Sürdürülebilir Kalkınma Amaçları

  • MakaleAçık Erişim2023
    3D data integration for geo-located cave mapping based on unmanned aerial vehicle and terrestrial laser scanner data

    Çömert, Resul; Özdemir, Samed; Bilgilioglu, Burhan Baha; Alemdag, Selçuk; Zeybek, Halil Ibrahim

    The Akçakale cave is a significant natural and cultural heritage site in the Black Sea region of eastern Turkey. The complex geometry and difficult-to-access areas of the cave have made the use of traditional mapping methods challenging. To overcome these limitations, this study utilized TLS and UAV technology to produce highly accurate 2D and 3D data for cave management and risk assessment purposes. The TLS system was used to create a detailed 3D point cloud of the cave interior, while the UAV system generated a 3D model of the surface topography outside the cave. The two sets of data were combined in the GIS environment using a geodetic network established in the study area, providing a common geodetic reference system for both TLS and UAV data. The study found that the cave area is 13,750 m2, which is smaller than the area of 18,000 m2 that was previously estimated using conventional measurement methods. The volume and ceiling heights of the cave were calculated using the elevation models generated from TLS point cloud data. The 3D point cloud data were also used to map dripstone locations on the floor and ceiling of the cave, and the boundaries of rock blocks on the ground were precisely determined. The study identified potential risks associated with the cave, particularly the risk of rockfall in the source rock areas around the cave entrance and the southern part of the cave. The nearest building to the cave is approximately 35 meters away, and all the buildings in the area are less than 300 meters from the cave. In the event of the cave collapse, the buildings in the southern part of the cave are at risk of rockfall. This study demonstrates the effectiveness of combining data from TLS and UAV systems to generate broad and sensitive cave mapping and risk assessment data, which are critical for cave management and safety. The collected data can be used for cave stability investigations and rockfall risk assessments. This study provides a foundation for future explorations of the Akcakale cave and highlights the potential for modern surveying techniques to enhance our understanding of complex geological structures such as caves.

    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
  • MakaleYalnız künye2021
    Long and short-term assessment of surface area changes in saline and freshwater lakes via remote sensing

    Yagmur, Nur; Bilgilioglu, Burhan Baha; Dervisoglu, Adalet; Musaoglu, Nebiye; Tanik, Aysegul

    Advances in remote sensing technology enable monitoring and detection of these vulnerable water bodies that bear numerous functions and ecological services beyond their intended use. As such, valuable data and information may be provided for long and short-term analyses and stored in a database for future projections. This paper initially grouped 18 natural lakes of the Konya Closed Basin of Turkey according to their salinity level. Freshwater, saline and brackish lakes have then undergone temporal analysis for every 5-year intervals via Landsat satellite images. Freshwater lake surfaces have not changed noticeably during the inspection period; however, saline waters have decreased in surface area by 32%. Beysehir Lake constituting 94% of the freshwater category and Tuz Lake representing 97% of the saline group were selected for the short-term analysis that was monthly conducted for years 2017 and 2018 with optical and SAR images to better verify cause and effect relationship.

    • SDG 6 · Temiz Su ve Sanitasyon
    • SDG 13 · İklim Eylemi
  • MakaleAçık Erişim2021
    Satellite-derived shallow wetland bathymetry using different classification algorithms and datasets

    Dervisoglu, Adalet; Yagmur, Nur; Bilgilioglu, Burhan Baha

    Remote sensing (RS) effectively identifies, analyzes, and monitors wetlands. In addition to these two-dimensional studies, RS is used with several techniques in determining shallow water depths. The primary purpose of this study is to obtain shallow wetland bathymetry utilizing spectral reflections obtained at different water depths by field study and satellite images. Machine learning (ML) algorithms, which are widely used in remote sensing, are used in this study. Four algorithms were selected as random forest (RF), support vector machine (SVM), Neural Networks (NN), and Maximum Likelihood Classification (MLC). Since machine learning algorithms use training samples/datasets, the classification accuracy is directly related to selecting these data. The effect of pixel counts on classification was investigated by using two different training data set also. Duden (Kulu) Lake, which is a shallow wetland, was chosen as the study area. The Iterative Self-Organizing Data Analysis Technique (ISODATA) classification algorithm divided into as many clusters as possible was applied on Sentinel-2 multispectral images. All classes were rede-fined using measured spectral signatures and were created a bathymetric map. This map was used as reference data in creating training sets and the accuracy assessment of ML algorithms. When the water surface areas obtained from algorithms were compared with the bathymetric map and Normalized Difference Water Index, the best result was obtained with RF. According to the accuracy assessment results, it was seen that the number of training data affects the accuracy, and the best results were obtained with SVM and RF algorithms with training data containing more pixels (overall accuracy 93.87% and 92.64, kappa 0.89 and 0.87, respectively).

    • SDG 6 · Temiz Su ve Sanitasyon
  • MakaleAçık Erişim2021
    Temporal monitoring of land use/land cover change in Kahramanmaraş city center

    Aliyazicioglu, Kubra; Beker, Fatmanur; Topaloglu, Raziye Hale; Bilgilioglu, Burhan Baha; Comert, Resul

    Irregular urbanization causes problems such as decrease in fertile agricultural areas, irregular industrialization and urbanization. To provide a healthier life opportunity for future generations without disturbing nature, it is essential to determine the temporal changes in land use and to make land management plans accordingly. In this study, land use/land cover (LULC) change occurred in Kahramanmaras province within 30 years was investigated by remote sensing and integration of Geographic Information Systems. Landsat satellite images of 1988-1998-2008-2018 were obtained for the production of LULC maps. Each image was classified according to supervised classification approach using the support vector machines (SVMs) algorithms. The confusion matrix was created for each year to examine the accuracy of the LULC maps. The overall accuracy of the thematic maps was obtained as 91.76%, 93.56%, 86.89% and 88.29%, respectively. Also, Kappa values of thematic maps for each year were obtained as 0.88, 0.91, 0.81 and 0.84, respectively. When the results were examined, the development of industry in the city area and the construction of the airport contributed to the development of the social and economic structure of the city. The increase in the number of housing in the related regions has led to an increase in the amount of urban areas and a decrease in agricultural areas.

    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    • SDG 15 · Karasal Yaşam
  • MakaleAçık Erişim2021
    Investigation of the effect of urbanization on land surface temperature example of Bursa

    Yamak, Beyzanur; Yagci, Zekeriya; Bilgilioglu, Burhan Baha; Comert, Resul

    Today, industrialization and urbanization in large cities cause an increase in the surfaces covered with man-made objects such as concrete and asphalt. The expansion of urban areas and increase in the using materials with high heat storage properties, directly affect the Land Surface Temperature (LST), which shows an increase in the sensible temperature of the region. LST is directly connected to the natural green vegetation of the land and varies widely in large urban areas, these differences related to the temperature is defined as the ‘urban heat island’. In this study, it was investigated the temporal variation of land surface temperature due to urbanization. Bursa, which is considered as a study area, has shown a rapid population increase since 1990 and a rapid increase in the number of buildings with the impact of urbanization and industrialisation. To determine the effect of this urbanization and industrialisation on land surface temperature, temporal change analysis of the surface temperature in the Bursa was observed with Landsat satellite images of 1988, 1998, 2008 and 2018. From produced maps, it was observed that the amount of green vegetation in urban areas decreased and as a consequence of this decrease, the surface temperature increased in the urban areas.

    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    • SDG 13 · İklim Eylemi