Resumen

PEREA-ARDILA, Mauricio Alejandro; ANDRADE-CASTANEDA, Hernán J.  y  SEGURA-MADRIGAL, Milena A.. Aboveground biomass and carbon estimation in the high-Andean forests of Boyacá, Colombia using remote sensing. Case study: Santuario de Fauna y Flora Iguaque. Rev. cartogr. [online]. 2021, n.102, pp.99-123.  Epub 14-Mar-2022. ISSN 2663-3981.  https://doi.org/10.35424/rcarto.i102.821.

Remote sensing is very important for monitoring the natural forests. In this study was estimated the aboveground biomass (AGB) and carbon (C) with remote sensing in the Santuario de Fauna y Flora Iguaque (SFFI) in Boyacá, Colombia. A total of 23 temporal sampling plots (TSP) of 250 m2 each were installed and all trees with diameter at breast height (dbh) ≥ 10 cm were measured. The real AGB was estimated using an allometric equations for species from high-Andean forests and was multiplied for 0,5 to estimate C. Only nine TSP fulfilled the criterion of a minimal tree density of 30 trees per plot, these were correlated with three vegetation indexes, Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index and Enhanced Vegetation Index (NDVI, SAVI and EVI) derived from two Landsat 8 images from dry and rainy season in 2016. A model to estimate AGB based on a vegetation index was developed in order to build carbon maps. The best model was based on NDVI in the dry season (adjusted R2 = 0.79 and root of mean square error of 17.1 Mg/ha). The forests in the SFFI stored a mean of 36.6 Mg C/ha in AGB. Also, was accumulated 163 Gg CO2e in the forests the SFFI that correspond emissions evited at the atmosphere. This case study was presented as the first exercise for estimated AGB and C with remote sensing tools for forest monitoring in protected areas of environmental importance and will serve as a reference for future investigations for the satellite monitoring of the region’s natural forests.

Palabras llave : Forest ecosystem; monitoring; satellite images; vegetation in-dexes; Landsat 8.

        · resumen en Español     · texto en Español     · Español ( pdf )