COD) will be made. The combination of ground measurements will enable accurate measurements of the required parameters. Initially, remote sensing retrieved data will be cross-correlated with in-situ ground measurements such as temperature, turbidity, suspended particulate matter and chlorophyll-a [1, 2, 3 and 4]. Micro-sensor technology will be used to retrieve temperature and turbidity measurements on a systematic basis. Such data will be correlated with satellite and in-situ measurements.
Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, edited by Christopher M. U. Neale, Antonino Maltese, Proc. of SPIE Vol. 7472, 74720P · © 2009 SPIE · CCC code: 0277-786X/09/$18 · doi: 10.1117/12.830582
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The results and the “know how’ from such technologies from monitoring water quality can be used from local authorities to monitor their municipal beaches or even from government departments of Cyprus which are involved in water quality.
Figure 1. Biodiversity: protected areas in Mediterranean. In square the Cyprus coastal and sea area
2.
LITERATURE REVIEW: REMOTE SENSING AND WIRELESS SENSORS
Water quality monitoring and assessment can be grouped into two main approaches: •
in situ sampling or collection
•
Earth observation (EO) or remotely sensed based on satellite
In situ methods can be both time consuming and locally expensive, so EO is an emerging capability that can greatly bolster traditional in situ methods. EO offers a potentially promising alternative for scientists and managers in assessing large numbers of water bodies in an economical and timely fashion if further scientific advances are made in this area. In- situ measurements have the considerable advantage of long term continuity and, although their reliability may also be questioned, they are the reference the satellite data have to conform to [5 and 6]. The use of satellite data for water quality mapping started in the 1970's [see 7; 8]. The satellite images have several advantages instead of situ measurements since they cover a vast area and information can be represented in maps through Geographic Information Systems (G.I.S.). Especially in Cyprus one Landsat image covers approximately all the island including the coastal beaches. Furthermore Aster images can cover an entire province and finally MODIS can cover the eastern region of the Mediterranean Sea. The different remote sensing satellites data are useful tool to provide information over various temporal and spatial scales for estimating water quality characteristics. Investigations [such as 9; 10] suggest that optical data like as Landsat TM and AVHRR can provide an alternative means for obtaining relatively low-cost, simultaneous information on surface water quality conditions from numerous lakes, coastal and oceanic areas. Although optical satellite data can present a synoptic monitoring of surface water quality, its quantitative use is still a difficult task [11]. Despite many efforts reported in the scientific literature during the past three decades, however, procedures using satellite imagery to measure surface water quality have not been adopted on a routine basis.
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As it was found from the literature monitoring of water-quality parameters requires repeated and frequent synoptic-scale observations. Satellites provide the only platform for such monitoring over continental and global scales, but most satellite sensors lack adequate spatial resolution, proper sensitivity, and calibration. MODIS data provide adequate resolution and sensitivity to observe estuaries of moderate size. Results show that it is possible to estimate water-quality parameters over synoptic scales anchored on concurrent ground-truth data [12]. Applications of satellite-measured sea surface temperature (SST) information in the coastal zone require temporal sampling frequencies sufficient to resolve ocean dynamics with spatial resolutions similar to those of terrestrial applications to resolve patterns within the bays, inlets, and estuaries of interest. Available satellite SST data from the AVHRR satellite may be used under cloud-free conditions and provide four to six images per day of a given target location with a maximum spatial resolution of 1.1 km at nadir. These data are suitable for resolution of most temporal dynamics but poorly suited for spatial resolution within coastal bays [13]. Wireless sensors have been recently been used to support water quality monitoring. Wireless Sensor networks facilitate the collection of diverse types of data (from temperature to imagery and sound) at frequent intervals over large areas, allowing an intensive and expansive sampling. Furthermore, real-time data flows allow researchers to react rapidly to events [14]. As Vesecky et al. have shown (2007) wireless sensors can be applied over a small minibuoy. This can be aimed at use in a coordinated, wireless networked array of buoys for near-surface ocean sensing. The size and cost is low enough that these versatile sensor platforms can be deployed easily and in quantity [15] 3. 3.1.
METHODOLOGY & RESOURCES
METHOD
In this project will be focus on recording and collection of available satellite data (e.g. MODIS Aqua, NOAA, Landsat and Aster satellites) to be used in illustrating the parameters related to water quality. Then, we will perform preprocessing of satellite images which includes geometric correction, radiometric and atmospheric corrections. These procedures will be applied after restoring radiometric techniques (removing noise and atmospheric effects). Afterwards a statistical correlation of the situ measurements of various parameters such as temperature, turbidity e.t.c. will be tested. The aim is to identify those parameters which can be detected directly from satellite data, and the reflectance of satellite spectral data in each channel using methods of empirical relationship variables (regression analysis or multiple linear regression), to determine the spectral signature of recovery information and the development of algorithms for calculating the pollution using satellite data. Overall methodology of the project is shown in Figure 2. Multi-spectral, Landsat, MODIS Aqua and Aster satellite images will be used. For the pre-processing and processing of the satellite images the ERDAS IMAGINE 9.3 software was used. The methodology is dived into three groups: in situ measurements, remote – sensing measurements and wireless sensor measurements: •
Applying geometric and radiometric correction including atmospheric correction and conversion of DN to units of radiance and then to reflectance.
•
Using satellite images to derive temperature and turbidity
•
Carry out in-situ measurements and analysis to support image-post processing by obtaining analyses for many important physical, chemical and microbiological variables.
•
Carry out laboratory measurements of the samples taken in situ if necessary.
•
Using ‘enclosure water’: Spectro-radiometers to measure the sea water reflectance in profile as high as 10 meters below the sea.
•
Using Wireless Sensor Network which be attached at buoys for pilot areas to verifying the results obtained from the images as well comparing with those of in situ measurements. In the case e.g. of a chemical spill from a ship, buoys would be deployed to monitor the progress and concentration of the pollutant or be anchored off sensitive coastlines.
•
Cartography the water quality in municipal beaches and other areas using these data over time.
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Figure 2: Proposed methodology
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3.3 WIRELESS SENSOR NETWORK FOR ASSISTING DATA COLLECTION A Wireless Sensors Network (WSN) will be employed in a case study area. The WSN will be used in other case studies in Cyprus in order to help the remote sensing data. The WSN will consist of one wireless node placed under a buoy. The WSN will actually be a data collection system deployed to collect and reliably transmit water quality parameters (such as temperature and turbidity) to a remote basestation hosted at the Remote Sensing Laboratory of the Cyprus University of Technology. The system also hosts a GPS sensor for identifying the exact position of the WSN and an event-driven smart camera for acquiring real-time pictures of the area and also a GPRS modem for communicating with the remote server. Figures 3- 5 shows snap-shots of the WSN equipments, which will be used for the project. As well as exploiting cheap sensors, the sensor network has been designed to operate autonomously, and adapt its rate of taking measurements, data processing and network communication, to local conditions. Power management has also been central to the design, with the autonomous AI used to control sensor node operation on the basis of available resources, in particular: communication bandwidth and battery power [16]. The sensor package was designed as a waterproof containing a sensor section, a data-logger and a microprocessor running the lightweight device control algorithm, designed to control the measurement rates, data processing, queue management, data aggregation and data forwarding, together with batteries. The sensor section incorporates a temperature sensor, a water-pressure sensor, from which wave-height can be derived, an optical backscatter sensor that measures turbidity, and an electrical conductivity sensor, which is used as a surrogate for salinity. The sensor package is suspended, designed to remain fixed on the seabed, thereby giving a consistent reference orientation for current velocities and clearance above the sea bed for the optical sensor. As part of prototype design, a decision was taken to modify a buoy, to house the radio and antenna.
Figure 3. Sensor design.
Figure 4. An example of real time data received in our lab from the sensors.
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Figure 5. Examples of WSN which will be consisting from one wireless node placed over a buoy.
3.4
IN SITU MEASUREMENTS
Analyses for many important physical, chemical and microbiological variables can be carried out in the field using apparatus made specifically for field use. A significant advantage of field analysis is that tests are carried out on fresh samples whose characteristics have not been contaminated or otherwise changed as a result of storage in a container. This is of special importance for samples that are to undergo microbiological analysis but cannot be transported to a laboratory within the time limits or under the optimum conditions. Some variables must be measured in the field, either in situ or very soon after the sample has been collected. Field analysis is necessary for temperature, transparency and pH [4]. In situ measurements of salinity and temperature give important and readily accessible information of homogeneity of the water masses within the study area. Dissolved oxygen may be determined in the field or the sample may be treated (fixed) in the field and the remainder of the analysis completed in a laboratory. If samples are to be chemically preserved before being transported to the laboratory, conductivity (if required) must be measured before preservative chemicals are added [4]. Samples should be taken with an appropriate sampler, such as a depth or grab sampler, a submersible pump or a hosepipe sampler. For nutrient poor (high transparency) water up to 6 liters will be required. For eutrophic waters, 1-2 litres are usually adequate. Collecting samples at depth requires special collectors of which there are several types (Ruttner, Kemmerer, Dussart, Valas, Watt, Niskin etc). One of the most common sampler is the Van Dorn and consists of a hollow cylinder of PVC and two rubber tube and also have a string attached to them. Prior the immersion in water the two valves are pulled out and the strings are attached to a lock fitted outside the cylinder. The cylinder open at both ends is lowered to the desired depth by means of graduated rope. A metallic messenger is released along the rope. The messenger strikes the lock and releases the two rubber valves to close the cylinder. The sampler then pulled out of the water and the sample transferred to a bottle for storage. It is also possible to take samples from different depths by pumping water through a plastic tube lowered to the desired depth [4; 17]. Sampling and field measurements and laboratory analysis in default «high risk» areas are planned in the future. In the future will take place field measurements (in situ) using portable field instruments and then proper maintenance and storage of collected water samples after the completion of sampling and analysis in the laboratory will follow. 4.
PRELIMINARY RESULTS
Some of the prelimary results include measurements from the GER1500 spectroradiometer in Paphos, Cyprus on different date internals, taken measure the percentage reflectance on the sea surface at different depths, (10cm, 20 cm, 50 cm and 1 meter). The measurements clearly show that where there was surface pollution, which includes suspended
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particles and soil on the sea surface. There spectral signature on the top 10 cm was showing less reflectance than when there was no pollution. Water samples were taken to analyze the water both at the surface and at the bottom of the sea.
Figure 3. Two spectroradiometric coastal measurements in Paphos Cyprus acquired on 24/3/09 and 2/4/09 showing the % reflectance on a clear and non clear water surface
5. CONCLUSIONS AND FUTURE WORK This new proposed monitoring system will allow the sustainable management of water resources since it can readily identify all point sources of pollution in coastal waters. A key advantage of this system is saving time compared with the process of site of in-situ sampling and analysis to identify point sources of pollution and thus reducing costs. The significance of immediate detection of pollution sources is the possibility of early treatment of environmental problems that arise and seeks to protect and restore the natural environment wherever possible.
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