I’m using a Sentera Double 4K/AGX710 Multi-spectral Sensor to map large wetlands and then classify into vegetation categories. For prior flights, we did not do radiometric calibration and I used the orthomosaics to do the classifications. But for our next flights we want to have data comparable across different days, so we’re considering a radiometric calibration target, which would then require me to use the reflectance bands imagery.
But, in these wetlands slivers of water show through vegetation and we get a lot of sunglint. Since the orthomosaics have color balancing between photos, it eliminates the sunglint. But if we do radiometric calibration and then use the reflectance band imagery, which doesn’t use color balancing, glint will be a problem. Also we get sunglint for almost 3 hours centered around solar noon, so it’s not feasible for us to avoid flying during that whole time.
Alternatively, would it work to continue to use the orthomosaics, but calculate band ratios to normalize each band for ambient light, and perform classifications with the band ratio rasters? That is, the new red band would be R/(R+G+B), etc. I’ve seen this done in satellite remote sensing but not sure if it works here.
Thanks for any insight!
single photo, showing glint:
reflectance imagery (radiometric correction set to “camera only”) showing noData and brightened pixels in sunglint spots: