On the use of artificial neural networks in remotely piloted aircraft acquired images for estimating reservoir’s bathymetry

Andrade, Laura Coelho de; Ferreira, Ítalo Oliveira; Silva, Arthur Amaral e; Teixeira, Victória Gibrim; Santos, Felipe Catão Mesquita

doi:10.1590/s1982-21702022000100006

Bol. Ciênc. Geod.

2022

DOI: 10.1590/s1982-21702022000100006

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On the use of artificial neural networks in remotely piloted aircraft acquired images for estimating reservoir’s bathymetry

Laura Coelho de Andrade

Ítalo Oliveira Ferreira

Arthur Amaral e Silva

et al.

Abstract: How to cite this article: ANDRADE, L.C. et al. On the use of artificial neural networks in remotely piloted aircraft acquired images for estimating reservoir's bathymetry.

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2024

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Comparative Analysis for Volume Estimation in Small Dams Using Conventional Bathymetry and Remote Sensing

Pacheco,

Orlando Junior,

Alencar

2024

GEOFRONTER

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The efficient management of water resources is a fundamental prerogative to guarantee sustainable development, especially in regions dependent on small dams to retain and dispose of water. These structures play an essential role in various activities, from providing drinking water to supporting agriculture. Within the scope of water management, the precise determination of the volume of water retained in dams is a critical aspect, directly influencing decisions related to the sustainable use of these resources. This study aimed to carry out a comparative analysis between conventional bathymetry and remote sensing, aiming to evaluate their accuracy in determining the accumulated volume of water in small dams. It was observed that both remote sensing methods II and III presented an overestimation of the volume accumulated in dams compared to conventional bathymetry. Method II demonstrated superior precision, with an error varying between 3.22% and 30.22%, which decreased as the area increased. On the other hand, method III presented an error ranging between 20.68% and 43.12%, following a similar pattern to that of method II in relation to the increase in area. It is concluded that remote sensing presents itself as a valid approach for estimating the water surface and accumulated volume, especially in small dams, being useful for preliminary and environmental studies in areas with low sediment deposition and no vegetation invasion, since conventional bathymetry often proves to be costly and logistical, especially in situations where access and size are challenging.

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Comparative Analysis for Volume Estimation in Small Dams Using Conventional Bathymetry and Remote Sensing

Pacheco,

Orlando Junior,

Alencar

2024

GEOFRONTER

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On the use of artificial neural networks in remotely piloted aircraft acquired images for estimating reservoir’s bathymetry

Abstract: How to cite this article: ANDRADE, L.C. et al. On the use of artificial neural networks in remotely piloted aircraft acquired images for estimating reservoir's bathymetry.

Cited by 1 publication

References 14 publications

Comparative Analysis for Volume Estimation in Small Dams Using Conventional Bathymetry and Remote Sensing

Comparative Analysis for Volume Estimation in Small Dams Using Conventional Bathymetry and Remote Sensing

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