Platform Prototype for the Prediction of Landslide Susceptibility Through a 4D WebGIS Equipped with Cellular Automata and Neural Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-59925-5_7
Reference15 articles.
1. Spizzichino, D., Margottini, C., Trigila, A., Iadanza, C.: Landslide impacts in Europe: Weaknesses and strengths of databases available at European and national scale. In: Margottini, C., Canuti, P., Sassa, K. (eds.) Landslide Science and Practice, 73–80. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-31325-7_9
2. Reichenbach, P., Busca, C., Mondini, A.C., Rossi, M.: Land use change scenarios and landslide susceptibility zonation: the briga catchment test area (Messina, Italy). In: Lollino, G., Manconi, A., Clague, J., Shan, W., Chiarle, M. (eds.) Engineering Geology for Society and Territory –Volume 1, pp. 557–561. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-09300-0_104
3. Bhattacharjee, K., Naskar, N., Roy, S., Das, S.: A survey of cellular automata: types, dynamics, non-uniformity and applications. Nat. Comput. 19, 433–461 (2020)
4. CCIS;V Barrile,2022
5. Bilotta, G., Genovese, E., Citroni, R., Cotroneo, F., Meduri, G.M., Barrile, V.: Integration of an innovative atmospheric forecasting simulator and remote sensing data into a geographical information system in the frame of agriculture 4.0 concept. AgriEngineering 5(3), 1280–1301 (2023)
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