Methodology to estimate lake turbidity using object- oriented classification of multispectral images

Authors

  • Carlos Quintana Sotomayor Departamento de Conservación y Protección de Recursos Hídricos Dirección General de Aguas Ministerio de Obras Públicas
  • Mario Lillo Saavedra Facultad de Ingeniería Agrícola Universidad de Concepción
  • Consuelo Gonzalo Martín Departamento de Arquitectura y Tecnología de Sistemas Informáticos Facultad de Informática Universidad Politécnica de Madrid
  • Juan Alberto Barrera Berrocal Facultad de Agronomía Universidad de Concepción

Keywords:

lake, turbidity, object-based image analysis, texture, environmental remote sensing

Abstract

This work implements an object-oriented multispectral image classification to quantify turbidity levels in the Grande Lagoon of San Pedro (Chile) (36° 51' S, 73° 06' W). The first step in this methodology is multiscale segmentation; then, to characterize the lagoon cover, different classes are defined according to the selection of training areas associated with data recorded in situ and texture descriptors. In the last stage, the accuracy of each test is evaluated using the Global Membership (PG) and the Global Stability (EG) indices proposed by this work and the results underwent a refinement process. The proposed methodology resulted in the creation of turbidity maps of the Grande Lagoon of San Pedro, Chile, where 86% of the lagoon surface is associated with a turbidity level between 1.0 and 1.7 NTU, indicating that the turbidity of this lagoon is low and homogeneous as compared to other lentic systems studied.

Published

2012-11-15

How to Cite

Quintana Sotomayor, C., Lillo Saavedra, M., Gonzalo Martín, C., & Barrera Berrocal, J. A. (2012). Methodology to estimate lake turbidity using object- oriented classification of multispectral images. Tecnología Y Ciencias Del Agua, 3(4), 143–150. Retrieved from https://revistatyca.org.mx/index.php/tyca/article/view/265

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