Find in Library

In order to explore the land ecological environment and landscape changes in the west, this paper builds an intelligent evaluation model based on image classification algorithms and geographic information systems. To address the challenges associated with video Geographic Information System (GIS) data retrieval, this study focuses on the organization model for such data and aims to achieve efficient and comprehensive key frame retrieval in video GIS. The research utilizes global features, local features, and deep features present in video GIS data to enhance the retrieval process and improve the quality and comprehensiveness of the retrieved results. A deep neural network is used to extract relevant features from the video GIS data, and hash coding is applied to encode the high-level features derived from the network. This approach enables efficient retrieval based on the extracted features, contributing to more accurate and relevant search results. The findings indicate that the model developed in this study has demonstrated certain practical benefits and can be effectively applied to video GIS data retrieval tasks.