This workflow can be found on the KNIME Workflow Public Server under
This KNIME workflow models the prediction of the burnt area by forest fires. It's based on the publication A Data Mining Approach to Predict Forest Fires using Meteorological Data by Cortez and Morais. The used dataset contains 517 fires from the Montesinho natural park in Portugal. For each incident weekday, month, coordinates, and the burnt area are recorded, as well as several meteorological data such as rain, temperature, humidity, and wind. The workflow reads the data and trains a regression model based on the spatial, temporal, and weather variables. The model is then used to predict the burnt area based the current date and the coordinates where the fire is spotted. This prediction can be used for calculating the forces sent to the incident.
The coordinates are entered in the dialog of the Get position and weather data metanode at the bottom left. If the workflow in run in the Webportal, they can be entered on the first page instead. Then the workflow uses the coordinates to get the current weather data using OpenWeatherMap webservices. With these values and the trained regression model, the area is predicted. The right part of the workflow prepares the data so that it is shown as an overlay to a OpenStreetMap. Color and size indicate the predicted burnt area. The generated images as well as the used data are finally rendered in a report:
This workflow makes use of the following extensions: