In paper considered the problem of using remote sensing monitoring ofthe exogenous processes. The satellite observations can used in tasks of detection of newly formed landslides, landslips and karst collapses. Practices hows that the satellite images of the same area, taken at different times, can have significant differences from each other. The reasons for these differences may include weather conditions, time of day, time of year and so on. Thus, itis necessary to perform the satellite images correction to bring them into thesame 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. The algorithm has been tested for the detection of clouds and karst collapses. In paper the results of algorithm work are given.