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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/37064
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Title: | Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests |
Authors: | Guerra-Hernández, Juan Narine, Lana Pascual, Adrian Gonzalez-Ferreiro, Eduardo Botequim, Brigite Malambo, Lonesome Neuenschwander, Amy Popescu, Sorin Godinho, Sérgio |
Issue Date: | 22-Sep-2022 |
Publisher: | Taylor & Francis |
Abstract: | The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides an extraordinary opportunity to
support global large-scale forest carbon mapping, but further research is needed in order to obtain
wall-to-wall forest aboveground biomass (AGB) maps with this technology. The effects of vegeta
tion structure on the performance of canopy height and AGB modeling using ICESat-2 photon-
counting light detection and ranging (LiDAR) data in Mediterranean forest areas have not been
previously studied in the literature. In this study, we combined recent ICESat-2 vegetation (ATL08)
data, Airborne Laser Scanning (ALS)- and field-based estimates, and a multi-sensor earth observa
tion composite for extrapolation of AGB estimates and AGB mapping. A diverse gradient of forest
Mediterranean ecosystems, distributed over 19,744.15 km2 of forest area in the region of
Extremadura (Spain), with different species and structural complexity forming 5 different forest
types (3 Quercus spp. dominated and 2 Pinus spp. dominated forests), was used to (i) evaluate the
precision of ICESat-2 canopy height estimations, (ii) develop ICESat-2-based AGB models, and (iii)
generate a spatially continuous prediction of AGB by using data from the satellite missions
Sentinel-1 (S1), Sentinel-2 (S2), Phased Array L-band Synthetic Aperture Radar (ALOS2/PALSAR2),
and Shuttle Radar Topography Mission (SRTM). First, ALS- and ICESat-2-derived metrics that best
described canopy height (p98 and rh98, respectively) were compared at the ATL08 segment level.
Second, ALS-based AGB values were derived at the ATL08 segment scale. Third, ALS-based AGB
estimates at the ICESat-2 segment level were used as dependent variables to fit ICESat-2-based
AGB models. Fourth, a multi-sensor approach was then implemented to predict ICESat-2-derived
AGB, by means of a Random Forest (RF) modeling technique, with predictors retrieved from S1, S2,
ALOS2/PALSAR2, and SRTM. Finally, RF was used to generate wall-to-wall AGB maps that were
compared with field-, ALS- and ICESat-2-based observations. The agreement between the ALS- and
ICESat-2-derived metrics related to the canopy height distribution was higher for Pinus spp. forest
than for the Quercus spp-dominated forests. The ICESat-2-based AGB models yielded model
efficiency (Mef) values between 0.56 and 0.80, with a RMSE ranging from 7.76 to 17.71 Mg ha−1
and rRMSE from 19.04 to 55.21%. The multi-sensor RF models provided the following results when
compared with the ICESat-2- and ALS-based AGB observations: R2 values of 0.63 and 0.64, and
RMSE values of 11.10 Mg ha−1(rRMSE = 28.15%) and 12.28 Mg ha−1 (rRMSE = 31.45%), respectively,
and an approximately unbiased result (0.03 Mg ha−1 and 0.09 Mg ha−1). When applied to the field-
based validation data set (4th Spanish National Forest Inventory (SNFI-4) plots = 508), the RF-
derived AGB model showed a relatively lower predictive capacity (R2 = 0.45), a higher RMSE value
(25.88 Mg ha−1) and slightly biased results (−1.47 Mg ha−1), especially for larger field-derived AGB
intervals. The results of this study serve to provide an initial quantitative assessment of the ICESat-2
ATL08 data for large-scale AGB estimation. The findings suggest that a multi-sensor approach may
be feasible for extrapolating ICESat-2-derived AGB estimates over areas where field or ALS
reference data are not available. |
URI: | http://hdl.handle.net/10174/37064 |
Type: | article |
Appears in Collections: | FIS - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
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