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Duet T processing thermal_ir values


I apologize if these are basic questions, this is my first time processing thermal images and I am struggling to find documentation. I am trying to process imagery taken from a Duet T rig and have downloaded and am using the template provided by SenseFly. I am not making any changes to the template and am following the directions on their page, but I am unsure about the results, as shown below

In the Reflectance Map panel, it says Min = 0 and Max = 38.56. What do these numbers represent? This is a very large range and shouldn’t be the case for our data.

But then, in Index Map, the Min = -37.09 and Max is still 38.56. If I import the file into R or ArcGIS Pro, these are the Min and Max values I see as well.

When visualizing in Color Maps and Prescription, the Min = -4.89 and Max = 20.34. Why are these different from above? Also, this is quite a range and seems incorrect. If I unclamp the values, there seem to be holes in the data, which are where I believe the Min and Max -37 to 38 are.

Why am I getting these odd Min and Max values and is there a way to process the images to get an actual value? These areas are of interest as they are shaded and in direct sun.

Which values should I use and should I consider temperatures? Do I need to do a conversion? Why does the Color Maps and Prescription remove the odd Min and Max values?

Thank you for any help.


The reflectance map provides the temperature reading as an output if you are using the thermal camera. As you are mapping a bigger area with multiple areas of interest the range you are getting is reasonable. But I am not sure why your temperature ranges to -37. This might mainly be due to the quality of the raw images.
The correct map to use is the index map or the reflectance map with the temperature range of -37.09 to 38.56. So, when you open it in the R or ArcGIS, you will have the temperature range from -37.09 to 38.56.
The reason you are getting unreliable data is mainly the result of bad raw images data which might have to do with camera quality.

Thanks Kapil. The raw images do show these odd values, so we will investigate the camera further.