Table 1 The main driving sources in three flux datasets estimating forest-related greenhouse gas fluxes for Brazil

Version/update

V1.1

NC4

9.0

time period

2001 to 2020 (whole period average)

Annually for 1990 to 2016

Manually adjusted in this study to:

2001 to 2020

1990 to 2020 (annual)

IPCC method

Gain–loss

Gain–loss*

Stock-difference*

Gain–loss*

Stock-difference*

Activity data

 Satellite used

– Landsat

– Landsat &Resourcesat-1

– Landsat

 Main driving dataset

– Hansen et al. 1979 [31]

– RADAMBRASIL, PROBIO

– MapBiomas

Spatial resolution of land use dataset

~ 30 m

~ 30 m

~ 30 m

Emission/removal factors

Emissions: wall-to-wall aboveground biomass and soil carbon supplemented by wall-to-wall driver of loss map. Removals: various sources for different forest types

Country-specific (~ IPCC Tier 2/3 methodology) data based on field measurements and; LiDAR and peer-reviewed literature

Follows NGHGI

Forest types considered

– Primary Forest

– Non-primary forest (old secondary forest)

– Young secondary forest

– Plantations (Forest plantations and tree crops)

– (Mangroves—excluded in this analysis)

– (Non-managed forests)

– Managed forest (including old growth forests under protection, conservation and indigenous lands)

– Secondary forest

– Plantations (forest plantations only)

– Protected forests**

– Secondary forest

– Plantation (Forest plantations only)

Forest transitions considered (land use and land use change)

– Forest remaining forest land

– Deforestation

– (Degradation)—considered retrospectively and non-spatially (Pearson et al. 2017) [72]

– Afforestation and reforestation

-Forest remaining forest land

– Deforestation

– Selective logging (Amazonia only)

– Afforestation and reforestation

– Forest remaining forest land

– Deforestation

– Degradation by fire

– Afforestation and reforestation