UAV-mounted thermal camera and its analysis on urban surface textures

Year 2024, Volume: 9 Issue: 1, 49 - 60, 15.02.2024

Efdal Kaya , Arzu Erener

https://doi.org/10.26833/ijeg.1288990

Abstract

Temperature increase, especially global warming, can be observed depending on various factors which led to several severe environmental problems. Urban areas are the most effected places by this temperature increase. Urban heat concentration, the so-called heat island effect, is high in structural areas. This situation causes human life to be adversely affected. Therefore, constant measurement and analyses are required to assess outdoor thermal comfort and thermal stress in urban areas. Today, unmanned aerial vehicle (UAV) systems are used as a rapid data production technique in Earth observation activities. Thermal cameras integrated into UAV systems can monitor the temperature values in urban areas precisely and constantly. This study focuses on the potential application of a UAV-mounted thermal camera system at a local scale due to its rapid response to surface temperature variables. A thermal camera UAV system to measure the energy fluxes and temperatures from the earth’s surface, which are integral to understanding landscape processes and responses. Thus, UAV thermal sensors were used directly for different land cover types in and around the Faculty of Engineering building of Kocaeli University in Turkey. Derived UAV surface temperatures were compared with simultaneously acquired in situ temperature measurements. Simultaneous terrestrial temperature measurements were obtained by using TFA ScanTemp 410 model surface temperature meter. A high correlation between UAV surface temperatures and terrestrial measurements was utilized by Pearson correlation with a 0.94 coefficient. It was concluded that the UAV-mounted thermal camera system is a promising tool that has increased opportunities to understand surface temperature variability at high spatial and temporal resolution.

Keywords

Thermal UAV, Remote Sensing, Pearson Correlation, Urban heat, Surface temperature

Project Number

FDK-2021-2183

References

• Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., ... & Sobrino, J. A. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing of Environment, 131, 14-37. https://doi.org/10.1016/j.rse.2012.12.008
• Al Kafy, A., Al Rakib, A., Akter, K. S., Rahaman, Z. A., Jahir, D. M. A., Subramanyam, G., ... & Bhatt, A. (2021). The operational role of remote sensing in assessing and predicting land use/land cover and seasonal land surface temperature using machine learning algorithms in Rajshahi, Bangladesh. Applied Geomatics, 13(4), 793-816. https://doi.org/10.1007/s12518-021-00390-3
• Aneesha Satya, B., Shashi, M., & Deva, P. (2020). Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India. Applied Geomatics, 12, 281-290. https://doi.org/10.1007/s12518-020-00298-4
• Gabriele, M., Brumana, R., Previtali, M., & Cazzani, A. (2023). A combined GIS and remote sensing approach for monitoring climate change-related land degradation to support landscape preservation and planning tools: The Basilicata case study. Applied Geomatics, 15(3), 497-532. https://doi.org/10.1007/s12518-022-00437-z
• Hoque, I., & Lepcha, S. K. (2020). A geospatial analysis of land use dynamics and its impact on land surface temperature in Siliguri Jalpaiguri development region, West Bengal. Applied Geomatics, 12(2), 163-178. https://doi.org/10.1007/s12518-019-00288-1
• Moisa, M. B., & Gemeda, D. O. (2021). Analysis of urban expansion and land use/land cover changes using geospatial techniques: a case of Addis Ababa City, Ethiopia. Applied Geomatics, 13(4), 853-861. https://doi.org/10.1007/s12518-021-00397-w
• Ndossi, M. I., & Avdan, U. (2016). Inversion of land surface temperature (LST) using Terra ASTER data: a comparison of three algorithms. Remote Sensing, 8(12), 993. https://doi.org/10.3390/rs8120993
• Khanal, S., Fulton, J., & Shearer, S. (2017). An overview of current and potential applications of thermal remote sensing in precision agriculture. Computers and Electronics in Agriculture, 139, 22-32. https://doi.org/10.1016/j.compag.2017.05.001
• Kraaijenbrink, P. D. A., Shea, J. M., Pellicciotti, F., De Jong, S. M., & Immerzeel, W. W. (2016). Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. Remote Sensing of Environment, 186, 581-595. https://doi.org/10.1016/j.rse.2016.09.013
• Kim, D., Yu, J., Yoon, J., Jeon, S., & Son, S. (2021). Comparison of accuracy of surface temperature images from unmanned aerial vehicle and satellite for precise thermal environment monitoring of urban parks using in situ data. Remote Sensing, 13(10), 1977. https://doi.org/10.3390/rs13101977
• Tiwari, A., Sharma, S. K., Dixit, A., & Mishra, V. (2021). UAV remote sensing for campus monitoring: a comparative evaluation of nearest neighbor and rule-based classification. Journal of the Indian Society of Remote Sensing, 49, 527-539. https://doi.org/10.1007/s12524-020-01268-4
• Polat, N., & Uysal, M. (2018). An experimental analysis of digital elevation models generated with Lidar Data and UAV photogrammetry. Journal of the Indian Society of Remote Sensing, 46(7), 1135-1142. https://doi.org/10.1007/s12524-018-0760-8
• Sharma, M., Raghavendra, S., & Agrawal, S. (2021). Development of an open-source tool for UAV photogrammetric data processing. Journal of the Indian Society of Remote Sensing, 49, 659-664. https://doi.org/10.1007/s12524-020-01237-x
• Das, S., & Jain, G. V. (2022). Assessment and prediction of urban expansion using CA-based SLEUTH urban growth model: A case study of Kolkata Metropolitan area (KMA), West Bengal, India. Journal of the Indian Society of Remote Sensing, 50(12), 2277-2302. https://doi.org/10.1007/s12524-022-01602-y
• Vinod, P. V., Trivedi, S., Hebbar, R., & Jha, C. S. (2023). Assessment of Trees Outside Forest (TOF) in Urban Landscape Using High-Resolution Satellite Images and Deep Learning Techniques. Journal of the Indian Society of Remote Sensing, 51(3), 549-564. https://doi.org/10.1007/s12524-022-01646-0
• Zengin, M., Yilmaz, S., & Mutlu, B. E. (2019). Atatürk University Campus in terms of spatial thermal comfort analysis of thermal camera images. Atatürk Üniversitesi Ziraat Fakültesi Dergisi/Atatürk University Journal of Agricultural Faculty, 50(3), 239-247. https://doi.org/10.17097/ataunizfd.535209
• Gülten, A. A., & Aksoy, U. T. (2011). Kentsel bir alanda ısı dağılımının termal görüntüleme yöntemiyle incelenmesi. Engineering Sciences, 6(4), 1582-1589.
• Yalçıner, C. Ç., Gündoğdu, E., Kurban, Y. C., & Altunel, E. (2017). Eski Eserlerdeki Yapısal Tahribatların Termal Görüntüleme ve Mikrodalga Nem Ölçümleri ile Belirlenmesi: Ayasofya Müzesi Örnek Çalışması. Çanakkale Onsekiz Mart Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 3(2), 34-47. https://doi.org/10.28979/comufbed.346240
• Ünal, Ö., Koc, F., Okur, A. A., Okur, E., & Özdüven, M. L. (2018). Using thermal imaging camera technique to evaluation of the aerobic stability of corn and wheat silage. Alınteri Journal of Agriculture Science, 33(1), 55-63.
• Çamoğlu, G., & Genç, L. (2013). Taze Fasulyede Su Stresinin Belirlenmesinde Termal Görüntülerin ve Spektral Verilerin Kullanımı. COMU Journal of Agriculture Faculty, 1(1), 15-27.
• Küçüktopcu, E., & Cemek, B. (2020). Kümeslerdeki ısı kayıplarının termal kamerayla izlenmesi. Anadolu Tarim Bilimleri Dergisi, 35(3), 404-409. https://doi.org/10.7161/omuanajas.758342
• Çayli, A., Akyüz, A. D. İ. L., Baytorun, A. N., Üstün, S., & Boyaci, S. (2016). Determination of structural problems causing heat loss with the thermal camera in greenhouses. Kahramanmaraș Sütçü İmam Üniversitesi Doğa Bilimleri Dergisi, 19(1), 5-14.
• Akçay, Ö. (2021). Photogrammetric analysis of multispectral and thermal close-range images. Mersin Photogrammetry Journal, 3(1), 29-36.
• Durgut, A., & Akçay, Ö. (2016). Termal kamera ile ekran kartının 3 boyutlu modelinin oluşturulması. Anadolu University Journal of Science and Technology A-Applied Sciences and Engineering, 17(1), 51-63. https://doi.org/10.18038/btda.72883
• Gulci, S., & Akay, A. E. (2016). Using thermal infrared imagery produced by unmanned air vehicles to evaluate locations of ecological road structures. Journal of the Faculty of Forestry-Istanbul University. 66(2), 698-709. http://dx.doi.org/10.17099/jffiu.76461
• Wu, Y., Shan, Y., Lai, Y., & Zhou, S. (2022). Method of calculating land surface temperatures based on the low-altitude UAV thermal infrared remote sensing data and the near-ground meteorological data. Sustainable Cities and Society, 78, 103615. https://doi.org/10.1016/j.scs.2021.103615
• Feng, L., Liu, Y., Zhou, Y., & Yang, S. (2022). A UAV-derived thermal infrared remote sensing three-temperature model and estimation of various vegetation evapotranspiration in urban micro-environments. Urban Forestry & Urban Greening, 69, 127495. https://doi.org/10.1016/j.ufug.2022.127495
• Qin, L., Yan, C., Yu, L., Chai, M., Wang, B., Hayat, M., ... & Qiu, G. Y. (2022). High-resolution spatio-temporal characteristics of urban evapotranspiration measured by unmanned aerial vehicle and infrared remote sensing. Building and Environment, 222, 109389. https://doi.org/10.1016/j.buildenv.2022.109389
• Jiang, L., Zhan, W., Tu, L., Dong, P., Wang, S., Li, L., ... & Wang, C. (2022). Diurnal variations in directional brightness temperature over urban areas through a multi-angle UAV experiment. Building and Environment, 222, 109408. https://doi.org/10.1016/j.buildenv.2022.109408
• Kim, D., Yu, J., Yoon, J., Jeon, S., & Son, S. (2021). Comparison of accuracy of surface temperature images from unmanned aerial vehicle and satellite for precise thermal environment monitoring of urban parks using in situ data. Remote Sensing, 13(10), 1977. https://doi.org/10.3390/rs13101977
• Ağca, M., Gültekin, N., & Kaya, E. (2020). İnsansız hava aracından elde edilen veriler ile kaya düşme potansiyelinin değerlendirilmesi: Adam Kayalar örneği, Mersin. Geomatik, 5(2), 134-145. https://doi.org/10.29128/geomatik.595574
• Ulvi, A. (2018). Analysis of the utility of the unmanned aerial vehicle (UAV) in volume calculation by using photogrammetric techniques. International Journal of Engineering and Geosciences, 3(2), 43-49. https://doi.org/10.26833/ijeg.377080
• Ulvi, A., & Toprak, A. S. (2016). Investigation of three-dimensional modelling availability taken photograph of the unmanned aerial vehicle; sample of kanlidivane church. International Journal of Engineering and Geosciences, 1(1), 1-7. https://doi.org/10.26833/ijeg.285216
• Yakar, M., & Doğan, Y. (2017). Mersin Silifke Mezgit Kale Anıt Mezarı fotogrametrik rölöve alımı ve üç boyutlu modelleme çalışması. Geomatik, 2(1), 11-17. https://doi.org/10.29128/geomatik.296763
• Şasi, A., & Yakar, M. (2018). Photogrammetric modelling of hasbey dar'ülhuffaz (masjid) using an unmanned aerial vehicle. International Journal of Engineering and Geosciences, 3(1), 6-11. https://doi.org/10.26833/ijeg.328919
• Kusak, L., Unel, F. B., Alptekin, A., Celik, M. O., & Yakar, M. (2021). Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory mapping. Open Geosciences, 13(1), 1226-1244. https://doi.org/10.1515/geo-2020-0299
• Alptekin, A., & Yakar, M. (2021). 3D model of Üçayak Ruins obtained from point clouds. Mersin Photogrammetry Journal, 3(2), 37-40. https://doi.org/10.53093/mephoj.939079
• Mirdan, O., & Yakar, M. (2017). Tarihi eserlerin İnsansız Hava Aracı ile modellenmesinde karşılaşılan sorunlar. Geomatik, 2(3), 118-125. https://doi.org/10.29128/geomatik.306914
• Ulvi, A., Yakar, M., Yiğit, A. Y., & Kaya, Y. (2020). İha ve Yersel Fotogrametrik Teknikler Kullanarak Aksaray Kızıl Kilisenin 3B Modelinin ve Nokta Bulutunun Elde Edilmesi. Geomatik, 5(1), 19-26. https://doi.org/10.29128/geomatik.560179
• Degerli, B., & Çetin, M. (2022). Evaluation from rural to urban scale for the effect of NDVI-NDBI indices on land surface temperature, in Samsun, Türkiye. Turkish Journal of Agriculture-Food Science and Technology, 10(12), 2446-2452. https://doi.org/10.24925/turjaf.v10i12.2446-2452.5535
• Cetin, M. (2015). Using GIS analysis to assess urban green space in terms of accessibility: case study in Kutahya. International Journal of Sustainable Development & World Ecology, 22(5), 420-424. https://doi.org/10.1080/13504509.2015.1061066
• Cetin, M. (2016). Sustainability of urban coastal area management: A case study on Cide. Journal of Sustainable Forestry, 35(7), 527-541. https://doi.org/10.1080/10549811.2016.1228072
• Zeren Cetin, I., Varol, T., & Ozel, H. B. (2023). A geographic information systems and remote sensing–based approach to assess urban micro-climate change and its impact on human health in Bartin, Turkey. Environmental Monitoring and Assessment, 195(5), 540. https://doi.org/10.1007/s10661-023-11105-z
• Zeren Cetin, I., & Sevik, H. (2020). Investigation of the relationship between bioclimatic comfort and land use by using GIS and RS techniques in Trabzon. Environmental Monitoring and Assessment 192, 1-14. https://doi.org/10.1007/s10661-019-8029-4
• https://www.paksoyteknik.com.tr/paksoy-topcon/iha/parrot-anafi-thermal.html