I'm working on satellite image processing, I'm calculating NDVI for time series analysis and vegetation prediction. I'm having a tough time removing the noisy data like,

  1. Cloud coverage
  2. Haze
  3. Cloud shadow

on Landsat-8 satellite image bands.

Is there any way to do this in Python?

I came across fmask package in python to mask cloud coverage but wasn't clear how to use it.

Then used pymakser but was only able to create a separate cloud mask file using BQA band of Landsat-8 but couldn't apply the mask on the image bands.

Finally tried using rio-cloud mask package but wasn't able to create the pre-requisite top of atmosphere reflectance for landsat-8 bands.

Also it'll be great if there's a method to just use the BQA band of Landsat-8 to remove noisy data from the TIF files using python.

  • Welcome to GIS SE! As a new user, you might want to take the Tour to get accustomed with i.a. the requirements of a question that seeks help in producing code/scripts; most importantly, to aid you in coding people usually want to see at least a minimum of your work and/or research so far. Do you have any code snippets that don´t work, or can refer to some sources you tried to implement maybe? Also, be as specific as you can about the tools/software you intend to use. You can always edit your question to include more information. – ThingumaBob Jun 15 '18 at 8:25

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