add doc

README.md

@@ -10,9 +10,6 @@ This project aims to calculate the average NDVI for Argentina using AWS Step Fun
 
 The NDVI images, sourced from the 'ndvi-satellite-images' S3 bucket, are provided by NASA satellites with a resolution of 256x256 pixels, representing bi-weekly NDVI values. Image filenames follow the "argentina_date.tif" pattern, with dates formatted as a four-digit year followed by a three-digit day of the year.
 
-The following image represent the application workflow. Each step in the flowchart is represented with a state in the step functions: 
-
-![Step function workflow](/wokflow%20faas.png)
 
 
 
@@ -56,4 +53,39 @@ Add a custom layer named **matplotlib**. This layer should include the rioxarray
 3. Function Code:
 In the Lambda function's code editor, paste the contents of the **Plot NDVI Time Series.py** script. This script contains the logic to plot the results, save it into png format and put it in S3 bucket.
 
+### Step function
+
+The following image represent the application workflow. Each step in the flowchart is represented with a state in the step functions: 
+
+![Step function workflow](/wokflow%20faas.png)
+
+
 
+#### Step 1: Create State Machine
+Log into the AWS Management Console and navigate to the AWS Step Functions page.
+Click on Create state machine to start the process of creating your workflow template.
+####  Step 2: Design Workflow Visually
+Choose **Design your workflow visually** to open the visual workflow editor. This option allows you to construct your state machine using a drag-and-drop interface.
+#### Step 3: Choose State Machine Type
+Select the **Standard** type for the state machine. If unsure about which type to select, click on Help me decide for a detailed comparison between **Standard** and **Express** types.
+After selecting the type, click Next to proceed to the workflow studio.
+#### Step 4: Use Flow Control
+Inside the workflow studio, navigate to the left-hand panel and select **Flow** control.
+Choose **Map**, which allows for parallel processing. Note that based on your workflow, you might not need to use Map if there's no parallel processing required.
+#### Step 5: Configure  a state to compute NDVI mean
+Drag and drop AWS Lambda from the Actions panel to add a task to invoke your Lambda function.
+Configure the task with the name of the Lambda function that computes the mean. Set the Payload option to use the state's input as the payload for the Lambda function.
+#### Step 6: Add Choice Flow
+Drag and drop the Choice state onto your workflow to create a branching logic.
+Configure the Choice state by adding rules:
+* Click Add new rule.
+* Set a condition by choosing the variable $.type.
+* For the operator, select is exactly and set the value to a String constant of "CSV" for the first condition.
+* Repeat the process for the second rule and set the value to "PNG".
+#### Step 7: Configure Lambda Tasks for the Condition
+Under each condition you've set in the Choice state, you will add the respective Lambda tasks:
+For CSV, drag another Lambda function onto the workflow and configure it to invoke the function that processes the data and outputs it to a CSV file.
+For PNG, do the same for the Lambda function that processes the data and outputs it to a PNG file.
+#### Step 8: Save and Test
+Once all the states are configured correctly, Save the state machine.
+Test your state machine by starting an execution and monitoring the results to ensure that it behaves as expected.