Evaluation of Regression Analysis and Neural Networks to Predict Total Suspended Solids in Water Bodies from Unmanned Aerial Vehicle Images

Tainá T Guimarães,Eniuce M Souza,Emilie C Koste,Luiz Gonzaga,Maurício R Veronez,Diego Brum,Frederico F Mauad

doi:10.3390/su11092580

Tainá T Guimarães, Eniuce M Souza + Show 5 more

Open Access

https://doi.org/10.3390/su11092580

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Abstract

The concentration of suspended solids in water is one of the quality parameters that can be recovered using remote sensing data. This paper investigates the data obtained using a sensor coupled to an unmanned aerial vehicle (UAV) in order to estimate the concentration of suspended solids in a lake in southern Brazil based on the relation of spectral images and limnological data. The water samples underwent laboratory analysis to determine the concentration of total suspended solids (TSS). The images obtained using the UAV were orthorectified and georeferenced so that the values referring to the near, green, and blue infrared channels were collected at each sampling point to relate with the laboratory data. The prediction of the TSS concentration was performed using regression analysis and artificial neural networks. The obtained results were important for two main reasons. First, although regression methods have been used in remote sensing applications, they may not be adequate to capture the linear and/or non-linear relationships of interest. Second, results show that the integration of UAV in the mapping of water bodies together with the application of neural networks in the data analysis is a promising approach to predict TSS as well as their temporal and spatial variations.

Highlights

The typical methodology for investigating water quality involves collecting water samples directly from various locations and laboratory analyses
The results of the laboratory analyses were satisfactory for the research and compatible with prior knowledge of the water quality in the study area and analysis of the spatial behavior of these parameters, which would later be compared with the unmanned aerial vehicle (UAV) images
Through analysis of the response that the sensor on board the UAV collected in the regions of visible and near infrared, it was possible to model the concentration of optically active compounds, such as suspended solids, and generate maps that allowed for their temporal monitoring and spatial analysis at the study site

Summary

Introduction

The typical methodology for investigating water quality involves collecting water samples directly from various locations and laboratory analyses. The results showed a significant improvement in the prediction of suspended solids data in the study area through the use of ANN in place of the simple and multiple linear and non-linear investigated RA.

Results

Conclusion