Digital twin forestry as an informatics framework integrating remote sensing ecosystem modelling and data assimilation

Forests are essential to the Earth system, regulating carbon, water, and biodiversity cycles while underpinning ecosystem resilience. Yet they face mounting pressures from climate and land-use change, requiring integrative informatics approaches that link high-resolution observations with advanced ecosystem models. This systematic review defines Digital Twin Forestry (DTF) as an emerging paradigm that continuously couples multisensor Earth Observation data with ecosystem models through data assimilation, enabling dynamic, uncertainty-aware forecasting and adaptive decision support. Following PRISMA 2020 guidelines, we synthesized 57 peer-reviewed studies published between 2016 and 2025 that combined EO datasets with ecosystem modeling and assimilation frameworks. Demonstrated advances include CubeSat constellations, spaceborne LiDAR, UAV hyperspectral systems, and hybrid machine-learning surrogates. Data assimilation methods such as Ensemble Kalman Filters and Particle Filters serve as computational bridges between multi-temporal observations and dynamic model states. Results reveal uneven biome representation, with tropical and boreal forests underrepresented compared to temperate zones, underscoring equity concerns in biodiversity-rich regions. While most forestry digital twins remain at prototype or early operational stages, continuous coupling of sensing platforms to models demonstrates the potential for near-real-time forecasting that extends beyond static inventories. Future priorities include physics-informed machine learning, FAIR-compliant cloud-native workflows, and expanded monitoring in underrepresented ecosystems. Embedding biodiversity and resilience monitoring into near-real-time, uncertainty-aware workflows will be critical, enabling DTF to evolve into operational systems that provide adaptive, policy-relevant decision support for climate-resilient forest management. This review offers an integrative roadmap for advancing DTF, contributing to global sustainability and supporting the United Nations Sustainable Development Goals, including Climate Action (SDG 13) and Life on Land (SDG 15).