Sync with prod branch

Co-authored-by: Alex Crown <acrown@microsoft.com>
Co-authored-by: Eduardo Rodrigues <edrodrigues@microsoft.com>
Co-authored-by: Rafael Padilha <rpadilha@microsoft.com>
Co-authored-by: Renato Luiz de Freitas Cunha <renato.cunha@microsoft.com>

docs/source/docfiles/markdown/WORKFLOW_LIST.md

@@ -124,6 +124,24 @@ Below is a list of all available workflows within the FarmVibes.AI platform. For
 - [`heatmap/classification` 📄](workflow_yaml/data_processing/heatmap/classification.md): Utilizes input Sentinel-2 satellite imagery & the sensor samples as labeled data that contain nutrient information (Nitrogen, Carbon, pH, Phosphorus) to train a model using Random Forest classifier. The inference operation predicts nutrients in soil for the chosen farm boundary.
 
 
+The workflow generates a heatmap for selected nutrient. It relies on sample soil data that contain information of nutrients.
+The quantity of samples define the accuracy of the heat map generation. During the research performed testing with
+samples spaced at 200 feet, 100 feet and 50 feet. The 50 feet sample spaced distance provided results matching to the
+ground truth. Generating heatmap with this approach reduce the number of samples.
+It utilizes the logic below behind the scenes to generate heatmap.
+  - Read the sentinel raster provided.
+  - Sensor samples needs to be uploaded into prescriptions entity in Azure data manager for Agriculture (ADMAg). ADMAg is having hierarchy
+  to hold information of Farmer, Field, Seasons, Crop, Boundary etc. Prior to uploading prescriptions, it is required to build hierarchy and
+  a prescription_map_id. All prescriptions uploaded to ADMAg are related to farm hierarchy through prescription_map_id. Please refer to
+  https://learn.microsoft.com/en-us/rest/api/data-manager-for-agri/ for more information on ADMAg.
+  - Compute indices using the spyndex python package.
+  - Clip the satellite imagery & sensor samples using farm boundary.
+  - Perform spatial interpolation to find raster pixels within the offset distance from sample location and assign the value of nutrients to group of pixels.
+  - Classify the data based on number of bins.
+  - Train the model using Random Forest classifier.
+  - Predict the nutrients using the satellite imagery.
+  - Generate a shape file using the predicted outputs.
+
 - [`index/index` 📄](workflow_yaml/data_processing/index/index.md): Computes an index from the bands of an input raster.
 
 - [`linear_trend/chunked_linear_trend` 📄](workflow_yaml/data_processing/linear_trend/chunked_linear_trend.md): Computes the pixel-wise linear trend of a list of rasters (e.g. NDVI).

src/vibe_core/vibe_core/terraform/aks/README.md

@@ -0,0 +1,21 @@
+How to use this terraform file?
+
+Install Terraform from https://developer.hashicorp.com/terraform/downloads
+
+In current directory, execute:
+
+terraform init
+terraform apply -var-file=example-vars.tfvars
+
+Terraform apply will ask you the following questions:
+You can also refer to example-vars.tfvars
+
+location - This is the Azure Region you want to deploy in. For example, westus2, eastus2, etc.
+tenantId - This is the Azure Tenant GUID of your Tenant. You can find this by going to Azure Active Directory or navigating to: https://ms.portal.azure.com/#view/Microsoft_AAD_IAM/ActiveDirectoryMenuBlade/~/Overview
+subscriptionId - This is the Subscription GUID for the subscription you want to us.
+namespace - This is the kubernetes namespace you want to deploy your services in. This will be a new namespace which the script will create. Recommneded value is "terravibes"
+acr_registry - This is the path to the Docker Registry where the images are location. Public location for FarmVibes is mcr.microsoft.com/farmai/terravibes
+acr_registry_username - Username to access the Docker Registry
+acr_registry_password - Password to access the Docker Registry
+prefix - A short prefix to distinguish your deployment
+resource_group_name - If you want to use an existing resource group, specify it here

src/vibe_core/vibe_core/terraform/aks/example-vars.tfvars

@@ -0,0 +1,7 @@
+tenantId="<FILL YOUR TENANT ID HERE>"
+subscriptionId="<FILL YOUR SUBSCRIPTION ID HERE>"
+acr_registry="mcr.microsoft.com/farmai/terravibes"
+namespace="terravibes"
+location="<FILL AZURE REGION HERE>"
+prefix="<FILL PREFIX HERE>"
+resource_group_name="<FILL IN AN EXISTING RG IF YOU WANT TO USE ONE>"