Paper
25 October 2010 Quantitative and qualitative coastal water quality parameters monitoring using field data and aerial photography: Porto (Portugal) beaches
Ana Teodoro, Joaquim Pais-Barbosa, Francisco Piqueiro, Ricardo Aguiar
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Abstract
Under the scope of the "Blue Flag" project, a field campaign in order to collect water samples and a photogrammetric survey were performed at the urban seashore beaches of Porto, in August of 2008. Several water quality parameters were measured in different stations, following the European Directive 2006/7/CE. However, only 14 stations appear in the area covered by the aerial photographs. Multiple linear regressions were established in order to estimate the relationship between the DNs and three different water quality parameters (WQP). All the established models were found to be statistically significant and can be used to explain a considerable part of the data variability (R2>66%). A qualitative analysis was also performed in order to identify hydromorphologic features/patterns and correlate them with several WQP. The aerial photographs were classified in 6 classes (beach, beachface, breaking zone, rocks, sediments and sea). The maximum likelihood classifier presented the best performance. Analyzing the results in a GIS environment, it is clear that: for coliforms parameter the highest values appear near the mouth of urban small rivers (beach and beachface); for turbidity the highest values are located in the sediments class; and for the dissolve oxygen the highest values are located in areas with higher dynamics (breaking zone and beachface).
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Ana Teodoro, Joaquim Pais-Barbosa, Francisco Piqueiro, and Ricardo Aguiar "Quantitative and qualitative coastal water quality parameters monitoring using field data and aerial photography: Porto (Portugal) beaches", Proc. SPIE 7831, Earth Resources and Environmental Remote Sensing/GIS Applications, 78311M (25 October 2010); https://doi.org/10.1117/12.864568
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KEYWORDS
Photography

RGB color model

Oxygen

Statistical analysis

Image classification

Data modeling

Geographic information systems

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