Measuring Crop Health Using Digital Earth Africa Data Cube
- Creators
- Digital Earth Africa
Description
What is it about
Background
Crop health or growth can vary in different fields even though they visually look similar thus leading to variability and unpredictability in revenue. Therefore, identifying the underperforming crops can be beneficial in scouting for crop disease and poor-performance fields to ensure management action is taken into consideration.
Digital earth Africa in this case uses satellite imagery to measure plant health over a given time and identify changes in growth patterns between similar fields. The sentinel 2 is a 20 m resolution imagery making it ideal for measuring the crop health over a large field. The normalized difference vegetation index NDVI is used to estimate the density of green on an area of land and track the crops as they reach the maturity stage. Comparing the NDVI of two similar planting areas can help to identify any anomalies in growth patterns.
This notebook allows for easy replication of analysis across Africa, by simply changing the analysis parameters. The user guide provides an overview of the analysis, resources used/supplied, and directions on how to reproduce the research.
This knowledge package includes the necessary data, computational resources, and instructions required to reproduce the methodology used in Digital Earth Africa's ''Measuring crop health'' Jupyter Notebook.
The User's Guide provides an overview of the application.
Knowledge Resources
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Additional details
- Available
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2022-11-24