Building a Methodological Reference Framework for Quantifying Tropical Deforestation with Remote Sensing

Ana Isabel Fernández-Montes de Oca, Adrián Ghilardi, Edith Kauffer, Jean Francois Mas, Víctor Sánchez-Cordero and José Alberto Gallardo-Cruz ()
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Ana Isabel Fernández-Montes de Oca: Departamento de Zoología, Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Adrián Ghilardi: Centro de Investigaciones en Geografia Ambiental, Universidad Nacional Autónoma de México, Morelia 58190, Mexico
Edith Kauffer: Centro de Investigaciones y Estudios Superiores en Antropología Social (CIESAS)-Sureste, San Cristobal de las Casa 29247, Mexico
Jean Francois Mas: Centro de Investigaciones en Geografia Ambiental, Universidad Nacional Autónoma de México, Morelia 58190, Mexico
Víctor Sánchez-Cordero: Departamento de Zoología, Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
José Alberto Gallardo-Cruz: Centro Transdisciplinar Universitario para la Sustentabilidad, Universidad Iberoamericana, Ciudad de México 01219, Mexico

Sustainability, 2025, vol. 17, issue 4, 1-18

Abstract: Deforestation is a major threat to the sustainability of natural resources. Thus, adequate estimates of deforestation are crucial for evaluating how sustainable programs are implemented. Still, there is controversy in estimating deforestation, as different estimates often produce contrasting or even conflicting results. It is known that variation in estimates depends on a wide diversity of variables that modify the methods for measuring deforestation, such as scale, types and complexity of vegetation, the definition used, and available inputs of information. This study developed a methodological tool to select the most suitable remote sensing method to measure deforestation in tropical forests. We conducted a systematic review of peer-reviewed publications quantifying deforestation with remote sensing and field data. The information was analyzed and synthesized to build a methodological framework of reference. The methodological and descriptive information of the selected publications served to construct four decision rules (excluding factors, classifier options, elements for choosing a classification, and additional information) for selecting a method for quantifying deforestation. We tested the functionality of this methodological framework of reference by quantifying the deforestation of tropical rainforests in southern Mexico. Based on the decision rules of the framework, two deforestation quantification classifiers were used in the study area (Maximum likelihood and spectral angle mapper (SAM)). We observed that Maximum likelihood had higher values of accuracy than SAM, although both values of accuracy were acceptable. This framework facilitates the selection of remote sensing methods for measuring deforestation by considering the characteristics of each study area and the available inputs. The use of this framework reduced the uncertainty in the estimates of deforestation by controlling a greater number of variables and provided a robust approach for adequately implementing sustainable programs in these threatened rainforests.

Keywords: land use land cover change; tree cover loss; decision support tool; estimates; uncertainty (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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