Overview

I​n the context of global environmental changes, the effects of climate change already trigger sudden events that pose critical challenges to urban environments. Urban heat islands and air quality have become significant concerns, severely impacting human and animal health, vegetation resilience, and biodiversity, often with hazardous consequences.

It is now well understood that vegetation, particularly trees, can provide effective solutions to mitigate these impacts: they can cool cities, improve air quality, and enhance biodiversity. However, urban-related stresses trigger physiological responses in trees to regulate water, carbon, and nitrogen levels, aiming to prevent or limit tissue and organ damage. These responses result in changes to evapotranspiration and photosynthesis processes, as well as metabolic shifts. Such modifications impair trees' ability to fulfill their regulatory role. 

During the summers of 2022 and 2023 submitted to prolonged drought and extreme temperatures, we observed that some trees died while others survived, despite seemingly unfavorable environmental conditions. This underscores the urgent need to deepen our understanding of how trees respond to climate change to better support city planners.

To date, few studies have comprehensively addressed tree stress, despite the fact that a combination of factors—including hydric stress, thermal stress, and pollution—is responsible for sudden dieback. 

MONI-TREE project aims to address this gap by combining advanced observation systems (multivariate remote sensing), experiments, simulations, field data, and machine learning to:

1) Identify early warning signs of tree dieback through short- and long-term multi-year monitoring and anomaly detection;

2) Generate city-scale maps of tree comfort indices to provide alerts and support decision-making for urban managers;

3) Determine urban patterns that are favorable or unfavorable to tree well-being and compare them with Local Climate Zones, which are established urban patterns linked to local climate conditions.