Design and Implementation of Intelligent Geographic Information System Based on Remote Sensing Data Mining
This paper have designed and implemented an intelligent geographic information system(GIS)based on remote sensing data mining,aiming to process and analyze massive remote sensing data.This system includes two core technologies:Semantic segmentation of remote sensing images and spatiotemporal trajectory pattern mining.The semantic segmentation of remote sensing images adopts an improved convolutional neural network model,achieving high-precision extraction of geographic features such as buildings and roads.The spatiotemporal trajectory pattern mining adopts spectral clustering algorithm to efficiently discover movement patterns and key positions in trajectory data.The system integrates functional modules such as remote sensing image processing,spatiotemporal data mining,geographic information visualization and analysis,and achieves intelligent geographic information services.
remote sensing data miningGISsemantic segmentation
NETL
NSTL
万方数据
