Abstract:
To formulate and monitor the progress of development policies, acquiring data with sufficient spatiotemporal details is inevitable. With the increasing availability of open remote-sensing data and open-source software packages, this research suggested the novelty integration of satellite data and spatial analytical methods, enabling a timely and costless framework for assessing the nationwide socioeconomic condition. Specifically, the spatial statistical and spatial econometrical methods were applied to geospatial data to identify the clustering patterns and the localized associations of inequality in Thailand. The spatial statistical results showed that Bangkok and its vicinity had been a cluster of high socioeconomic conditions, representing the spatial inequality of development. In addition, results of the spatial econometrical models showed that the satellite-based indicators could identify the socioeconomic condition (with p-value < 0.010 and R-squared ranging between 0.345 and 0.657). Inequality indicators (i.e., Gini, Thiel and Atkinson) were then constructed by using survey-based and satellite-based data, informing that spatial inequality has been slowly declining. These findings recommended the new establishment of polycentric growth poles that offer economic opportunities
and reduce spatial inequality. In addition, in accordance with Sustainable Development Goal 10 (reduced inequalities), this analytical framework can be applied to country-specific implications along with the global scale extensions.
