Derivation of regional aerodynamic roughness length by combining optical remote sensing and ground measurements over agricultural land in Heihe River Basin

2014 ◽  
Author(s):  
Qiting Chen ◽  
Li Jia ◽  
Ronald Hutjes
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Roughness Length ◽  
Agricultural Land ◽  
Heihe River Basin ◽  
Heihe River ◽  
Optical Remote Sensing ◽  
Aerodynamic Roughness Length ◽  
Aerodynamic Roughness

scholarly journals Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China

2010 ◽  
Vol 7 (3) ◽  
pp. 3397-3421 ◽  
Author(s):  
J. Colin ◽  
R. Faivre ◽  
M. Menenti
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
River Basin ◽  
Surface Density ◽  
Roughness Length ◽  
Heihe River ◽  
Surface Model ◽  
Aerodynamic Roughness Length ◽  
Passive Remote Sensing ◽  
Aerodynamic Roughness

Abstract. Roughness length of land surfaces is an essential variable for the parameterisation of momentum and heat exchanges. The growing interest about the estimation of the surface turbulent flux parameterisation from passive remote sensing lead to an increasing development of models, and the common use of simple semi-empirical formulations to estimate surface roughness. Over complex surface land cover, these approaches would benefit from the combined use of passive remote sensing and land surface structure measurements from Light Detection And Ranging (LIDAR) techniques. Following early studies based on LIDAR profile data, this paper explores the use of imaging LIDAR measurements for the estimation of the aerodynamic roughness length over a heterogeneous landscape of the Heihe river basin, a typical inland river basin in the northwest of China. LIDAR points were used to extract a Digital Surface Model (DSM) and a Digital Elevation Model (DEM) from a single flight pass over an irrigated area covered by field crops, small trees arrays and tree hedges, with a ground resolution of 1 m and a total surface of 7.2 km2. As a first step, the DSM is used to estimate the plan surface density and frontal surface density of obstacles to wind flow and compute a displacement height and roughness length following strictly geometrical approaches. In a second step, both the DSM and DEM are introduced in a Computational Fluid Dynamics model (CFD) to calculate wind fields from the surface to the top of the Planetary Boundary Layer (PBL), and invert wind profiles for each calculation grid and compute a roughness length. Examples of the use of these three approaches are presented for various wind direction together with a cross-comparison of results on heterogeneous land cover and complex roughness element structures.

scholarly journals Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China

2010 ◽  
Vol 14 (12) ◽  
pp. 2661-2669 ◽  
Author(s):  
J. Colin ◽  
R. Faivre
Keyword(s):  
Remote Sensing ◽  
Surface Roughness ◽  
Land Cover ◽  
River Basin ◽  
Land Surface ◽  
Surface Density ◽  
Roughness Length ◽  
Aerodynamic Roughness Length ◽  
Passive Remote Sensing ◽  
Aerodynamic Roughness

Abstract. Roughness length of land surfaces is an essential variable for the parameterisation of momentum and heat exchanges. The growing interest in the estimation of the surface turbulent flux parameterisation from passive remote sensing leads to an increasing development of models, and the common use of simple semi-empirical formulations to estimate surface roughness. Over complex surface land cover, these approaches would benefit from the combined use of passive remote sensing and land surface structure measurements from Light Detection And Ranging (LIDAR) techniques. Following early studies based on LIDAR profile data, this paper explores the use of imaging LIDAR measurements for the estimation of the aerodynamic roughness length over a heterogeneous landscape of the Heihe river basin, a typical inland river basin in the northwest of China. The point cloud obtained from multiple flight passes over an irrigated farmland area were used to separate the land surface topography and the vegetation canopy into a Digital Elevation Model (DEM) and a Digital Surface Model (DSM) respectively. These two models were then incorporated in two approaches: (i) a strictly geometrical approach based on the calculation of the plan surface density and the frontal surface density to derive a geometrical surface roughness; (ii) a more aerodynamic approach where both the DEM and DSM are introduced in a Computational Fluid Dynamics model (CFD). The inversion of the resulting 3-D wind field leads to a fine representation of the aerodynamic surface roughness. Examples of the use of these three approaches are presented for various wind directions together with a cross-comparison of results on heterogeneous land cover and complex roughness element structures.

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