INVESTIGATION OF THE SHADOW EFFECT OF URBANIZATION ON GREEN AREAS WITH SHADOW IMPACT ANALYSIS

Öz

Today, the use of information technologies has made life easier and helps people to take precautions against problems that may arise in the future. 3D Geographic Information Systems is also used for various purposes to facilitate human life today. One of these goals is to improve the foresight ability in plans. In the studies carried out until today, the power of 3D to produce solutions to various problems in the world is revealed. In this study, the effects of urban shadowing because of wrong urbanization have been investigated by using the power of 3D Geographic Information Systems. The data was provided via Open Street Map, which is an open-source map provider. The obtained data were analyzed and a park which is the surrounding area is not yet developed was determined. In the aim of the study, new buildings were added around the park by evaluating the direction of urban growth and possibilities, and the effect of the shadow it created on the sunbathing time of the park was investigated. It is obvious that social areas such as park areas are important for people to reach the sun they need. As a result, it is necessary to investigate the shadow effects of newly constructed buildings in order to increase the sunshine duration in the park areas.

Anahtar Kelimeler

• 3D GIS
• Shadow Impact Analysis
• Smart Cities
• Urban Development

Kaynakça

1. Şenol, H. İ., Ernst, F. B., & Akdağ, S., “Kentsel Dönüşüm Alanlarının Geotasarım Yöntemi ile Planlanması: Eyyübiye Örneği.” Harran Üniversitesi Mühendislik Dergisi, 3(3), 63-69, 2018.
2. Şenol, H. İ., & Kaya, Y., “İnternet Tabanlı Veri Kullanımıyla Yerleşim Alanlarının Modellenmesi: Çiftlikköy Kampüsü Örneği.” Türkiye Fotogrametri Dergisi, 1(1), 11-16, 2019.
3. Redweik, P., Catita, C., & Brito, M., “Solar energy potential on roofs and facades in an urban landscape.” Solar Energy, 97, 332–341, 2013.
4. Eicker, U., Monien, D., Duminil, É., & Nouvel, R., “Energy performance assessment in urban planning competitions.” Applied Energy, 155, 323–333, 2015.
5. Santos, T., Gomes, N., Freire, S., Brito, M. C., Santos, L., & Tenedório, J. A., “Applications of solar mapping in the urban environment.” Applied Geography, 51, 48–57, 2014.
6. Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., & Çöltekin, A., “Applications of 3D city models: State of the art review.” ISPRS International Journal of Geo-Information, 4(4), 2842–2889, 2015.
7. Gooding, J., Crook, R., & Tomlin, A. S., “Modelling of roof geometries from low-resolution LiDAR data for city-scale solar energy applications using a neighbouring buildings method.” Applied Energy, 148, 93–104, 2015.
8. Vermeulen, T., Knopf-Lenoir, C., Villon, P., & Beckers, B., “Urban layout optimization framework to maximize direct solar irradiation.” Computers, Environment and Urban Systems, 51, 1–12, 2015.

9. Aarsen, R., Janssen, M., Ramkisoen, M., Biljecki, F., Quak, W., & Verbree, E., “Installed base registration of decentralised solar panels with applications in crisis management.” The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(3), 219, 2015
10. Saran, S., Wate, P., Srivastav, S. K., & Krishna Murthy, Y. V. N., “CityGML at semantic level for urban energy conservation strategies.” Annals of GIS, 21(1), 27–41, 2015.
11. Köninger, A., & Bartel, S., “3D-GIS for urban purposes.” Geoinformatica, 2(1), 79–103, 1998.
12. Ellul, C., & Altenbuchner, J., “Investigating approaches to improving rendering performance of 3D city models on mobile devices.” Geo-Spatial Information Science, 17(2), 73–84, 2014.
13. Yiğit, A. Y., Orhan, O., & Ulvi, A., “Investigation of The Rainwater Harvesting Potential at the Mersin University, Turkey.” Mersin Photogrammetry Journal, 2(2), 64-75, 2020.
14. Buyuksalih, G., Bayburt, S., Baskaraca, A. P., Karim, H., & Rahman, A. A., “Calculating solar energy potential of buildings and visualization within unity 3d game engine.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42(4/W5), 2017.
15. Lonergan, C., & Hedley, N., “Unpacking isovists: a framework for 3D spatial visibility analysis.” Cartography and Geographic Information Science, 43(2), 87–102, 2016.
16. Peters, R., Ledoux, H., & Biljecki, F., “Visibility Analysis in a Point Cloud Based on the Medial Axis Transform.” UDMV, 7–12, 2015.
17. Zhou, K., Lindenbergh, R., & Gorte, B., “Automatic shadow detection in urban very-high-resolution images using existing 3D models for free training.” Remote Sensing, 11(1), 72, 2019.
18. Strzalka, A., Alam, N., Duminil, E., Coors, V., & Eicker, U., “Large scale integration of photovoltaics in cities.” Applied Energy, 93, 413–421, 2012.
19. Memduhoglu, A., & Basaraner, M., “An approach for multi-scale urban building data integration and enrichment through geometric matching and semantic web.” Cartography and Geographic Information Science, 49(1), 1-17, 2022.
20. Smelik, R. M., Tutenel, T., Bidarra, R., & Benes, B., “A survey on procedural modelling for virtual worlds.” In Computer Graphics Forum, 33(6), 31-50, 2014.
21. Besuievsky, G., & Patow, G., “Customizable lod for procedural architecture.” In Computer Graphics Forum, 32(8), 26-34, 2013.
22. Gaisbauer, W., Prohaska, J., Schweinitzer, U., & Hlavacs, H., “Endless city driver: procedural generation of realistic populated virtual 3D city environment.” In Augmented Reality and Virtual Reality, pp. 171-184, 2020.
23. Sani, M. J., & Rahman, A. A., “GIS and BIM integration at data level: A review.” The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 299-306, 2018.