Surface Water Change Detection via Water Indices and Predictive Modeling Using Remote Sensing Imagery: A Case Study of Nuntasi-Tuzla Lake, Romania

Şerban, Cristina; Maftei, Carmen; Dobrica, Gabriel

doi:10.3390/w14040556

Cited by 24 publications

(10 citation statements)

References 29 publications

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“…Serban et al [15] implemented a model to detect the change in surface water. This case study is taken from a lake named Nuntasi-Tuzla from Romania.…”

Section: Literature Surveymentioning

confidence: 99%

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ECDSA-Based Water Bodies Prediction from Satellite Images with UNet

Rupa

Gadamsetty

et al. 2022

Water

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The detection of water bodies from satellite images plays a vital role in research development. It has a wide range of applications such as the prediction of natural disasters and detecting drought and flood conditions. There were few existing applications that focused on detecting water bodies that are becoming extinct in nature. The dataset to train this deep learning model is taken from Kaggle. It has two classes, namely water bodies and masks. There is a total of 2841 sentinel-2 satellite images with corresponding 2841 masks. Additionally, the present work focuses on using UNet, Tensorflow to detect the water bodies. It uses a Nadam optimizer to reduce the losses. It also finds best-optimized parameters for the activation function, a number of nodes in each layer. This proposed model achieves integrity by embedding a security feature Elliptic Curve Digital Signature Algorithm (ECDSA). It generates a digital signature for the predicted area of water bodies which helps to secure the key and the detected water bodies while transmitting in a channel. Thus, the proposed model ensures the performance accuracy of 94% which can also work the same for edge detection, detection in blurred and low-resolution images. The model is highly robust.

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“…Serban et al [15] implemented a model to detect the change in surface water. This case study is taken from a lake named Nuntasi-Tuzla from Romania.…”

Section: Literature Surveymentioning

confidence: 99%

“…Nadam is the best optimization technique, which is an improved version of Adam. Gradient descent is the basic optimization technique further versions like Adam, Nadam were introduced to remove flaws in the Gradient Descent [15]. NAG momentum is used in the Nadam optimizer.…”

Section: Module 4: Nadam Optimizermentioning

confidence: 99%

ECDSA-Based Water Bodies Prediction from Satellite Images with UNet

Rupa

Gadamsetty

et al. 2022

Water

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show abstract

“…5 indices NDVI, NDWI, MNDWI, WNDWI and WRI were used to check the changes. The results showed that Landsat images were evaluated to have a higher kappa coefficient and overall accuracy than MADIS images due to their high spatial resolution [1]. Also, in 2022, using remote sensing and GIS methods, the coastal wetlands in Burolus Lake in Egypt were investigated.…”

Section: Introductionmentioning

confidence: 99%

RS-Based Assessment: Spatial-Temporal Changes in Water Basins of Tar and Havir Lakes

Ashinfar

Vahidi

Hatamzadeh

et al. 2023

IJECC

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In recent studies several factors such as landslides, volcanoes, glaciers, tectonic factors and karst forms such as flooded pulleys resulting of karsts development cause the formation of lakes in mountainous areas. The mountain lakes of Iran, including Tar and Havir lakes, are mainly formed by landslides. In this research investigation of water basins changes for (Tar and Hoyer lakes) by remote sensing method in the period from 2013 to 2022 have been done. It has been tried to select appropriate Landsat 8 satellite images in terms of cloud cover and image quality from the time when the lakes are full of water. The training and testing data were selected with the same distribution in the whole image to make the classifications more accurate. After estimate kappa coefficient and overall accuracy for all kind of supervised and unsupervised methods, the results obtained from the two classification methods of maximum likelihood and support vector machine with linear kernel from Tar and Havir lakes, the conclusion was that the classification method of support vector machine with linear kernel have better distinguish land and water areas and it is the best method for classifying water basins located in mountainous areas. The amount of water in Tar and Havir lakes had been increased from 2013 to 2017but in 2018, the water area of both lakes decreased significantly, and in 2019, the largest water area for the lakes was observed and calculated. In 2020, there is no big change in the water area of the two lakes, and from 2020 to 2022, the amount of water in the two lakes is decreasing.

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“…15 Spectral water indices are more accurate compared to other methods such as classification techniques, or linear unmixing. 7,16,17 Among the spectral indices of water most used in the literature, in 18 the authors developed the Normalized Difference Water Index (NDWI) using green and near-infrared (NIR) spectral ranges to maximize water characteristics. 18 replaced NIR with shortwave infrared (SWIR) and derived the modified NDWI (MNDWI).…”

Section: Introductionmentioning

confidence: 99%

A timely efficient and robust multi-source and multitemporal routine for determination of surface water area in large water reservoirs

Facco¹,

Guasselli²,

Zanotta³

et al. 2021

IJH

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The Brazilian electrical system has gone through conflicts resulting from recent water crisis. Timely indicators are crucial for properly acting in order to mitigate upcoming problems. In this work we evaluate the potential of Reservoir Water Level (RWL) and Surface Water Area (SWA) indices for estimating physical parameters in the management of water resources. We tested Landsat 8 (L8) and Sentinel-2 (S2) optical image time series, Sentinel-1 (S1) radar, spectral indices and validation with Jason-3 (J3) altimetry. The methodology was developed in the Google Earth Engine (GEE) operational routine, which streamlined the SWA mapping. The best results were between S2 and NDWI and threshold 0, with R² = 0.88 and RMSE of 11.59 km². As main limitations, we highlight the cloud cover for the optical images, which can decrease the temporal sampling, as well as the SAR backscatter response in the presence of bare soil and aquatic vegetation. We could attest that periodic remote sensing data are particularly useful for timely updating spatial variations of RWL and SWA in reservoirs.

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Surface Water Change Detection via Water Indices and Predictive Modeling Using Remote Sensing Imagery: A Case Study of Nuntasi-Tuzla Lake, Romania

Cited by 24 publications

References 29 publications

ECDSA-Based Water Bodies Prediction from Satellite Images with UNet

ECDSA-Based Water Bodies Prediction from Satellite Images with UNet

RS-Based Assessment: Spatial-Temporal Changes in Water Basins of Tar and Havir Lakes

A timely efficient and robust multi-source and multitemporal routine for determination of surface water area in large water reservoirs

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