Conference Agenda

Megacities—defined as Functional Urban Areas (FUAs) of more than 10 million inhabitants—are global hotspots of population growth, economic activity, and environmental pressure. Their development trajectories shape regional and global emission patterns, yet a comprehensive understanding of how urban expansion, air pollution, and economic development interact over time has remained limited. While prior research has examined either urban growth or atmospheric pollution trends, an integrated analysis linking both dimensions within a socio-economic framework is still lacking. This study addresses this gap by leveraging long-term Earth Observation (EO) datasets to systematically analyze settlement growth and tropospheric nitrogen dioxide (NO₂) pollution across 38 megacities between 1996 and 2015. Using the World Bank income classification, we evaluate whether observed environmental and urbanization patterns align with the Environmental Kuznets Curve (EKC)—a hypothesis that posits a non-linear (inverted U-shaped) relationship between environmental degradation and economic development.

Urban green space accessibility represents a critical dimension of sustainable planning and public health outcomes. This research quantifies compliance with the "3-30-300" framework - requiring residents to view three trees from home, neighborhoods to maintain 30% canopy coverage, and proximity to public green space within 300 meters across Montreal Island and Quebec City. While this policy has gained substantial theoretical traction, empirical implementation assessment in Canadian urban contexts remains limited. Employing high-resolution remote sensing imagery, deep learning-based land cover classification, and LiDAR-derived canopy data, we conducted comprehensive spatial analysis of both municipalities. Road network data from OpenStreetMap enabled walkability assessment. Integrated compliance metrics (I330300) revealed stark disparities: Montreal achieved 20.93% compliance, while Quebec City registered merely 2.69%. These findings underscore substantial green space accessibility deficits across both municipalities, with particular concentration in peripheral neighborhoods. Spatial statistical analysis identified pronounced clustering of non-compliance zones, demonstrating heterogeneous distribution of environmental amenities. Population demographic analysis revealed significant correlations between socioeconomic indicators and green space availability, suggesting environmental inequity patterns. Such disparities raise critical equity concerns regarding differential access to environmental services and associated health benefits. These results directly advance United Nations Sustainable Development Goal 11 objectives for establishing inclusive, sustainable cities. The quantitative assessment methodology demonstrates the efficacy of integrating remote sensing, machine learning, and spatial analysis for evidence-based urban environmental policy evaluation. Findings provide empirical foundations for targeted interventions addressing green space deficits in underserved urban communities, enabling data-driven municipal planning strategies that prioritize equitable environmental resource distribution and enhanced public health outcomes.

This presentation examines heat stress and mitigation capacity around transit stops during an extreme heat wave in Vancouver, Canada. Using hyperlocal microclimate modelling and high-resolution urban geometry data, we estimate “feels-like” Mean Radiant Temperature and shade availability to develop two new indicators: the Transit Stop Heat Stress Index and the Transit Stop Mitigation Capacity Index. Results reveal strong spatial and socio-economic disparities, with higher heat exposure and fewer mitigation features in lower-income neighbourhoods. The study demonstrates how microclimate data can guide climate-responsive, equitable transit planning under intensifying heat conditions.

Landfills are among the largest anthropogenic sources of methane, yet accurately detecting and quantifying their emissions remains challenging due to diffuse release patterns, complex terrain, and weather-driven variability. This presentation introduces a drone-based monitoring approach that uses a path-integrated Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor to detect and quantify methane emissions at a municipal landfill in London, Canada. Methane measurements collected throughout the year, together with on-site meteorological observations, were integrated into an inverse atmospheric plume-dispersion model to estimate emission rates. This contribution demonstrates the potential of drone-based TDLAS measurements to provide practical, high-resolution landfill methane monitoring and to reduce uncertainties in greenhouse gas reporting and mitigation efforts.

Climate change and urbanization transform life globally, with direct impacts on each other, yet they are rarely studied together across disciplines. The Synergy Grant urbisphere (https://urbisphere.eu), funded by the European Research Council (ERC), aims to forecast feedbacks between climate and cities. With new synergies between four disciplines (spatial planning, remote sensing, modelling and ground-based observations), urbisphere incorporates city dynamics and human behaviour into climate forecasts/projections, focusing on within-city dynamics of peoples’ activities and how these can be up-scaled to cities globally. urbisphere is studying inter/intra-city form and function (demographics, mobility, climate adaptation and vulnerability planning typologies), exploring human/socio-economic vulnerability, exposure, risk perception, coping/adaptive measures to climatic stressors and settlement/building typologies.

urbisphere is developing new ways to represent city dynamics for weather/climate models. These models are informed by the urbisphere developed Earth Observation system, using space-borne/airborne and ground based sensors with near real-time data transmission, processing and visualization of data from 500+ sensors, including a network of ceilometers, scintillometers, Doppler wind lidars, flux towers combined with street-level and indoor sensors. Combined these measure the 3-dimensional state of the atmosphere and the surface. These observations are providing both new understanding of urban surface-atmosphere processes and datasets for model evaluation at unprecedented detail.