Mountainous village relocation planning with 3D GIS virtual imaging space model and neural network

Abstract

China’s mountainous village relocation planning faces the problems of extensive survey ranges and high travel costs, and current planning still depends on traditional field visits and census data survey method. To improve efficiency and control costs, digital survey methods are proposed to support efficient data collection and produce data with accurate spatial reference . This research discusses a specific survey method for relocation planning using virtual imaging space modeling based on 3D GIS combined with neural network algorithm. A digital village model of a pilot village is established by oblique photography and WEBGIS technology, while the improved Mask R-CNN algorithm is adopted to identify and classify different buildings in the village. A relocation plan including the number of buildings in each class and the reclamation area is provided and the cost and value of the plan is fully evaluated. The results demonstrate that compared with the traditional survey method, the proposed method of digital survey can better address the issue of remote mountain areas, including provide more accurate, complete and sustainable information, make the surveying and planning more convenient, efficient and smart and improve the objectivity of village relocation planning.

Keywords

• 3d gis
• virtual imaging space
• neural network model
• relocation planning
• digital village