Author Topic: Altum reflectance calibration, best practices for chunks  (Read 8121 times)


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Altum reflectance calibration, best practices for chunks
« on: December 11, 2019, 10:27:40 PM »

I am working with a relatively large area of interest (~160 acres), that was broken up into 4 flights. Imagery was acquired with a Micasense Altum. I treat each flight as its own chunk, and essentially follow this workflow:

import folder
align photos
import and adjust GCP markers
optimize cameras
gradual selection and reoptimize cameras until satisfactory error is achieved
reflectance calibration (panel only, clear day)
dense cloud
merge chunks
Build DEM from dense cloud
Build orthomosaic from DEM(normalize band sensitivity is checked)
raster transform, dividing bands 1-5 by 32768, and converting thermal centikelvin to Celsius
Export ortho as bigTIFF with raster transform set to index values

The main problem I am encountering is that when I merge the chunks this is somehow impacting the reflectance calibration. The reflectance values are lower than if I export orthomosaics from individual chunks. This effect is apparent immediately when I merge chunks because the images appear darker (I am using the same reference band in merged and individual chunks: NIR). Also, it is severe enough that I can see flight lines of different flights when visually assessing the raster in GIS software.

What is going wrong, and how can I remedy the situation? Any advice would be greatly appreciated.


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Re: Altum reflectance calibration, best practices for chunks
« Reply #1 on: October 06, 2023, 02:08:13 PM »

Im processing my altum images right now. And is it necessary to divide by 32768 and why?