Tecnologías geoespaciales para mapear el capital natural y promover empleo agropecuario sostenible en México

Ariel Vázquez-Elorza

doi:10.55965/setp.5.10.a1

Authors

Ariel Vázquez-Elorza Universidad Tecnológica del Valle de Toluca, Toluca, Estado de México, México https://orcid.org/0000-0002-6710-8935

DOI:

https://doi.org/10.55965/setp.5.10.a1

Keywords:

natural capital index, population employed in the primary sector, geospatial mapping, spatial autocorrelation

Abstract

Context. The use of natural capital and the distribution of employment in agriculture and livestock are unequal among Mexican regions. Some of them concentrate on ecological wealth and the employed population (rural-urban), while others show environmental degradation or underutilization of labor.

Problem. There is a lack of research that combines ecological and labor indicators in geospatial maps to support informed decision making. Are there significant spatial patterns between the Natural Capital Index (NCI) and the Principal Economic Location Quotient (PELQ) that allow identifying priority areas for sustainable development?

Purpose. This study analyzes the spatial patterns between natural capital and agricultural employment from a multidisciplinary approach that integrates environmental economics, economic geography, and spatial analysis in Mexico. It seeks to generate innovative knowledge aligned with the 2030 Agenda and the SDGs (8, 13, and 15). It is framed within social and organizational innovation according to the Oslo Manual. It promotes territorial sustainability through interaction between disciplines.

Methodology. This research is quantitative, non-experimental, and exploratory-explanatory, based on spatial and statistical analyses using 2021 secondary census and aggregated data. A geospatial database was built from official environmental and socioeconomic sources. Moran’s binomial index and LISA analysis were applied in R® to identify spatial clusters of consistency between ICN and CLEp, with statistical significance at the 95% confidence level (p ≤ 0.05).

Theoretical and practical findings. Significant positive associations were found in a total of 73 municipalities. High clustering was observed in the Northeast, Central and Southeast regions. The value of natural capital as a productive asset and the usefulness of spatial analyses to guide public policies were confirmed.

Originality. This study integrates environmental and socioeconomic variables from a spatial perspective to generate new applicable knowledge.

Conclusions and limitations. This study proposes an interdisciplinary innovation in territorial planning by integrating environmental and labor variables using spatial tools. Future research should integrate climate and institutional data to improve sustainable policy making.

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Author Biography

Ariel Vázquez-Elorza, Universidad Tecnológica del Valle de Toluca, Toluca, Estado de México, México

Research Professor at the Universidad Tecnológica del Valle de Toluca, Toluca, Estado de México, México

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