General

Long-term (1990–2019) monitoring of forest cover changes in the humid tropics

Background

Tropical moist forests are essential for biodiversity, climate regulation, and global carbon storage, yet they face increasing pressure from deforestation and degradation. Accurate, long-term monitoring of forest dynamics is necessary to support climate policies, including REDD+ and Nationally Determined Contributions (NDCs). Previous studies have provided partial insights, but a comprehensive spatial and temporal characterization of forest degradation and recovery remains limited. Advances in satellite imagery and cloud computing now enable consistent monitoring at pantropical scales.

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National forest monitoring system assessment tool – Quick guidance

Background

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User-Driven Land Cover Change Prediction Map Tool for Land Conservation Planning

Background

Effective conservation planning requires forward-looking tools that anticipate land cover change, rather than relying solely on historical analysis. Rapid urbanization and land-use change threaten ecosystems and biodiversity, particularly in regions experiencing development pressure. Traditional models often lack accessibility for nontechnical users, limiting their application in real-world decision-making. Integrating machine learning with user-friendly platforms can enhance stakeholder engagement and improve conservation outcomes.

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Integrating satellite-based forest disturbance alerts improves detection timeliness and confidence

Background

Satellite-based forest monitoring systems are essential for detecting deforestation and supporting climate change mitigation efforts. Multiple alert systems exist, including Global Land Analysis and Discovery (GLAD)-Landsat, GLAD-Sentinel-2, and RADD, each with distinct capabilities and limitations related to sensor type and environmental conditions. Optical systems struggle under cloud cover, while radar systems may miss certain disturbance signals. This creates uncertainty for users and highlights the need for integrated monitoring approaches.

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Near real-time monitoring of tropical forest disturbance by fusion of Landsat, Sentinel-2, and Sentinel-1 data

Background

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Afforestation and Reforestation Have Varying Biodiversity Impacts Across and Within Biomes

Background

Afforestation and reforestation (AR) are widely promoted as nature-based solutions (NbS) for carbon dioxide removal and climate mitigation. Global initiatives aim to expand forest cover significantly to meet climate targets. However, AR can produce unintended biodiversity impacts, particularly when implemented in ecosystems such as grasslands or savannas, where native species are not adapted to forest conditions. The ecological outcomes of AR vary across biomes and species, highlighting the need for spatially explicit, biodiversity-sensitive planning frameworks.

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Tropical dry forest land use/land cover change detection using semi-supervised deep learning algorithms and remote sensing

Background

Open access copy available

Remote sensing of drylands: An overview

Background

Open access copy available

A systematic review on remote sensing of dryland ecological integrity: Improvement in the spatiotemporal monitoring of vegetation is required

Background

Open access copy available

Life cycle impacts of forest management and wood utilization on carbon mitigation: knowns and unknowns

Background

Forests currently remove 2-3 GtC yr⁻¹ from the atmosphere, while global wood harvest exceeds 3-4 billion m³ yr⁻¹, creating complex interactions between forest carbon stocks, harvested wood products, and the substitution of wood for more emission-intensive materials. Lifecycle assessment (LCA) is widely used to evaluate these interactions, but differing system boundaries, baselines, and treatment of carbon pools can lead to very different conclusions about mitigation benefits. Clarifying where evidence is robust and where major uncertainties remain is essential for designing coherent forest-climate policy.

Open access copy available
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