Articles | Volume 19, issue 5
Biogeosciences, 19, 1377–1394, 2022
https://doi.org/10.5194/bg-19-1377-2022
Biogeosciences, 19, 1377–1394, 2022
https://doi.org/10.5194/bg-19-1377-2022

Research article 07 Mar 2022

Research article | 07 Mar 2022

MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas

Rahayu Adzhar et al.

Data sets

On the delineation of tropical vegetation types with an emphasis on forest/savanna transitions (https://www.forestplots.net) M. Torello-Raventos, T. Feldpausch, E. Veenendaal, F. Schrodt, G. Saiz, T. Domingues, G. Djagbletey, A. Ford, J. Kemp, B. Marimon, B. H. Marimon-Junior, E. Lenza, J. A. Ratter, L. Maracahipes, D. Sasaki, B. Sonké, L. Zapfack, H. Taedoumg, V. Daniel, and J. Lloyd https://doi.org/10.1080/17550874.2012.762812

raster: Geographic Data Analysis and Modeling R. J. Hijmans http://CRAN.R-project.org/package=raster

MOD44B MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 250m SIN Grid V006 M. C. DiMiceli https://doi.org/10.5067/MODIS/MOD44B.006

Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error (https://e4ftl01.cr.30 usgs.gov/MEASURES/GFCC30TC.003/) J. O. Sexton, X.-P. Song, M. Feng, P. Noojipady, A. Anand, C. Huang, D.-H. Kim, K. M. Collins, ,S. Channan, C. DiMiceli, and J. R. Townshend https://doi.org/10.1080/17538947.2013.786146

Model code and software

VCF_vs_sites R. Adzhar, D. I. Kelley, N. Dong, C. George, M. Torello Raventos, E. Veenendaal, T. R. Feldpausch, O. L. Philips, S. L. Lewis, B. Sonké, H. Taedoumg, B. Schwantes Marimon, T. Domingues, L. Arroyo, G. Djagbletey, G. Saiz, and F. Gerard https://github.com/douglask3/VCF_vs_sites

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Short summary
The MODIS Vegetation Continuous Fields (VCF) product underestimates tree cover compared to field data and could be underestimating tree cover significantly across the tropics. VCF is used to represent land cover or validate model performance in many land surface and global vegetation models and to train finer-scaled Earth observation products. Because underestimation in VCF may render it unsuitable for training data and bias model predictions, it should be calibrated before use in the tropics.
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