Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests
Creators: name: Guerra-Hernández, Juan
name: Narine, Lana L.
name: Pascual, Adrián
name: Gonzalez-Ferreiro, Eduardo
name: Botequim, Brigite
name: Malambo, Lonesome
name: Neuenschwander, Amy
name: Popescu, Sorin C.
name: Godinho, Sergio
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: Ecology
subject: FOS: Biological sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: Plant Biology

description: 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 vegetation 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 observation composite for extrapolation of AGB estimates and AGB mapping. A diverse gradient of forest Mediterranean ecosystems, distributed over 19,744.15 km<sup>2</sup> of forest area in the region of Extremadura (Spain), with different species and structural complexity forming 5 different forest types (3 <i>Quercus</i> spp. dominated and 2 <i>Pinus</i> 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 <i>Pinus</i> spp. forest than for the <i>Quercus</i> 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<sup>−1</sup> 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: <i>R</i><sup>2</sup> values of 0.63 and 0.64, and RMSE values of 11.10 Mg ha<sup>−1</sup>(rRMSE = 28.15%) and 12.28 Mg ha<sup>−1</sup> (rRMSE = 31.45%), respectively, and an approximately unbiased result (0.03 Mg ha<sup>−1</sup> and 0.09 Mg ha<sup>−1</sup>). 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 (<i>R</i><sup>2</sup> = 0.45), a higher RMSE value (25.88 Mg ha<sup>−1</sup>) and slightly biased results (−1.47 Mg ha<sup>−1</sup>), 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.