Revealing the proximate drivers behind global tree cover loss using multisourced remote sensing products during 2000–2020

Revealing the proximate drivers behind global tree cover loss using multisourced remote sensing products during 2000–2020

Description:

Understanding the proximate drivers of tree cover loss is crucial for guiding forest management policies, while significant challenges remain in accurately and comprehensively identifying these drivers on a global scale. Here, we developed a decision tree framework using multisourced remote sensing products, including land-cover, human footprint, fire, forest management practices, and standardized-precipitation evapotranspiration index, to attribute the global tree cover loss to five human drivers and three natural drivers.

Essential Information

1)       Filename: StartYear_EndYear_Latitude[num]Longitude[num]

2)       Data type: uint8

3)       Spatial Resolution: 30 m

4)       Temporal Resolution: 2000–2005, 2005–2010, 2010–2015, and 2015–2020.

5)       Coordinate System: GCS_WGS_1984

6)       Value: The values 1-8 correspond to Impervious Surface Expansion, Agricultural Encroachment, Forestry Activity, Human-Induced Fire, Other Human drivers, Wildfire, Persistent Drought, and Other Natural drivers, respectively.