NERC Data Catalogue Service
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.
Default
Identification info
- Metadata Language
- English (en)
- Dataset Reference Date ()
- 2017-06-07T11:12:52
- Dataset Reference Date ()
- 2017-06-07T11:12:52
- Identifier
- Centre for Environmental Data Analysis (CEDA) / e5fb0e74b8104302a43e8a24dc45e038
Centre for Environmental Data Analysis (CEDA)
-
custodian
Rutherford Appleton Laboratory
,
Harwell
,
Oxon
,
OX11 0QX
,
United Kingdom
01235446432
Centre for Environmental Data Analysis (CEDA)
-
distributor
Rutherford Appleton Laboratory
,
Harwell
,
Oxon
,
OX11 0QX
,
United Kingdom
01235446432
Centre for Environmental Data Analysis (CEDA)
-
point_of_contact
Rutherford Appleton Laboratory
,
Harwell
,
Oxon
,
OX11 0QX
,
United Kingdom
01235446432
Centre for Environmental Data Analysis (CEDA)
-
publisher
Rutherford Appleton Laboratory
,
Harwell
,
Oxon
,
OX11 0QX
,
United Kingdom
01235446432
- Maintenance and update frequency
- notPlanned
- Update scope
- dataset
- Keywords
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- Forest biomass
- Uncertainty
- Forest probability
- MODIS
- ALOS PALSAR
- SRTM
- Carbon
- MaxEnt
- REDD +
- GEMET - INSPIRE themes, version 1.0 ()
-
- orthoimagery
- Limitations on Public Access
- otherRestrictions
- Other constraints
- Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
- Use constraints
- otherRestrictions
- Spatial representation type
- grid
- Topic category
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- Imagery base maps earth cover
N
S
E
W
))
- Begin date
- 2004-01-01T00:00:00
- End date
- 2012-12-31T23:59:59
- Code
- WGS 84
Distribution Information
- Data format
-
-
GeoTiff, 16 Bit
()
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GeoTiff, 16 Bit
()
- Resource Locator
-
CEDA Data Catalogue Page
Detail and access information for the resource
- Resource Locator
-
DOWNLOAD
Download Data
- Resource Locator
-
CEDA Data Catalogue Page
Detail and access information for the resource
- Resource Locator
-
DOWNLOAD
Download Data
- Quality Scope
- dataset
Report
- Dataset Reference Date ()
- 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.
Metadata
- File identifier
- e5fb0e74b8104302a43e8a24dc45e038 XML
- Metadata Language
- English (en)
- Character set
- 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646
- Parent identifier
- National Centre for Earth Observation (NCEO) Core datasets 82b29f96b8c94db28ecc51a479f8c9c6
- Resource type
- dataset
- Metadata Date
- 2023-03-24T00:23:39
- Metadata standard name
- UK GEMINI
- Metadata standard version
- 2.3
Centre for Environmental Data Analysis (CEDA)
Rutherford Appleton Laboratory
,
Harwell
,
Oxon
,
OX11 0QX
,
United Kingdom
01235446432
