Quantifying water storage within the north of Lake Naivasha using sonar remote sensing and Landsat satellite data

Walker, David J.; Shutler, J. D.; Morrison, Edward H.J.; Harper, David M.; Hoedjes, J.C.B.; Laing, Chris

doi:10.1016/j.ecohyd.2021.07.011

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…In geological applications, Landsat series multispectral data are widely used in the fields of remote sensing lithology identification, geological tectonics interpretation, and mineralization and alteration information extraction due to its low economic cost, relatively high spectral resolution, and large coverage area. In this paper, Landsat 8 OLI data source is applied to process and analyse the lithological features of the acquired remote sensing data images [7,8] .…”

Section: Acquisition and Pre-processing Of Surface Lithology Remote S...mentioning

confidence: 99%

Automatic identification method of surface lithology based on remote sensing satellite data and machine learning

Wang

2024

Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024)

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Multi-source remote sensing data fusion could compensate for the lack of spatial or spectral resolution of single-source remote sensing images. In this paper, we took the rocky area as the research object and carried out a machine learning lithology classification study based on combining spatial features and spectral features, and proposed an automatic identification method of surface lithology based on limit learning and watershed segmentation. By comparing and analyzing typical machine learning algorithms, the combination of spectral features and spatial features was incorporated into the algorithm to form a set of high-precision lithology automatic identification methods. The experimental results showed that the method in this paper performed better than the traditional SVM classification method based on spectral features in terms of classification accuracy and Kappa coefficient, especially after the extreme learning fusion watershed segmentation algorithm.

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Section: Acquisition and Pre-processing Of Surface Lithology Remote S...mentioning

confidence: 99%

Automatic identification method of surface lithology based on remote sensing satellite data and machine learning

Wang

2024

Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024)

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“…Hence, this research aims to target the long-term climatic trends of the natural lakes of western Greece, Trichonis, Lysimacheia, Ozeros, and Amvrakia, using remote sensing water area estimations as the main water content indicator. The abovementioned choice, of the water area as an indirect index of water storage, is considered justified due to the converging conclusions of various studies towards the high correlation between water area and water storage timeseries [ 2 , 24 , 25 , 30 , 47 , 48 , 49 , 50 ]. Moreover, this research aims to analyse the simultaneous trends of importance to the water cycle climate variables, such as precipitation and temperature, as well as human interference in the land use pattern of each lake basin.…”

Section: Introductionmentioning

confidence: 99%

Investigating Hydroclimatic Variables Trends on the Natural Lakes of Western Greece Using Earth Observation Data

Gourgouletis

Baltas

2023

Sensors

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Expected global climate change is allegedly becoming more intense, and the impacts on water resources are being tracked in various hydroclimatic regimes. The present research investigates a hydrologically important area of Greece, where four natural lakes are concentrated. It aims to quantify any potential long-term trends in lake water area, precipitation, and temperature timeseries. Water area timeseries spanning four decades are estimated by the mNDWI from Landsat satellite imagery and used as an index of each lake’s water storage. Precipitation and temperature measurements are obtained from the open access datasets Hydroscope and ERA5-Land, respectively. All of the timeseries were tested seasonally and annually with the Pettitt and Mann–Kendal tests for statistically significant breakpoints and trends detection. No timeseries analysis resulted in a statistically significant (at 0.05 or 0.1 levels) annual or seasonal trend. The hydroclimatic regime over the past forty years in western Greece is found to have been relatively stable. Land use was also assessed to have been relatively unchanging, converging to the overall stability of the local water regime. However, the findings of this research should not be interpreted as a reassurance against climate change, but as a call to further research for the detailed regional and local assessment of climate change and hydroclimatic variability with acknowledged statistical approaches.

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Lake Naivasha

Renaut,

Owen

2023

Syntheses in Limnogeology

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Quantifying water storage within the north of Lake Naivasha using sonar remote sensing and Landsat satellite data

Cited by 6 publications

References 22 publications

Automatic identification method of surface lithology based on remote sensing satellite data and machine learning

Automatic identification method of surface lithology based on remote sensing satellite data and machine learning

Investigating Hydroclimatic Variables Trends on the Natural Lakes of Western Greece Using Earth Observation Data

Lake Naivasha

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