AGB-MEX Forrest BIOMASS map for Mexico V1.0

Ground data from the National Forest and Soil Inventory of Mexico (INFyS) were used to calibrate a maximum entropy (MaxEnt) algorithm to generate forest biomass (AGB), its associated uncertainty, and forest probability maps. The input predictor layers for the MaxEnt algorithm were extracted from the moderate resolution imaging spectrometer (MODIS) vegetation index (VI) products, ALOS PALSAR L-band dual-polarization backscatter coefficient images, and the Shuttle Radar Topography Mission (SRTM) digital elevation model. A Jackknife analysis of the model accuracy indicated that the ALOS PALSAR layers have the highest relative contribution (50.9%) to the estimation of AGB, followed by MODIS-VI (32.9%) and SRTM (16.2%). The forest cover mask derived from the forest probability map showed higher accuracy (κ = 0.83) than alternative masks derived from ALOS PALSAR (κ = 0.72–0.78) or MODIS vegetation continuous fields (VCF) with a 10% tree cover threshold (κ = 0.66). The use of different forest cover masks yielded differences of about 30 million ha in forest cover extent and 0.45 Gt C in total carbon stocks. The AGB map showed a root mean square error (RMSE) of 17.3 t C ha− 1 and R2 = 0.31 when validated at the 250 m pixel scale with inventory plots. The error and accuracy at municipality and state levels were RMSE = ± 4.4 t C ha− 1, R2 = 0.75 and RMSE = ± 2.1 t C ha− 1, R2 = 0.94 respectively. We estimate the total carbon stored in the aboveground live biomass of forests of Mexico to be 1.69 Gt C ± 1% (mean carbon density of 21.8 t C ha− 1), which agrees with the total carbon estimated by FAO for the FRA 2010 (1.68 Gt C). The new map, derived directly from the biomass estimates of the national inventory, proved to have similar accuracy as existing forest biomass maps of Mexico, but is more representative of the shape of the probability distribution function of AGB in the national forest inventory data. Our results suggest that the use of a non-parametric maximum entropy model trained with forest inventory plots, even at the sub-pixel size, can provide accurate spatial maps for national or regional REDD + applications and MRV systems.

Date (Publication): 2017-06-07T11:12:52

Date (Creation): 2017-06-07T11:12:52

Citation identifier: https://catalogue.ceda.ac.uk/uuid/e5fb0e74b8104302a43e8a24dc45e038

Citation identifier: Centre for Environmental Data Analysis (CEDA) / e5fb0e74b8104302a43e8a24dc45e038

Point of contact

Organisation name	Individual name	Electronic mail address	Role
Unavailable	Rodriguez-Veiga, Pedro	Unavailable	Author
Unavailable	Balzter, Heiko	Unavailable	Author
Unavailable	Tansey, Kevin	Unavailable	Author
Centre for Environmental Data Analysis (CEDA)		support@ceda.ac.uk	Custodian
Centre for Environmental Data Analysis (CEDA)		support@ceda.ac.uk	Distributor
Natural Environment Research Council (NERC)		unknown	Principal investigator
Centre for Environmental Data Analysis (CEDA)		support@ceda.ac.uk	pointofContact
Unavailable	Rodriguez-Veiga, Pedro	Unavailable	pointofContact
Centre for Environmental Data Analysis (CEDA)		support@ceda.ac.uk	Publisher

Maintenance and update frequency: Not planned

Update scope: Dataset

Keywords

Forest biomass
Uncertainty
Forest probability
MODIS
ALOS PALSAR
SRTM
Carbon
MaxEnt
REDD +

GEMET - INSPIRE themes, version 1.0

orthoimagery

Access constraints: Other restrictions

Other constraints: Public data: access to these data is available to both registered and non-registered users.

Use constraints: Other restrictions

Other constraints: Under the following licence http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.

Spatial representation type: Grid

Language: English

Topic category

Imagery base maps earth cover

Begin date: 2004-01-01T00:00:00

End date: 2012-12-31T23:59:59

Unique resource identifier: WGS 84

Distribution format

Name	Version
GeoTiff, 16 Bit

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
Centre for Environmental Data Analysis (CEDA)		support@ceda.ac.uk	Distributor

OnLine resource

Protocol	Linkage	Name
	https://catalogue.ceda.ac.uk/uuid/e5fb0e74b8104302a43e8a24dc45e038	CEDA Data Catalogue Page

OnLine resource

Protocol	Linkage	Name
	http://data.ceda.ac.uk/neodc/nceo_biomass_maps/data/AGB-MEX/	DOWNLOAD

OnLine resource

Protocol	Linkage	Name
	http://dx.doi.org/10.1016/j.rse.2016.06.004	Magnitude, spatial distribution and uncertainty of forest biomass stocks in Mexico.data, algorithm, methods, uncertainty characterization and validation)

Hierarchy level: Dataset

Conformance result

Title: Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services

Date (Publication): 2010-12-08

Statement: Data provided by Pedro Rodriguez-Veiga of University of Leicester as part of NCEO Terrestrial Carbon and Vegetation workplan area . This work was supported by Copernicus Initial Operations - Network for Earth Observation Research Training (GIONET). GIONET was funded by the European Commission, Marie Curie Programme, Initial Training Networks, Grant Agreement number PITN-GA-2010-264509. Pedro Rodriguez-Veiga and Heiko Balzter were supported by the NERC National Centre for Earth Observation (NCEO). Heiko Balzter was also supported by the Royal Society Wolfson Research Merit Award, 2011/R3.