Using neural networks in remote sensing monitoring of exogenous processes
Ruslan V. Sharapov, Alexey D. Varlamov · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
In paper considered the problem of using remote sensing monitoring of the exogenous processes. The satellite observations can used in tasks of detection of newly formed landslides, landslips and karst collapses. Practice shows that the satellite images of the same area, taken at different times, can have significant differences from each other. For this reason, it is necessary to perform the images correction to bring them into the same species, removing impact of changes in weather conditions, etc. In addition, it is needed to detect the clouds in the images. Clouds interfere with the analysis of images. The detection of exogenous processes manifestations can be make after these actions. For image correction and object detection can be used the neural networks. In paper are given the algorithm for image correction and the structure of a neural network.