### UAVs and Data Capabilities
Their imagery supports 3D point cloud creation, down to centimeter accuracy, once processed using computer vision techniques [50]. In addition to data collection, UAVs enable real-time monitoring and analysis in the urban environment. They can be equipped with sensors and instruments to measure climate-related information, such as temperature, humidity, air quality, and solar radiation, in real time [51; 52]. This real-time monitoring allows for immediate feedback and decision making, facilitating timely responses to climate-related events and informing urban planning and management strategies. The flexibility, automation, and miniaturization of UAV platforms enable nimble, customizable 3D data capture tailored to project sites. Multi-copter drones can hover and rotate over targets of interest, acquiring geometrically accurate imagery that is challenging to match via alternative approaches [46]. Meanwhile, achieving comparable perspectives and positional flexibility using manned aircrafts would have substantially higher costs and logistic complexities. UAVs' capacity for on-demand, close-range data acquisition makes them a uniquely valuable geomatics tool providing efficient, scalable, and high-quality 3D spatial data. Additionally, unlike satellite platforms that have fixed orbital periods, UAVs can be deployed on demand to collect targeted data in response to evolving needs. Their low-altitude flight allows for centimeter-scale image resolutions, capturing details, such as individual trees, buildings, and transportation infrastructures. Customizable sensor payloads can integrate high-precision RGB, multispectral, thermal, and LiDAR instruments to match the specific data requirements of each study. A study by [PERSON] et al. [53] highlighted that drones provided data of unprecedented spatial, spectral, and temporal resolutions, making them ideal for monitoring the environment. They bridge the gap between field observations and remote sensing by providing high-quality spatial-resolution details over large areas in a cost-effective way. Moreover, the researchers [54] developed a simulation platform called InDrone to model UAV flight behavior and human-drone interactions for indoor infrastructure inspections. By visualizing the spatiotemporal relationships between UAV dynamics, sensor coverage, environment reconstructions, and operator commands, InDrone enables the analysis and optimization of collision avoidance algorithms and pilot training protocols. Refining these capabilities can improve the UAV navigation stability and data collection accuracy when mapping indoor thermal and air-quality conditions that influence building energy usage. The study demonstrated how leveraging UAV flight simulations could further develop automated, human-assisted, and collaborative methodologies for UAVs to safely and precisely acquire climate-relevant data at new interior vantage points. This supports the emerging potential of UAVs for the fine-grained, versatile, and comprehensive monitoring of built infrastructure emissions and hazards linked to climate change resilience. These studies exemplify how UAVs can host customized payloads to acquire geospatial data at centimeter resolutions. Their ability to flexibly sample the built environment at low altitudes provides climate researchers with unprecedented details for energy use, emissions, and environmental hazards. This supports the development of spatially targeted, timely interventions to advance local climate resilience.