Integration of geospatial data-driven approaches enhances our ability to capture urban ecosystem changes at variable spatial and temporal scales. Despite many recent advances, there is a growing need for interdisciplinary frameworks that integrate geospatial data science approaches for better understanding of rapidly developing urban ecosystem dynamics and associated challenges. In this session, we aim to highlight emerging geospatial and data science approaches that integrate remote sensing, spatial analysis, machine learning, and computational modelling to investigate urban ecosystem changes and their impacts.

Topics of interest include:

- Urban heat island effects and dynamics

- Urban land-use/ land-cover changes

- Urban-climate interactions, their mechanisms and dynamics

- Urban climate modelling and simulations

We aim to bring together researchers from diverse disciplines to share innovative methodologies, highlight emerging research trends, and foster collaboration toward developing sustainable, data-driven solutions for urban ecosystems.

• A - Atmospheric Sciences
• B - Biogeosciences
• EP - Earth and Planetary Surface Processes