Profile URL: https://hdl.handle.net/20.500.13091/12029
Job Title:Dr. Öğr. Gör.
Email Address:tkaydin@ktun.edu.tr
Main Affiliation:07. 17. Department of Map and Cadastre
Status: Current Staff
ORCID:
0000-0001-6903-0847
0000-0001-6903-0847Scopus ID:
58988090800
58988090800YÖK Akademik: 13FCCBCBB6EE0C47
Google Scholar:
Sm7b7HwAAAAJ
Sm7b7HwAAAAJWeb of Science ID:
KXI-7390-2024
KXI-7390-2024Name Variants:
Aydın, T. Kağan Aydın, T. K.
5 results
Scholarly Output Search Results
Now showing 1 - 5 of 5
Article Spatial Effects of Urban Road Network Development on Land Surface Temperature and Vegetation Dynamics: The Case of Selçuklu District (2015–2025)(2026) Aydin, Taha KağanIn the Selçuklu district of Konya province, changes associated with the expanding road network, together with variations in Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) between 2015 and 2025, were evaluated. In this context, Remote Sensing (RS) and Geographic Information System (GIS) techniques were employed to assess the relationship between transportation infrastructure transformation and changes in the urban thermal environment and vegetation dynamics. Landsat satellite data were processed on the Google Earth Engine (GEE) platform, and NDVI and LST analyses were conducted for the summer months (June–July–August) of 2015 and 2025. Road network data were obtained from OpenStreetMap (OSM) via the Overpass Turbo interface, and spatial analyses were carried out in the ArcGIS environment.The findings indicate that the total road network length increased by 28.75% (approximately 360 km) over the ten-year period. This increase was mainly concentrated in residential, track, and secondary road classes, reflecting the acceleration of urban expansion processes. In parallel, a significant rise in surface temperatures was observed, with median LST values increasing from 33.38°C to 42.12°C. NDVI analyses revealed generally limited overall change, although the median NDVI value increased by approximately 7.86%. However, spatial variations indicate vegetation loss in areas of intense urban development. Consistent with the inverse relationship between NDVI and LST, areas with reduced vegetation exhibited higher temperature increases, whereas lower temperature values were observed in areas with dense vegetation.Overall, the results demonstrate that road network expansion has significant implications not only for transportation development but also for urban thermal conditions and vegetation patterns. Integrating environmental indicators such as LST and NDVI into road network planning can support decision-makers in mitigating urban heat accumulation, optimizing transportation networks, and promoting sustainable urban development.Article Spatial and Socio-Economic Dynamics of Local Government-Led Urban Transformation(Geomatik Journal, 2026-04-29) Aydin, Taha KaganContinuously evolving socio-economic dynamics, rapid population growth, migration flows, disaster risks, and infrastructure deficiencies lead to physical deterioration and functional loss in existing urban areas. In Turkiye, the presence of aged building stock with low structural performance in earthquake-prone regions has made urban transformation an inevitable necessity. Transformation policies, which have been on the agenda since the 1980s, aim to reduce disaster risks and foster more habitable, sustainable and socially equitable urban environments. This study examines the spatial, social and economic dimensions of urban transformation through the Aksa Park and Akıncı Park projects implemented in the Karatay district of Konya. Findings based on document analysis and field investigations indicate that transformation projects are not limited to physical redevelopment; they also contribute to the reduction of social inequalities, enhancement of quality of life and strengthening of residents' place attachment. Furthermore, the study emphasizes that property should not be considered solely as a physical asset but rather as a socio-spatial construct encompassing social relations, neighborhood memory and everyday spatial practices. In conclusion, the findings underscore the necessity of adopting holistic planning approach that integrates the physical, social, cultural and environmental dimensions of urban transformation processes.Article Citation - WoS: 1Citation - Scopus: 1Determining Future Scenarios of Urban Areas With Cellular Automata/Markov Chain Model Method(Springer Science and Business Media Deutschland GmbH, 2024-04-16) Aydın, T.K.; Durduran, S.S.As a result of the rapid increase in the world population, the earth surface has started to be damaged due to natural and artificial effects. The extent of the damage to nature can be determined by examining the temporal changes of land use and land cover (LULC). In order to offer healthier and more sustainable living spaces, scientists have produced many studies on the changes in nature. Within the scope of this study, 5 basic training classes were created with the help of Landsat satellite images and CORINE data, covering the period of 1985–2018 for Ereğli-Bor Sub-Basin, which is one of the 9 sub-basins of Konya Closed Basin located in the Central Anatolian Region of Türkiye. Landsat Satellite images, Google Earth Program and CORINE data were overlaid to create a basic training class as artificial areas, agricultural areas—pasture areas—forest areas and wetlands and these areas were classified by supervised classification method. The study was carried out on an area of approximately 331057 ha in and around Ereğli district. Modeling was carried out with the Cellular Automata (CA) Markov Chain Model to determine the urban development potential in the region. In order to estimate the modeling accuracy, the 2018 prediction model was created according to the 2018 reference map, and the validation between the two data was analyzed with the kappa statistics. According to kappa statistics values, it was determined that K_location and K_standard values were 0.9301 and 0.8935, respectively. As a result of the validation in sufficient standards, future prediction models were appliedArticle Citation - WoS: 3Determining Future Scenarios of Urban Areas With Cellular Automata/Markov Chain Model Method; Example of Ereğli District Konya-Türkiye (2030-2040)(Springer Heidelberg, 2024) Aydın, Taha Kağan; Durduran, S. SavasAs a result of the rapid increase in the world population, the earth surface has started to be damaged due to natural and artificial effects. The extent of the damage to nature can be determined by examining the temporal changes of land use and land cover (LULC). In order to offer healthier and more sustainable living spaces, scientists have produced many studies on the changes in nature. Within the scope of this study, 5 basic training classes were created with the help of Landsat satellite images and CORINE data, covering the period of 1985-2018 for Ere & gbreve;li-Bor Sub-Basin, which is one of the 9 sub-basins of Konya Closed Basin located in the Central Anatolian Region of T & uuml;rkiye. Landsat Satellite images, Google Earth Program and CORINE data were overlaid to create a basic training class as artificial areas, agricultural areas-pasture areas-forest areas and wetlands and these areas were classified by supervised classification method. The study was carried out on an area of approximately 331057 ha in and around Ere & gbreve;li district. Modeling was carried out with the Cellular Automata (CA) Markov Chain Model to determine the urban development potential in the region. In order to estimate the modeling accuracy, the 2018 prediction model was created according to the 2018 reference map, and the validation between the two data was analyzed with the kappa statistics. According to kappa statistics values, it was determined that K_location and K_standard values were 0.9301 and 0.8935, respectively. As a result of the validation in sufficient standards, future prediction models were applied; future models and result maps were prepared for the years 2030-2040. According to the modeling results, it is estimated that the artificial area class in Ere & gbreve;li district will reach 122.74 km2 by 2030 and 142.24 km2 in 2040. In addition, it was expressed in detail with the prediction results and maps that there will be a decrease in pasture, forest and agricultural areas in the region until 2030 and 2040. As a result, it is predicted that the ecological balance in the region will change and agricultural production may decrease as a result of the decline in agricultural pasture and forest areas. For this reason, it has been revealed that it is important for the future of humanity that plans such as environmental layout and master development plans to be made by regional manager in the region for the future should be planned in line with the results to be obtained as a result of future prediction models.Article Optimum Location Selection for Photovoltaic Power Plants Based on Best-Worst Method: Example of Karatay District Konya, Türkiye(John Wiley and Sons Inc, 2025-12-29) Aydın, T.K.Türkiye is a sunny region with very high potential for electricity generation from solar energy. This study identifies the most suitable areas for photovoltaic (PV) power plants in the Karatay district of Konya province using a combination of GIS (Geographical Information System) and the Best Worst Method (BWM). Based on the weighting of seven criteria (land use, proximity to existing transmission lines, proximity to residential areas, distance to the road network, slope, land aspect, elevation map), pairwise comparisons yielded a CR (ξ*) of 0.0863514. The regional distribution of suitable areas was calculated as 16,982.87 ha (6.04%) very suitable, 68,516.53 ha (24.38%) suitable, and 31,147.46 ha (11.08%) less suitable, while 164,143.23 ha (58.41%) were unsuitable. The most influential criteria were land use (C1) and aspect (C6), with a weight value of 0.30 (30%). BWM enables two-sided comparisons using less data than other methods, increasing the reliability of results under uncertainty and producing more qualified outputs in location selection. The region's flat topography with high annual solar potential highlights the methodological novelty of the study. Elevation was the least effective factor, whereas land use was the most significant. Given the strong agricultural and livestock sectors, ensuring that PV facilities do not compromise these activities is critical, as establishing them on fertile lands may threaten food security and ecosystems. The quantified distribution of suitability classes and relative importance of criteria provide practical guidance for decision-makers (municipalities, private sector, energy investors, etc.), helping prioritize suitable areas while minimizing conflicts with agricultural and environmental values. © 2025 American Institute of Chemical Engineers.
Research Topics
Domains
Physical SciencesSocial Sciences
Fields
Environmental ScienceSocial SciencesComputer Science
Subfields
Global and Planetary ChangeManagement, Monitoring, Policy and LawHealth, Toxicology and MutagenesisSociology and Political ScienceArtificial IntelligenceEcology
Specific Research Areas
Land Use and Ecosystem Services
Soil and Land Suitability Analysis
Urban Green Space and Health
Disaster Management and Resilience
Solar Radiation and Photovoltaics
Wildlife-Road Interactions and Conservation
Sustainable Development Goals
11SUSTAINABLE CITIES AND COMMUNITIES
4
Research Products
15LIFE ON LAND
2
Research Products
2ZERO HUNGER
2
Research Products
10REDUCED INEQUALITIES
1
Research Products
7AFFORDABLE AND CLEAN ENERGY
1
Research Products
17PARTNERSHIPS FOR THE GOALS
1
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
Documents
2
Citations
1
h-index
1
Documents
1
Citations
1
Publication Collaboration
| Affiliation Name | Count |
|---|---|
| Konya Technical University | 4 |
| Necmettin Erbakan University | 2 |
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Data obtained from OpenAlex
| Journal | Count |
|---|---|
| Earth science informatics | 1 |
| Earth Science Informatics | 1 |
| Environmental Progress & Sustainable Energy | 1 |
| Geomatik | 1 |
| Turkish Journal of Remote Sensing | 1 |
Current Page: 1 / 1
Scholarly Output
5
Articles
5
Views / Downloads
6/0
Supervised MSc Theses
0
Supervised PhD Theses
0
WoS Citation Count
4
Scopus Citation Count
1
Patents
0
Projects
0
WoS Citations per Publication
0.80
Scopus Citations per Publication
0.20
Open Access Source
4
Supervised Theses
0
Scopus Quartile Distribution
Competency Cloud
