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Agrosilvicultura y Medioambiente Volumen 1, Número 1, 2023
zona de manglar siendo esta de vegetación
densa y los más bajos a cuerpos de agua y
suelos desnudos, ambos índices mostraron
un comportamiento similar en la diferencia-
ción de los tipos de cobertura y como indi-
cador de estado de vigor vegetativo, obte-
niendo los valores más altos para SAVI, no
obstante en investigaciones realizadas por
Gonzaga (2015), en su estudio de aplica-
ción de índices de vegetación (IV) derivados
de imágenes satelitales para análisis de co-
berturas vegetales en la provincia de Loja,
Ecuador, logra similar comportamiento con
respecto a los valores para NDVI y SAVI sien-
do los valores más bajos para SAVI y los más
altos para NDVI; correspondiendo los valo-
res más altos a áreas con menor densidad
vegetal y suelo desnudo, y, los valores más
altos a cobertura de pastos.
Sin embargo, investigaciones realizadas
por Sánchez. (2007), demostraron que los
dos (IV) presentan una capacidad discri-
minatoria de los modelos de combustible
bastante alta, porque de las 45 parejas de
modelos de combustibles, sólo reflejan es-
tadísticamente iguales 5 en NDVI y 7 en
SAVI, resulta bastante llamativo el hecho de
que sea el NDVI el que permite discriminar
más modelos de combustible, pese a ser el
índice de vegetación más sencillo y que no
intenta reducir el efecto del suelo. Esto pue-
de deberse al hecho de que en la zona de
estudio la mayor parte de las formaciones
vegetales presentan una densidad bastante
alta, que puede hacer innecesario el uso de
índices de vegetación más complejos.
Vani. & Ravibabu (2017) estima que en los
dos (IV) la cubierta forestal muestra valores
altos, donde la discrepancia de tendencia
para la cubierta forestal es similar en todos
los conjuntos de datos, el NDVI y SAVI con
0.5 muestran un valor alto, SAVI -0.9 elimina
el efecto de fondo del suelo y proporciona
los valores precisos para este tipo de sitios.
Con los inconvenientes encontrados apli-
cando los (IV) no se ha podido observar una
diferencia significativa en estos años.
Conclusiones
El determinar la cobertura del área de es-
tudio en la presente investigación permite
estimar que el 39,65% (23 ha) del manglar
está desprovisto de vegetación debido al
aumento progresivo de la urbanización y la
expansión de piscinas camaroneras.
Los índices de vegetación evaluados, NDVI
y SAVI derivados de imágenes del sensor
PLEIADES permitieron estimar el estado
vegetal de la cobertura de manglar en el
área de estudio, presentando una mínima
diferencia para cada cobertura, a su vez
permitieron caracterizar y discriminar los di-
ferentes tipos de coberturas, teniendo una
imperceptible diferenciación para ambos
índices.
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