Data for: Does Built-Up Intensity Moderate the Cooling Efficiency of Urban Green Space? A Multi-City Google Earth Engine Analysis of Tropical Southeast Asian Cities

Data and code for the manuscript "Does Built-Up Intensity Moderate the Cooling Efficiency of Urban Green Space? A Multi-City Google Earth Engine Analysis of Tropical Southeast Asian Cities" (Forum Geografi, submission 19485). The dataset contains 100 m grid cells for four cities (Jakarta, Kuala Lumpur, Ho Chi Minh City, Bangkok) in 2015, 2017, 2019, 2021 and 2023: land surface temperature (Landsat 8/9 Collection 2 Level-2), NDVI, NDBI, NDWI, VIIRS night-time light, SRTM elevation, GHS-POP population, and a building-height index from the Google Open Buildings 2.5D Temporal Dataset. Version 2.1.0 (revision): adds the water-mask sensitivity scenarios, city-by-year fixed-effects models, map figures, the Google Earth Engine export scripts (main export, GHS-POP, Open Buildings), the R join script that builds DATA_FULL_WITH_CONTROLS.csv, and all R scripts and output tables that reproduce the numbers in the paper. This record replaces an earlier upload (10.5281/zenodo.23686160, v2.0.0) whose zip lacked the dry-season file Bangkok_2015.csv. Folder structure: 01_gee_scripts, 02_data (a_analysis_data, b_raw_gee_export, c_ghs_pop, d_open_buildings, e_dry_season), 03_r_scripts, 04_outputs, 05_supplementary. See README.md. Notes: GHS-POP for 2023 uses the modelled 2025 epoch; Open Buildings for 2015 uses the 2016 epoch as a proxy. BUILT_HEIGHT_VOL is the cell mean of the building_height band and is an index of built height, not building volume. KualaLumpur_2015.csv in e_dry_season has no optical bands and is excluded from all analyses. Source data licences apply to the underlying products (USGS/NASA Landsat, NOAA VIIRS, SRTM, JRC GHSL, Google Open Buildings).