Urban Mapping and Growth Prediction using Remote Sensing and GIS Techniques, Pune, India

9 citations as recorded by crossref.

1. Modeling land use change using Cellular Automata and Artificial Neural Network: The case of Chunati Wildlife Sanctuary, Bangladesh K. Islam et al. https://doi.org/10.1016/j.ecolind.2018.01.047
2. Multilayer Perceptron for the Future Urban Growth of the Kharj Region in 2040 A. Alshahrane & H. Altuwaijri https://doi.org/10.3390/su15097037
3. Enabling Advanced Land Cover Analytics: An Integrated Data Extraction Pipeline for Predictive Modeling With the Dynamic World Dataset V. Radermecker et al. https://doi.org/10.1109/JSTARS.2025.3542282
4. Prediction of Urban Area Expansion with Implementation of MLC, SAM and SVMs’ Classifiers Incorporating Artificial Neural Network Using Landsat Data S. Zare Naghadehi et al. https://doi.org/10.3390/ijgi10080513
5. Blue-Green Infrastructure (BGI) network in urban areas for sustainable storm water management: A geospatial approach R. Kaur & K. Gupta https://doi.org/10.1016/j.cacint.2022.100087
6. Predicting urban growth of Arriyadh city, capital of the Kingdom of Saudi Arabia, using Markov cellular automata in TerrSet geospatial system H. Altuwaijri et al. https://doi.org/10.1007/s12517-019-4261-z
7. A systematic review of urban sprawl studies in India: a geospatial data perspective V. Saini & R. Tiwari https://doi.org/10.1007/s12517-020-05843-4
8. Predicting future urban growth scenarios and potential urban flood exposure using Artificial Neural Network-Markov Chain model in Miami Metropolitan Area S. Rifat & W. Liu https://doi.org/10.1016/j.landusepol.2022.105994
9. Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Gazipur City Corporation, Bangladesh M. Uddin et al. https://doi.org/10.3390/su151612329