• Green infrastructure reduces UHI by 1–4 °C (up to 5 °C in optimal cases), enhances biodiversity. • Cool roofs cut temperatures by 2–4 °C, save 20–40% cooling energy (building-scale, hot climates. • ML achieves high predictive accuracy (up to ∼95% for LST/hotspot mapping in specific contexts). • Low-income areas face 2–3 °C higher UHI, need targeted fixes. • Hybrid blue-green systems cool by 2–3 °C in tropical cities. Urban Heat Islands (UHIs) represent a pressing challenge in contemporary cities, exacerbating energy demand, public health risks, and climate vulnerability. This comprehensive review synthesizes recent advancements in UHI mitigation, critically evaluating a spectrum of strategies, including green infrastructure, high-albedo and reflective materials, urban design modifications, and emerging technological interventions. Quantitative evidence demonstrates that green roofs and vegetated façades typically reduce local temperatures by 1–4 °C, though evidence from arid cities indicates limited cooling or potential net warming from certain low-evapotranspiration vegetation types due to reduced albedo effects, while reflective surface enhancements may lower urban ozone concentrations by up to 7% (modeling estimates under widespread adoption in specific regions). Innovative tools, such as machine learning (ML) for predictive modeling, remote sensing for high-resolution monitoring, and geographic information systems (GIS) for spatial analysis, are highlighted for their ability to inform targeted interventions with ML achieving predictive accuracies up to ∼95% for LST/hotspot mapping in select contexts, though challenges including data limitations and generalizability remain. Case studies across Southeast Asia, Europe, and North America reveal regional differences in mitigation efficacy, emphasizing context-specific planning. Key implementation challenges—including financial costs, scalability constraints, maintenance requirements, and socio-economic inequities—are critically examined, alongside potential synergies and trade-offs between strategies. Expanded analyses incorporate megacities such as Singapore, New York, and Los Angeles, exploring novel approaches like AI-driven adaptive systems, industrial-zone vegetation restoration, and hybrid blue-green infrastructure. Comparative assessments across climatic zones elucidate strategy effectiveness, while spatial and temporal UHI trends are mapped to guide decision-making. By emphasizing integrated, equitable, and policy-informed approaches, this review provides actionable insights for urban planners and policymakers, supporting the design of sustainable, resilient cities capable of mitigating UHI impacts and enhancing urban livability in the face of global climate change.

Understanding the spatial factors influencing land-use transitions is essential for sustainable land management. This study analyzed nationwide land-use change in Japan over 45 years using 100 m governmental land-use grids, examining the effects of institutional zoning and pre-existing land-use patterns. A comparison of 1976 and 2021 land use revealed that 76.4% of grids exhibited no change, 5.5% experienced urbanization, 4.8% were newly cultivated, 4.5% were abandoned; 1.2% underwent crop conversion, 2.1% experienced vegetation succession, 2.0% were affected by residential relocation, 1.7% involved the creation of new water bodies, 0.9% reflected waterway stabilization, and 0.8% fell into other categories. Among unchanged grids, forests accounted for 59.6%; water bodies, 29.7%; urban land, 3.1%; farmland and paddy fields, 7.1%; and wastelands, 0.4%. Urban planning boundaries effectively mitigated uncontrolled sprawl, However, farmland abandonment occurred more frequently within designated urban planning zones. In contrast, conservation areas were effective in maintaining both farmland and forest land uses. Proximity to DIDs accelerated both urban and non-urban transitions—including farmland abandonment and new cultivation—indicating that the 500–2,000 m range from DIDs constitutes the primary sprawl zone. In this zone, land-use dynamics appear to be shaped more by demographic proximity than by regulatory control. These findings highlight how planning frameworks and population distribution jointly determine land-use trajectories, providing an empirical basis foundation for refining land-use policies that balance urban containment, farmland and forest conservation, and sustainable land management amid demographic decline.

This study presents a fully automated pipeline for mapping Physiologically Equivalent Temperature (PET) at high spatial resolution and simulating potential access to cooler paths for pedestrians in cities. PET quantifies the combined effect of solar and thermal radiation on humans and is key to assessing outdoor comfort. The pipeline automatically extracts building footprints, infers building heights, and computes shadows and sky-view factors. It uses Google Earth Engine to obtain tree canopy layers and other open-access satellite data products to compute vegetation, impervious surfaces, and water bodies, which help generate surface albedo maps. Solar irradiance, Mean Radiant Temperature (MRT), and PET maps are then created using meteorological inputs retrieved from the NASA Power API. The generated maps are then fed into an OSM-based routing engine to identify shorter, cooler paths. This open-source tool can provide researchers, urban planners, and public health practitioners with relevant information to evaluate heat-mitigation strategies and design more comfortable, resilient outdoor spaces.