Distributed Computation of NDVI from Landsat Images Using Cloud Dataflow

Distributed Computation of NDVI from Landsat Images Using Cloud Dataflow

45 minutes 7 Credits


Google Cloud Self-Paced Labs


In this lab you process Landsat data in a distributed manner using Apache Beam and Cloud Dataflow. This lab is part of a series of labs on processing scientific data.

Before starting this lab, we highly recommend you read this blog post on what this pipeline does, what methods it uses, and what the results look like.

What you learn

In this lab, you:

  • Examine Apache Beam code to carry out Landsat processing
  • Submit Beam pipeline to Dataflow runner
  • View job details

Consider using Apache Beam on Cloud Dataflow to scale out compute-intensive jobs that meet these conditions:

  1. Your data is not tabular and you can not use SQL to do the analysis. (If it is tabular, use BigQuery).

  2. Large portions of the job are embarrassingly parallel -- in other words, you can process different subsets of the data on different machines.

  3. Your logic involves custom functions, iterations, etc...

  4. The distribution of the work varies across your data subsets.

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Create a Cloud Storage bucket

Run Step

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Launch the Dataflow Job

Run Step

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