Parameterization of Aerodynamic Roughness Length and Zero Plane Displacement Over Tropical Region Using Airborne LiDAR Data
DOI:
https://doi.org/10.11113/jt.v73.4328Keywords:
Airborne LiDAR, aerodynamic roughness length, zero plane displacement, forestAbstract
Airborne LiDAR data has been one of the reliable data for individual tree properties estimation. High density airborne LiDAR data has been used previously for detailed reconstruction of tree geometry. The aim of this study is to estimate aerodynamic roughness over specific height (Zo/H) and zero plane displacement (do) over forest area using airborne LiDAR data. The results of this study will be very useful as a main guideline for related applications to understand the role of carbon and hydrological cycles, land cover and land use change, habitat fragmentation, and biogeographical modeling. The airborne LiDAR data is first classified into ground and non-ground classes. The ground points are interpolated for digital terrain model (DTM) generation and the non-ground points are used to generate digital surface model (DSM). Canopy height model (CHM) is then generated by subtracting DTM from DSM. Individual tree delineation is carried out on the CHM and individual tree height is used together with allometric equation in estimating height to crown base (HCB) and diameter at breast height (DBH). Tree crown delineation is carried out using the Inverse Watershed segmentation approach. Crown diameter, HBC and DBH are used to estimate individual tree frontal area and the total frontal area over a specific ground surface is further calculated by subtracting the intersected crowns and trunks from the total area of tree crowns and trunks. The considered ground area i.e. plants area determined the final spatial resolution of the Zo/H and do. Both parameters are calculated for different wind directions that were assumed to be originated from North/South and East/West. The results show that the estimated Zo/H and do have similar pattern and values with previous studies over vegetated area.Â
References
X. Tian, et al. 2011. Estimating Zero-plane Displacement Height and Aerodynamic Roughness Length Using Synthesis of LiDAR and SPOT-5 data. Remote Sensing of Environment. 115: 2330–2341.
K. J. Schaudt and R. E. Dickinson. 2000. An Approach to Deriving Roughness Length and Zero-plane Displacement Height From Satellite Data, Prototyped with BOREAS data. Agricultural and Forest Meteorology.. 104: 143–155.
B. J. Choudhury and J. L. Monteith. 1988. A Four-layer Model for the Heat Budget of Homogenous Land Surfaces. Quarterly Journal of the Royal Meteorological Society. 144: 373–398.
M. R. Raupach. 1994. Simplified Expression for Vegetation Roughness Length and Zero-plane Displacement as Functions of Canopy Height and Area Index. Boundary Layer Meteorology. 71: 211–216.
T. Nakai, et al. 2008. Parameterisation of Aerodynamic Roughness Over Boreal, Cool- and Warm-Temperate Forests. Agricultural and Forest Meteorology. 148: 1916–1925.
E. Paul-Limoges, et al. 2013. Estimation of Aerodynamic Roughness of a Harvested Douglas-fir Forest Using Airborne LiDAR. Remote Sensing of Environment. 136: 225–233.
W. G. M. Bastiaanssen, et al. 1998. A Remote Sensing Surface Energy Balance Algorithm for Land (SEBAL) 1. Formulation. Journal of Hydrology. 212–213: 198–212.
J. Colin, et al. 2006. A Multi-scales Surface Energy Balance System for Operational Actual Surface Evapotranspiration Monitoring. 178–184.
G. J. Roerink, et al. 2000. S-SEBI: A Simple Remote Sensing Algorithm to Estimate the Surface Energy Balance. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere. 25: 147–.
J. Colin, et al. 2006. Accuracy Vs. Operability: A Case Study Over Barrax in the Context of the DEMETER Project. 75-83.
M. Menenti and J. C. Ritchie. 1994. Estimation of Effective Aerodynamic Roughness of Walnut Gulch Watershed with Laser Altimeter Measurement. Water Resources Research. 30: 1329–1337.
K. J. Schaudt and R. E. Dickinson. 2000. An Approach to Derivig Roughness Length and Zero-displacement Height from Satellite Data, Prototyped with BOREAS Data. Agricultural and Forest Meteorology. 104: 143–155.
A. C. D. Vries, et al. 2003. Effective Aerodynamic Roughness Estimated from Airborne Laser Altimeter Measurements of Surface Features. International Journal of Remote Sensing. 24: 1545–1558.
J. Colin and R. Faivre. 2010. Aerodynamic Roughness Length Estimation from Very High-resolution Imaging LIDAR Observations over the Heihe Basin in China. Hydrology and Earth System Sciences. 14: 2661—2669.
A. Wehr. 2009. LiDAR Systems and Calibration. In Topographic Laser Ranging and Scanning, J. Shan and C. K. Toth, Eds. ed Boca Raton, Florida: Taylor & Francis Group. 108.
Zhang, K., S. C. Chen, D. Whitman, M. L. Shyu, J. H. Yan, and C. C. Zhang. 2003. A Progressive Morphological Filter for Removing Nonground Measurements from Airborne LIDAR Data. IEEE Transactions on Geoscience and Remote Sensing. 41: 872–882.
M. Z. A. Rahman and B. Gorte. 2009. Tree Crown Delineation from High Resolution Airborne Lidar Based on Densities of High Points. In ISPRS Workshop Laserscanning 2009, Paris, France.
T. Okuda, et al. 2004. Estimation of Aboveground Biomass in Logged and Primary Lowland Rainforests using 3-D Photogrammetric Analysis. Forest Ecology and Management. 203: 63–75.
D. C. Morton, et al. 2014. Amazon Forests Maintain Consistent Canopy Structure And Greenness During The Dry Season. Nature. 506: 221–224.
Lettau, H. 1969. Note on Aerodynamic Roughness-parameter Estimation on the Basis of Roughness-Element Description. Journal of Applied Meteorology. 8(5): 828–832,
Counihan J. 1971. Wind Tunnel Determination of the Roughness Length as a Function of the Fetch and Roughness Density of Three Dimensional Roughness Elements. Atmospheric Environment. 5: 637–642.
Macdonald, R., et al. 1998. An Improved Method for the Estimation of Surface Roughness of Obstacle Arrays. Atmospheric Environment. 32(11): 1857–1864.
Wieringa, J. 1992. Updating the Davenport Roughness Classification. Journal of Wind Engineering and Industrial Aerodynamics. 41(1): 357–368,
Shao, Y. and Y. Yang. 2005. A Scheme for Drag Partition Over Rough Surfaces. Atmospheric Environment. 39(38): 7351–7361.
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