Building a Global Local Climate Zone (LCZ) Database for Urban Climate Studies
Lu Liang, Professor
Landscape Architecture and Environmental Planning
Applications for Spring 2025 are closed for this project.
Understanding urban climate dynamics, such as the Urban Heat Island (UHI) effect, requires comprehensive datasets on urban morphology and land cover. Local Climate Zones (LCZs) provide a standardized framework for classifying urban and rural areas based on their physical and surface properties. A global LCZ database is essential for analyzing urban climates, supporting sustainable urban planning, and developing climate adaptation strategies.
This research project focuses on expanding and refining a global LCZ database using advanced remote sensing techniques and Google Earth Engine (GEE). The project aims to integrate satellite-derived data, urban morphology metrics, and machine learning approaches to improve the resolution and accuracy of LCZ mapping. The resulting database will serve as a cornerstone for global urban climate studies and decision-making.
Role: • Utilize Google Earth Engine (GEE) to process and analyze satellite imagery for LCZ classification.
• Develop and implement scripts in Python or JavaScript for data processing, feature extraction, and model training.
• Assist in compiling and validating datasets from various global sources, ensuring data quality and consistency.
• Collaborate on the development of LCZ classification workflows, including the integration of remote sensing and geospatial data.
Qualifications: • Excellent problem-solving skills and attention to detail and accuracy (required).
• Proficiency in remote sensing techniques and familiarity with satellite imagery analysis (required).
• Experience with Google Earth Engine (GEE) for geospatial data processing (required).
• Strong coding skills in Python and/or JavaScript, with a focus on geospatial analysis (required).
• Strong interest in urban studies, environmental science, or related fields (preferred).
• Ability to work independently and as part of a team (required).
Day-to-day supervisor for this project: Yuye Zhou (PhD student)
Hours: 6-8 hrs
Engineering, Design & Technologies Environmental Issues