Recommended method for creating terrain & roughness maps?

[sarah]

There are many possible methods of creating .MAP files in WAsP Map Editor, WindPRO, WindFarmer etc., and many sources of raw data.

To the WAsP Team: Which method is recommended by the WAsP Team to WAsP Users as the most accurate method? Is freely available data, such as that from the SRTM website or that from dataforwind.com, of good enough quality or is it recommended to create terrain and roughness by hand using WAsP Map Editor?

To WAsP Users: Which data sources and which methods do WAsP Users recommend from their experience?

Thanks for your comments!

[jfcorbett]

You can usually buy very good electronic maps from the local country's geographical authority (e.g. Ordnance Survey in UK, Lantmäteriet in Sweden, etc.).


As for maps made by satellite remote-sensing, aside from STRM, I've used ASTER (also download here).


Creating maps "by hand" by scanning paper maps and clicking contours is a very nice hobby for masochists!

[Niels Gylling Mortensen]

jfcorbett's post pretty much sums up what the WAsP team would recommend with respect to elevation maps, I guess. But I would like to add a few details:


Digital elevation maps (contour lines or grids) may be quite expensive, so a combination of data is often the most cost-effective solution. Say, buy hi-res accurate contours for the wind farm site and its immediate surroundings, and use SRTM data for the terrain some distance away.


SRTM data are usually a very good starting point, but beware of areas of 'white space' (no data) in some parts of the world. You can add detail (additional contours and spot heights) to an SRTM map from a commercial database or a large-scale topographical map (some hand-digitising required). For elevation maps, detail and accuracy are most important close to the wind turbine and met. station sites.


SRTM data (the SWBD data set) can also give you the coastlines and lakes in an area, though it may take some editing to prepare these roughness change lines for WAsP.


Digitising by hand is indeed a slow and tedious process, though there is also a 'zen' aspect to the process that some people like ;-) If you can get hold of the printed contours only (say, the contour layer in the traditional printing process), it is also possible to scan and vectorise the contours using a software tool.

[Niels Gylling Mortensen]

Land cover (roughness length) maps are a little trickier to construct and often require some digitising by hand. Coastline contours may be constructed from the SWBD (SRTM Water Body Data) data set or using e.g. the Coastline Extractor (http://www.ngdc.noaa.gov/mgg/coast/); the Map Editor can import both formats. SWBD data also contains lakes and rivers.


The land cover may be digitised from scanned, large-scale topographic map sheets, satellite imagery or aerial photographs. Some people use Google Earth directly for the digitising (Add | Path or Polygon) and convert the resulting KML file to MAP format. The roughness values have to be added manually afterwards.


Remember that all maps and imagery correspond to a specific date; the land cover map should reflect the conditions you are modelling (say, use a historic map for the met. station site, recent Google Earth imagery for the wind farm site and so on).


Lots of land cover data are available in raster format, but to my knowledge there is no standard procedure for transforming such data to WAsP vector maps. It is straightforward to import such data into GIS software, but it takes some analysis and GIS modelling to make a good roughness map in a format that can be used by WAsP. – Would be interesting to hear about experiences using raster land cover data!

[cristi.stoian]

Because in Romania we don't have digital maps (here digital maps means a simple scan from the paper map with geo-ref coordinates), i do all the work manually. Near the met mast or the wind turbines i'm defining by hand all the height lines, if i have topographical measures i also combined them, then i complete the extended area with the SRTM lines.
For the roughness map, i use a combination of GoogleEarth/Global Mapper/Autocad.
Because the national/military maps are to old i'm making a grid, then i export this grid in GoogleEarth, i select a squere from this grid, then zoom at maxim, make a screen shot. After i have screentshots for all the squares, i merge the images and i geo-ref them. Then i import this image in Autocad and define the roughness areas. I don't use WAsP Map Editor for this because it's hard to zoom in/out or use other functions for drawing. From Autocad i export everything to MAP Editor, then set the roughness values. Also, with Global Mapper i make an export for Google Earth, with the defined roughness areas, with different hatch for different area type, in order to see everything clearly in Google Earth.

It'a a lot of hard work, but i know some wind reports made by others using scaned paper maps, with turbines placed in villages, or in lakes, because they didn't check the GoogleEarth.

[jfcorbett]

@cristi.stoian:

I find it much easier to draw polygons directly in Google Earth, place them in a "folder", and save that folder as a KML file. You can then read the contours from that file (by parsing the XML) and convert them to WAsP map format.


I wrote my own little program to do this conversion, but I'm sure Global Mapper or some other fancy GIS program can do this as well.


Exporting images from Google Earth and geo-referencing them is much more time-consuming... I've tried both methods, and I can say that KML-->MAP saves you a lot of time.

[cristi.stoian]

i've heard that are some methods to auto download maps from GoogleEarth, EMD has a tool for this, but Google didn't alowed them to put this feature into the commercial version of WindPRO.
Do you know anything about the possibility of downloading maps from GoogleEarth?

[Reuven Shenkar]

@jfcorbett:
Thanks for mentioning this option. For some reason I didn't think about it myself. It is possible to read KML into SAGA and QGIS (both open-source codes), let alone commercial GIS software. But I guess parsing the XML directly to MAP is the fastest. Now I only need to figure out how to write such a parser myself.