Stochastic Radiative Transfer Model Simulate of lidar waveform over 3D canopy from two field campaigns in support of DESDYNI mission
Liang
Xu, Boston University, xuliang@bu.edu
(Presenting)
Mitchell
A
Schull, Boston University, schull@bu.edu
Arindam
Samanta, Boston University, arindam.sam@gmail.com
Crystal
L
Schaaf, Boston University, schaaf@bu.edu
Curtis
E
Woodcock, Boston University, curtis@bu.edu
Alan
H
Strahler, Boston University, alan@bu.edu
Ranga
B
Myneni, Boston University, ranga.myneni@gmail.com
Yuri
Knyazikhin, Boston University, jknjazi@bu.edu
The three-dimensional structure of a forest – its composition, density, height, crown geometry, within-crown foliage distribution and properties of individual leaves – is related to its above-ground live biomass, and hence, the amount of carbon. The development of remote sensing technology for the estimation of forest biomass is therefore a high priority. Active waveform lidar sensors provide direct estimates of tree and crown height and vertical canopy profiles. But the 3D canopy structure has a distinct impact on the lidar waveform, which makes its difficult to retrieve the vertical canopy structure in a straightforward way. In this study, we try to quantify the 3D effect by utilizing the pair correlation function, which is originally the key input parameter to the stochastic radiative transfer equation. The pair correlation function is the most natural and physically meaningful way of measuring canopy structure over a wide range of scales. It can be derived not only from remote sensing data, but also from field measurements of tree stand structure. Sites in Harvard Forest and Sierra Nevada were selected in the data analysis and the vertical distributions of pair correlation functions were retrieved from the 3D scenes constructed from allometry (in Harvard Forest) and ground lidar system – Echidna (in Sierra Nevada). The simulated lidar waveforms were calculated from a simplified version of the time-dependent stochastic radiative transfer model for derived pair correlation functions in each site. Airborne lidar data from LVIS over both sites were used to validate the simulated waveform. The results show that if spatial correlation is ignored, (a) one cannot simulate ground return for dense vegetation and thus much data could be interpreted incorrectly and, (b) the spatial correlation has direct impact on the shape of the lidar waveform.
Presentation Type: Poster
Poster Session: Field Campaigns
NASA TE Funded Awards Represented:
Myneni, Ranga
A SYNERGISTIC STUDY FOR LIDAR AND PASSIVE OPTICAL REMOTE SENSING OF FOREST HORIZONTAL STRUCTURE IN SUPPORT OF DESDYNI MISSION