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Öğe Advantages and Benefits of Three Dimensional Calculation of Land Areas for Parties(Ali ULVİ, 2023) Kundupoğlu, Kadir; Avşar, Emin ÖzgürNatural Land areas are calculated by reducing them to a two-dimensional plane without regarding the topography. Farmers actually using more extensive lands, receive less agricultural support from the government, as the surface area is not considered. Similarly, the taxes collected by the government are lower. In this study, in addition to tax and agricultural support, analyses were also carried out in terms of expropriation and consolidation. Instead of the area calculation on a two-dimensional plane, the surface model produced from images obtained from unmanned aerial vehicles was used to perform the area calculation. The advantages and benefit analyses of the three-dimensionally calculated area in terms of the state and landowners were presentedÖğe Assessment of Segmentation Parameters for Object-Based Land Cover Classification Using Color-Infrared Imagery(Mdpi, 2018) Akçay, Özgün; Avşar, Emin Özgür; İnalpulat, Melis; Genç, Levent; Cam, AhmetUsing object-based image analysis (OBIA) techniques for land use-land cover classification (LULC) has become an area of interest due to the availability of high-resolution data and segmentation methods. Multi-resolution segmentation in particular, statistically seen as the most used algorithm, is able to produce non-identical segmentations depending on the required parameters. The total effect of segmentation parameters on the classification accuracy of high-resolution imagery is still an open question, though some studies were implemented to define the optimum segmentation parameters. However, recent studies have not properly considered the parameters and their consequences on LULC accuracy. The main objective of this study is to assess OBIA segmentation and classification accuracy according to the segmentation parameters using different overlap ratios during image object sampling for a predetermined scale. With this aim, we analyzed and compared (a) high-resolution color-infrared aerial images of a newly-developed urban area including different land use types; (b) combinations of multi-resolution segmentation with different shape, color, compactness, bands, and band-weights; and (c) accuracies of classifications based on varied segmentations. The results of various parameters in the study showed an explicit correlation between segmentation accuracies and classification accuracies. The effect of changes in segmentation parameters using different sample selection methods for five main LULC types was studied. Specifically, moderate shape and compactness values provided more consistency than lower and higher values; also, band weighting demonstrated substantial results due to the chosen bands. Differences in the variable importance of the classifications and changes in LULC maps were also explained.Öğe Boundary Extraction Based on Dual Stream Deep Learning Model in High Resolution Remote Sensing Images(2021) Akçay, Özgün; Kınacı, Ahmet Cumhur; Avşar, Emin Özgür; Aydar, UmutBoundary extraction in remote sensing has an important task in studies such as environmental observation, risk management and monitoring urban growth. Although significant progress has been made in the different calculation methods proposed, there are issues that need improvement, especially in terms of accuracy, efficiency and speed. In this study, dual stream network architecture of three different models that can obtain boundary extraction by using normalized Digital Surface Model (nDSM), Normalized Difference Vegetation Index (NDVI) and Near-Infrared (IR) band as the second stream, was explained. Model I is designed as the original HED, whereas the second stream of Model II, III, and IV use nDSM, nDSM + NDVI and nDSM + NDVI + IR, respectively. Thus, by comparing the models trained based on different data combinations, the contribution of different input data to the success of boundary extraction was revealed. For the training of the models, boundary maps produced from The International Society for Photogrammetry and Remote Sensing (ISPRS) Potsdam data set and input datasets augmented by rotation, mirroring and rotation were used. When the test results obtained from two-stream and multidata- based models are evaluated, 11% higher recall values have achieved with Model IV compared to the original HED. The outcomes clearly revealed the importance of using multispectral band, height data and vegetation information as input data in boundary extraction beside commonly used RGB images.Öğe Landfill Site Selection Using Spatial Information Technologies: A Case Study for Bodrum District(Lütfiye KUŞAK, 2021) Nehteparov, Cansu; Avşar, Emin ÖzgürWith the rapid increase of the world's population, waste production is also increasing exponentially. Although these wastes must be disposed of in landfill sites under control according to national and international decrees, some of the waste is still disposed of in wild irregular landfill sites. Environmental pollution and health risks occur as a result of these wild irregular landfill sites. Besides, criteria need to be considered for suitable areas that solid waste landfill sites to be built. One of the areas where solid waste is disposed of in wild irregular landfill sites is the Bodrum district of Muğla province. In this study, related literature for criteria selection was reviewed and analysis for the study area has performed. Since national and international regulations differ for restricted areas, common approaches in the reviewed studies have been used to identify restricted areas. Furthermore; the weight of the criteria was determined according to the usage frequency of each criterion in the literature. As the result, the reclassification maps according to each criterion and the site selection map obtained by weighting all the criteria were produced by the means of the spatial analysis methods of Geographical Information SystemsÖğe The effect of jpeg compression in close range photogrammetry(Selcuk Univ Press, 2017) Akçay, Özgün; Erenoğlu, Ramazan Cüneyt; Avşar, Emin ÖzgürDigital photogrammetry, using digital camera images, is an important low-cost engineering method to produce precise three-dimensional model of either an object or the part of the earth depending on the image quality. Photogrammetry which is cheaper and more practical than the new technologies such as LIDAR, has increased point cloud generation capacity during the past decade with contributions of computer vision. Images of new camera technologies needs huge storage space due to larger image file sizes. Moreover, this enormousness increases image process time during extraction, orientation and dense matching. The Joint Photographic Experts Group (JPEG) is one of the most commonly used methods as lossy compression standard for the storage purposes of the oversized image file. Particularly, image compression at different rates causes image deteriorations during the processing period. Therefore, the compression rates affect accuracy of photogrammetric measurements. In this study, the close range images compressed at the different levels were investigated to define the compression effect on photogrammetric results, such as orientation parameters and 3D point cloud. The outcomes of this study show that lower compression ratios are acceptable in photogrammetric process when moderate accuracy is sufficient.
