Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Ane, B.K.(2)
- Ben Ahmed, M.(2)
- Boudhir, A.A.(2)
- Karas, I.R.(2)
- Akbulut, Z.(1)
- Akbulut, Zeynep(1)
- Bayram, B.(1)
- Comert, R.(1)
- Dihkan, M.(1)
- Gunen, M.A.(1)
- Hisoglu, Seyit(1)
- Isikdag, U.(1)
- Karsli, F.(1)
- Karslı, Fevzi(1)
- Ozdemir, S.(1)
- Sefercik, U.G.(1)
- Özdemir, Samed(1)
Yayınlar
- BildiriAçık Erişim2025Comparative Analysis of Vision Foundation Models For Building Segmentation in Aerial Imagery
Akbulut, Zeynep; Özdemir, Samed; Karslı, Fevzi; Sefercik, U.G.
Visual Foundation Models (VFMs) demonstrate impressive generalization capabilities for image segmentation and classification tasks, leading to their increasing adoption in the remote sensing field. This study investigates the performance of VFMs in zero-shot building segmentation from aerial imagery using two model pipelines: Grounded-SAM and SAM+CLIP. Grounded-SAM integrates the Grounding DINO backbone with a Segment Anything Model (SAM) while SAM+CLIP first employs SAM for generating masks followed by Contrastive Language Image Pretraining (CLIP) for classification. The evaluation, performed on the WHU building dataset using Precision, Recall, F1 score, and intersection over union (IoU) metrics, revealed that Grounded-SAM achieved F1-score of 0.83 and IoU of 0.71. SAM+CLIP achieved F1-score of 0.65 and IoU of 0.49. While Grounded-SAM excelled at accurately delineating partially occluded and irregularly shaped buildings, SAM+CLIP was able to segment larger buildings but struggled with delineating smaller ones. Given the impressive performance of VFMs in zero-shot building segmentation, future efforts aimed at refining these models through fine-tuning or few-shot learning could significantly expand their application in remote sensing.
- BildiriAçık Erişim2024AN ANALYSIS OF NEIGHBOURHOOD TYPES FOR POINTNET++ IN SEMANTIC SEGMENTATION OF AIRBORNE LASER SCANNING DATA
Akbulut, Z.; Ozdemir, S.; Karsli, F.; Dihkan, M.; Isikdag, U.; Bayram, B.
The objective of the study is to conduct a comprehensive examination of how different neighbourhood types, namely spherical, cylindrical, and k-nearest neighbour (kNN), influence the feature extraction capabilities of the PointNet++ architecture in the semantic segmentation of Airborne Laser Scanning (ALS) point clouds. Two datasets are utilized for semantic segmentation analysis: the Dayton Annotated LiDAR Earth Scan (DALES) and the ISPRS 3D Semantic Labelling Benchmark datasets. In the experiments, the kNN method exhibited approximately 1% higher accuracy in weighted mean F1 and intersection over union (IoU) metrics compared to the spherical and cylindrical neighbourhood types on the DALES dataset. However, in the generalization experiment conducted on the ISPRS dataset, the spherical neighbourhood achieved the best results in these metrics, outperforming the cylindrical neighbourhood by a small margin. Notably, the kNN method was the least accurate, with a decrease in accuracy of approximately 1% in both weighted mean IoU and F1 scores. These findings suggest that the features extracted from spherical and cylindrical neighbourhood types are more generalizable compared to those from the kNN method.
- BildiriAçık Erişim2021QUALITY ASSESSMENT of PANSHARPENED RASAT and LANDSAT-8 IMAGES USING SYNTHETIC SENTINEL-2 PANCHROMATIC IMAGE
Gunen, M.A.; Karas, I.R.; Ben Ahmed, M.; Boudhir, A.A.; Ane, B.K.
Technical and physical limitations often do not allow images to be acquired with high spatial and spectral resolution. Pansharpened images obtained by fusing high spatial resolution panchromatic images and multi-spectral images are widely used in GIS applications. In this study, it is aimed to increase the spatial resolution of the RASAT and Landsat-8 multispectral satellite images with synthetic Sentinel-2 panchromatic data. Six different pansharpening methods were used to test the success of the synthetic panchromatic data generation method using dataset with two different land use/land cover properties. Seven full reference image quality assessment metrics and two referenceless image quality assessment metrics were used to perform quantitative comparison.
- BildiriAçık Erişim2021GIS-BASED OPTIMUM SITE SELECTION for SOLAR ELECTRIC VEHICLE CHARGING STATION: ANKARA-ISTANBUL HIGHWAY CASE
Hisoglu, Seyit; Comert, R.; Karas, I.R.; Ben Ahmed, M.; Boudhir, A.A.; Ane, B.K.
Energy sources are divided into renewable and non-renewable sources. It can be seen that non-renewable energy resources are not adequately meeting the increased demands of worldwide technological developments, increasing population, and global consumption. Therefore, the demand for renewable resources is increasing day by day. When it comes to the use of non-renewable carbon-based fossil fuels, one of the first areas that come to mind is undoubtedly the Automotive sector. Today, it is realized that one of the main reasons for the lack of electric motor cars compared to petroleum fuelled cars, is the scarcity of electric vehicle charging stations and the difficulty of their accessibility. In this study; an analysis of solar-powered electric charging stations site selection was carried out for electric vehicles. The Ankara-Istanbul highway, which has a high traffic density, was chosen as the sample route for the study. Within the scope of the study, the areas where stations can be installed on the highway were carried out using the Multi-Criteria Decision Making Method with the help of Geographic Information System. Solar radiation, slope, aspect, land use/land cover, traffic volume and proximity to the road, criteria of the route, and site selection analysis were determined as input data. The maps of the determined criteria were arranged according to the study area and prepared for analysis. The criteria maps obtained were reclassified according to the above-mentioned criteria and scoring system. After the reclassification process, the weighting of each criteria which affect the analysis was determined by the researched literature and an overlapping process was carried out. According to the results map produced as a result of the overlay analysis, the appropriate area has been determined for the electric charging stations working with solar energy. On the defined route within the scope of the study, a proposal has been made for a total of 13 stations, 8 in Ankara, 3 in Bolu, 1 in Kocaeli, and 1 in Istanbul. This study, it is aimed to encourage automobile users to make greater use of electric motor vehicles, which would be a more environmentally friendly and sustainable choice, and ultimately more economical.
- DergiInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives