H3 Hexagon-Based Advanced Rural-Urban Metrics Analysis and Modeling (2000-2020) in Thailand, Southeast Asia

Over the past decades, the relationship between populations and built environments has undergone rapid changes worldwide, creating a pressing need for new data within relevant geographic contexts to support metrics and decision-making. This is especially true in developing and upper-middle-income countries, where rapid urbanization and population growth have significantly altered the urban-rural landscape. Thailand serves as a case study, illustrating how changes in population, built-area expansion, population density per built surface and volume, and land consumption rates have strongly influenced patterns along the rural-urban continuum (RUC). This data descriptor introduces a unique and scalable dataset informed by H3 hexagonal spatial aggregations. The dataset utilizes open-source global data products from WorldPop and the Global Human Settlement Layer (GHSL), along with various derived metrics. It includes 40 variables related to built environments, population metrics, and land consumption for mainland Thailand from 2000 to 2020, in 10-year increments. This dataset can support the development of evidence-based urban-rural land use policies and programs, metrics of population-built environment changes, and addressing questions about Thailand's evolution into a middle-income economy with changing urban and rural spaces over the past two decades.