Assessment of aerodynamic roughness length using remotely sensed land cover features and MODIS

• Main Authors: Abbas, M. R., Rasib, A. W., Abbas, T. R. A., Ahmad, B., Dutsenwai, H. S.
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: G70.39-70.6 Remote sensing
• Online Access: http://eprints.utm.my/id/eprint/95765/1/MalikRashidAbbas2021_AssessmentofAerodynamicRoughness.pdf; http://eprints.utm.my/id/eprint/95765/; http://dx.doi.org/10.1088/1755-1315/722/1/012015
• Institution: Universiti Teknologi Malaysia

Wind speed profile has a significant role in environmental transport phenomena whereby Roughness length is a governing factor that determines wind speed profile. Normally, relatively crude estimates of roughness length are used in global climate models based on constant values for each specific land cover category. However, a significant variation may exist within any one of these land cover categories. For this reason, it is necessary to derive detailed roughness length distribution over areas under consideration. Satellite observations can be used to assess the details of roughness length distribution. The aim of the present study was to develop method for roughness length assessment based on remotely sensed Normalized Difference Vegetation Index (NDVI) and landscape images for the entire Iraq area. The NDVI was generated using MODIS data (MOD13Q1) at 250 m resolution acquired on 23th April 2015 for whole Iraq. And the landscape images were classified based on land use and land cover (LU/LC) that relates general classes of LU/LC and values of roughness length coefficient. Taking into consideration a specific range of NDVI values of each landscape category, a correlation analysis was used to determine the aerodynamic roughness between the values of (NDVI) and the aerodynamic roughness based on the European Wind Atlas classification and the Royal Netherlands Meteorological Institute. A quantitative relationship was set up to retrieve the aerodynamic roughness length from MODIS data (MOD13Q1) where R2 = 0.96. Experiments prove that the proposed methodology can provide accurate roughness length estimations for the spatial and temporal analysis of land surface. The findings of this study will enhance sustainability in Iraq and many other regions of the world, thus, supporting the Sustainable Development Goals (SDGs) through the establishment of wind farms especially in countries with coastal areas that can serve as a major source of the national electricity.