Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-022-05721-0.pdf
Reference57 articles.
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2. Alkandari A, Aljaber SJ (2015) Principle component analysis algorithm (PCA) for image recognition. In: 2015 international conference on computing technology and information management (ICCTIM) pp 76–80 https://doi.org/10.1109/ICCTIM.2015.7224596
3. Ascott MJ, Bloomfield JP, Karapanos I et al (2020) Managing groundwater supplies subject to drought: perspectives on current status and future priorities from England (UK). Hydrogeol J 293(29):921–924. https://doi.org/10.1007/s10040-020-02249-0
4. Azimi S, Hassannayebi E, Boroun M, Tahmoures M (2020) Probabilistic analysis of long-term climate drought using steady-state Markov chain approach. Water Resour Manag 34:4703–4724. https://doi.org/10.1007/s11269-020-02683-5
5. Bagheri MH, Bagheri A, Sohooli GA (2016) Analysis of changes in the Bakhtegan lake water body under the influence of natural and human factors. Iran-Water Resour Res 12(3):1–11
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