APPLICATION OF REMOTE SENSING AND GIS TECHNOLOGIES IN SURFACE TEMPERATURE OF MOUNTAIN LANDSCAPES
U.Sh. Gasimova
qulviyesh@gmail.com
DOI: 10.59423/gnr.2024.11.37.008
Annotation. In recent years, due to global climate change, there have been certain changes in the temperature indicators of the soil surface cover. These changes were especially evident in the highlands. The main reason for this is the increase of the land area due to the shrinking of the areas with the melting of the glaciers, which has led to an increase in the temperature on the earth’s surface. The increase in temperature on the soil surface has increased the degradation of summer pastures. In the presented article, the results of the study of surface temperature in the natural landscapes located in the southeast of the high mountain part of the Greater Caucasus were analyzed. At that time, modern methods and methods were used. Satellite images of the research area taken from the Landsat 9 satellite and related to June 2024 were analyzed in the ArcGIS program. Bands 4, 5 and 10 were used in the study. Bands 4 and 5 were used in the vegetation study, and band 10 was used in other analyses. It was determined that the area’s vegetation has an important role in changing the surface temperature.
Keywords: GIS, climate, temperature, high altitu-de, surface temperature, NDVI, Landsat 9.
References
- Abdul G.F., Al-Shehhi M.R., Cho C.S., Ghedira H. Gradient Boosting and Linear Regression for Estimating Coastal Bathymetry Based on Sentinel-2 Images. Remote Sens., 14, 2022, pp. 5037.
- Cai J., Luo J., Wang S., Yang S. Feature selection in machine learning: A new perspective. Neuro-computing, 2018, 300, pp. 70–79.
- Li Z.L., Wu H., Duan S.B., Zhao W. Satellite remote sensing of global land surface temperature: Definition, methods, products, and applications. Rev. Geophys., 61, 2023, pp. e2022RG000777
- Masek J.G., Michael A.W., Brian M., Joel M. Landsat 9: Empowering open science and applications through continuity. Remote Sensing of Environment 248, 2020, pp. 111968. doi: https://doi.org/10.1016/j.rse.2020.111968
- Ren H., Ye X., Liu R., Dong J., Qin Q. Improving land surface temperature and emissivity retrieval from the Chinese Gaofen-5 satellite using a hybrid algorithm. IEEE Trans. Geosci. Remote Sens. 56, 2018, pp. 1080–1090
- Ye X., Ren H., Liang Y., Zhu J., Guo J., Nie J. Cross-calibration of Chinese Gaofen-5 thermal infrared images and its improvement on land surface temperature retrieval. Int. J. Appl. Earth Obs. Geoinf. 101, 2021, pp. 102357
- Ye X., Ren H., Nie J., Hui J., Jiang C. Simultaneous Estimation of Land Surface and Atmospheric Parameters From Thermal Hyperspectral Data Using a LSTM-CNN Combined Deep Neural Network. IEEE Geosci. Remote Sens. Lett. 19, 2022, pp. 1–5
- Wang M., Zhang Z., Hu T., Liu X.A Practical Single-Channel Algorithm for Land Surface Temperature Retrieval: Application to Landsat series data. J. Geophys. Res. Atmos. 124, 2019, pp. 299–316
- Zhang, Y.; Liu, J.; Shen, W. A Review of Ensemble Learning Algorithms Used in Remote Sensing Applications. Appl. Sci. 2022, 12, 8654.
- Zhu X., Duan S., Li Z-L., Zhao W., Wu H. Retrieval of land surface temperature with topographic effect correction from Landsat 8 thermal infrared data in mountainous areas. IEEE Trans. Geosci. Remote Sens. 59, 2020, pp. 6674–6687
Accepted for publication: November 15, 2024
Download article
U.Sh. Gasimova – Applicatıon of remote sensing and GIS technologies in surface temperature of mountain landscapes. Geography and Natural Resources, №2 (22), 2024, pp. 47-51.
