Integrating Satellite Data with Ground-Based Low-Cost Sensors for Hourly Fine-Scale Land Surface Temperature Mapping: A Case Study in Bentley, Western Australia

Abstract

Climate change and rapid urbanisation are intensifying the urban heat island effect, increasing thermal stress, degrading air quality, and leading to rising energy demand. Monitoring neighbourhood-scale heat requires Land Surface Temperature (LST) observations at fine spatial and temporal resolutions, yet satellite thermal products are limited by revisit frequency, acquisition time, and cloud cover. This study developed a novel approach integrating satellite-derived land cover characteristics with continuous contact-based temperature measurements from low-cost LoRaWAN sensors and geostatistical modelling to generate hourly LST maps at 10 m resolution. The technique provides communities with simpler, affordable methods for measuring heat islands and supporting mitigation strategies. Observations from 52 locations across Curtin University’s Bentley campus in Perth, Western Australia, were combined with land cover indices. Empirical Bayesian Kriging captured spatial and temporal urban heat patterns with a root mean square error of approximately 3 °C, representing a bias of near 1 °C. Predictions were consistent with Landsat-derived LST, revealing persistent heat retention over asphalt and cooler conditions associated with vegetation. Integrating satellite-derived predictors with ground measurements provides continuous fine-scale information to identify local heat hotspots and inform targeted mitigation. Unlike satellite data, these low-cost ground measurements could be collected with the help of urban practitioners, developers, and academic institutions.