Development of a Python-Based Computational Algorithm to Calculate the Aridity Index. Case Study: North Pacific Basin

Arid regions cover more than half of the Mexican territory and are increasingly affected by climate variability and anthropogenic pressures. This study aims to develop a Python-based computational algorithm that automates the calculation of the Aridity Index (AI), facilitating the classification of arid regions in the North Pacific Hydrological Administrative Region. UNEP's AI method was used, integrating satellite-derived precipitation and potential evapotranspiration data. The algorithm was tested for the years 2000,2010, and 2023, and results show a significant increase in semi-arid regions, from 18.7 % to 40.1 % of the total area. In contrast, subhumid and humid areas have decreased notably. The tool enables reproducible, scalable aridity mapping and offers a basis for regional planning. All code and instructions are available at https://github.com/Norsuiza/ARCPYIA.git.

• Publication year

  2025

• Venue

  2025 13th International Conference in Software Engineering Research and Innovation (CONISOFT)

• Publication date

  2025-10-27

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/CONISOFT66928.2025.00015
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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