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-Reference-Cited by-同舟云学术

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

Published:2022-11-30 Issue:1 Volume:116 Page:1291-1314
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Mokarram Marzieh,Pham Tam Minh^ORCID

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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