Aurora provides you with satellite images and helps you analyze those images in real-time. The workflow section lets you play around and derive all the necessary information from an AOI through various in-house machine learning and statistical models. Let’s understand what it exactly is.

​
Workflow

As the name suggests, workflow refers to a structured sequence of activities that can be created and managed within the platform. Workflows in Aurora are meant to automate the process of data extraction and analysis by visually designing an efficient process using data and processing blocks.

​
Data Blocks

Data blocks represent the input data or information that is required for the workflow. This includes the AOI you created comprising images selected and the AOI boundary. Data blocks serve as the starting point for the workflow, providing the initial dataset on which the workflow’s operations will be performed.

The data block (AOI block) provides two outputs: Raster and Vector, depending on the input required for the next node, the right output should be chosen.

​
Processing Blocks

Processing blocks represent the operations or tasks that are to be applied to the input data. These operations include all the models and tools offered by Aurora. Processing blocks define the sequence of actions to be taken on the input data. They determine how the data is modified, analyzed, or processed within the workflow.

​
Jobs

Workflows are run to produce output where each instance when the workflow is run is called a Job. Jobs help you run the workflows repeatedly, eliminating the need to create the same workflow for each data block or processing block. Jobs are further divided into two tabs: Overview and Insights. As the name suggests, “Overview” tells you about the workflow you created and Insights showcases the results generated from the workflow.

Assuming you have not created any workflows yet, please follow the process given below to create a new workflow:

  1. Workflow Interface: You can access the workflow section by clicking on the workflow button on the side navbar. Click on the New Workflow button to create a workflow and provide a name for your workflow.
  2. Starting with an Empty Canvas: When initiating the workflow creation process, you will find a blank workspace called a canvas. This canvas is where the workflow is constructed.
  3. Selecting Data and Processing Blocks: Users interact with a node table that contains data blocks and processing blocks. Data blocks represent input data (AOI), while processing blocks (Models) symbolize operations to be applied to the data.
  1. Placing Blocks on the Canvas: Users select data and processing blocks from the node table and drag them onto the canvas. This action populates the canvas with the necessary components for the workflow.
  1. Selecting Assets: After adding a data block, select the asset associated with the data block on which you wish to run the model
  2. Connecting Blocks: To establish the order of operations, users connect the data and processing blocks on the canvas by drawing lines or connectors between them. These connections determine how data flows from one block to another.
  3. Customizing and Configuring: Users can customize and configure each block on the canvas, specifying parameters and settings to meet the workflow’s specific requirements.
  1. Execution: Once you are done with connecting and configuring, you must save the workflow to run the job on the workflow. Click on the “Run” icon to run a job on the selected workflow.

Previous
Water Quality Index