Difference between revisions of "WindSight - Premium Data Layers by DHI GRAS"
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To use satellite-based data in the wind-energy flow modelling chains and to integrate those data into wind-energy yield assessments. That was one of the main goals of the InnoWind project that took place during years 2017-2020 and where EMD International A/S formed a project partnership with the Technical University of Denmark, DHI GRAS, Vestas and Vattenfall, see more at www.innowind.dk. The project was finalized in spring 2020 with a lot of fast-track data-products derived from satellite and remote sensing missions being available directly in windPRO, see our dedicated [[:Category:InnoWind|InnoWind]] wiki page. During the project, DHI GRAS has developed its ''DHI GRAS InnoWind Premium Data Service''. This service allows DHI GRAS to deliver data-layers of forest-height, land-cover and leaf-area-index in 20m resolution – based on Sentinel 1 and Sentinel 2 source data - with data layers being derived using machine-learning algorithms. These data are easily read with windPRO 3.4 – as they are typically delivered in geotiff-format. | To use satellite-based data in the wind-energy flow modelling chains and to integrate those data into wind-energy yield assessments. That was one of the main goals of the InnoWind project that took place during years 2017-2020 and where EMD International A/S formed a project partnership with the Technical University of Denmark, DHI GRAS, Vestas and Vattenfall, see more at www.innowind.dk. The project was finalized in spring 2020 with a lot of fast-track data-products derived from satellite and remote sensing missions being available directly in windPRO, see our dedicated [[:Category:InnoWind|InnoWind]] wiki page. During the project, DHI GRAS has developed its ''DHI GRAS InnoWind Premium Data Service''. This service allows DHI GRAS to deliver data-layers of forest-height, land-cover and leaf-area-index in 20m resolution – based on Sentinel 1 and Sentinel 2 source data - with data layers being derived using machine-learning algorithms. These data are easily read with windPRO 3.4 – as they are typically delivered in geotiff-format. | ||
| − | + | '''Point of contact for DHI GRAS data:<br>''' | |
WindPRO and WAsP users that is interested in this products may contact Torsten Bondo (tbon@dhigroup.com) from DHI GRAS for further details and pricing, see also [https://www.dhi-gras.com/ www.dhi-gras.com]. | WindPRO and WAsP users that is interested in this products may contact Torsten Bondo (tbon@dhigroup.com) from DHI GRAS for further details and pricing, see also [https://www.dhi-gras.com/ www.dhi-gras.com]. | ||
Revision as of 14:14, 19 March 2020
Introduction
To use satellite-based data in the wind-energy flow modelling chains and to integrate those data into wind-energy yield assessments. That was one of the main goals of the InnoWind project that took place during years 2017-2020 and where EMD International A/S formed a project partnership with the Technical University of Denmark, DHI GRAS, Vestas and Vattenfall, see more at www.innowind.dk. The project was finalized in spring 2020 with a lot of fast-track data-products derived from satellite and remote sensing missions being available directly in windPRO, see our dedicated InnoWind wiki page. During the project, DHI GRAS has developed its DHI GRAS InnoWind Premium Data Service. This service allows DHI GRAS to deliver data-layers of forest-height, land-cover and leaf-area-index in 20m resolution – based on Sentinel 1 and Sentinel 2 source data - with data layers being derived using machine-learning algorithms. These data are easily read with windPRO 3.4 – as they are typically delivered in geotiff-format.
Point of contact for DHI GRAS data:
WindPRO and WAsP users that is interested in this products may contact Torsten Bondo (tbon@dhigroup.com) from DHI GRAS for further details and pricing, see also www.dhi-gras.com.
Premium Data Samples and windPRO legends
6 packages of premium sample data are available for download for WAsP and windPRO users: These are for different parts of the world, while the two Danish ones are for the area around the DTU Risø campus and the other from the Danish National Test Station at Østerild. The 3 data layers of land-cover, LAI and canopy height are packed into a zip-file and available below.
- Denmark, Risø - available here
- Denmark, Østerild - here
- Portugal, Perdigao - here
- Mexico, Chihuahua - here
- South Africa, Humansdorp here
- Sweden, Ryningsnæs - here
Note: While it is possible to load these data into windPRO versions 3.3 and earlier versions - we recommend to use windPRO 3.4 (64-bit version) to load the data. This version will be available in early spring 2020 and holds improvements to read geo-tiff files into the line-object and area-objects of windPRO.
Legends to use with these files are available here as a zip file. To use these legends, please unpack the content to your folder with the windPRO 'standards'. Typically this will be within this folder:
c:\WindPRO Data\3.4\Standards
Cheat Sheet: Use DHI GRAS InnoWind Premium Data in windPRO
These data layers are typically used with the forest models in windPRO, i.e. the displacement height calculator and the ORA tool. We have a created a small cheat-sheet that describes how these new data-layers are loaded into the respective objects in windPRO - and how they are 'consumed' in the different calculations.
- InnoWind data in windPRO - cheat sheet - here (pdf-format)
Please note that the cheat-sheet is also useful for understanding how raster-based data can be 'consumed' in a varity of ways in the different objects in windPRO - and how the data layers are consumed within the various calculations.
External Links
DHI GRAS: https://www.dhi-gras.com/