Preparing Imagery for Time-Series Analysis

I am attempting to prepare PlanetScope imagery for a time-series analysis. I have read a bit about transforming imagery into Analysis-Ready Data (ARD), so I am aware of the general steps in the process. This is the high-level workflow I have come up with so far:

masking --> normalization --> compositing --> co-registration

However, I am not sure how to implement these steps. Does anyone have any resources that describe how to prepare imagery for time-series analysis in as much detail as possible?

Some other details:

I am using 8-band imagery from SuperDove sensors
I have downloaded imagery as analytic surface reflectance at this point (but am open to other formats)
I am using Python to acquire and process this imagery.

Thanks for any help you can provide.

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Hi @kristofj,

There is an 8 course series on Planet University for using Planet Data in Python.

Check them out here: Getting Started Using Planet Data with Python

Hi @kristofj,

There is an 8 course series on Planet University for using Planet Data in Python.

Check them out here: Getting Started Using Planet Data with Python

Thank you for the tip, ely. I will take a peek through these.

Do you know if there is any content that addresses pre-processing imagery in preparation for time-series analysis or, more specifically, scene-level normalization?