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Library novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique

novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique

novel application of satellite radar data: measuring carbon sequestration and detecting degradation in a community forestry project in Mozambique

Resource information

Date of publication
December 2013
Resource Language
ISBN / Resource ID
AGRIS:US201500059598
Pages
159-170

Background: It is essential that systems for measuring changes in carbon stocks for Reducing Emissions from Deforestation and Forest Degradation (REDD) projects are accurate, reliable and low cost. Widely used systems involving classifying optical satellite data can underestimate degradation, and by classifying the landscape ignore the natural heterogeneity of biomass.Aims: To assess the ability of repeat L-band radar to detect areas of small increases or decreases in above-ground biomass (AGB) across a Miombo woodland landscape.Methods: ALOS PALSAR L-band cross-polarised (HV) radar data from 2007 and 2009 were used to create maps of AGB, calibrated using 58 field plots. The change in AGB was assessed for land parcels with known landcover histories: (i) 500 ha of new agroforestry; (ii) 9500 ha of protected (REDD) areas; and (iii) 23 ha of land where degradation occurred between 2007 and 2009.Results: Increases in AGB were detected in both the agroforestry and REDD areas (0.4 and 1.1 Mg C ha⁻¹ year⁻¹, respectively), while the degraded areas showed a decrease of 3 Mg C ha⁻¹ year⁻¹.Conclusions: PALSAR data can be used to detect losses and gains in AGB in woodland ecosystems. However, further work is needed to precisely quantify the uncertainties in the change estimates, and the extent of false-positive and false-negative change detections that would result from using such a system.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Mitchard, Edward T.A.
Meir, Patrick
Ryan, Casey M.
Woollen, Emily S.
Williams, Mathew
Goodman, Lucy E.
Mucavele, Joey A.
Watts, Paul
Woodhouse, Iain H.
Saatchi, Sassan S.

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Data Provider
Geographical focus