Global forest management data for 2015 at a 100 m resolution

Area of Science:

• Forestry Science
• Remote Sensing
• Geographic Information Systems (GIS)

Background:

• Global forest management data is essential for conservation and sustainable practices.
• Existing data lacks global consistency and high spatial detail.
• Understanding forest status is critical for ecosystem services and biodiversity.

Purpose of the Study:

• To create the first globally consistent, high-resolution forest management map.
• To provide reference data for various forest management classes.
• To support sustainable forest management, restoration, and conservation initiatives.

Main Methods:

• Developed a reference dataset of 226,000 locations via expert and crowdsourcing (Geo-Wiki).
• Combined reference data with PROBA-V satellite imagery time series.
• Generated a global 100m resolution map for the year 2015.

Main Results:

• Achieved accuracies ranging from 58% to 80% for different forest management classes.
• Mapped prevalent classes: intact, managed, planted, plantation forests, oil palm, and agroforestry.
• The map provides spatially explicit forest management information at 100m resolution.

Conclusions:

• The reference dataset and map offer critical insights into global forest ecosystem status.
• This resource can inform investigations into the value of forests for species and ecosystem services.
• Enables improved planning for sustainable forest management and conservation globally.