An app for explainable and interactive crop modeling, contribution to the ML4Earth-Hackathon-2022
Many good tools for crop modeling and explainability are available. However, they usually require coding skills to use. cornXplain is an attempt to reduce the entry barrier to explainable crop modeling, and create an interactive, browser-like environment that strips away the complexity of a GIS or programming language. By being accessible and responsive, exploring crop models can be fun.
We create a three-component dashboard linking around a speedy crop model. The three components allow the user to explore the input data, the model performance and variable importances, and counterfactual scenarios.
Allows the user to visualize the data that goes into the model, with links to further information on the web.
A quick overview of the models structure with key performance metrics. This gives the user at-a-glance information about how the model functions, how good it is, and which variables it uses.
Here, the user can change the environmental variables that are input to the model - within reason - to explore possible scenarios and how the model responds to changes in certain variables.
