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Identification of Eroded and Erosion Risk Areas Using Remote Sensing and GIS in the Quebrada Seca watershed
Identificación de áreas erosionadas y en riesgo de erosión mediante percepción remota y SIG en la microcuenca Quebrada Seca
DOI:
https://doi.org/10.15446/ing.investig.105003Keywords:
spectral Euclidean distance, vegetation indices, principal components analysis, maximum likelihood (en)distancia espectral euclidiana, índices de vegetación, análisis de componentes principales, máxima verosimilitud (es)
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 mini-mum area size of interest, could help to consider necessary soil conservation measures.
El objetivo de esta investigación fue identificar áreas erosionadas y en riesgo de erosión (AERE) como indicadores de degradación de suelos por erosión hídrica en una cuenca semiárida de los Andes venezolanos en el año 2017. Para ello, se emplearon técnicas de percepción remota y sistemas de información geográfica (SIG), enfocándose en los datos espectrales de reflectancia de una imagen satelital, dada la ausencia de información pluviográfica continua y datos de propiedades del suelo en países en vías de desarrollo. Esta metodología implicó la estimación del riesgo potencial de erosión hídrica (RPEH) y la generación de cartografía de áreas erosionadas y en riesgo (AEER) a partir del cálculo de distancia espectral euclidiana a suelos desnudos y de una técnica de percepción remota seleccionada mediante regresión lineal. Se determinaron curvas ROC (características operativas del receptor) para definir umbrales de clasificación, los cuales fueron validados mediante una clasificación supervisada y asociados a valores de RPEH. Los resultados principales indican que EAER1 identificó más áreas erosionadas con suelos desnudos (229,77 ha) a diferencia de EAER2 (195,57 ha). De igual modo, se evidenció que la primera alternativa tuvo mayores aciertos en contraste con la segunda (sumatoria de los tres primeros componentes principales). El análisis de RPEH, además de las cartografías de erosión desarrolladas y otros datos y criterios como el tamaño del área mínima de interés, podrían ayudar a considerar medidas necesarias en cuanto a conservación de suelos.
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1. Cristopher Camargo Roa, Carlos Eduardo Pacheco Angulo, Tatiana Gómez-Orgulloso, Roberto López-Falcón, Sergio Alberto Monjardín-Armenta. (2025). Identificación de áreas erosionadas y en riesgo de erosión utilizando imágenes Landsat 8 OLI y Sentinel-2, procesamiento digital y SIG. Revista de Ciencias, 27(2) https://doi.org/10.25100/rc.v27i2.13572.
2. Muralitharan Jothimani, Prafulla Kumar Panda, Leulalem Shano, Ephrem Getahun, Zerihun Dawit. (2025). Remotely Sensed Rivers in the Age of Anthropocene. Environmental Science and Engineering. , p.115. https://doi.org/10.1007/978-3-031-82311-4_6.
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Copyright (c) 2023 Cristopher Edgar Camargo Roa, Carlos E. Pacheco-Angulo, Sergio A. Monjardin-Armenta, Roberto López-Falcón, Tatiana Gómez-Orgulloso
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