I want to generate an output raster map which indicates the areas of wind and solar energy potentials. My study area is India. I have created GHI (Global Horizontal Irradiance) raster map (by interpolating point GHI values available). Similarly, I created wind speed map,by interpolating MERRA satellite data. Now for making Wind-Solar hybrid map, if I add the two raster layers by "Raster Calculator" of Spatial Analyst Tool in ArcGIS 10.1, then this is the right way of doing this?

  • Interpolated GHI from point data! Wow, how is this can be done?
    – FelixIP
    Commented Aug 29, 2017 at 9:58
  • I had GHI data with lat/long, in CSV format, which I imported to ArcGIS 10.1 software and by using IDW method of interpolation, in Spatial Analyst Tool of ArcToolBox, I interpolated GHI point data.
    – Anuja Negi
    Commented Aug 29, 2017 at 10:00
  • How does it handle deep valleys that hardly see any sunshine at all?
    – FelixIP
    Commented Aug 29, 2017 at 10:07
  • Since the study area is large (Country India which is ~ 3million square km) and GHI is the total amount of shortwave radiation received from above by a surface horizontal to the ground. So, with such a large distance, all undulations of the surface seems almost plane. So, for a broader idea of, which zone of the country receives more solar irradiance, GHI values suffice. If we zoom-in to high potential zones, then we consider other aspects like slope, angle of radiance etc. and calculate the solar potential of the area.
    – Anuja Negi
    Commented Aug 29, 2017 at 10:17

2 Answers 2


I would first normalize your values, then find the average of those normalized values in each cell.

This assumes that you apply an equal weighting to solar and wind energy generation methods. If you want to weight them differently, multiply the normalized values by the weight before finding the average.

The weighted overlay tool more or less performs this process for you

  • Thank you. It helped me to proceed in right direction. :)
    – Anuja Negi
    Commented Aug 29, 2017 at 9:27

Combining different data for decision making often has a part of subjectivity, but this can be driven by some expert knowledge.

I would try to reclassify (using reclassify tool) each raster based on this expert knowledge in order to have the same scale (e.g. from zero (very bad) to 10 (excellent) ). Once you have the same scale of appreciation for your inputs, you can combine the two rasters using you weighted average (e.g. with raster calculator) depending on how much focus you want to put on each layer. Again, selecting the weights can be tricky, but if you don't know which layer is the most important, the safest method consists in taking the arithmetic average.

As a remark, it is better to always try to quantify in the same unit if possible. So if you are able to translate wind speed and solar energy into values of electric energy, then you will have a better combination of the two energy sources and you should not try an average but take the maximum of the two sources (assuming that you cannot build both at the same place, the spatially hybrid map would consist in using the best device at each location, not mixing them locally.)

  • Thanks. This gave some clarity to me. Also I want to clear one more thing, that is it fine if I give equal weightage to both the layers and just simply add them in raster calculator (because they hold equal importance)?
    – Anuja Negi
    Commented Aug 29, 2017 at 9:02
  • as I said, giving the same weight is the safest method when you don't have information. So it is OK, but you should look at how much power you can have in the "best case" of solar and wind energy to make sure that they are not too much different.
    – radouxju
    Commented Aug 29, 2017 at 9:13

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