IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p8499-d1154176.html
   My bibliography  Save this article

Geospatial-Temporal Dynamics of Land Use in the Juárez Valley: Urbanization and Displacement of Agriculture

Author

Listed:
  • Carlos Manjarrez-Domínguez

    (Facultad de Ciencias Agrotecnológicas, Universidad Autónoma de Chihuahua, Chihuahua 31310, Mexico)

  • Mario Iván Uc-Campos

    (Licenciatura en Geoinformática, Universidad Autónoma de Ciudad Juárez, División Cuauhtemoc, Ciudad Cuauhtémoc, Chihuahua 31600, Mexico)

  • Mario Edgar Esparza-Vela

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • María del Rosario Baray-Guerrero

    (Facultad de Ciencias Agrotecnológicas, Universidad Autónoma de Chihuahua, Chihuahua 31310, Mexico)

  • Omar Giner-Chávez

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • Eduardo Santellano-Estrada

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

Abstract

Urbanization and industrial development in the Juárez Valley, Chihuahua, Mexico, have led to the abandonment and loss of productive agricultural areas. However, the extent and dynamics of this phenomenon are not precisely known due to the lack of updated information. Therefore, it is necessary to geospatially represent these changes over time and predict their probability of persistence into the future to provide decision-making tools for this border region of Mexico. Landsat images were processed, and random forest was applied as a classifier to obtain land uses from 1980 to 2020. The Land Change Modeler options in Terrset™ were executed to generate land use changes, persistence and probabilities. Results showed that urban, built-up areas gained 19,962 ha by 2020 while crops lost 1675 ha. Agricultural permanence has been consolidated over time (persistence until 2020 of 0.83), but evidence suggests that this persistence will decrease in the future due to urbanization (decreasing to 0.59 by 2100). This could jeopardize the availability of primary products and food, lead to land abandonment and exacerbate socio-demographic expansion in this vulnerable region.

Suggested Citation

  • Carlos Manjarrez-Domínguez & Mario Iván Uc-Campos & Mario Edgar Esparza-Vela & María del Rosario Baray-Guerrero & Omar Giner-Chávez & Eduardo Santellano-Estrada, 2023. "Geospatial-Temporal Dynamics of Land Use in the Juárez Valley: Urbanization and Displacement of Agriculture," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8499-:d:1154176
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/8499/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/11/8499/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Shigeaki F. Hasegawa & Takenori Takada, 2019. "Probability of Deriving a Yearly Transition Probability Matrix for Land-Use Dynamics," Sustainability, MDPI, vol. 11(22), pages 1-11, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sri Murniani Angelina Letsoin & David Herak & Fajar Rahmawan & Ratna Chrismiari Purwestri, 2020. "Land Cover Changes from 1990 to 2019 in Papua, Indonesia: Results of the Remote Sensing Imagery," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    2. Wafaa Majeed Mutashar Al-Hameedi & Jie Chen & Cheechouyang Faichia & Biswajit Nath & Bazel Al-Shaibah & Ali Al-Aizari, 2022. "Geospatial Analysis of Land Use/Cover Change and Land Surface Temperature for Landscape Risk Pattern Change Evaluation of Baghdad City, Iraq, Using CA–Markov and ANN Models," Sustainability, MDPI, vol. 14(14), pages 1-31, July.
    3. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    4. Peng Tian & Luodan Cao & Jialin Li & Ruiliang Pu & Hongbo Gong & Changda Li, 2020. "Landscape Characteristics and Ecological Risk Assessment Based on Multi-Scenario Simulations: A Case Study of Yancheng Coastal Wetland, China," Sustainability, MDPI, vol. 13(1), pages 1-20, December.
    5. Changqing Sun & Yulong Bao & Battsengel Vandansambuu & Yuhai Bao, 2022. "Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    6. René Ulloa-Espíndola & Jenny Cuyo-Cuyo & Elisa Lalama-Noboa, 2023. "Towards Rural Resilience: Assessing Future Spatial Urban Expansion and Population Growth in Quito as a Measure of Resilience," Land, MDPI, vol. 12(2), pages 1-30, January.
    7. Cláudia M. Viana & Jorge Rocha, 2020. "Evaluating Dominant Land Use/Land Cover Changes and Predicting Future Scenario in a Rural Region Using a Memoryless Stochastic Method," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
    8. Ehab Hendawy & A. A. Belal & E. S. Mohamed & Abdelaziz Elfadaly & Beniamino Murgante & Ali A. Aldosari & Rosa Lasaponara, 2019. "The Prediction and Assessment of the Impacts of Soil Sealing on Agricultural Land in the North Nile Delta (Egypt) Using Satellite Data and GIS Modeling," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    9. Yongjiu Feng & Jiafeng Wang & Xiaohua Tong & Yang Liu & Zhenkun Lei & Chen Gao & Shurui Chen, 2018. "The Effect of Observation Scale on Urban Growth Simulation Using Particle Swarm Optimization-Based CA Models," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    10. Luoman Pu & Jiuchun Yang & Lingxue Yu & Changsheng Xiong & Fengqin Yan & Yubo Zhang & Shuwen Zhang, 2021. "Simulating Land-Use Changes and Predicting Maize Potential Yields in Northeast China for 2050," IJERPH, MDPI, vol. 18(3), pages 1-21, January.
    11. Man Li & Yanfang Zhang & Huancai Liu, 2022. "Carbon Neutrality in Shanxi Province: Scenario Simulation Based on LEAP and CA-Markov Models," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    12. 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.
    13. Camila Orellana Pereira & Rossana Escanilla-Minchel & Alejandra Cortés González & Hernán Alcayaga & Mauricio Aguayo & Miguel Aguayo Arias & Alejandro N. Flores, 2022. "Assessment of Future Land Use/Land Cover Scenarios on the Hydrology of a Coastal Basin in South-Central Chile," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    14. Sandip Giri & Sourav Samanta & Partho Protim Mondal & Oindrila Basu & Samiran Khorat & Abhra Chanda & Sugata Hazra, 2022. "A geospatial assessment of growth pattern of aquaculture in the Indian Sundarbans Biosphere Reserve," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 4203-4225, March.
    15. 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.
    16. Nij Tontisirin & Sutee Anantsuksomsri, 2021. "Economic Development Policies and Land Use Changes in Thailand: From the Eastern Seaboard to the Eastern Economic Corridor," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    17. Yangcheng Hu & Yi Liu & Changyan Li, 2022. "Multi-Scenario Simulation of Land Use Change and Ecosystem Service Value in the Middle Reaches of Yangtze River Urban Agglomeration," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
    18. Jessica Strzempko & Robert Gilmore Pontius, 2023. "The Flow Matrix Offers a Straightforward Alternative to the Problematic Markov Matrix," Land, MDPI, vol. 12(7), pages 1-18, July.
    19. Chul-Min Song, 2021. "Analysis of the Effects of Local Regulations on the Preservation of Water Resources Using the CA-Markov Model," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
    20. Jie Liu & Lang Zhang & Qingping Zhang, 2019. "The Development Simulation of Urban Green Space System Layout Based on the Land Use Scenario: A Case Study of Xuchang City, China," Sustainability, MDPI, vol. 12(1), pages 1-19, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8499-:d:1154176. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.