ArticleScientific data2024
A global annual fractional tree cover dataset during 2000-2021 generated from realigned MODIS seasonal data.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Urban Habitat Mosaics Structure Gene Flow but Preserve Genetic Diversity in an Invasive Termite.Ecology and evolution · 2026Article
- Continuous frost causes a greater reduction in forest growth than isolated frost in the Northern Hemisphere.Nature communications · 2025Article
- A globally consistent negative effect of edge on aboveground forest biomass.Nature ecology & evolution · 2025Article
- Lightning Impacts on Global Forest and Carbon Dynamics: Current Understanding and Knowledge Gaps.Global change biology · 2025Article
- A global annual fractional tree cover dataset during 2000-2021 generated from realigned MODIS seasonal data.Scientific data · 2024Article
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Authors and funding
6 authors.
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Abstract
Fractional tree cover facilitates the depiction of forest density and its changes. However, it remains challenging to estimate tree cover from satellite data, leading to substantial uncertainties in forest cover changes analysis. This paper generated a global annual fractional tree cover dataset from 2000 to 2021 with 250 m resolution (GLOBMAP FTC). MODIS annual observations were realigned at the pixel level to a common phenology and used to extract twelve features that can differentiate between trees and herbaceous vegetation, which greatly reduced feature dimensionality. A massive training data, consisting of 465.88 million sample points from four high-resolution global forest cover products, was collected to train a feedforward neural network model to predict tree cover. Compared with the validation datasets derived from the USGS circa 2010 global land cover reference dataset, the R
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