A Global Dataset of Location Data Integrity-Assessed Reforestation Efforts

Area of Science:

• Environmental Science
• Remote Sensing
• Climate Change Mitigation

Background:

• Afforestation and reforestation are key strategies for climate change mitigation via carbon sequestration.
• Current verification methods often rely on self-reported data, raising concerns about reliability and integrity in voluntary carbon markets.
• Increasing scrutiny necessitates robust validation of carbon offset projects.

Purpose of the Study:

• To present a comprehensive global dataset of afforestation and reforestation efforts.
• To introduce a standardized metric, the Location Data Integrity Score (LDIS), for assessing the quality of georeferenced planting site data.
• To enhance accountability and data integrity within the voluntary carbon market.

Main Methods:

• Compiled a dataset of 1,289,068 planting sites from 45,628 projects over 33 years.
• Integrated primary (meta-)information with time-series satellite imagery and secondary data.
• Developed and applied the Location Data Integrity Score (LDIS) to assess georeferenced location data quality.

Main Results:

• Approximately 79% of monitored georeferenced planting sites failed at least one LDIS indicator.
• 15% of monitored projects lacked machine-readable georeferenced data.
• The dataset provides millions of linked Sentinel-2 satellite images, valuable for computer vision tasks.

Conclusions:

• Significant data integrity issues exist in afforestation and reforestation projects, challenging reliable carbon sequestration assessment.
• The developed dataset and LDIS are crucial for improving transparency and accountability in carbon markets.
• The dataset serves as valuable training data for remote sensing and computer vision applications in environmental monitoring.