
Overview
A framework integrating the Budyko model has been developed to distinguish between rainfed and irrigated cropland areas across Africa. This expands on remote sensing land cover products available for agricultural water studies in Africa and thereby helps address the need for deeper insights into cropland patterns. Validation against an independent dataset revealed an overall accuracy of 73% with high precision and specificity scores. These results validate the framework’s effectiveness in identifying irrigated areas while minimizing errors in misclassifying rainfed areas as irrigated.
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- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- high-confidence cropland map (HCCM)
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::iwmi-datasets/Cropland_partition/HCCM/
- AWS region
- af-south-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://iwmi-datasets/Cropland_partition/HCCM//
- Description
- Cropland partitioning all data
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::iwmi-datasets/Cropland_partition/
- AWS region
- af-south-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://iwmi-datasets/Cropland_partition//
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IWMI DIWASA Rainfed and Irrigated Cropland Map for Africa was accessed on DATE from https://registry.opendata.aws/cropland_partitioining .
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