Predicting the future landscape of Dhanbad District: an analysis of land-use change and urban sprawl through cloud computing and neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Economics and Econometrics,Geography, Planning and Development
Link
https://link.springer.com/content/pdf/10.1007/s10668-023-03998-0.pdf
Reference72 articles.
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2. Ahmad, F., Goparaju, L., & Qayum, A. (2017). LULC analysis of urban spaces using Markov chain predictive model at Ranchi in India. Spatial Information Research, 25(3), 351–359. https://doi.org/10.1007/s41324-017-0102-x
3. Al-shalabi, M., Pradhan, B., Billa, L., Mansor, S., & Althuwaynee, O. F. (2013). Manifestation of remote sensing data in modeling urban sprawl using the SLEUTH model and brute force calibration: A case study of Sana’a city, Yemen. Journal of the Indian Society of Remote Sensing, 41(2), 405–416.
4. Al-sharif, A. A., & Pradhan, B. (2015). A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS. Geocarto International, 30(8), 858–881.
5. Ankur, P., Chatterjee, S., & Gupta, K. (2022). Evaluation on the change characteristics of ecosystem service in Dhanbad district of Jharkhand India based on land use change. GeoJournal. https://doi.org/10.1007/s10708-022-10588-6
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