@inproceedings{da98901c721046c09ec8a9090c084f7a,
title = "Forest biomass estimation using radar and lidar synergies",
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.",
keywords = "forest biomass, lidar-radar synergies",
author = "Siyuan Tian and Tanase, {Mihai A.} and Rocco Panciera and J. Hacker and Kim Lowell",
year = "2013",
doi = "10.1109/IGARSS.2013.6723238",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "2145--2148",
booktitle = "2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS",
address = "United States",
note = "2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 ; Conference date: 21-07-2013 Through 26-07-2013",
}