arXiv:2604. 22433v2 Announce Type: replace Abstract: Heat exposure connects the built environment and public health, directly shaping the livability and sustainability of urban areas.
arXiv:2608.23857v1 Announce Type: new Abstract: Urban heat islands (UHIs) are intensifying under climate change, exacerbating thermal exposure risks. Their two primary observations, land surface temp...
arXiv:2606. 11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify because multi-sensor observations are rarely available in consistent, analysis-ready form at the necessary spatiotemporal scales.
arXiv:2609.40140v2 Announce Type: cross Abstract: Extreme heat is where urban adaptation needs kilometer-scale data the most, but the simulations training a downscaler can cost more than they save, a...
AlphaEarth, a satellite foundation model, maps Earth’s surface into numerical embeddings that allow comparison across places and time. An audit of its representations for 1,000 urban areas in 162 countries shows that cities occupy a distinct but overlapping region on the hypersphere, with continent, climate, and degrees of urbanisation explaining a portion of the variation. The study finds that cities in developing countries exhibit less contrast in vegetation and texture, and that annual changes in a city’s representation are largely driven by model updates rather than pixel changes.
arXiv:2509. 04991v2 Announce Type: replace-cross Abstract: Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes.
arXiv:2606. 15890v1 Announce Type: new Abstract: Understanding urban wellbeing from multimodal data requires integrating heterogeneous spatial and temporal signals, posing significant challenges for current multimodal large language models (MLLMs).
arXiv:2606. 20034v1 Announce Type: new Abstract: Understanding urban spatial morphology is critical for climate modeling, risk assessment, and sustainable urban design, and Local Climate Zone (LCZ) mapping provides the basic framework for this.
arXiv:2609.23508v1 Announce Type: cross Abstract: As part of HVAC systems, residential heating provides foundational infrastructure for human habitation in cold weather. However, research on how resi...
arXiv:2608.13856v2 Announce Type: replace-cross Abstract: Timely urban-canopy information is essential for linking remote sensing with heat, mobility, and neighborhood planning. We developed an optic...
arXiv:2505. 02979v4 Announce Type: replace-cross Abstract: We propose a novel inverse-modelling approach that estimates the parameters of a simple land-surface model (LSM) by assimilating data into a differentiable, physics-based forward model formulated using convolutional operations.
arXiv:2609.28154v1 Announce Type: new Abstract: Global building and settlement datasets increasingly support population mapping, exposure assessment, urban monitoring, and other analyses of the built...
BEACON is a tri‑modal contrastive learning framework that enriches AlphaEarth embeddings by aligning physical representations from Earth‑observation imagery with semantic POI text and human behavioral POI visitation data, while keeping the deployed model image‑only. In a Houston case study, BEACON outperformed six baselines on nine downstream tasks, achieving up to 43% higher R² for obesity prevalence, 34% for poor mental health, and 22% for median household income under a linear probe.