Articles | Volume 3, issue 1
https://doi.org/10.5194/wes-3-353-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-353-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2018
Research article |
| 08 Jun 2018
| 08 Jun 2018
From lidar scans to roughness maps for wind resource modelling in forested areas
Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark
Peter Enevoldsen
Center for Energy Technologies, Aarhus University, Aarhus, Denmark
Envision Energy, Silkeborg, Denmark
Neil Davis
Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark
Johan Arnqvist
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Ebba Dellwik
Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark
Viewed
Total article views: 5,128 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 12 Feb 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,228 | 1,747 | 153 | 5,128 | 157 | 143 |
- HTML: 3,228
- PDF: 1,747
- XML: 153
- Total: 5,128
- BibTeX: 157
- EndNote: 143
Total article views: 4,414 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jun 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,916 | 1,353 | 145 | 4,414 | 147 | 132 |
- HTML: 2,916
- PDF: 1,353
- XML: 145
- Total: 4,414
- BibTeX: 147
- EndNote: 132
Total article views: 714 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 12 Feb 2018)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 312 | 394 | 8 | 714 | 10 | 11 |
- HTML: 312
- PDF: 394
- XML: 8
- Total: 714
- BibTeX: 10
- EndNote: 11
Viewed (geographical distribution)
Total article views: 5,128 (including HTML, PDF, and XML)
Thereof 4,156 with geography defined
and 972 with unknown origin.
Total article views: 4,414 (including HTML, PDF, and XML)
Thereof 3,492 with geography defined
and 922 with unknown origin.
Total article views: 714 (including HTML, PDF, and XML)
Thereof 664 with geography defined
and 50 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
20 citations as recorded by crossref.
- Characterizing wind gusts in complex terrain F. Letson et al. 10.5194/acp-19-3797-2019
- A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management L. Zhao et al. 10.1007/s11356-022-19902-8
- Land Cover Control on the Drivers of Evaporation and Sensible Heat Fluxes: An Observation‐Based Synthesis for the Netherlands F. Jansen et al. 10.1029/2022WR034361
- One-year-long turbulence measurements and modeling using large-eddy simulation domains in the Weather Research and Forecasting model A. Peña & J. Mirocha 10.1016/j.apenergy.2024.123069
- Single Column Model Simulations of Icing Conditions in Northern Sweden: Sensitivity to Surface Model Land Use Representation E. Janzon et al. 10.3390/en13164258
- On the socio-technical potential for onshore wind in Europe: A response to critics P. Enevoldsen et al. 10.1016/j.enpol.2021.112147
- Wind energy resource assessment for Mukdahan, Thailand S. Polnumtiang & K. Tangchaichit 10.1080/15435075.2021.1941039
- Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019 F. Kestel et al. 10.1002/ldr.4659
- Deriving Aerodynamic Roughness Length at Ultra-High Resolution in Agricultural Areas Using UAV-Borne LiDAR K. Trepekli & T. Friborg 10.3390/rs13173538
- Satellite-based estimation of roughness lengths and displacement heights for wind resource modelling R. Floors et al. 10.5194/wes-6-1379-2021
- Socio-technical constraints in German wind power planning: An example of the failed interdisciplinary challenge for academia F. Permien & P. Enevoldsen 10.1016/j.erss.2019.04.021
- Estimating wind conditions in forests using roughness lengths: A matter of data input P. Enevoldsen 10.1177/0309524X19849849
- Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes R. Floors & M. Nielsen 10.3390/en12112038
- Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend M. Nazir et al. 10.3390/su12093778
- The making of the New European Wind Atlas – Part 1: Model sensitivity A. Hahmann et al. 10.5194/gmd-13-5053-2020
- Variation in Zero Plane Displacement and Roughness Length for Momentum Revisited A. Kunadi et al. 10.1007/s10546-024-00876-8
- Enhancing compound flood simulation accuracy and efficiency in urbanized coastal areas using hybrid meshes and modified digital elevation model E. Hamidi et al. 10.1016/j.scs.2025.106184
- A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea H. Li et al. 10.1016/j.gsf.2021.101229
- Østerild: A natural laboratory for atmospheric turbulence A. Peña 10.1063/1.5121486
- New European Wind Atlas: The Østerild balconies experiment I. Karagali et al. 10.1088/1742-6596/1037/5/052029
19 citations as recorded by crossref.
- Characterizing wind gusts in complex terrain F. Letson et al. 10.5194/acp-19-3797-2019
- A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management L. Zhao et al. 10.1007/s11356-022-19902-8
- Land Cover Control on the Drivers of Evaporation and Sensible Heat Fluxes: An Observation‐Based Synthesis for the Netherlands F. Jansen et al. 10.1029/2022WR034361
- One-year-long turbulence measurements and modeling using large-eddy simulation domains in the Weather Research and Forecasting model A. Peña & J. Mirocha 10.1016/j.apenergy.2024.123069
- Single Column Model Simulations of Icing Conditions in Northern Sweden: Sensitivity to Surface Model Land Use Representation E. Janzon et al. 10.3390/en13164258
- On the socio-technical potential for onshore wind in Europe: A response to critics P. Enevoldsen et al. 10.1016/j.enpol.2021.112147
- Wind energy resource assessment for Mukdahan, Thailand S. Polnumtiang & K. Tangchaichit 10.1080/15435075.2021.1941039
- Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019 F. Kestel et al. 10.1002/ldr.4659
- Deriving Aerodynamic Roughness Length at Ultra-High Resolution in Agricultural Areas Using UAV-Borne LiDAR K. Trepekli & T. Friborg 10.3390/rs13173538
- Satellite-based estimation of roughness lengths and displacement heights for wind resource modelling R. Floors et al. 10.5194/wes-6-1379-2021
- Socio-technical constraints in German wind power planning: An example of the failed interdisciplinary challenge for academia F. Permien & P. Enevoldsen 10.1016/j.erss.2019.04.021
- Estimating wind conditions in forests using roughness lengths: A matter of data input P. Enevoldsen 10.1177/0309524X19849849
- Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes R. Floors & M. Nielsen 10.3390/en12112038
- Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend M. Nazir et al. 10.3390/su12093778
- The making of the New European Wind Atlas – Part 1: Model sensitivity A. Hahmann et al. 10.5194/gmd-13-5053-2020
- Variation in Zero Plane Displacement and Roughness Length for Momentum Revisited A. Kunadi et al. 10.1007/s10546-024-00876-8
- Enhancing compound flood simulation accuracy and efficiency in urbanized coastal areas using hybrid meshes and modified digital elevation model E. Hamidi et al. 10.1016/j.scs.2025.106184
- A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea H. Li et al. 10.1016/j.gsf.2021.101229
- Østerild: A natural laboratory for atmospheric turbulence A. Peña 10.1063/1.5121486
1 citations as recorded by crossref.
Latest update: 08 Jul 2025
Short summary
Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a large impact on the estimated performance of wind turbines, particularly in forested areas. Traditionally the estimation of the surface roughness is based on a subjective process that requires assigning a value to each land use class in the vicinity of the wind farm. Here we propose a new method which converts lidar scans from a plane into maps that can be used for wind flow modelling.
Applying erroneous boundary conditions (surface roughness) for wind flow modelling can have a...
Altmetrics
Final-revised paper
Preprint