Abstract
The coastal zone is a dynamic area in which processes with different origins and scales interact. Several techniques can be used for coastal zone monitoring. Remote sensing is a powerful tool for monitoring coastal processes and oastal areas. The quality of coastal water is a very important issue, and remote sensing optical sensors can be used to quantify water quality parameters such as suspended sediments. Therefore, it is possible to estimate the total suspended matter (TSM) concentration with multispectral satellite images. To extract meaningful information, the satellite data need to be validated with in situ measurements. The main objective of this work was to quantify TSM concentrations in the breaking zone with in situ measurements. In situ validation is important for the accuracy of correlations established. A section of the northwest coast of Portugal, near Aveiro city, was chosen as a test area, and all in situ measurements were done in this area. Several in situ techniques have been used to establish a relationship between seawater reflectance and TSM concentration for the range of wavelengths from 400 to 900 nm. Empirical relationships were established for equivalent reflectance values by SPOT/HRVIR (high-resolution visible Terra/ASTER (advanced spaceborne thermal emission and reflection radiometer), and Landsat TM (thematic mapper) at visible and near-infrared equivalent bands and TSM concentrations. The reflectance values were used to estimate TSM concentration with the use of the relationships established by in situ measurement. The reflectance of all bands of the satellite images tested showed high correlation with TSM in the wavelengths between 500 and 900 nm. The water leaving equivalent reflectance for each sensor equivalent band in the visible and near-infrared wavelengths was calculated, and a relationship between seawater reflectance and TSM concentration was established. The model coefficients and correlation factors for identical bands on different sensors presented good similarity. The work presented shows that TSM concentration in the breaking zone can be obtained directly from simulated multispectral satellite data. However, in situ measurements are essential to calibrate the process and establish the empirical relationships between TSM concentration and water leaving reflectance. The same empirical relationships found with in situ measurements will be used to estimate the TSM concentrations directly from real satellite data to try to quantify the sedimentary balance in the study area for the period of the satellite data.

Abstract
Remote sensing techniques are a powerful tool for monitoring littoral zones. Optical sensors can be used to quantify water quality parameters such as suspended sediments. It is possible to estimate the Total Suspended Matter (TSM) concentration using multi-spectral satellite images. In order to extract meaningful information, the satellite data needs to be validated with in situ measurements. The main objective of this work was to quantify the TSM in sea breaking zone, using multi-spectral satellite images. A part of the northwest coast of Portugal, centered around Aveiro, was chosen as a test area. Several methodologies have been used to establish a relationship between the above sea water reflectance and the TSM concentration. Various field trips were done in order to simultaneously obtain water samples and reflectance measurements. A relationship between TSM concentration and reflectance was established for the range 400 - 900 nm. Data from Landsat TM, SPOT HRVIR and ASTER were calibrated and geometric corrected. The reflectance values were used to estimate the TSM concentration using the relationships established using the field measurements. The model coefficients and correlation factors, for identical bands on different sensors, presented a high similarity. The results have been incorporated in a Geographical Information System (GIS).

Abstract
The coastline of Portugal is periodically surveyed by aircraft and the photographs acquired, usually at 1:8000 scale, are used for coastal protection studies. The air photo surveys are expensive and there would be great benefits if they could be replaced by processed images from Earth Observation Satellites. This paper presents the results of an ongoing project, which aims to evaluate the applicability of passive satellite images for coastal protection studies. Images from Landsat TM, SPOT HRVIR and ASTER were used. The initial visual inspection of these images was very encouraging. Two lines of work are currently being pursued - a quantitative and an image exploration approach. The first attempts to estimate the amount of sediments present in the various areas around the sea-breaking zone, by calibrating and atmospherically correcting the satellite images, and to use an established relationship between the amount of suspended sediments and the seawater reflectance. The second approach is to use unsupervised classification and data clustering algorithms to automatically identify different areas in the sea-breaking zone. The current status of each line of work is described and the plans for future work discussed.

Abstract
An agglomerative hierarchical clustering method, which uses both spectral and spatial information for the aggregation decision, is proposed here. The method is suitable for large multispectral images, provided that an unsupervised classification is previously applied. The method is tested on a synthetic image and on a satellite image of the coastal zone.

Abstract
This paper presents a system for the automatic processing of Digital Images obtained from Gel Electrophoresis. The system identifies automatically the number and the location of lanes in the digital image, as well as the location of bands on each lane, without any intervention from the user. A reference lane with a know substance is used to compute the molecular weight of the observed (unknown) bands. The system performance was tested using 12 images, obtained from 4 gels with 3 different exposures. A total of 5443 bands were tested in 12 images, 672 reference / observed lane pairs. The average error in the estimation of molecular weight of 9.2%.

Abstract
Standard granulometry methods are used to count the number of disjoint grains in digital images. For the case of overlapping grains, the standard method is not effective. Two alternative methods for counting overlapping grains in digital images are proposed. The methods are based on mathematical morphology and are suitable for grains of circular shape. The standard and overlapping methods were tested with a Monte-Carlo simulation using 32500 synthetic images with various grain sizes and quantities, as well as different levels of noise. The overall average counting error for all images tested with intermediate amount of noise (zero mean Gaussian noise with sigma = 0.05) was 6.03% for the standard method, and 4.40% and 3.56% for the overlapping methods. The performance of the proposed methods was found to be much better than the standard method for images with significant overlap between grains.