PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collections

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/5

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Citation - WoS: 10
Citation - Scopus: 13
Investigation of Landslide Detection Using Radial Basis Functions: a Case Study of the Takent Landslide, Turkey
(SPRINGER, 2020) Zeybek, Mustafa; Şanlıoğlu, İsmail
This paper investigates landslide detection over flat and steep-slope areas with large forest cover using different radial basis function interpolation methods, which can affect the quality of a digital elevation model. Unmanned aerial vehicles have been widely used in landslide detection studies. The generation of image-based point clouds is achievable with various matching algorithms from computer vision systems. Point cloud-based analysis was performed by generating multi-temporal digital elevation models to detect landslide displacement. Interpolation methodology has a crucial task to fill the gaps in insufficient areas that result from filtered areas or sensors that do not generate spatial information. Radial basis function interpolations are the most commonly used technique for estimating the unknown values in survey areas. However, the quality of the radial basis function interpolation methods for landslide studies has not been thoroughly investigated in previous studies. In this study, radial basis function interpolation methods are investigated and compared with the global navigational satellite systems, which provide high accuracy for geodetic measurement systems. The main purpose of this study was to investigate the various radial basis function models to detect landslides using a point cloud-based digital elevation model and determine the quality of detection with global navigational satellite systems. As a result of this study, each of the radial basis function-generated digital elevation models was found to be statistically compatible with global navigational satellite systems, resulting in displacements from the ground truth data.
Citation - WoS: 7
Citation - Scopus: 8
Seasonal Drought Analysis of Aksehir Lake With Temporal Combined Sentinel Data Between 2017 and 2021 Spring and Autumn
(Springer, 2022) Makineci, Hasan Bilgehan
The threat of drought has been felt almost worldwide in recent years. It is critical to determine the causes of drought and how seasonal changes affect it. Additionally, it is necessary to determine the speed and impact area of drought, monitor drought areas, and attempt to find solutions against drought. With the developing satellite sensing systems, remote sensing methods are being used to investigate topics such as the increase and extent of drought, uncontrolled water consumption in agricultural activities, and the effects of unnatural pollutants on freshwater resources such as lakes and rivers. Using Synthetic Aperture Radar (SAR) satellite data to monitor changes in water bodies is a relatively new area of study in remote sensing. The spatial extent and seasonal change (spring and autumn) of droughts between 2017 and 2021 in Aksehir Lake were determined from Sentinel-1A SAR satellite data, and the Normalized Differential Water Index (NDWI) was calculated using Sentinel-2A optical satellite data and Standardized Precipitation Index (SPI) in this research. In addition, a different approach was applied to determine the change of wetland boundaries more accurately by converting the linear Sigma0 band to the decibel (dB) band and applying a non-linear 3 x 3 maximum filter to the dB band to Sentinel-1A data. Consequently, it has been established that Aksehir Lake, which used to have wetlands during the spring seasons but began to dry up in the autumn seasons, had completely dried up in both periods in 2021.

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Browsing PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collections by Department "Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Harita Mühendisliği Bölümü"