Hi Claytonb, Really interesting analysis. I currently use a Canon S110 modified by Sensfly for NDVI and I wondered if there could be a big difference with a camera with separate sensors - I noticed now the accuracy that the camera can offer. Impressive! I also use Pix4D pro, what are the slight modification to the NDVI formula? (I imagine they will be different depending on the type of filter) And also, where did you find the calibration board? With known reflectance?

Thanks Alex

Hi Alex, I would recommend contacting Charlie Langlois at Labsphere- clanglois@labsphere.com They can make affordable($300 range)targets that are smaller 2X2" pieces that work great with same quality and accuracy as the targets that cost thousands. The formula I used in the above comparison subtracted around 40% of the pixel value in the red channel. I imagine it can be very different with different sensors and filters. It also changes based on the shutter speed, ISO as well so you will have to play with it to see what you can get. Luckily I had the RedEdge camera and a Greenseeker to verify values and know what I was aiming for in the formula modification.

I really liked this note too! I'm interested in how this dataset could be used as a "test set" for software development as well. There are a range of software packages (and methods using only Photoshop or Gimp) to do NDVI colormaps, and this is a great, well-documented and well-controlled set that could be used to validate the software procedures different packages use.

Thanks for posting such a great and clear note!

Thanks @Claytonb for this really interesting post. Could you detail a bit more about how you calibrated your images with reflectance targets please?

@everydayduffy -For the above comparison I used the calibration option in Pix4D pro. It consisted of drawing a region of interest on the image of the reflectance panel and inputting the known values for given wavelength. Ned Horning has an excellent plugin used with ImageJ that does a great job using calibration targets with known reflectance values. https://publiclab.org/notes/nedhorning/07-22-2015/introducing-the-calibration-plugin-for-imagej-fiji

Thank you @Claytonb.

@Claytonb, This is a great post and comparison. I have a couple questions, I'm using the V2 NoIR Raspberry Pi camera and #2007 filter they provide is a good place to start with this but really isn't ideal it seems if you want anything better than an estimation as it doesn't have great blue transmission. What is the advantage of using the red + IR bandpass rather than the BG3 Blue + IR filter other sites recommend and what would the small threadless filter cost me? Also, I understand why you would want to subtract the IR leakage in the red channel but is 40% a number you got from the reflectance calibration or just a rough estimate? I would be very interested in how you came up with that. Thanks for the post!

@Artichoke23 - What I have seen in testing is that a red filter will give you much greater contrast and sensitivity in crop vigor. A good example is corn. Stressed corn leaves will continue to absorb blue while reflecting much more red than healthy leaves. Ned Horning has a good note showing why red filters should work well with NDVI(https://publiclab.org/notes/nedhorning/11-01-2013/why-a-red-filter-should-work-well-for-ndvi) I'm not certain on the cost of specific filters but MidOpt can do custom stuff too(http://midopt.com/filters/db660850/) The 40% is what worked for specific settings on that Canon camera. I confirmed the NDVI of specific trees then adjusted the formula until I got the same value. The percentage of NIR in the blue channel to subtract from the red goes up dramatically if the images are not calibrated with reflectance targets.

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