Publications

Zhou, ZL; Zhang, CL; Zou, XY; Zhang, XY; Zuo, XF; Zhang, ZD; Zhou, JX; Cao, ZH (2024). Estimating lateral cover of vegetation and gravel using NDVI and albedo. CATENA, 239, 107899.

Abstract
Vegetation and gravel are typical flexible and rigid roughness elements, respectively, in drylands, where they influence the strength and distribution of the interactions between airflow and the surface. The lateral cover of these elements, a composite indicator that describes their height, width, and density, affects the relationship between roughness element characteristics and the airflow's drag, and is an important parameter in shear-stress partitioning models. However, this parameter is difficult to describe on a regional scale and no suitable method is available. Previous regional wind erosion studies used the fractional cover indicator, which ignores the sheltering effect in the horizontal direction of the roughness elements. In this study, we measured vegetation and gravel lateral and fractional cover and surface albedo on the Inner Mongolia Plateau in northern China. The lateral cover was significantly related to the fractional cover. We found a significant relationship between groundmeasured lateral cover and the calculated shadow (1-albedo), thereby confirming the potential of the albedo approach to describe aerodynamic sheltering. We used this result to develop a method for determining the lateral cover of gravel over wide areas using surface shadow estimated from MODIS albedo products combined with vegetation cover from normalized-difference vegetation index (NDVI). Using the new method, we predicted the spatial distribution of vegetation and gravel cover on the Inner Mongolia Plateau. The lateral vegetation cover decreased gradually from northeast to southwest; lateral gravel cover showed the opposite trend. Our results reveal the sheltering effect of roughness elements, which cannot be described by fractional vegetation cover alone in conventional models. This has important implications for wind erosion and dust emission models based on shear-stress partitioning.

DOI:
10.1016/j.catena.2024.107899

ISSN:
1872-6887