Remote sensing

Remote Sensing for Environmentally Responsive Urban Design explores how emerging sensing technologies can transform the way environmental performance is quantified, validated, and monitored across buildings and districts. Building on our recent review of tools, methods, and knowledge gaps in remote sensing for the built environment, this research examines the potential of multispectral, thermal, LiDAR, UAV-based, and satellite-based data to capture key indicators such as surface temperature, shading behaviour, material degradation, vegetation dynamics, and microclimatic patterns. Developed in close collaboration with Prof. Fadi Kizel and the Multidimensional Analysis in Remote Sensing (MARS) Laboratory at the Technion, this work establishes a foundation for integrating remote sensing into performance-driven urban analytics. Looking ahead, we aim to develop workflows that use thermal imaging, drone-based sensing, and satellite time-series to monitor building envelopes, detect heat losses, evaluate tree-driven cooling, and validate simulation-based environmental assessments. By connecting remote sensing data with computational design and microclimate modelling, this research opens new possibilities for evidence-based, adaptive, and environmentally responsive urban design at scale.