Evolución de la vegetación de un bosque de colina baja aplicando sensores remotos durante el periodo 2019-2023, distrito de Mazán, Loreto. 2024

• Autor: Pinedo Yudichi, Rocian Conny
• Formato: tesis de grado
• Fecha de Publicación: 2025
• Institución: Universidad Nacional De La Amazonía Peruana
• Repositorio: UNAPIquitos-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.unapiquitos.edu.pe:20.500.12737/12065
• Enlace del recurso: https://hdl.handle.net/20.500.12737/12065
• Nivel de acceso: acceso abierto
• Materia: Índice de vegetación; Sensores ópticos; Imágenes satelitales; Bosque tropical; https://purl.org/pe-repo/ocde/ford#4.01.02

The evolution of vegetation in a low hill forest was analyzed using remote sensing during the period from 2019 to 2023 in the district of Mazán, Loreto. For this purpose, a quantitative and descriptive methodology based on NDVI and EVI vegetation indices was used. The study shows a general trend of decrease in the Normalized Difference Vegetation Index (NDVI), and also a drop in the Enhanced Vegetation Index (EVI), although the latter is less pronounced. Both EVI and NDVI exhibit considerable variability between years. The coefficient of determination R²=0,058 suggests that only 5,8% of the variability in NDVI is related to the variable “x”, indicating a weak connection. However, the very low p-value shows that this relationship is statistically significant (<0,05). The regression equation, y=2,58,3×10⁵x, shows a slight reduction in NDVI with increasing “x”. Similarly, the R²=0,063 indicates that only 6,3% of the variability of EVI is due to the variable “x”, also suggesting a weak relationship. Despite this, the low p-value indicates that the relationship is statistically significant (<0,05). The regression equation, y=3,15-0,000014x, reflects a slight decrease in EVI with increasing “x”.