Scope and topics
This session will explore how Earth Observation, ecological measurements, and modeling
can support the planning, monitoring, and assessment of climate-smart ecosystem restoration
across terrestrial and aquatic ecosystems for nature positive futures.
The focus will be on understanding how restoration contributes to biodiversity recovery,
ecosystem functioning, local climate regulation, and resilience to environmental change.
Applications may include forests, wetlands, grasslands, peatlands, agricultural landscapes,
marine ecosystems, freshwater and subterranean ecosystems and other degraded or
recovering environments.
We welcome methodological advances and case studies combining satellite, airborne, or
UAV observations with field measurements, ecological data, and AI/machine learning.
Particular emphasis will be placed on approaches that move beyond mapping land cover
changes to assessing ecosystem condition, recovery trajectories, biodiversity outcomes, and
ecosystem services.
We encourage contributions that investigate where, when, and under what conditions
restoration supports ecological recovery, climate adaptation, and ecosystem resilience,
including comparisons of restoration approaches, their effectiveness, uncertainties, and
potential trade-offs.
List of topics:
- Monitoring ecosystem restoration and recovery: Mapping ecosystem condition,
structural change, and recovery trajectories using optical, radar, LiDAR,
hyperspectral, and satellite time-series observations. - Microclimate and climate-regulation services: Assessing land surface temperature,
evapotranspiration, moisture conditions, albedo, and related indicators, including links
with field-based microclimate measurements. - Biodiversity and ecosystem functioning: Combining remotely sensed indicators of
habitat quality, vegetation structure, and environmental heterogeneity with ecological
observations. - Ecosystem resilience, disturbance, and restoration risks: Investigating drought, heat
stress, fire, flooding, degradation, and other pressures, alongside indicators of
ecosystem vulnerability and recovery. - AI/ML and data integration: Integrating multi-source Earth Observation, ecological,
and environmental datasets to identify restoration priorities, compare scenarios, and
quantify uncertainty.
Organizers
Sara Alibakhshi, Chair of Data Science in Earth Observation, Technical University of Munich, Germany
sara.alibakhshi@gmail.com
Felicia O. Akinyemi, Geomatics, Department of Environmental and Life Sciences, Karlstad University, Sweden
felicia.akinyemi@kau.se;
Jan Haas, Geomatics, Department of Environmental and Life Sciences, Karlstad University, Sweden
jan.haas@kau.se
Chima Iheaturu, Land Systems and Sustainable Land Management Unit, Institute of Geography, University
of Bern, Switzerland chima.iheaturu@unibe.ch
Paulo J. Murillo-Sandoval, Departamento de Infraestructura y Geomática, Facultad de Ciencias del Hábitat, Diseño e
Infraestructura, Universidad del Tolima, Colombia, pjmurillos@ut.edu.co