Name
Abstract | ||
|---|---|---|
This study investigates the improvement in above ground biomass estimates when using a synergistic model based on lidar derived forest structural information (i.e., canopy cover percentage) and radar backscatter. The results were cross-compared with a radar only model. A two-layered radar backscatter model was also tested. The results showed that lidar-based structural information has the potential to increase the accuracy of biomass estimation by up to 20% depending on polarization and acquisition date. A smaller improvement was observed when using a modeled estimate of the forest canopy cover as would be the case of a future lidar/radar joint space-borne mission. The two-layered vegetation backscatter model did not improve the biomass estimation accuracy with errors being higher when compared to a single-layer vegetation model. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IGARSS.2013.6723238 | IGARSS |
Keywords | Field | DocType |
forest canopy cover percentage,synergistic model,lidar-based structural information,polarization,lidar derived forest structural information,above ground biomass estimates,two-layered radar backscatter model,remote sensing by radar,acquisition date,australia,optical radar,forest biomass estimation accuracy,single-layer vegetation model,two-layered vegetation backscatter model,future lidar/radar joint space-borne mission,forest biomass,lidar-radar synergies,vegetation mapping,spaceborne radar,vegetation,radar polarimetry,measurement,biomass,backscatter,laser radar | Radar,Tree canopy,Meteorology,Biomass,Vegetation,Radar backscatter,Computer science,Backscatter,Remote sensing,Lidar,Canopy | Conference |
ISSN | ISBN | Citations |
2153-6996 | 978-1-4799-1114-1 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siyuan Tian | 1 | 1 | 0.69 |
| Mihai A. Tanase | 2 | 54 | 7.66 |
| Rocco Panciera | 3 | 174 | 18.17 |
| Jörg M. Hacker | 4 | 38 | 4.08 |
| Kim Lowell | 5 | 14 | 5.62 |