Details

Autor(en) / Beteiligte

• Asner, Gregory P.
• Mascaro, Joseph

Titel

Mapping tropical forest carbon: Calibrating plot estimates to a simple LiDAR metric

Ist Teil von

• Remote sensing of environment, 2014-01, Vol.140, p.614-624

Ort / Verlag

New York, NY: Elsevier Inc

Erscheinungsjahr

2014

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals Complete

Beschreibungen/Notizen

• Mapping aboveground carbon density (ACD) in tropical forests can enhance large-scale ecological studies and support CO2 emissions monitoring. Light Detection and Ranging (LiDAR) has proven useful for estimating carbon density patterns outside of field plot inventory networks. However, the accuracy and generality of calibrations between LiDAR-assisted ACD predictions (EACDLiDAR) and estimated ACD based on field inventory techniques (EACDfield) must be increased in order to make tropical forest carbon mapping more widely available. Using a network of 804 field inventory plots distributed across a wide range of tropical vegetation types, climates and successional states, we present a general conceptual and technical approach for linking tropical forest EACDfield to LiDAR top-of-canopy height (TCH) using regional-scale inputs of basal area and wood density. With this approach, we show that EACDLiDAR and EACDfield reach nearly 90% agreement at 1-ha resolution for a wide array of tropical vegetation types. We also show that Lorey's Height – a common metric used to calibrate LiDAR measurements to biomass – is severely flawed in open canopy forests that are common to the tropics. Our proposed approach can advance the use of airborne and space-based LiDAR measurements for estimation of tropical forest carbon stocks. •The accuracy and generality of LiDAR-assisted carbon mapping remains uncertain in tropical forests.•An approach is developed to calibrate LiDAR top-of-canopy height to field-estimated aboveground carbon density.•At 1-ha resolution, LiDAR estimates of aboveground carbon density approach 90% agreement with field-estimated carbon density.•This approach will reduce cost and effort to calibrate LiDAR metrics to field estimates of tropical forest carbon stocks.