Dávila-Cisneros et al. (2026) Measuring Land Cover Changes in a Mining Area in Mexico Using Remote Sensing and Machine Learning

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Land
• Year: 2026
• Date: 2026-09-29
• Authors: Saúl Dávila-Cisneros, Ana Gabriela Castañeda-Miranda, Erick Dante Mattos-Villarroel, Víktor I. Rodríguez-Abdalá, Carlos Francisco Bautista-Capetillo, Cruz Octavio Robles Rovelo, Dania Isaura Pasillas-Pasillas, Lorena Ceballos-Pérez, Alejandra Noemí López-Díaz, Luis Alberto Flores Chaires
• DOI: 10.3390/land15101826

Research Groups

• Instituto Nacional de Investigaciones Forestales y Agropecuarias (INIFAP)
• Universidad Autónoma Metropolitana (UAM)

Short Summary

This study proposes a methodology for identifying the best algorithm and data combination to measure land cover changes induced by open-pit mining in Mexico, using remote sensing techniques with multi-temporal Landsat 5 and 8 satellite imagery.

Objective

• Investigate the most accurate method for measuring land cover changes caused by open-pit mining in Mexico

Study Configuration

• Spatial Scale: Regional scale (Mexico)
• Temporal Scale: Multi-temporal (using data from different years)

Methodology and Data

• Models used: Spectral Angle Mapping (SAM) algorithm, supervised classification with machine learning algorithms
• Data sources: Landsat 5 and 8 satellite imagery

Main Results

• The SAM algorithm combined with bands 6, 5, and 4 yielded the best results, with an accuracy of 85.16% and a Kappa coefficient of 0.79.
• Land cover changes showed an increase in water body surface area (556.83 ha), mining cover (1729.35 ha), infrastructure (2.61 ha), and bare soil (1488.15 ha), while also showing a loss of soil (2372.49 ha), scrubland (1444.59 ha), and vegetation (9.45 ha).

Contributions

• This study contributes to the development of sustainable management strategies for open-pit mining by providing an accurate method for measuring land cover changes.

Funding

• This research was funded by CONACYT (Project number: XXXXXXX)

Citation

@article{DávilaCisneros2026Measuring,
  author = {Dávila-Cisneros, Saúl and Castañeda-Miranda, Ana Gabriela and Mattos-Villarroel, Erick Dante and Rodríguez-Abdalá, Víktor I. and Bautista-Capetillo, Carlos Francisco and Rovelo, Cruz Octavio Robles and Pasillas-Pasillas, Dania Isaura and Ceballos-Pérez, Lorena and López-Díaz, Alejandra Noemí and Chaires, Luis Alberto Flores},
  title = {Measuring Land Cover Changes in a Mining Area in Mexico Using Remote Sensing and Machine Learning},
  journal = {Land},
  year = {2026},
  doi = {10.3390/land15101826},
  url = {https://doi.org/10.3390/land15101826}
}