I am building a app to see the progress of deforestation. Over time i would like to take a satellite image from a location and see what percentage of that image contains forest.
I have attempted google's vision API, it does not have this functionality.
Is this something that can be done in OpenCV or must I do this from scratch with semantic segmentation or something similar?
So far I could see in the documentation there doesn't seem to be any pattern/texture recognition for the API. My belief is that you could try to do a dominant color recognition. if your image data has enough data of differentiable colors, I think you should be able to get an acceptable analysis.
PD: Having some experience with satellital imagery processing, as additional info, I can comment that the usual way to find out the status of the land for plants, forest and general crop development and health is though color analysis.
Nonetheless, Satellite/drone images are mostly multispectral and several UV bands are extensively used as biomass behaves very different with season/health/development status with the combination of visible and UV electromagnetic bands.
Have you tried to look at the satellite image recognition Kaggle competitions? There are a lot of discussions as well as available scripts for tasks similar to yours: Links: https://www.kaggle.com/c/dstl-satellite-imagery-feature-detection Example script: https://www.kaggle.com/arpandhatt/satellite-image-classification
