Fig. 3: Identification of importance of sectors impacting the environmental footprint index.

The horizontal variables represent sectors differentiated in the calculation of environmental footprint index, and the vertical variables represent the different types of footprint intensity (FI) and footprint pressure (FP) in each sector, for example, CFI represent carbon footprint intensity, CFP represent carbon footprint pressure. A greater importance (darker color blocks) index indicates greater significance of the FP/FI of the sector on the environmental footprint index. Methods for measuring feature importance in machine learning are applied, where the Accuracy Decrease method, within Random Forest, assesses feature importance by removing each feature individually and measuring the resultant decrease in model accuracy, indicating how critical the feature is to the model’s performance.