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I am trying to determine if a given property may be amenable for a ground based commercial solar project.

Among basic requirements there is flatness (5% slope or less), so I am trying to determine the slope suitability.

What is the best method to determine it?

If it helps I have a DEM LiDAR image of the area pulled in and have created 1' contours off of it already.

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    Jan 17, 2018 at 12:32
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2 Answers 2

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You mention 3D Analyst so I am assuming you have ArcGIS.

  • Use the tool ArcToolbox-3D Analyst Tools-Raster Surface-Slope to create a slope surface from your LiDAR data.
  • Use the tool ArcToolbox-3D Analyst Tools-Raster Reclass-Reclassify and give all the values > 5% slope NoData, and all the areas <=5% slope a value of 1. All the pixels with a value of 1 are all the places that have adequate slope.

You could do a similar reclassification with all your raster layers, then add the resulting layers up. The resulting summation will likely have values between 1-3. The 3 value pixels will be the areas that satisfy your three conditions. Build there.

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You can take the DEM and run the "Slope" tool in 3D Analyst. It is under the "Surface" Toolset. Choose "percentage" as the output type.

Once you have the "Slope" raster you can run the Reclass tool to find the ideal slope you are needing (5%). You can reclassify 5% as 1 and everything else as 0. You could add additional classes to identify those areas moderate to less ideal. You can convert the reclassed raster to polygon for use in your model.

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  • Ok I just performed that function. I chose the percent rise as my output measurement. Once I pull Up my symbology and go to reclassification, I'm seeing break values in 9 classes with the lowest being 0.6174475373 and the highest being 13.12076092. Are these the percentage values? If so, How can I simply this by only showing 5% or less?
    – Natedawg5509
    Jan 15, 2018 at 20:02
  • Yes. Those are percentages. Click the classify button and using the options choose the ranges you want for your classification.
    – Keagan Allan
    Jan 15, 2018 at 20:06

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