TY - JOUR
T1 - Forest Biomass Estimation at High Spatial Resolution: Radar Versus Lidar Sensors
AU - Tanase, Mihai
AU - Panciera, Rocco
AU - Lowell, Kim
AU - Aponte, Cristina
AU - Hacker, Jorg
AU - walker, jeffrey
PY - 2014
Y1 - 2014
N2 - This letter evaluates the biomass-retrieval error in pine-dominated stands when using high-spatial-resolution airborne measurements from fully polarimetric L-band radar and airborne laser scanning sensors. Information on total above-ground biomass was estimated through allometric relationships from plot-level field measurements. Multiple-linear-regression models were developed to model relationships between biomass and radar/lidar data. Overall, lidar data provided lower estimation errors (17.2 t · ha-1, 28% relative) when compared with radar data (30.3 t · ha-1, 61% relative). However, for the 30-100 t · ha-1 biomass range, the relative error from radar-based models was only 9% higher than that from lidar-based models. This suggests that high-spatial-resolution radar data could provide fundamentally similar results to lidar for some biomass intervals. This is an important finding for large-scale biomass estimation that needs to rely upon satellite data, as there are no lidar satellites planned for the foreseeable future.
AB - This letter evaluates the biomass-retrieval error in pine-dominated stands when using high-spatial-resolution airborne measurements from fully polarimetric L-band radar and airborne laser scanning sensors. Information on total above-ground biomass was estimated through allometric relationships from plot-level field measurements. Multiple-linear-regression models were developed to model relationships between biomass and radar/lidar data. Overall, lidar data provided lower estimation errors (17.2 t · ha-1, 28% relative) when compared with radar data (30.3 t · ha-1, 61% relative). However, for the 30-100 t · ha-1 biomass range, the relative error from radar-based models was only 9% higher than that from lidar-based models. This suggests that high-spatial-resolution radar data could provide fundamentally similar results to lidar for some biomass intervals. This is an important finding for large-scale biomass estimation that needs to rely upon satellite data, as there are no lidar satellites planned for the foreseeable future.
KW - Biomass
KW - L-band radar
KW - Small-footprint lidar
UR - http://www.scopus.com/inward/record.url?scp=84882446665&partnerID=8YFLogxK
U2 - 10.1109/LGRS.2013.2276947
DO - 10.1109/LGRS.2013.2276947
M3 - Article
VL - 11
SP - 711
EP - 715
JO - Geoscience and Remote Sensing Letters, IEEE
JF - Geoscience and Remote Sensing Letters, IEEE
SN - 1545-598X
IS - 3
M1 - 6583278
ER -