Una revisión del uso de imágenes Sentinel-2 para el monitoreo de la cobertura boscosa a nivel global
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El presente trabajo tuvo como objetivo realizar una revisión sistemática del uso de imágenes Sentinel-2 para el monitoreo de la cobertura boscosa a nivel global, para lo cual se empleó el protocolo propuesto por Prisma 2009. La búsqueda de los artículos científicos publicados entre el 2015 y 2021 se realizó en las bases de datos: Scopus y Science Direct, analizándose un total de 65 artículos en los que se detalla los diferentes tipos de clasificadores utilizados para procesar las imágenes S-2, la exactitud temática lograda en la cartografía, así como el aumento, mantenimiento o retroceso de los bosques y sus principales causas a nivel mundial. Como resultados se encontró que Random Forest (RF) es el clasificador más utilizado para el procesamiento digital de las imágenes S-2, el cual logra en la mayoría de los casos una exactitud temática superior al 85%. En los trabajos multitemporales, se ha encontrado que la cobertura boscosa en Sudamérica y África se ha visto disminuida por actividades como la agricultura y ganadería. Mientras que, en algunos países asiáticos la cobertura boscosa se ha incrementado como consecuencia de la implementación de programas de reforestación y manejo forestal comunitario. Por lo que lo resultados sugieren que las imágenes Sentinel-2 presentan un enorme potencial para llevar a cabo el seguimiento continuo y sistemático de la pérdida o ganancia de los bosques en todo el planeta.
Ronald Hugo Puerta Tuesta, Universidad Nacional Agraria de la Selva, Tingo María, Perú
https://orcid.org/0000-0001-5777-7855
José Alberto Iannacone Oliver, Universidad Nacional Federico Villarreal, Lima, Perú.
https://orcid.org/0000-0003-3699-4732
Manuel Emilio Reategui Inga, Universidad Nacional Intercultural de la Selva Central Juan Santos Atahualpa, Perú.
https://orcid.org/0000-0002-5417-6509
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Aceptado 2023-09-28
Publicado 2023-10-20
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