IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i7p1442-d1699003.html
   My bibliography  Save this article

Historical Land Cover Dynamics and Projected Changes in the High Andean Zone of the Locumba Basin: A Predictive Approach Using Remote Sensing and Artificial Neural Network—Cellular Automata Model

Author

Listed:
  • German Huayna

    (Department of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Victor Pocco

    (Department of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Edwin Pino-Vargas

    (Department of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Pablo Franco-León

    (Laboratory of Ecological Processes, Research Group of Arid Zones, Deserts and Climate Change (ADERIZA), Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Jorge Espinoza-Molina

    (Department of Architecture, Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Fredy Cabrera-Olivera

    (Department of Geological Engineering-Geotechnics, Jorge Basadre National University, Tacna 2300, Peru)

  • Bertha Vera-Barrios

    (Faculty of Mining Engineering, National University of Moquegua, Moquegua 18001, Peru)

  • Karina Acosta-Caipa

    (Department of Architecture, Jorge Basadre Grohmann National University, Tacna 23000, Peru)

  • Lía Ramos-Fernández

    (Departament of Water Resources, Universidad Nacional Agraria La Molina, Lima 15024, Peru)

  • Eusebio Ingol-Blanco

    (Department of Civil Engineering, New Mexico State University, Las Cruces, NM 88003, USA)

Abstract

The conservation and monitoring of land cover represent crucial elements for sustainable regional development, especially in fragile high Andean ecosystems. This study evaluates the spatiotemporal changes in land use and land cover (LULC) in the Locumba basin over the period of 1984–2023. A hybrid modeling approach combining artificial neural networks (ANN) and cellular automata (CA) was employed to project future changes for 2033, 2043, and 2053. The results reveal a significant reduction in glaciers and lagoons throughout the Locumba basin, with notable declines from 1984 to 2023, while vegetated areas, particularly grasslands and wetlands, experienced substantial expansion. Specifically, grasslands increased by 273.7% relative to their initial coverage, growing from 57.87 km 2 in 1984 to over 220.31 km 2 in 2023, with projections indicating continued growth to over 331.62 km 2 by 2053. This multitemporal analysis provides crucial information for anticipating future land dynamics and underscores the urgent need for strategic conservation planning to mitigate the continued loss of strategic ecosystems in the high Andean region of Tacna.

Suggested Citation

  • German Huayna & Victor Pocco & Edwin Pino-Vargas & Pablo Franco-León & Jorge Espinoza-Molina & Fredy Cabrera-Olivera & Bertha Vera-Barrios & Karina Acosta-Caipa & Lía Ramos-Fernández & Eusebio Ingol-B, 2025. "Historical Land Cover Dynamics and Projected Changes in the High Andean Zone of the Locumba Basin: A Predictive Approach Using Remote Sensing and Artificial Neural Network—Cellular Automata Model," Land, MDPI, vol. 14(7), pages 1-26, July.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:7:p:1442-:d:1699003
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/7/1442/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/14/7/1442/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ana Caroline Pinheiro & Paulo Canas Rodrigues, 2024. "Hierarchical Time Series Forecasting of Fire Spots in Brazil: A Comprehensive Approach," Stats, MDPI, vol. 7(3), pages 1-24, June.
    2. Chaoxu Luan & Renzhi Liu, 2022. "A Comparative Study of Various Land Use and Land Cover Change Models to Predict Ecosystem Service Value," IJERPH, MDPI, vol. 19(24), pages 1-20, December.
    3. 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.
    4. Haile Belay & Assefa M. Melesse & Getachew Tegegne, 2024. "Scenario-Based Land Use and Land Cover Change Detection and Prediction Using the Cellular Automata–Markov Model in the Gumara Watershed, Upper Blue Nile Basin, Ethiopia," Land, MDPI, vol. 13(3), pages 1-34, March.
    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. Yun Jiang & Guoming Du & Hao Teng & Jun Wang & Haolin Li, 2023. "Multi-Scenario Land Use Change Simulation and Spatial Response of Ecosystem Service Value in Black Soil Region of Northeast China," Land, MDPI, vol. 12(5), pages 1-21, April.
    2. Fabián Argandoña-Castro & Fernando Peña-Cortés, 2025. "A Systematic Review of Developments in Farmland Cover in Chile: Dynamics and Implications for a Sustainable Future in Land Use," Sustainability, MDPI, vol. 17(9), pages 1-20, April.
    3. Xingwang Hu & Weihua Liao & Yifang Wei & Zhiyan Wei & Shengxia Huang, 2024. "Analysis of Land Use Change and Its Economic and Ecological Value under the Optimal Scenario and Green Development Advancement Policy: A Case Study of Hechi, China," Sustainability, MDPI, vol. 16(12), pages 1-20, June.
    4. Xufeng Cao & Jiqin Han & Chonggang Liu, 2025. "Analysis of Cultivated Land Change and Its Driving Forces in Jiangsu Province, China," Land, MDPI, vol. 14(4), pages 1-17, April.
    5. Mengyao Li & Hongxia Luo & Zili Qin & Yuanxin Tong, 2023. "Spatial-Temporal Simulation of Carbon Storage Based on Land Use in Yangtze River Delta under SSP-RCP Scenarios," Land, MDPI, vol. 12(2), pages 1-18, February.
    6. Yuhua Jiao & Yuhui Wang & Chenghong Tu & Xuenan Hou & Chunjuan Lyu & Xiang Fan & Lu Xia, 2024. "Spatiotemporal Evolution and Future of Carbon Storage in Resource-Based Chinese Province: A Case Study from Shanxi Using PLUS–InVEST Model Prediction," Sustainability, MDPI, vol. 16(11), pages 1-25, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jlands:v:14:y:2025:i:7:p:1442-:d:1699003. 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.