This study aimed to investigate the performance and sensitivity of 3D photogrammetric models generated without GCPs (ground control points). To determine whether the models with no GCPs retained accuracy in all terrain types as well as under varying climate or meteorological conditions, two separate studies were conducted in two areas with different characteristics (elevation, slope, topography, and meteorological differences). The study areas were initially modelled with GCPs and were later modelled without GCPs. Furthermore, some of the dimensions and areas within the modelled regions were measured using terrestrial techniques (with GPS/GNSS) for accuracy analyses. After regional modelling was conducted with and without GCPs, different territories with different slopes and geometric shapes were selected. Various length, area and volume measurements were carried out over the selected territories using both models (generated with and without GCPs). The datasets obtained from the measurement results were compared, and the measurements obtained using the models produced with GCPs were accepted as the true values. The length measurement results provided various levels of success. The first study area exhibited very promising length measurement results, with a relative error less than 1% and an RMSE (root mean square error) of 0.139 m. In the case of the area measurements, in the first study area (Sivas), a minimum relative error of 0.04% and a maximum relative error of 1.05% with an RMSE of 1.264 m² were obtained. In the second study areas (Artvin), a minimum relative error of 0.56% and a maximum relative error of 5.27% with an RMSE of 1.76 m² were achieved. Finally, in the case of the volume measurements, for the first study area (Sivas), a minimum relative error of 0.8% and a maximum relative error of 6.8% as well as an RMSE of 2.301 m³ were calculated. For the second study area (Artvin), the minimum relative error of the volume measurements was 0.502%, and the maximum relative error was 2.01%, with an RMSE of 7.061 m³.

This study aims to determine the impact of the International Civil Aviation Organization’s (ICAO) taxiway system development stages on runway capacity and delays in a single-runway airport that serves mixed operations by using a combined approach integrating the capacity-demand estimation analyses. We proposed a generic and systematic approach to taxiway development alternatives based on the ICAO guidelines rather than case-specific improvements presented in previous studies. The Samsun Çarşamba Airport (LTFH), which has the most basic level of taxiway layout, was chosen as a case study. The development stages were modeled and run in a fast-time simulation environment for different traffic scenarios based on historical data. As a result of modelling, average airborne and gate waiting delay of arrivals, queue delay of departures, taxi times, and runway occupation times were obtained. In addition, gate sensitivity and cost-benefit analyses were carried out. A triple exponential smoothing forecast was performed for different scenarios including normal, runway closures, COVID-19, and recovery from COVID-19. Practical capacities of the stages were revealed using the results of simulation and traffic demand forecasts. In addition, we evaluated the potential operational improvements of the stages by modifying a previously presented mathematical model. The proposed approach can assist airport operators in predicting the airport capacity saturation and selecting the best capacity improvement strategy for unexpected events.

First responders to forest fires, especially in areas that cannot be reached by land, are carried out by helicopters. In large forest lands, the necessity of helicopters to reach fire areas in the shortest time reveals the importance of heliport locations. In this study, the set-covering problem is handled by optimizing heliport locations in a heavily forested Milas district of Muğla, Turkey, where forest fires have occurred severely in recent years. The aim is to cover the entire region with a minimum number of heliports within specified response times. The forest density of the relevant region is integrated as weights into the mathematical model based on geographic information systems (GIS) during location-allocation. In addition, several conditions related to the study area, such as their proximity to roads, distance to settlement areas, slope, wetlands, altitude, the existence of heliports or airports, and others, were defined on 2 × 2 km grids and analyzed in ArcGIS for use in mathematical modeling, which was developed as a multi-objective programming model. In the first model, different initial attack (IA) times are considered, and the tradeoffs between IA time coverages and heliport locations are revealed by using the ɛ constraint method. Then, in the second model, the water sources are evaluated to provide recommendations for further extended attack (EA) and additional water sources (pools) considering the existing ones. Mathematical modeling is used to determine Pareto optimal heliport and additional water source locations for both IA and EA in the forest fires, respectively. Finally, the potential savings of the proposed model are quantified by comparing the model results with the current locations of the helicopters and water sources based on historical fire data.

Bu araştırmada, hasarlı yapıların hızlı ve güvenilir bir şekilde tespit edilebilmesi için derin öğrenme algoritmalarında evrişimsel sinir ağı mimarisinin bir modeli olan Mask Region-based Convolutional Neural Network (Mask R-CNN) modeli kullanılarak hasar tespiti yapılmaya çalışılmıştır. Eğitim alanı olarak 2010 yılında Haiti’de meydana gelen 316.000 insanın öldüğü, 280.000 civarı yapının hasar gördüğü 7.0 büyüklüğündeki deprem bölgesi seçilmiştir. Bölgede 5 cm ve 7 cm çözünürlüğe sahip insansız hava aracı görüntüleri çalışmada kullanılmıştır. Görüntüler ilk aşamada üç sınıfta “hasarlı”, “az hasarlı” ve “hasarsız” olarak eğitilip test edilmiştir. İnsansız hava aracı verileri ile yapılan test işleminde ise yapılar %58.62 oranıyla bulunmuş ve bulunan yapılar %83.53 genel doğrulukla sınıflandırılmıştır. İkinci aşamada görüntüler “hasarlı” ve “hasarsız” olarak iki sınıfta etiketlenip eğitim ve test işlemi gerçekleştirilmiştir. İnsansız hava aracı verileri ile yapılan test işleminde ise yapılar %74.50 oranıyla bulunmuş ve bulunan yapılar %95.12 genel doğruluk oranıyla sınıflandırılmıştır.

Producing accurate spatial data with stereo photogrammetric techniques is a challenging task, and the central projection of the space needs to be defined as closely as possible to its real form in each image taken for the relevant production. Interior camera parameters that define the exact imaging geometry of the camera and the exterior orientation parameters that locate and rotate the imaging directions in a coordinate system have to be known accurately for this correct definition. All distortions sourcing from lens and sensor planes and their recording geometry are significant as they are not suitable for detection with manual measurements. It is of vital importance to clearly understand the camera self-calibration concept with respect to the lens and the sensor plane geometry and include every possible distortion source as an unknown parameter in the calibration adjustments as they are all modellable systematic errors. In this study, possible distortion sources and self-calibration adjustments are explained in detail with a recently developed visualization software. The distortion sources investigated in the study are radial, tangential, differential scale, and axial skewing distortion. Thanks to the developed software, image center point, distorted grids, undistorted grids, and principal points were visualized. As a result, the most important element of obtaining accurate and precise photogrammetric productions is the correct definition of the central projection of the space for each image, and therefore, the study explains an accurate and robust procedure with the correct definition and use of correct camera internal parameters.

Rip akıntıları her yıl dünya çapında binlerce ölüme neden olan küresel bir kıyı tehlikesidir. Türkiye’de de özellikle Karadeniz kıyılarında yaz aylarında rip akıntıları nedeniyle çok sayıda suda boğulma vakası gerçekleşmektedir. Samsun’un Atakum ilçesi; coğrafi konumu, sahili ve tesisleri ile Orta ve Doğu Karadeniz Bölgesinin yaz aylarında en fazla turist çeken bölgesi olmakla birlikte Türkiye’de rip akıntılarının en çok yaşandığı sahillerin başında gelmektedir. Uzaktan algılama, rip akıntı tehlikesi ile ilgili araştırmalar yönünden çok önemli bir potansiyele sahip olmasına rağmen literatürde çok az çalışma mevcuttur. Bu çalışma ile Atakum’da 2007-2021 yılları arasında Google Earth Pro üzerinden erişilen 22 adet yüksek çözünürlüklü uydu görüntüsünden rip akıntıları belirlenerek alanın rip akıntı tehlikesi incelenmiştir. 22 görüntünün 9’unda rip akıntıları tespit edilmiş olup, 10 lokasyonda 3 ve daha fazla tarihte rip akıntısı gerçekleştiği görülmüştür. Çalışmanın sonucunda Samsun-Atakum’un rip akıntı tehlikesi yönünden kritik özellikte olduğu belirlenmiştir. Çalışma ayrıca yüksek çözünürlüklü uydu görüntülerinin rip akıntı tehlikesinin belirlenmesinde yüksek bir potansiyele sahip olduğunu ortaya koymuştur.