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Structural attributes estimation in a natural tropical forest fragment using very high-resolution imagery from unmanned aircraft systems
Estimación de atributos estructurales en un fragmento de bosque tropical natural utilizando imágenes de muy alta resolución obtenidas con sistemas aéreos no tripulados
DOI:
https://doi.org/10.15446/esrj.v26n1.95405Keywords:
UAS imagery, Crown delineation, Forest height, Canopy Height Models (CHM), REDD (en)Imágenes UAS, delineación de copa, altura del bosque, modelos de altura del dosel (CHM), REDD (es)
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Structural attributes are fundamental biophysical parameters of forest, useful for ecological and environmental monitoring and planning. Canopy height is an important input for the estimation of several biophysical parameters as aboveground biomass and carbon stock, and can be related with forest degradation, deforestation, and emission reduction. Thus, an accurate canopy height estimation is a crucial issue in climate change studies and REDD+ initiatives. VHR imagery from unmanned aircraft systems has been studied as a low cost mean for canopy height estimation at local scales, but the accuracy in the estimation is a factor that determines its utility. We evaluated the ability of VHR imagery from unmanned aircraft systems to derive structural attributes, specifically tree-crown area and height, in a natural tropical forest fragment located in the foothills of the Andes Mountains, in the humid tropical forests of the region known as Biogeographic Chocó, South America. The region is one of the most biodiverse areas of the world and has a high level of endemism, but it is also at higher risk of natural-resource loss. We used a structure from motion approach to derive canopy height models of the forest fragment, and we applied mean-shift algorithms to identify single tree crowns. The accuracy assessment was performed using reference data derived from field campaigns and visually interpretation of VHR imagery. The estimated root-mean-square error of the population of vertical errors for the canopy height model was 3.6 m. The total accuracy for delineating tree crowns was 73.9%. We found that using VHR imagery, specific trees and canopy gaps can be identified and easily monitored, which is an important step in conservation programs. We also discuss the usefulness of these findings in the context of fragmented forests and the tradeoffs between the price of a LIDAR system and the accuracy of this approach.
Los atributos estructurales son parámetros biofísicos fundamentales de un bosque, útiles para el monitoreo y la planificación ecológica y ambiental. La altura del dosel de un árbol es un insumo importante para la estimación de varios parámetros biofísicos como la biomasa aérea y las reservas de carbono, y puede relacionarse con la degradación forestal, la deforestación y la reducción de emisiones. Por lo tanto, una estimación precisa de la altura del dosel es un tema crucial en los estudios de cambio climático y las iniciativas REDD+. Las imágenes VHR de sistemas de aeronaves no tripuladas se han estudiado como un medio de bajo costo para la estimación de la altura del dosel a escalas locales, pero la precisión en su estimación es un factor que determina su utilidad. Se evaluó la capacidad de las imágenes VHR de los sistemas de aeronaves no tripuladas para derivar atributos estructurales, específicamente el área y la altura de las copas de los árboles, en un fragmento de bosque tropical natural ubicado en las estribaciones de la Cordillera de los Andes, en los bosques tropicales húmedos de la región conocida como Chocó Biogeográfico, Sudamérica. La región es una de las áreas con mayor biodiversidad del mundo y tiene un alto nivel de endemismo, pero también tiene el mayor riesgo de pérdida de recursos naturales. Se usó un enfoque de estructura a partir de movimiento para derivar modelos de altura del dosel del fragmento de bosque, y se aplicaron algoritmos de desplazamiento medio para identificar las copas de árbol. La evaluación de la precisión se realizó utilizando datos de referencia derivados de campañas de campo e interpretación visual de imágenes VHR. El error cuadrático medio estimado de la población de errores verticales para el modelo de altura del dosel fue de 3,6 m. La precisión total para delinear las copas de los árboles fue del 73,9%. Se encuentra que utilizando imágenes VHR, se pueden identificar y monitorear fácilmente árboles específicos y brechas, lo cual es un paso importante en los programas de conservación. También se discute la utilidad de estos hallazgos en el contexto de bosques fragmentados y las compensaciones entre el precio de un sistema LIDAR y la precisión de este enfoque.
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