Modeling, Goalsetting, and Frameworks

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.

Open access copy available

Belize National Forest Monitoring System 2001-2020

Background

Belize’s diverse ecosystems, land tenure systems, and land-use dynamics require a robust and flexible National Forest Monitoring System (NFMS). Early efforts focused on establishing permanent forest inventory plots in the late 1990s to address data gaps in forest structure and carbon dynamics. Over time, Belize has expanded its forest monitoring framework to integrate both ground-based and remote sensing approaches, ensuring transparency, consistency, and national ownership of forest data systems.

Open access copy available

Framework for National Forest Monitoring System

Background

Open access copy available

National forest monitoring system assessment tool – Quick guidance

Background

Open access copy available

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.

Open access copy available

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.

Open access copy available

Mangroves protect coastal economic activity from hurricanes

Background

With more frequent and severe weather events anticipated due to climate change, coastal communities are interested in practical coastal defense interventions to protect their public and private assets and prevent disruptions to economic activity from tropical storms. Studies have documented mangrove forests’ ability to reduce wave action, wind velocity, and storm surge, making mangroves a cost-effective form of coastal protection. Yet, the relationship between how large a mangrove belt must be to provide significant protection and how mangroves mitigate tropical storm effects and economic damages is still unknown.

Open access copy available

Tipping Points of Amazonian Forests: Beyond Myths and Toward Solutions

Background

Open access copy available

Strong Climate Mitigation Potential of Rewetting Oil Palm Plantations on Tropical Peatlands

Background

Tropical peatlands store vast quantities of carbon and therefore play a crucial role in global climate regulation. In Indonesia, extensive areas of peatland have been drained and converted to oil palm plantations and other agricultural uses. Drainage exposes peat to oxygen, accelerating decomposition and releasing large amounts of carbon dioxide into the atmosphere. Since degraded peatlands are estimated to contribute significantly to global greenhouse gas emissions, restoration strategies such as peatland rewetting have gained increasing attention as potential natural climate solutions.

Open access copy available

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

Background

Open access copy available
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