Private Cloud Deployment of Land Resource Management Information Framework based on Cyclic Random Forest Algorithm

This paper proposes a model definition method for CRFs that integrates multiple cues, such as image spectrum, directional gradient histogram, and multi-scale and multi-directional Texton texture, for the deployment of a private cloud of land resource management information framework. Using the above characteristics, the cyclic random forest ion algorithm is selected to define the CRFs correlation potential function; the key technical nodes such as the overall positioning, security management and synchronous application of the core business of land resource management “One Map” database construction are discussed comprehensively, which effectively improves the The city's land and resources management is precise, standardized and scientific.