SciELO - Scientific Electronic Library Online

 
vol.43 issue3Near-Infrared Spectroscopy: Assessment of Soil Organic Carbon Stock in a Colombian OxisolLeachate Treatment via TiO2/UV Heterogeneous Photocatalysis: A Multiple Polynomial Regression Model author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Ingeniería e Investigación

Print version ISSN 0120-5609

Abstract

CAMARGO-ROA, Cristopher E. et al. Identification of Eroded and Erosion Risk Areas Using Remote Sensing and GIS in the Quebrada Seca watershed. Ing. Investig. [online]. 2023, vol.43, n.3, pp.1-.  Epub Apr 25, 2024. ISSN 0120-5609.  https://doi.org/10.15446/ing.investig.105003.

The aim of this research was to identify eroded areas and areas at risk of erosion (EAER) as indicators of soil degradation by water erosion in a semiarid watershed of the Venezuelan Andes in 2017. To this effect, remote sensing techniques and geographic information systems (GIS) were used, focusing on spectral reflectance data from a satellite image, given the absence of continuous pluviographic information and data on soil properties in developing countries. This methodology involved estimating the potential water erosion risk (PWER) and mapping eroded and erosion risk areas (EAER) based on calculating the spectral Euclidean distance to bare soils and a remote sensing technique, which was selected via linear regression. Receiver operating characteristics (ROC) curves were determined to define classification thresholds, which were validated by means of a supervised classification and associated to PWER values. The main results indicate that EAER1 identified more eroded areas with bare soils (229,77 ha) as opposed to EAER2 (195,57 ha). Similarly, it was evident that the first alternative was more successful that the second (sum of the first three principal components). The PWER analysis, in addition to the erosion mapping developed and other data and criteria, such as minimum area size of interest, could help to consider necessary soil conservation measures.

Keywords : spectral Euclidean distance; vegetation indices; principal components analysis; maximum likelihood.

        · abstract in Spanish     · text in English     · English ( pdf )