Enhanced agriculture datasets for remote crop monitoring, crop type mapping and yield prediction - Lacuna
Creators
Description
Yield Data Points for Zimbabwe
In 2023, PULA Advisors, an Agri-fintech company dedicated to providing affordable agricultural insurance to smallholder farmers, created a dataset through the support of the Lacuna fund grant. This dataset was meticulously compiled after conducting a field mission in Zimbabwe to collect yield measurements from farmers. The data collection process involved the use of predefined crop-cut protocols, which measured random yields within an 8-meter by 5-meter area on a farm. Yield measurements were taken at two key stages: during harvesting and after the produce had been dried to determine wet weight and dry weight, respectively. Subsequently, the data was aggregated to represent Megatonnes per Hectare, as specified in the attribute table. Additionally, the dataset includes location-related attributes, enabling the training of scalable machine-learning models for yield prediction and the generation of crop mask data for the crops featured in the dataset.
Methods (English)
Use Cases
Common use cases for these datasets can be in yield prediction and crop mask generation. This information can be used to inform policy around agriculture and food security. There is a manual attached to this repository in PDF format for review and practice on the use of this published data.
Files
Yield_forecasting _and_Crop_Mask_LACUNA_Technical_Manual_2.pdf
Additional details
Additional titles
- Subtitle (English)
- Yield predition training datasets
- Subtitle (English)
- Crop type mapping use case
Dates
- Updated
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2023-09-01The data collection was last collected on this date, marking the last date for field mission to small holder farmers.