Methodology to estimate lake turbidity using object- oriented classification of multispectral images
Keywords:
lake, turbidity, object-based image analysis, texture, environmental remote sensingAbstract
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.Downloads
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By Instituto Mexicano de Tecnología del Agua is distributed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Based on a work at https://www.revistatyca.org.mx/. Permissions beyond what is covered by this license can be found in Editorial Policy.