Integrating remote sensing data and ground information for solving natural resource and environmental problems

Abstract

We consider the rationale for the integration of remote sensing data and ground information using a statistical criterion to solve natural resources and environmental problems. The method is proposed to be implemented as the module of the "computer assistant". The algorithm that describes a set of the sequence of operations for automation of the decision-making procedure is presented. This algorithm should free the operator from a significant amount of subjective and labor-intensive work, which is performed using visual methods. Based on the proposed methodology, we perform the object recognition in aerospace images of the territory with different geological and landscape conditions and, respectively, with standard objects of different classes with different sets of values of informative features (of different nature and dimension). For the recognition and classification of images of studied objects, the probabilities of the ratios of informative features of the studied areas to ones of each standard object present in the aerospace image were determined. The results of testing the proposed methodology are presented on the examples of assessing oil and gas prospects in the areas of the Dnieper-Donetsk cavity and the problem of classifying crops of different varieties in different periods of vegetation in the agricultural fields in the Kyiv region.