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
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 m...
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2025-07-01
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| author | 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-Blanco |
| author_facet | 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-Blanco |
| author_sort | German Huayna |
| collection | DOAJ |
| description | 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<sup>2</sup> in 1984 to over 220.31 km<sup>2</sup> in 2023, with projections indicating continued growth to over 331.62 km<sup>2</sup> 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. |
| format | Article |
| id | doaj-art-bf1a0528c3474b47b8beeb5fcb067749 |
| institution | Kabale University |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj-art-bf1a0528c3474b47b8beeb5fcb0677492025-08-20T03:35:38ZengMDPI AGLand2073-445X2025-07-01147144210.3390/land14071442Historical 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 ModelGerman Huayna0Victor Pocco1Edwin Pino-Vargas2Pablo Franco-León3Jorge Espinoza-Molina4Fredy Cabrera-Olivera5Bertha Vera-Barrios6Karina Acosta-Caipa7Lía Ramos-Fernández8Eusebio Ingol-Blanco9Department of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, PeruDepartment of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, PeruDepartment of Civil Engineering, Jorge Basadre Grohmann National University, Tacna 23000, PeruLaboratory of Ecological Processes, Research Group of Arid Zones, Deserts and Climate Change (ADERIZA), Jorge Basadre Grohmann National University, Tacna 23000, PeruDepartment of Architecture, Jorge Basadre Grohmann National University, Tacna 23000, PeruDepartment of Geological Engineering-Geotechnics, Jorge Basadre National University, Tacna 2300, PeruFaculty of Mining Engineering, National University of Moquegua, Moquegua 18001, PeruDepartment of Architecture, Jorge Basadre Grohmann National University, Tacna 23000, PeruDepartament of Water Resources, Universidad Nacional Agraria La Molina, Lima 15024, PeruDepartment of Civil Engineering, New Mexico State University, Las Cruces, NM 88003, USAThe 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<sup>2</sup> in 1984 to over 220.31 km<sup>2</sup> in 2023, with projections indicating continued growth to over 331.62 km<sup>2</sup> 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.https://www.mdpi.com/2073-445X/14/7/1442land covercellular automataartificial neural networkspatiotemporal analysisecosystem conservation |
| spellingShingle | 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-Blanco 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 land cover cellular automata artificial neural network spatiotemporal analysis ecosystem conservation |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | land cover cellular automata artificial neural network spatiotemporal analysis ecosystem conservation |
| url | https://www.mdpi.com/2073-445X/14/7/1442 |
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