Assessment Method of Lake´s Water Quality Based on Remote-Sensed Image and Support Vector Machine

This paper introduces a data fusion processing method based on remote-sensed image data and the algorithm of support vector machine, and analyzes an experiment on the water quality monitoring data of Taihu Lake. This method builds a SVM model to map remote sensing image into dispersed water quality classifications of lake´s water quality monitoring spots, then, it distinguishes the whole lake´s water quality condition combining with this model. By comparing with the results, the experiment shows that the results of the identifications of water quality of Taihu Lake match the practical water quality conditions well by using such method, and it provides a convenient and effective technical mean for monitoring and assessment of large catchments, as well, it has a good applied value on other fields.