Mapping and estimating the total living biomass and carbon in low‐biomass woodlands using landsat 8 CDR data
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Date
2016-06-24
Journal Title
Journal ISSN
Volume Title
Publisher
CrossMark
Abstract
Background: A functional forest carbon measuring, reporting and verification (MRV) system to support climate
change mitigation policies, such as REDD+, requires estimates of forest biomass carbon, as an input to estimate emis-
sions. A combination of field inventory and remote sensing is expected to provide those data. By linking Landsat 8
and forest inventory data, we (1) developed linear mixed effects models for total living biomass (TLB) estimation as a
function of spectral variables, (2) developed a 30 m resolution map of the total living carbon (TLC), and (3) estimated
the total TLB stock of the study area. Inventory data consisted of tree measurements from 500 plots in 63 clusters in
a 15,700 km 2 study area, in miombo woodlands of Tanzania. The Landsat 8 data comprised two climate data record
images covering the inventory area.
Results: We found a linear relationship between TLB and Landsat 8 derived spectral variables, and there was no clear
evidence of spectral data saturation at higher biomass values. The root-mean-square error of the values predicted
by the linear model linking the TLB and the normalized difference vegetation index (NDVI) is equal to 44 t/ha (49 %
of the mean value). The estimated TLB for the study area was 140 Mt, with a mean TLB density of 81 t/ha, and a 95 %
confidence interval of 74–88 t/ha. We mapped the distribution of TLC of the study area using the TLB model, where
TLC was estimated at 47 % of TLB.
Conclusion: The low biomass in the miombo woodlands, and the absence of a spectral data saturation problem sug-
gested that Landsat 8 derived NDVI is suitable auxiliary information for carbon monitoring in the context of REDD+,
for low-biomass, open-canopy woodlands.
Description
Keywords
Biomass, Carbon, Modeling, Miombo woodlands, REDD+, NDVI