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Land Use and Land Cover Change Assessment and Future Predictions in the Matenchose Watershed, Rift Valley Basin, Using CA-Markov Simulation

Author

Listed:
  • Markos Mathewos

    (Faculty of Biosystems and Water Resource Engineering, Institute of Technology, Hawassa University, Hawassa P.O. Box 05, Ethiopia)

  • Semaria Moga Lencha

    (Faculty of Biosystems and Water Resource Engineering, Institute of Technology, Hawassa University, Hawassa P.O. Box 05, Ethiopia
    Faculty of Agriculture and Environmental Sciences, University of Rostock, 18051 Rostock, Germany)

  • Misgena Tsegaye

    (Faculty of Biosystems and Water Resource Engineering, Institute of Technology, Hawassa University, Hawassa P.O. Box 05, Ethiopia)

Abstract

Land use and land cover change (LULC) is known worldwide as a key factor of environmental modification that significantly affects natural resources. The aim of this study was to evaluate the dynamics of land use and land cover in the Matenchose watershed from the years 1991, 2003, and 2020, and future prediction of land use changes for 2050. Landsat TM for 1991, ETM+ for 2003, and Landsat-8 OLI were used for LULC classification for 2020. A supervised image sorting method exhausting a maximum likelihood classification system was used, with the application using ERDAS Imagine software. Depending on the classified LULC, the future LULC 2050 was predicted using CA-Markov and Land Change Models by considering the different drivers of LULC dynamics. The 1991 LULC data showed that the watershed was predominantly covered by grassland (35%), and the 2003 and 2020 LULC data showed that the watershed was predominantly covered by cultivated land (36% and 52%, respectively). The predicted results showed that cultivated land and settlement increased by 6.36% and 6.53%, respectively, while forestland and grassland decreased by 63.76% and 22.325, respectively, from 2020 to 2050. Conversion of other LULC categories to cultivated land was most detrimental to the increase in soil erosion, while forest and grassland were paramount in reducing soil loss. The concept that population expansion and relocation have led to an increase in agricultural land and forested areas was further reinforced by the findings of key informant interviews. This study result might help appropriate decision making and improve land use policies in land management options.

Suggested Citation

  • Markos Mathewos & Semaria Moga Lencha & Misgena Tsegaye, 2022. "Land Use and Land Cover Change Assessment and Future Predictions in the Matenchose Watershed, Rift Valley Basin, Using CA-Markov Simulation," Land, MDPI, vol. 11(10), pages 1-28, September.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1632-:d:922532
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    References listed on IDEAS

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    1. Motuma Shiferaw Regasa & Michael Nones & Dereje Adeba, 2021. "A Review on Land Use and Land Cover Change in Ethiopian Basins," Land, MDPI, vol. 10(6), pages 1-18, June.
    2. Megersa Kebede Leta & Tamene Adugna Demissie & Jens Tränckner, 2021. "Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    3. Rahel Hamad & Heiko Balzter & Kamal Kolo, 2018. "Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    4. Guan, DongJie & Li, HaiFeng & Inohae, Takuro & Su, Weici & Nagaie, Tadashi & Hokao, Kazunori, 2011. "Modeling urban land use change by the integration of cellular automaton and Markov model," Ecological Modelling, Elsevier, vol. 222(20), pages 3761-3772.
    5. Berihun, Mulatu Liyew & Tsunekawa, Atsushi & Haregeweyn, Nigussie & Meshesha, Derege Tsegaye & Adgo, Enyew & Tsubo, Mitsuru & Masunaga, Tsugiyuki & Fenta, Ayele Almaw & Sultan, Dagnenet & Yibeltal, Me, 2019. "Exploring land use/land cover changes, drivers and their implications in contrasting agro-ecological environments of Ethiopia," Land Use Policy, Elsevier, vol. 87(C).
    6. Gezahegn Weldu Woldemariam & Anteneh Derribew Iguala & Solomon Tekalign & Ramireddy Uttama Reddy, 2018. "Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia," Land, MDPI, vol. 7(1), pages 1-25, February.
    7. Desta, Hayal & Fetene, Aramde, 2020. "Land-use and land-cover change in Lake Ziway watershed of the Ethiopian Central Rift Valley Region and its environmental impacts," Land Use Policy, Elsevier, vol. 96(C).
    8. Auwalu Faisal Koko & Wu Yue & Ghali Abdullahi Abubakar & Roknisadeh Hamed & Akram Ahmed Noman Alabsi, 2020. "Monitoring and Predicting Spatio-Temporal Land Use/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automata and Markov Chain Model (CA-Markov)," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    9. Youjung Kim & Galen Newman & Burak Güneralp, 2020. "A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models," Land, MDPI, vol. 9(8), pages 1-22, July.
    10. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    11. Wenjie Wang & Chuanrong Zhang & Jenica M. Allen & Weidong Li & Mark A. Boyer & Kathleen Segerson & John A. Silander, 2016. "Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut," Land, MDPI, vol. 5(3), pages 1-22, July.
    12. Hailu, Alemenesh & Mammo, Siraj & Kidane, Moges, 2020. "Dynamics of land use, land cover change trend and its drivers in Jimma Geneti District, Western Ethiopia," Land Use Policy, Elsevier, vol. 99(C).
    13. Melaku Bogale Fitawok & Ben Derudder & Amare Sewnet Minale & Steven Van Passel & Enyew Adgo & Jan Nyssen, 2020. "Modeling the Impact of Urbanization on Land-Use Change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov Chain Approach," Land, MDPI, vol. 9(4), pages 1-17, April.
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    1. Juliana Mio de Souza & Paulo Morgado & Eduarda Marques da Costa & Luiz Fernando de Novaes Vianna, 2023. "Predictive Scenarios of LULC Changes Supporting Public Policies: The Case of Chapecó River Ecological Corridor, Santa Catarina/Brazil," Land, MDPI, vol. 12(1), pages 1-24, January.
    2. Selamawit Haftu Gebresellase & Zhiyong Wu & Huating Xu & Wada Idris Muhammad, 2023. "Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    3. Shuangqing Sheng & Hua Lian, 2023. "The Spatial Pattern Evolution of Rural Settlements and Multi-Scenario Simulations since the Initiation of the Reform and Opening up Policy in China," Land, MDPI, vol. 12(9), pages 1-26, September.

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