Análisis temporal de la distribución de claros del dosel en bosques naturales: comparación de rodales manejados y no manejados mediante imágenes QuickBird y UltraCam-D
Resumen
Objetivo del estudio: Tiene como objetivo investigar y analizar los patrones de distribución temporal y espacial de los claros del dosel en masas forestales manejadas y no manejadas utilizando imágenes de teledetección de diferentes fuentes, enfatizando la relevancia de estos patrones en el contexto de los procesos naturales y las intervenciones humanas. Área de estudio: Rodales gestionados y no gestionados del Plan Forestal Dr. Bahramnia, bosque de Hircanian, provincia de Golestán, Irán. Material y métodos: Se utilizaron imágenes satelitales de alta resolución, incluidas imágenes aéreas digitales QuickBird (2007) y UltraCam-D (2011), para detectar espacios en el dosel. Este estudio empleó métodos de clasificación basados en píxeles, como los algoritmos Support Vector Machine (SVM) y Maximum Likelihood (ML), junto con métodos basados en objetos, incluidos el vecino más cercano (NN), el bosque aleatorio (RF), el árbol de decisión (DT) y Bayes, para clasificar y extraer espacios en el dosel. Los patrones de distribución espacial se analizaron utilizando el índice del vecino más cercano, la autocorrelación espacial y la agrupación basada en el tamaño de la brecha, empleando estadísticas globales de Getis-Ord y locales de Moran. Resultados principales: Los resultados indicaron que los métodos de clasificación basados en píxeles lograron una mayor precisión en el mapeo de áreas con y sin brechas, con el algoritmo ML alcanzando una precisión del 98,763% y un coeficiente Kappa de 0,974 en 2007, y el algoritmo SVM logrando una precisión del 98,899% y un coeficiente Kappa de 0,976 en 2011. El índice de vecino más cercano reveló una distribución espacial regular de las brechas tanto en áreas administradas como no administradas. se encuentra. El análisis de agrupamiento mostró patrones distintos para espacios pequeños, medianos y grandes, con rodales gestionados que exhiben agrupamiento y rodales no gestionados que muestran patrones aleatorios y regulares. Aspectos destacados de la investigación: Este estudio subraya la importancia de los datos de teledetección de alta resolución y los algoritmos de clasificación avanzados para mapear con precisión la dinámica de los claros del dosel, proporcionando información valiosa para el manejo forestal sostenible.
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