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Yayın A point cloud filtering method based on anisotropic error model(John Wiley and Sons Inc, 2023-12) Özendi, Mustafa; Akça, Devrim; Topan, HüseyinMany modelling applications require 3D meshes that should be generated from filtered/cleaned point clouds. This paper proposes a methodology for filtering of terrestrial laser scanner (TLS)-derived point clouds, consisting of two main parts: an anisotropic point error model and the subsequent decimation steps for elimination of low-quality points. The point error model can compute the positional quality of any point in the form of error ellipsoids. It is formulated as a function of the angular/mechanical stability, sensor-to-object distance, laser beam's incidence angle and surface reflectivity, which are the most dominant error sources. In a block of several co-registered point clouds, some parts of the target object are sampled by multiple scans with different positional quality patterns. This situation results in redundant data. The proposed decimation steps removes this redundancy by selecting only the points with the highest positional quality. Finally, the Good, Bad, and the Better algorithm, based on the ray-tracing concept, was developed to remove the remaining redundancy due to the Moiré effects. The resulting point cloud consists of only the points with the highest positional quality while reducing the number of points by factor 10. This novel approach resulted in final surface meshes that are accurate, contain predefined level of random errors and require almost no manual intervention.Yayın Direct usage of occupancy data for multiregime speed-flow rate models(American Society of Civil Engineers (ASCE), 2023-01) Aksoy, Göker; Öğüt, Kemal SelçukEarly macroscopic traffic flow models were based on observations of volume, speed, and density. The invention of traffic sensors has supplied a wealth of data for the development of more accurate macroscopic flow models. However, traffic sensors typically collect volume, speed, and occupancy data. Researchers prefer to convert occupancy to density because of the density usage in earlier models; however, for this conversion, the average length of passed vehicles must be determined. This length is frequently estimated by researchers. However, because the explanatory variable (density) is not observed but produced, this estimation weakens the model results. Considering these challenges, this research proposes a novel traffic flow modeling approach based on occupancy. The proposed method was tested in three speed-flow rate relationship regions, one of which is congested and two of which are free flow. Free flow speed, capacity, queue discharge flow, breakpoint flow rate, and optimum speed can all be determined more precisely with this method. Furthermore, the nonlinear relationship between speed and flow rate was clarified. The proposed traffic flow model is extremely useful, especially for dynamic traffic management applications, because it is based on directly gathered data such as volume, speed, and occupancy.Yayın Advanced drought analysis using a novel copula-based multivariate index: a case study of the Ceyhan River Basin(Springer Science and Business Media Deutschland GmbH, 2025-02) Terzi, Tolga Barış; Önöz, BihratDrought is a severe natural disaster that poses significant risks to both social and ecological systems. Detecting drought is challenging due to its gradual development, which makes it difficult to identify and predict, often resulting in significant impacts on the affected regions. Therefore, accurate and dependable monitoring of drought conditions is essential for the development and implementation of effective mitigation strategies. Drought indices play a crucial role in monitoring drought conditions, with single-variable indices commonly employed in the literature to evaluate drought severity. While these indices are typically effective at characterizing the specific type of drought for which they were designed, they often fall short in offering a comprehensive view of overall drought conditions. The multivariate standardized drought index (MSDI) is a comprehensive tool that assesses drought conditions by integrating multiple hydrometeorological variables. Widely employed in the literature in both parametric and empirical forms, the MSDI is recognized for its effectiveness in detecting drought in an integrated manner. This study focuses on a particular challenge related to the calculation of MSDI using copula families. The novel methodology introduced in this paper involves selecting the most suitable copula family for each data subset using AIC and BIC criteria. Rather than applying a single copula family to the entire dataset, this approach utilizes multiple copula families for different subsets, thereby ensuring optimal modeling for each distinct group of data. The Ceyhan River Basin (CRB) is used as a case study to apply the proposed methodology. The drought characteristics of the basin are analyzed using both the newly developed MSDI and conventional single-variable indices, and the performance of the new methodology is evaluated. The application of this approach in the CRB demonstrated its effectiveness in identifying both concurrent and isolated occurrences of meteorological and hydrological droughts, thereby facilitating a more integrated and precise assessment of drought characteristics. Results indicated that the proposed MSDI detected drought events that were overlooked by single-variable indices and improved classification accuracy over the conventional MSDI.
