scispace - formally typeset
G

Guido R. van der Werf

Researcher at VU University Amsterdam

Publications -  96
Citations -  26036

Guido R. van der Werf is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Greenhouse gas & Climate change. The author has an hindex of 47, co-authored 84 publications receiving 18076 citations. Previous affiliations of Guido R. van der Werf include United States Department of Agriculture.

Papers
More filters
Journal ArticleDOI

Variability of fire carbon emissions in equatorial Asia and its nonlinear sensitivity to El Niño

TL;DR: In this article, the amount and variability of fire carbon emissions in equatorial Asia over the period 1997-2015 were estimated by combining satellite observations of active fire, burned area, and atmospheric concentrations of combustion tracers with a Bayesian inversion.
Journal ArticleDOI

Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations

TL;DR: In this article, the authors adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface-atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations.
Journal ArticleDOI

Precipitation-fire linkages in Indonesia (1997–2015)

TL;DR: In this paper, the authors investigated how various fire and precipitation datasets can be merged to better compare the fire dynamics in 1997 and 2015 as well as in intermediary years and found that the nonlinearity between rainfall and fire in Indonesia stems from longer periods without rain in extremely dry years.
Journal ArticleDOI

Optimal use of land surface temperature data to detect changes in tropical forest cover

TL;DR: In this paper, the authors examined different ways to use land surface temperature (LST) to detect changes in tropical forest cover and found that using data sampled during the end of the dry season (∼1-2 months after minimum monthly precipitation) had the greatest predictive skill.