Author(s): S. Ajisha; R. Manjula

Linked Author(s):

Keywords: Rtificial Neural Network; CA-Markov; Cellular Automata; Landsat; LULC prediction; Noyyal Basin

Abstract: The monitoring and management of environmental parameters depends substantially on Land Use Land Cover (LULC) prediction. Multiple frameworks have been created to forecast future LULC, with CA-Markov and CA-ANN being the most well-liked models by researchers. The purpose of this study is to compare and contrast these two model’s performances in terms of LULC prediction features, including their pros and cons as well. This study uses the Cellular Automata (CA) -Markov model and the CA-ANN (Artificial Neural Network) model to anticipate and assess the future LULC of the Noyyal River Basin (36,000 sq. km), TamilNadu, India. Both models give equivalent results which shows that, the Noyyal basin experiences rapid urbanization between the years 2031 and 2041, with a drop in the area used for agriculture, water bodies, and forests and an increase in the area used for barren land and urban areas. Also, area difference is also observed in some of the predicted classes for both models. The kappa value for predicted LULC using CA-Markov and CA-ANN models is 0.832 and 0.739 respectively.

DOI: https://doi.org/10.3850/iahr-hic2483430201-359

Year: 2024