Intelligent Identification of Survival Environment Information of Typical Endangered Animals
There are many kinds of geological environment problems, the frequency of occurrence is high, and the scope of influence is wide, which is not conducive to human survival and sustainable development. Therefore, identifying the geological environment information in the geological environment is of great significance for geological environment protection and ecological civilization construction. This paper focuses on remote sensing data, and carries out intelligent identification research on the typical geological living environment information of the endangered animal in the Dabie Mountains. This paper researches and develops robust system software to realize the human-machine interactive intelligent division of geological environment resources, and improve the division efficiency and precision. Reduce the labor intensity of the division and interpretation of artificial geological environment resources. The intelligent identification of new remote sensing data is realized by using SVM support vector machine algorithm and using MVC technology framework. In this paper, the mean shift segmentation algorithm is used as the remote sensing image segmentation algorithm, and the mean shift segmentation algorithm is implemented and improved under the 64-bit system platform. The carrying capacity of the mean value drift segmentation algorithm of remote sensing image data is improved. Before using the algorithm to segment the remote sensing image, the segmentation phenomenon caused by the Mean shift segmentation algorithm is improved, and the effectiveness of the method is proved by experiments. In view of the advantages and disadvantages of automatic computer interpretation and visual interpretation, this paper uses ARIMA model method to interpret remote sensing images. Based on the new remote sensing data and the proposed method system, it can effectively identify the typical geological environment information in the text, and provide scientific theoretical and technical support for geological environment protection and ecological civilization construction.