The main technical problem that may arise when trying to monitor hydrological ecosystems is that the number of desired images of a region of interest in a specific space-time window is not always available and some of the available images need to be discarded due to insufficient quality which means a considerable decrease in the size of the sample set. For this reason, the number of image samples can be multiplied by the number of satellite sensors that have detection bands in the same spectral range, available in the same space-time window. Prior to this fusion of samples, a comparison is made of the sensors placed in the available satellite platforms to validate the compatibility of them due to the difference in the characteristics of the satellite vehicle, the characteristics of each sensor, and the difference in time when the pictures were taken. In our case, the area of interest is the Gulf of California because it is an enormous biological rich ecosystem, making it an excellent scenario for climate change monitoring. This work also exposes the effect of anomalous data, such as the negative values and those outside the expected range in the images, the reason why they appear and the strategies used to minimize their effect. Finally, the scope and limitations of performing a combined use of the data coming from different satellites, thus increasing the number of available images and thus making more precise estimates of optical parameters of seas and oceans.
It has been realized an estimation of variance of the sea surface slopes through the variances on images that consist of bright and dark regions that are called glitter pattern. The probability distribution of the sea surface slopes has been used considering a non-Gaussian case taking in account the skewness and the kurtosis of the sea surface slopes. These relationships of variance have been calculated for five different angles of light incidence on the sea surface and for four different heights of the image sensor. The brightness in the glittern pattern has been modeled using a Gaussian function with information of the incident and reflection light angle in its argument. Some computational aspects and applications for optical engineering are mentioned.
The reflection of the sunlight over the sea surface is called glitter pattern. In previous works where the one-dimensional case was analyzed, the glitter function was mathematically described by a rect function. This rect function has proven to be a very good representation of the glitter pattern. A Gaussian glitter function is used like a first approximation to the rect function. The statistical relationship between the variance and the correlation function of the intensities of the image, the glitter pattern, and the variance of the sea surface slopes are obtained and analyzed. The analytical solutions for these relationships are given by different equations; however, the graphic representations are very similar.
The reflection of the sunlight over the sea surface is called glitter pattern. In previous works, when the onedimensional case is analyzed, the glitter function was mathematically described like a rect function. This rect function has proved to be a very good representation of the glitter pattern. In this paper a Gaussian glitter function is used like a first approximation to the rect function. The statistical relationship between the variance of the intensities of the image, the glitter pattern, and the variance of the sea surface slopes is obtained and analyzed. The analytical solutions in this relationship are mathematical different but the graphics are very similar.
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