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Vol. 18 No. 2 (2024)
Horticultural Excellence: Innovations in Quality, Technology, and Sustainability

Other species section

Determining of variables influencing soil organic carbon content of PNR-Cortadera paramo (Colombia) via remote sensing

https://doi.org/10.17584/rcch.2024v18i2.17464

Published 2024-05-01

  • Pablo César Serrano-Agudelo
    • ,
  • Luis Joel Martínez-Martínez
    • ,
  • Pablo Antonio Serrano-Cely
    • ,
  • Adriana Bolívar-Gamboa
    • ,
  • Diego Fernando Moreno-Pérez

Pablo César Serrano-Agudelo
Unidad de Planificación Rural Agropecuaria, Bogota (Colombia)

Luis Joel Martínez-Martínez
Universidad Nacional de Colombia, Facultad de Ciencias Agrarias, Bogota (Colombia)

Pablo Antonio Serrano-Cely
Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias Agropecuarias, Grupo de investigación GIPSO, Tunja (Colombia)

Adriana Bolívar-Gamboa
Investigador Independiente, Tunja (Colombia)

Diego Fernando Moreno-Pérez
Investigador Independiente, Tunja (Colombia)

Estimation of soil organic carbon at 15 to 30 cm depth. Source: P.C. Serrano-Agudelo

Abstract

The soil organic carbon (SOC) content under climate change scenarios is essential, especially in areas of difficult access such as the high-altitude Tropical paramos. This study aimed to correlate the digital elevation model (DEM) derivatives, spectral indices from Sentinel-1 and Sentinel-2, and WorldClim data with in situ SOC content in the PNR-Cortadera paramo (Boyaca, Colombia). Based on 169 soil samples collected at two depths (0-15 and 15-30 cm) organic carbon was determined using the Walkley-Black method. SOC contents ranged from 25 to 200 t HA-1 at 0-15 cm and from 33 to 466 t ha-1 at 15-30 cm. Altitude, temperature, NDVI, TWI0-15 cm, MRVBF, LS factor0-15 cm and VH band polarization showed the highest correlations and the lowest variance inflation factor. The highest SOC contents are located in the central and southern area of the paramo due to the higher altitude, greater precipitation and presence of vegetation cover.

Keywords

Soil recognition, High tropics, Climate change, Carbon dioxide capture and storage, Remote sensing

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