Recognition and Spatial Distribution of Rural Buildings in Vietnam

Abstract

The research on the distribution of rural buildings is one of the fundamental works of urban–rural development in Vietnam. Adopting a Mask R-CNN deep learning framework and collecting sub-meter remote sensing images, this research used a remote sensing interpretation model of rural buildings trained based on East Asian characteristics of rural buildings and successfully recognized about 2.87 million rural buildings in 34 Vietnamese provincial administrative districts with a total area of rural buildings of 2492 million square meters. The reliability of the identification results was verified by manual detection and quantitative statistics, and a multi-scale database of rural buildings in Vietnam based on individual rural buildings was created. Based on the database, this paper analyzes the distribution characteristics of rural buildings and summarizes characteristics of rural building distribution at the country, regional, and provincial scales. The identification results lay the foundation for the next study of urban–rural relations in Southeast Asia and the construction of a basic database on villages.