Neural networks-based simulation of land cover scenarios in Doon valley, India

Land cover transformation is one of the foremost aspects of human-induced environmental change, having an extensive history dating back to antiquity. The present study aims to simulate the process of land cover change based on different policy-based scenarios so as to provide a basis for sustainable development in Doon valley, India. For this purpose, an artificial neural network-based spatial predictive model was developed for the Doon valley. The predictive model generated future land cover patterns under three policy scenarios, i.e. baseline scenario, compact growth scenario and hierarchical growth scenario (HGS). The simulated land cover patterns mirror where land cover patterns are headed in the valley by year 2021. The result suggests that unabated continuation of the present pattern of land cover transformation will result in a regional imbalance. However, this skewed development can be corrected by altering the current growth trend as revealed in the compact growth and HGSs.