A robust approach for predicting land use/cover changes through integrated LSTM neural networks and cellular automata
Author:
Funder
College of Agriculture Natural Resources, University of Tehran
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10668-024-05144-w.pdf
Reference70 articles.
1. Aburas, M. M., Ho, Y. M., Ramli, M. F., & Ash’aari, Z. H. (2016). The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review. International Journal of Applied Earth Observation and Geoinformation, 52, 380–389. https://doi.org/10.1016/j.jag.2016.07.007
2. Bekkar, M., & Alitouche, T. A. (2013). Imbalanced data learning approaches review. International Journal of Data Mining and Knowledge Management Process, 3(4), 15. https://doi.org/10.5121/ijdkp.2013.3402
3. Bielecka, E. (2020). GIS spatial analysis modeling for land use change. A bibliometric analysis of the intellectual base and trends. Geosciences, 10(11), 421. https://doi.org/10.3390/geosciences10110421
4. Boulila, W., Ghandorh, H., Khan, M. A., Ahmed, F., & Ahmad, J. (2021). A novel CNN-LSTM-based approach to predict urban expansion. Ecological Informatics, 64, 101325. https://doi.org/10.1016/j.ecoinf.2021.101325
5. Cao, C., Dragićević, S., & Li, S. (2019). Short-term forecasting of land use change using recurrent neural network models. Sustainability, 11(19), 5376. https://doi.org/10.3390/su11195376
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