Yer Yüzey Sıcaklığı (LST) ve Normalleştirilmiş Fark Bitki Örtüsü (NDVI) Arasındaki İlişkinin Değerlendirilmesi

Öz

Gün geçtikçe artan iklim değisikliği ve etkileri hayatı olumsuz etkilemektedir. Dünya ortalama sıcaklığı artmakta ve yağış rejimi iklim değisikliği etkileri ile değişmektedir. Bu çalışmada 2013-2018 ve 2023 yılları için Muş ili özelinde yer yüzey sıcaklıklarındaki (LST) değişimler ve normalleştirilmiş fark bitki örtüsü indeksi (NDVI) hesaplamaları yapılmış ve haritalandırılmıştır. Elde edilen NDVI ve LST sonuçları karşılaştırılmış ve korelasyon analizi yapılmıştır. 2018 yılında en yüksek LST değerleri elde edilmiştir. Çalışma alanının özellikle güneybatısı ve kuzeybatısında NDVI değerlerine göre daha fazla bitki örtüsüne sahip olduğu görülmüştür. LST değerlerinin ortalama sıcaklıktaki değişimle paralel sonuçlar gösterdiği, örneğin ortalama sıcaklığın 2018 yılında arttığı, 2023 yılında ise düştüğü, LST değerlerinde de aynı sonuçların gözlendiği görülmüştür. Oluşturulan uzay mekansal haritalar incelendiğinde NDVI değerinin düşük olduğu bölgelerde LST değerlerinin daha yüksek olduğu gözlense de, NDVI ve LST arasında çalışma periyodu süresince güçlü bir korelasyon gözlenmemiştir. Bu çalışma ile Muş ilindeki bitki örtüsü ve toprak sıcaklığındaki değişimler bölgesel ölçekte incelenebilecek ve gerekli tedbirler alınmasında faydalı olacaktır.

Anahtar Kelimeler

• Yer Yüzey Sıcaklığı (LST)
• Normalleştirilmiş Fark Bitki Örtüsü (NDVI)
• Uzaktan Algılama
• Landsat 8

Evaluating the Correlation Between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI)

Öz

Climate change and its effects, which are increasing day by day, and adversely affect the human life. The world's average temperature trend is tend to increase and the precipitation regime is changing with the effects of climate change. In this study, changes in Land Surface Temperature and Normalized Difference Vegetation Index were calculated and mapped in Mus province for the years 2013-2018 and 2023. The obtained NDVI and LST results were compared and correlation analysis was performed. The highest values of LST were obtained in the year 2018. It was observed that the study area had more vegetation, especially in the southwest and northwest, according to NDVI values. It was observed that LST values demonstrated parallel results with the change in average temperature. For example, the average temperature increased in 2018, and decreased in 2023 and the same results were observed for the LST values. When the spatial-temporal maps were examined, it was observed that LST values were higher in regions where NDVI values were low, but a strong correlation between NDVI and LST was not observed during the study period. With this study, changes in vegetation and land surface temperature in Mus province can be examined on a regional scale and will be useful in taking necessary precautions.

Anahtar Kelimeler

• Land surface temperature (LST)
• Normalized Difference Vegetation Index (NDVI)
• Remote sensing
• Landsat 8

Kaynakça

1. Acar, R. (2024). Evaluation of Susurluk Basin Flows Using Trend Analysis Methods. Firat University Journal of Experimental and Computational Engineering, 3(1), 65–74. https://doi.org/10.62520/fujece.1421090.
2. Amiri, R., Weng, Q., Alimohammadi, A., & Alavipanah, S. K. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113(12), 2606–2617. https://doi.org/10.1016/j.rse.2009.07.021.
3. Anbazhagan., S., & Paramasivam., C. . (2016). Statistical Correlation between Land Surface Temperature (LST) and Vegetation Index (NDVI) using Multi-Temporal Landsat TM Data. International Journal of Advanced Earth Science and Engineering, 5(1), 333–346. https://doi.org/10.23953/cloud.ijaese.204.
4. Balcik, F. B. (2014). Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices. Environmental Modelling and Assessment, 186, 859–872. https://doi.org/10.1007/s10661-013-3427-5.
5. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. https://doi.org/https://doi.org/10.4324/9780203771587.
6. Eckert, S., Hüsler, F., Liniger, H., & Hodel, E. (2015). Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia. Journal of Arid Environments, 113, 16–28. https://doi.org/10.1016/j.jaridenv.2014.09.001.
7. Gorgani Sara, A., Panahi, M., & Rezaie, F. (2013). The Relationship between NDVI and LST in the urban area of Mashhad, Iran. International Conference on Civil Engineering Architecture & Urban Sustainable Development, November. https://www.researchgate.net/publication/265601825_The_Relationship_between_NDVI_and_LST_in_the_urban_area_of_Mashhad_Iran.
8. Guha, S. (2021). Dynamic seasonal analysis on LST-NDVI relationship and ecological health of Raipur City, India. Ecosystem Health and Sustainability, 7(1). https://doi.org/10.1080/20964129.2021.1927852.

9. Guha, S., & Govil, H. (2021). An assessment on the relationship between land surface temperature and normalized difference vegetation index. Environment, Development and Sustainability, 23(2), 1944–1963. https://doi.org/10.1007/s10668-020-00657-6.
10. Jafari, R., & Hasheminasab, S. (2017). Assessing the effects of dam building on land degradation in central Iran with Landsat LST and LULC time series. Environmental Monitoring and Assessment, 189(2). https://doi.org/10.1007/s10661-017-5792-y.
11. Julien, Y., Sobrino, J. A., Mattar, C., Ruescas, A. B., Jiménez-Muñoz, J. C., Sòria, G., Hidalgo, V., Atitar, M., Franch, B., & Cuenca, J. (2011). Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001.
12. International Journal of Remote Sensing, 32(7), 2057–2068. https://doi.org/10.1080/01431161003762363 Jung, M., & Chang, E. (2015). NDVI-based land-cover change detection using harmonic analysis. International Journal of Remote Sensing, 36(4), 1097–1113. https://doi.org/10.1080/01431161.2015.1007252.
13. Korkmaz, M. (2022). Yozgİli̇ni̇n Kuraklik Araştirmasi Ve TrenAnali̇zi̇. Engineering Sciences, 17(3), 21–34. https://doi.org/10.12739/nwsa.2022.17.3.1a0479.
14. Li, W., Cao, Q., Lang, K., & Wu, J. (2017). Linking potential heat source and sink to urban heat island : Heterogeneous effects of landscape pattern on land surface temperature. Science of the Total Environment, 586, 457–465. https://doi.org/10.1016/j.scitotenv.2017.01.191.
15. Li, Z., Tang, B., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A. (2013). Remote Sensing of Environment 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.
16. Li, Z., Wu, H., Duan, S., Zhao, W., Ren, H., & Liu, X. (2022). Satellite Remote Sensing of Global Land Surface Temperature : Definition , Methods , Products , and Applications. Reviews of Geophysics, 61, 1–77. https://doi.org/10.1029/2022RG000777.
17. Marzban, F., Sodoudi, S., & Preusker, R. (2018). The influence of land-cover type on the relationship between NDVI–LST and LST-Tair. International Journal of Remote Sensing, 39(5), 1377–1398. https://doi.org/10.1080/01431161.2017.1402386.
18. Mercan, Ç. (2020). Yer Yüzey Sıcaklığının Termal Uzaktan Algılama Görüntüleri ile Araştırılması: Muş İli Örneği. Türkiye Uzaktan Algılama Dergisi, 2(2), 42–49. https://dergipark.org.tr/tr/pub/tuzal.
19. Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502.
20. Orhan, O., Ekercin, S., & Dadaser-Celik, F. (2014). Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area , Turkey. The Scientific World Journal, 2014. https://doi.org/http://dx.doi.org/10.1155/2014/142939.
21. Sahebjalal, E., & Dashtekian, K. (2013). Analysis of land use-land covers changes using normalized difference vegetation index ( NDVI ) differencing and classification methods. African Journal of Agricultural Research, 8(37), 4614–4622. https://doi.org/10.5897/AJAR11.1825.
22. Sekertekin, A., & Kutoglu, S. H. (2016). Evaluation of spatio-temporal variability in Land Surface Temperature : A case study of Zonguldak , Turkey. Environmental Monitoring and Assessment, 188. https://doi.org/10.1007/s10661-015-5032-2.
23. Song, J., Du, S., Feng, X., & Guo, L. (2014). The relationships between landscape compositions and land surface temperature: Quantifying their resolution sensitivity with spatial regression models. Landscape and Urban Planning, 123, 145–157. https://doi.org/10.1016/j.landurbplan.2013.11.014.
24. Sruthi, S., & Aslam, M. A. M. (2015). Agricultural Drought Analysis Using the NDVI and Land Surface Temperature Data; a Case Study of Raichur District. Aquatic Procedia, 4(Icwrcoe), 1258–1264. https://doi.org/10.1016/j.aqpro.2015.02.164.
25. Sun, D., & Kafatos, M. (2007). Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America. Geophysical Research Letters, 34(24), 1–4. https://doi.org/10.1029/2007GL031485.
26. Tan, J., Yu, D., Li, Q., Tan, X., & Zhou, W. (2020). Spatial relationship between land-use / land-cover change and land surface temperature in the Dongting Lake area , China. Scientific Reports, 10(9245), 1–9. https://doi.org/10.1038/s41598-020-66168-6.
27. Tan, K. C., Lim, H. S., MatJafri, M. Z., & Abdullah, K. (2012). A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery. Environmental Monitoring and Assessment, 184(6), 3813–3829. https://doi.org/10.1007/s10661-011-2226-0.
28. Tomlinson, C. J., Chapman, L., Thornes, J. E., & Baker, C. (2011). Remote sensing land surface temperature for meteorology and climatology: A review. Meteorological Applications, 18(3), 296–306. https://doi.org/10.1002/met.287.
29. Tonyaloğlu, E. E. (2019). Kentleşmenin Kentsel Termal ÇevrÜzeri̇ndekEtki̇si̇niDeğerlendi̇ri̇lmesi̇, Efeler İnci̇rli̇ova (Aydin)Örneği̇. Turkish Journal of Landscape Research, 2(1), 1–13.
30. Ullah, W., Ahmad, K., Ullah, S., Tahir, A. A., Javed, M. F., Nazir, A., Abbasi, A. M., Aziz, M., & Mohamed, A. (2023). Analysis of the relationship among land surface temperature (LST), land use land cover (LULC), and normalized difference vegetation index (NDVI) with topographic elements in the lower Himalayan region. Heliyon, 9(2), e13322. https://doi.org/10.1016/j.heliyon.2023.e13322.
31. Wang, Y. (2010). Dynamics of Land Surface Temperature in Response to Land-Use / Cover Change. Geographical Research, 49(1), 23–36. https://doi.org/10.1111/j.1745-5871.2010.00686.x.
32. Yücer, E. (2023). Albedo, Yer Yüzey Sıcaklığı Ve Ndvı Arasındaki İlişkinin Landsat-7 Ve Landsat-8 Uydu Verileri Kullanılarak İncelenmesi: Safranbolu Örneği. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 26(1), 177–190.