6 November 2014 Parameterization of aerodynamic roughness of China’s land surface vegetation from remote sensing data
Deyong Hu, Liwei Xing, Shengli Huang, Lei Deng, Yingjun Xu
Author Affiliations +
Abstract
Aerodynamic roughness length (z0) is one of the important parameters that influence energy exchange at the land–atmosphere interface in numerical models, so it is of significance to accurately parameterize the land surface. To parameterize the z0 values of China’s land surface vegetation using remote sensing data, we parameterized the vegetation canopy area index using the leaf area index and land cover products of moderate resolution imaging spectroradiometer data. Then we mapped the z0 values of different land cover types based on canopy area index and vegetation canopy height data. Finally, we analyzed the intra-annual monthly z0 values. The conclusions are: (1) This approach has been developed to parameterize large scale regional z0 values from multisource remote sensing data, allowing one to better model the land–atmosphere flux exchange based on this feasible and operational scheme. (2) The variation of z0 values in the parametric model is affected by the vegetation canopy area index and its threshold had been calculated to quantify different vegetation types. In general, the z0 value will increase during the growing season. When the threshold in the dense vegetation area or in the growing season is exceeded, the z0 values will decrease but the zero-plane displacement heights will increase. This technical scheme to parameterize the z0 can be applied to large-scale regions at a spatial resolution of 1 km, and the dynamic products of z0 can be used in high resolution land or atmospheric models to provide a useful scheme for land surface parameterization.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Deyong Hu, Liwei Xing, Shengli Huang, Lei Deng, and Yingjun Xu "Parameterization of aerodynamic roughness of China’s land surface vegetation from remote sensing data," Journal of Applied Remote Sensing 8(1), 083528 (6 November 2014). https://doi.org/10.1117/1.JRS.8.083528
Published: 6 November 2014
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Vegetation

Aerodynamics

Atmospheric modeling

Data modeling

Remote sensing

MODIS

Spatial resolution

Back to Top