Matthew Fagan, Department of Geography and Environmental systems
Do-Hyung Kim, United Nations Children’s Fund, New York, NY, USA
The proposed research has two main objectives: 1) to produce an updated map of tropical reforestation categories, following the methods laid out in Fagan et al. (2022; https://www.nature.com/articles/s41893-022-00904-w), and 2) to produce a global version of the reforestation category map that includes temperate regions. Specifically, the reforestation categories map will classify areas where tree cover has increased in height into three main land uses: tree plantations, natural regrowth, and nonforest (i.e., error). The map will reclassify the new 30 meter resolution GLAD lab Global Forest Canopy Height product (https://glad.umd.edu/dataset/GLCLUC2020), focusing on 2020 forest patches that have grown from 0 meters to at least 5 meters in height (2000-2020). This reclassification will be accomplished through machine learning analysis of satellite spectral and radar data collected over the tree height gain patches.