**3. Data**

186 Environmental Monitoring

to measure these changes in the spectral signature and relate these measured changes by empirical or analytical models to water quality parameters. The spectral resolution of most satellite imagery is insufficient to identify (concentrations of) individual components that affect water quality. In most cases, satellite remote sensing is used to investigate the dynamics of sediment loads in reservoirs and lakes (Vrieling, 2006). Many studies found significant linear or nonlinear relationships between in situ determined suspended sediment concentration near the surface of inland water bodies and atmospherically corrected spectral reflectance derived from satellite remote sensing data, such as Landsat (Nellis et al., 1998; Schiebe et al., 1992) and SPOT-HRV (Chacon-Torres et al., 1992). Because sediment characteristics, like texture and color, influence the water reflection, developed empirical relationships are not easily transferable to other regions where erosion entrains different sediment types. Therefore, until a universal equation does not exist, most models of suspended sediment are site-specific (Liu et al., 2003). Thermal infrared (TIR) satellite images can be also used to study transport processes in lakes, such as wind-driven upwelling and surface circulation, providing a measure of spatial variability and horizontal distribution of water temperature that conventional field-based measurements cannot provide, (Steissberg et al., 2006, Zhen-Gang Ji et al., 2006). There still remain many unanswered questions about the effective implementation of integrated remote sensing / GIS techniques into a lake /

environmental monitoring program, and these are analyzed in this presentation.

ecosystems.

**2. Pilot project area** 

Fig. 1. Pilot project area

lakes are included in the Chapter.

The objective of our research is to better understand the use of integrated application of remote sensing / GIS techniques on monitoring various environmental factors of lake

About 65% of the surface waters of Greece are in its north-western part, in the periphery of West Macedonia. Some of the most valuable lakes of Europe in terms of biodiversity are located in this area, (Figure 1). The analysis of the basins of Macro Prespa and Vegoritis

> Optical sensors are widely used for environmental impact monitoring. Satellite images with moderate to high spatial resolution have facilitated scientific research activities at landscape and regional scales. Different sensor properties are important to be considered, when evaluating their possible use for environmental monitoring.

> These properties refer to spatial, spectral, radiometric temporal resolution, signal-to-ratio and finally launch date, length of the time series. Multi-temporal Landsat images are the main source of information. LANDSAT-1 was the world's first earth observation satellite, launched by the United States in 1972. Following LANDSAT-1, LANDSAT-2, 3, 4, 5, and 7 were launched. LANDSAT-7 is currently operated as a primary satellite, although an instrument malfunction occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired since July 14, 2003 have been collected in 'SLC-off' mode. Of all remotely sensed data, those acquired by Landsat sensors have played the most pivotal role in spatial and temporal scaling: given the more than 30-year record of Landsat data, mapping land and vegetation cover change and derived surfaces in environmental modeling is becoming commonplace (Cohen and Goward, 2004).

Monitoring Lake Ecosystems Using Integrated Remote

Different units of measurement.

Fig. 3. Data and methods of analysis

Different types of data.

Sensing / Gis Techniques: An Assessment in the Region of West Macedonia, Greece 189

The interpretation process is set up and activated upon receipt of each image. There are several factors which can influence the quality of RS images and can affect whether or not they are even worth acquiring, e.g.: *Weather, Smoke, Time, Sensors and Sensor performance.*

Flawed images, or those having too much cloud cover, were rejected and alternatives sought. Only images with less than 10% cloud cover for the watershed areas or lakes of our pilot study area were used for the analysis. For example 5 out of the 7 collected images for the year 2011 shown in Fig. 4 were used while scenes D and H were rejected. This criterion significantly reduced the pool of images suitable for analysis but most years had at least one winter-spring / one summer-autumn image that met the criterion. From the pool of 38 images we selected 10 Landsat TM images, 2 Landsat ETM and 1 MSS images for reference spanning a ~ 35- year period (1974-2011). Another restriction refers to the scan line problem of the LANDSAT ETM scanner which made practically unusable these images for the analysis of Vegoritis lake. However, Prespa lakes are recorded properly and so Landsat

ETM images with acquisition dates after the 2003 have been included in the analysis.

All Landsat images were registered to the Greek Geodetic Datum of 1987 (EGSA '87) using the Landsat 17 January 2011 scene as a reference. The root mean square error (RMSE) for positional accuracy was generally less than 0.5 pixels (~ 10 m for Landsat TM). A nearestneigbour resampling scheme was used to preserve the original brightness values of the images. The most rigorous method of radiometric calibration involves the use of radiative transfer models to produce an absolute correction. However, some data required to perform such a calibration are unavailable for historic images. We tested simple radiometric correction techniques such as dark pixel subtraction, Sun angle correction and normalization of multi temporal images to a single reference scene but found these insufficient as the area should have: (1) similar elevation to the rest of the scene, (2) minimal vegetation, (3) a

relatively flat surface, and (4) constant pattern or general appearance over time.

Analysts should be familiar with these factors when interpreting the RS data.

Fig. 2. Climate - rainfall (B) vs hydrology water level(A) measurements of Macro Prespa (A / B left) and Vegoritis lake (A / B right)

The Landsat images that have been used in the current study have been acquired from the USGS / NASA: http://edcsns17.cr.usgs.gov/NewEarthExplorer/ . SRTM DEM data that are available from the USGS server at http://dds.cr.usgs.gov/srtm/ and ASTER-DEM http://www.gdem.aster.ersdac.or.jp/ have been also included in the analysis.

ENVISAT / MERIS, ASTER satellite systems are relatively new systems and their data are also evaluated as far as monitoring the lake water systems is concerned. Much emphasis is given to extract information concerning a variety of parameters like land cover change that influences (indirectly) lake water quality. The effects of anthropogenic land cover modification on lakes are also analyzed by incorporating detailed information about land surface properties derived from Earth Observation data. The data inventory that is prepared and reported in the current submission includes acquisition of land cover maps, geological maps, compilation of hydrogeological maps based on analysis of relevant data, compilation of digital elevation models, analysis of multi-temporal satellite data and land cover maps. The amount of the above information is reviewed and analyzed and the result of the compilation is shown in the form of various maps.
