Predicting Urban Land Expansion and Local Economic Growth by Integrating CLUE-S and Economic Model: an Application to Ban Chang District, Thailand

Timely and granular information on urban and economic growth is necessary for achieving sustainable development goals. This study aims to predict economic growth and urban land-use change in one of the fastest-growing cities in Thailand—Ban Chang District—from 2021 to 2030. Geospatial and economic data obtained from Google Earth Engine and government agencies were utilized to meet the objective. This paper presents a newly developed modeling framework that integrates CLUE-S with a structural equation model to predict economic growth and urban land-use change at the district level. The obtained results show that the average spatial accuracy of the model is 92%. Under normal circumstances, the results suggest urban land expansion to take place in the central, western, and southern parts of Ban Chang District. In addition to urban land growth, the compound annual growth rate of Ban Chang’s GDP between 2021 and 2030 is 5.6%. Operating based on open data and open-source software packages, the modeling framework developed in this study can be applied to other developing countries for timely monitoring the economic growth at the city or district level.