Inference of replanting in forest fire affected land using data mining technique

Abstract

Forest fire is one of the natural calamities. The impact of fire on forest soil depends on its intensity and it also affects soil fertility, nutrients, and properties of soil like texture, color, and moisture content. Fire is beneficial and dangerous for soil nutrients based on its strength and it’s duration. In less severity fire, fermentation of soil matter increases nutrients, which results in rapid growth of plants. The natural/artificial biodegradation of soil can rebuild the forest. In the proposed work the effort is made in prediction of possibility of re-plantation in previously forest fire affected area. The analysis and prediction of soil nutrients is done using Naive Bayesian classification.