In Situ Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions

Citation

Labriere N, Tao S, Chave J, Scipal K, Toan TL, Abernethy K, Alonso A, Barbier N, Bissiengou P, Casal T, Davies SJ, Ferraz A, Hérault B, Jeffery KJ & White LJT (2018) In Situ Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11 (10), pp. 3617-3627. https://doi.org/10.1109/jstars.2018.2851606

Abstract
Tropical forests are a key component of the global carbon cycle. Yet, there are still high uncertainties in forest carbon stock and flux estimates, notably because of their spatial and temporal variability across the tropics. Several upcoming spaceborne missions have been designed to address this gap. High-quality ground data are essential for accurate calibration/validation so that spaceborne biomass missions can reach their full potential in reducing uncertainties regarding forest carbon stocks and fluxes. The BIOMASS mission, a P-band SAR satellite from the European Space Agency (ESA), aims at improving carbon stock mapping and reducing uncertainty in the carbon fluxes from deforestation, forest degradation, and regrowth. In situ activities in support of the BIOMASS mission were carried out in French Guiana and Gabon during the TropiSAR and AfriSAR campaigns. During these campaigns, airborne P-band SAR, forest inventory, and lidar data were collected over six study sites. This paper describes the methods used for forest inventory and lidar data collection and analysis, and presents resulting plot estimates and aboveground biomass maps. These reference datasets along with intermediate products (e.g., canopy height models) can be accessed through ESA's Forest Observation System and the Dryad data repository and will be useful for BIOMASS but also to other spaceborne biomass missions such as GEDI, NISAR, and Tandem-L for calibration/validation purposes. During data quality control and analysis, prospects for reducing uncertainties have been identified, and this paper finishes with a series of recommendations for future tropical forest field campaigns to better serve the remote sensing community.

Keywords
Computers in Earth Sciences; Atmospheric Science

Notes
Additional co-authors: Gaelle Jaouen, David Kenfack, Lisa Korte, Simon L Lewis, Yadvinder Malhi, Herve R Memiaghe, John R Poulsen, Maxime Rejou-Mechain, Ludovic Villard, Gregoire Vincent, and Sassan Saatchi

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing: Volume 11, Issue 10

• Accepted Manuscript