Browsing by Author "Ates, AM"

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    The Performance Analysis of Different Water Indices and Algorithms Using Sentinel-2 and Landsat-8 Images in Determining Water Surface: Demirkopru Dam Case Study
    Yilmaz, OS; Gulgen, F; Sanli, FB; Ates, AM
    In this study, the most appropriate algorithm and water index to determine the boundaries of the dam water surface using remote sensing (RS) techniques were investigated. Water surface boundaries of Demirkopru Dam were determined using Sentinel-2 L2A (MSI) and Landsat-8 (OLI) satellite images. Demirkopru Dam was chosen as the study area as it is suitable for floating photovoltaic (FPV) solar power plant installation. Normalized difference water index (NDWI) and modified NDWI indices were used to determine the water surface boundaries of the dam. Thirty-six classification results were obtained using K-means, maximum likelihood classification (MLC), and random forest (RF) algorithms. The best classification accuracies of the produced maps have been calculated as 80.3%, 73.1%, and 73.2% by RF, MLC, and K-means, respectively. In addition, the water coastlines determined by classifications were compared with the continuously operating reference station (CORS-TR) data in a local area by calculating the root-mean-square error (RMSE). Compared with the CORS-TR measurements of the dam coastline obtained from the images classified by the RF algorithm, the minimum RMSE values were calculated as 13.8 m and 10.1 m for Landsat and Sentinel images, respectively. While the minimum RMSE value for coastlines obtained with various layer stacks of Landsat images classified by the MLC algorithm is 36.7 m, it could not be calculated in Sentinel images due to poorer classification results. For the coastlines obtained from the images classified by the K-means algorithm, the minimum RMSE values were calculated as 14.5 m and 9.6 m for Landsat and Sentinel images, respectively. According to the comparisons based on classification accuracy and CORS-TR measurements, it is concluded that the RF algorithm performs better than others for the dam water surface. Moreover, it was determined that the NDWI presented better results when the water level was the lowest for Demirkopru Dam. Also, in this study, the MLC algorithm has better results in detecting water surfaces using Landsat images. It was concluded that the K-means algorithm is also very effective in water surface detection. In this study, various water extraction indices, algorithms and free Landsat and Sentinel images were used to extract the water surface in a selected reservoir for the FPV installation. This study guides a series of algorithms and indexes used to detect water surfaces. In addition, it has been shown that the use of RS techniques, which are more practical than classical approaches in determining water boundaries, will be more effective in planning and design in terms of engineers, investors and various organizations who will realize the FPV installation.
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    Investigation of Water Quality in Izmir Bay With Remote Sensing Techniques Using NDCI on Google Earth Engine Platform
    Yilmaz, OS; Acar, U; Sanli, FB; Gülgen, F; Ates, AM
    In this study, the effects of algal blooms occurring in Izmir Bay in the summer of 2024 on marine ecosystems were investigated using remote sensing techniques on Google Earth Engine platform. The normalized difference chlorophyll index (NDCI) was calculated from January to the end of September and the chlorophyll-a density was analyzed. Additionally, an NDCI time series analysis was conducted between September 2018 and 2024 at the designated points. The values, which fluctuated narrowly until 2022, showed a sharp increase in 2024. NDCI, which vary between -0.4 and 0.2 in January 2024 and increase up to 0.8 toward the summer months, indicate that algal blooms are occurring, concentrated in critical areas such as Kar & scedil;& imath;yaka, Bayrakl & imath;, and Alsancak Port. These findings revealed a connection between the sudden fish deaths in the bay during the summer of 2024 and algal blooms, as well as the deterioration of water quality.
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    Determination of the appropriate zone on dam surface for floating photovoltaic system installation using RS and GISc technologies
    Yilmaz, OS; Gülgen, F; Ates, AM
    This study aims to reveal suitable places where floating photovoltaic-solar power plants (FPVSPPs) can be installed on the dam surface using the possibilities of remote sensing (RS) and geographical information science (GISc) technologies. Past satellite images from Landsat and Sentinel platforms allow researchers to analyse shoreline changes in the dam surface. Shoreline extraction is a crucial process for the FPV-SPP to stay afloat despite external constraints. In this study, changes in dam water levels were determined by classifying 20-year satellite images and analysing a 32-year global surface water dynamics dataset. The water surface area was calculated as 1,562.40 ha using the random forest (RF) algorithm and the normalized differences water index (NDWI) on Google Earth Engine (GEE) cloud platform. In addition, solar analysis was carried out with GISc using annual solar radiation maps shuttle radar topography mission (SRTM) data, which directly affects the energy production of FPVSPPs. It has been calculated that the solar radiation on the water surface varies between 1,554 kWh/m2-year and 1,875 kWh/m2-year. These calculated values were divided into five different classes, and it was observed that 88.5% of the dam surface had a very high level of solar radiation compared to other areas. Higher efficiency will be obtained from the FPV-SPP to be installed in this region compared to the systems to be installed in other regions. It has been observed that the radiation values in other parts of the water surface are lower due to topographic shading. These analyses revealed energy zones with high production potential, thereby easing the decision-making process for investors planning to establish FPV-SPPs.
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    Mapping burn severity and monitoring CO content in Turkiye's 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform
    Yilmaz, OS; Acar, U; Sanli, FB; Gulgen, F; Ates, AM
    This study investigated forest fires in the Mediterranean of Turkiye between July 28, 2021, and August 11, 2021. Burn severity maps were produced with the difference normalised burned ratio index (dNBR) and difference normalised difference vegetation index (dNDVI) using Sentinel-2 images on the Google Earth Engine (GEE) cloud platform. The burned areas were estimated based on the determined burning severity degrees. Vegetation density losses in burned areas were analysed using the normalised difference vegetation index (NDVI) time series. At the same time, the post-fire Carbon Monoxide (CO) column number densities were determined using the Sentinel-5P satellite data. According to the burn severity maps obtained with dNBR, the sum of high and moderate severity areas constitutes 34.64%, 20.57%, 46.43%, 51.50% and 18.88% of the entire area in Manavgat, Gundogmus, Marmaris, Bodrum and Koycegiz districts, respectively. Likewise, according to the burn severity maps obtained with dNDVI, the sum of the areas of very high severity and high severity constitutes 41.17%, 30.16%, 30.50%, 42.35%, and 10.40% of the entire region, respectively. In post-fire NDVI time series analyses, sharp decreases were observed in NDVI values from 0.8 to 0.1 in all burned areas. While the Tropospheric CO column number density was 0.03 mol/m(2) in all regions burned before the fire, it was observed that this value increased to 0.14 mol/m(2) after the fire. Moreover, when the area was examined more broadly with Sentinel 5P data, it was observed that the amount of CO increased up to a maximum value of 0.333 mol/m(2). The results of this study present significant information in terms of determining the severity of forest fires in the Mediterranean region in 2021 and the determination of the CO column number density after the fire. In addition, monitoring polluting gases with RS techniques after forest fires is essential in understanding the extent of the damage they can cause to the environment.
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    Rooftop solar Photovoltaic (PV) plant - One year measured performance and simulations
    Ates, AM; Singh, H
    In this study, 1-year real life performance of a 30kWp rooftop solar PV power plant installed at the Koprubasi Vocational School of the Manisa Celal Bayar University was evaluated and is presented here. The PV plant is comprised of 116 polycrystalline modules mounted 15 cm proud of the roof surface providing a gap between roof surface and the bottom of the panels for air circulation. The panels were tilted at 12 degrees with horizontal and orientated at an azimuth angle of -20 degrees. Measured power output of the plant was compared against the predictions of a spreadsheet based simulation model developed. Results were found to be in excellent agreement with the measured values. Annual array yield, final yield and reference yield values of the system that produced 45,592 kWh of energy, under an average 1,818 kWh/m(2)/a radiation incident on the panels inclined surfaces, were found to be 4.25, 4.97 and 4.16 h/d, respectively. The annual performance ratio of the system has been calculated as 83.61% and the capacity factor 17.35%. It has been determined that the power plant displaced 23.5 tonnes of CO2 emissions in 2018. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.
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    Using remote sensing to calculate floating photovoltaic technical potential of a dam's surface
    Ates, AM; Yilmaz, OS; Gulgen, F
    A dam with a hydroelectric power plant (HEPP) prevents flooding while generating electricity and providing controlled irrigation of agricultural land. An open dam surface causes a substantial loss in water resources over the course of a year due to evaporation. In this paper, the authors propose to occupy the idle dam area with a floating photovoltaic (FPV) solar power plant (SPP) to generate electrical energy and to conserve water by minimizing evaporation. Since the shoreline of a dam used for agricultural irrigation continually changes, the most critical challenge in installing a SPP is to determine the suitable area to be covered with FPV panels. In this study, the shoreline changes of the Demirkopru Dam in Manisa, Turkey, were monitored over 20 years from Landsat and Sentinel satellite images using the supervised classification in the Google Earth Engine. The minimum surface area of the dam was found to be 1,562.45 ha. Installing a 2.03 GWp FPV SPP horizontally on this surface and obtaining 3,328.33 GWh annual energy is feasible. Moreover, the FPV panels can prevent 28,231,026.90 m(3) of water from evaporating. Approximately 7.82% of the water used for electricity production in 2019 can be recovered with the installation of this SPP.
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    A novel approach suggestion for assessing the impact of topographic shading on the estimation of the floating photovoltaic technical potential
    Yilmaz, OS; Ates, AM; Gülgen, F
    This study presents a novel approach for the implementation of floating photovoltaic (FPV) systems at the Ayvali hydroelectric power plant (HPP) in Turkiye. The method proposed in this study accounts for dynamic changes in water levels to accurately calculate the shading effects induced by topography. First, the minimum reservoir surface for the FPV system was calculated using remote sensing (RS). The minimum reservoir surface area, which was determined as 504.69 ha using 60 Sentinel-2 satellite images, was calculated using machine learning al-gorithms on the Google Earth Engine (GEE) platform, support vector machines (SVM) and automatic water extraction index (AWEI). In the second stage, new digital elevation model (DEM) maps were produced by overlapping monthly changes in water height with ALOS PALSAR data and solar analysis was performed on them. An annual global horizontal irradiance (GHI) map was produced using these maps, and it was divided into five classes to emphasize differences in production potential. The results revealed that 1083.45 GWh of elec-tricity can be produced annually by installing FPV in very high and high potential areas. However, as the moderate, low, and very low regions represent only 5.02% of the reservoir surface and there is a 1.68-fold difference in production potential between the highest and lowest areas due to topography-induced shading near the coastline, it was concluded that FPV installation would not be efficient in those regions. This study highlights the significance of incorporating topography-induced shading and emphasizes the importance of employing RS and geographic information system (GIS) techniques to achieve this objective.
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    Perceptions of students and teachers participating in a science festival regarding science and scientists
    Ates, Ö; Ates, AM; Aladag, Y
    Background: Numerous studies have been conducted to identify students' perceptions of science and scientists since the 1950s. Those studies have revealed that students have stereotypical perceptions, on which teachers may have a significant effect. It is, therefore, essential to determine both teachers' and students' perceptions. Purpose: The aim of this study is to investigate students' and teachers' perceptions of science and scientists. Sample: The sample for the study consisted of 85 students and 47 teachers who participated in a science festival. Design and methods: The study is based on a descriptive survey model. Data were collected using the Draw-A-Scientist Test (DAST) and Word Association Test (WAT), and analyzed using content analysis. Results: Participants' drawings focused on scientists' physical characteristics, type of activity, working environment and the materials used while conducting experiments. A scientist was often depicted as a man in a lab coat with strange hair and eyeglasses and using laboratory materials. Teachers made more detailed drawings of scientists' working style and environment and more detailed associations with the nature of science, ways of acquiring scientific knowledge and scientific process. Unlike teachers, students emphasized space-related concepts both in their drawings and word associations. Conclusion: This study shows that both teachers and students possess various stereotypical perceptions of scientists aligned with the previous studies. However, the number of scientists drawn as happy and female is higher than the previous studies, which is a promising finding. Moreover, students' drawings consisting symbols or alternative images that evoked space in particular is one of the several aspects which differentiate this study from most studies. This study also shows that using drawings and word association tests together provides a richer understanding of people's views of science and scientists than using only one measurement tool.
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    Unlocking the floating photovoltaic potential of Turkiye's hydroelectric power plants
    Ates, AM
    The massive surface of the water accumulated in the basins of hydroelectric power plants (HEPPs) can be considered an excellent opportunity for floating photovoltaics (FPV). Turkiye is among the countries that can utilize this potential with its large HEPPs. In this study, the surface areas of 76 HEPPs in Turkiye were deter-mined using the Random Forest algorithm over Google Earth Engine, and the technical potential of FPV that could be installed in these areas was evaluated over five scenarios. In addition, the water recovery that can be obtained with the FPV installation has been calculated. When the entire surfaces of the dams are used, the FPV technical potential and the amount of water recovered are 380,439.85 MW and 25.40 km3/year, respectively. Even when only 10% of the surfaces of the dams are used, the FPV technical potential meets 39.67% of Turkiye's total installed power capacity. Moreover, the water recovered from evaporation meets 7.3% of the surface water used for agricultural irrigation. In addition, it has been calculated that the FPV electricity generation potential of HEPPs producing 674,280.17 GWh of electricity in 2020 is 13.82 times higher than the hydroelectric potential. The results demonstrated how great the FPV solar power plant potential that the country HEPPs carries on their idle water surfaces.
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    Identifying system characteristics of autonomous wind turbines: Measurement system design
    Ates, AM; Cetin, NS
    In this study, an autonomous wind turbine system has been simulated. Meteorological data gathered at the turbine's location and the turbine's characteristics have been measured in one-second periods of time. Based on these measurement values, simulation values and measured values have been compared synchronously, using a software program prepared in a graphic media. The study initially used the MATLAB program for turbine simulation. However, the MATLAB program ran too slowly because of the study's large amount of data calculations. Moreover, observation of measured data simulation results on the same graph and simultaneous Internet results proved to be inefficient. For these reasons, a new program, Turbine Analyzer, was prepared, using Delphi programming language. Simulation results taken from MATLAB and Turbine Analyzer were compared, and the newly written program was tested. In this study, an original system, created to conduct turbine tests, has achieved characteristics tests of small-scale (20 kW and below) autonomous wind turbines. (C) 2013 AIP Publishing LLC.