Conclusion

This study demonstrates the application of temporal remote sensing data and Geoinformatics in mapping and understanding of urban dynamics. Advance geo-visualisation of urban growth would aid in decision making towards sustainable cities with basic infrastructure and amenities. Identification of regional factors that are most likely to influence a land-use changes has improved the accuracy of prediction. The predictions of land use/cover changes through CA-Markov model suggest a continual increase in urban settlements with a decline in local ecology and natural vegetation covers. The prediction using CA help to design sustainable urban transportation system.