A Python-Based Application for Retrieving Land Surface Temperature (LST) from Landsat Imagery
Subject Areas : Natural resources and environmental managementzahra parvar 1 , عبدالرسول سلمان ماهینی 2
1 - PhD student ,Environmental science and engineering, Faculty of Fisheries and Environmental Science, Department of Environmental Science, Gorgan University of Agricultural Sciences and Natural Resources.
2 - دانشگاه علوم کشاورزی و منابع طبیعی گرگان- دانشکده شیلات و محیط زیست- گروه محیط زیست
Keywords: Radiative Transfer Equation, Split window algorithm, Single Channel Algorithm, remote sensing, Mono Window Algorithms,
Abstract :
Abstract LST (land surface temperature) derived from thermal infrared remote sensing images is directly related to land use and land cover changes. Remote sensing, as an irreplaceable method to obtain LST at global and regional scales, enables effective monitoring of LST with Spatio-temporal continuity. LST helps in separating urban areas from bare areas and improves land use/cover generation through classification of remotely sensed imagery. In this study, a Python-based user interface was developed to make land surface temperature retrieval easier and faster. LST can be retrieved by inputting required parameters in different methods such as Single Channel Algorithm (SCA), Radiative Transfer Equation (RTE) method, Split Window Algorithm (SWA), and two Mono Window Algorithms (MWA), from Landsat missions (Landsat 5, 7, and 8). Comparing the results in this study showed that RTE and SCA with root mean square error (RMSE) equal to 3.76 and 8.97 degrees Celsius had the highest and lowest accuracy. LST is affected by atmospheric particulate matter, land cover and urban morphology. Various methods of LST retrieval consider surface temperature, water vapor and other atmospheric factors. The developed user interface helps researchers and managers in monitoring land surface temperature change through time as affected by land use/cover, especially urban land use
1. Barsi J A, Schott J R, Hook S J, Raqueno N G, Markham B L and Radocinski R G. 2014. Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration. Remote Sensing, 6(11), 11607-11626. Retrieved from.
2. Cheng J, Meng X, Dong S and Liang S. 2021. Generating the 30-m land surface temperature product over continental China and USA from landsat 5/7/8 data. Science of Remote Sensing, 4: 100032, doi https://doi.org/10.1016/j.srs.2021.100032.
3. Cristóbal J, Jiménez-Muñoz J C, Prakash A, Mattar C, Skoković D and Sobrino J A. 2018. An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band. Remote Sensing, 10(3), doi 10.3390/rs10030431.
4. Diaz L R, Santos D C, Käfer P S, Rocha N S, Costa S T, Kaiser E A and Rolim S B. 2021. Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model. Atmosphere, 12(11), doi 10.3390/atmos12111436.
5. Doxani G, Vermote E F, Roger J-C, Skakun S, Gascon F, Collison A, De Keukelaere L, Desjardins C, Frantz D, Hagolle O, Kim M, Louis J, Pacifici F, Pflug B, Poilvé H, Ramon D, Richter R and Yin F. 2023. Atmospheric Correction Inter-comparison eXercise, ACIX-II Land: An assessment of atmospheric correction processors for Landsat 8 and Sentinel-2 over land. Remote Sensing of Environment, 285: 113412, doi https://doi.org/10.1016/j.rse.2022.113412.
6. Ebrahimi A, Motamedvaziri B, Nazemosadat S M J and Ahmadi H. 2020. Assessing the relationship between land surface temperature with vegetation and water area change in Arsanjan county, Iran. Journal of RS and GIS for Natural Resources, 11(4): 65-86, doi dorl.net/dor/20.1001.1.26767082.1399.11.4.4.4. (In Persian).
7. Fekrat H, Asghari Saraskanrood S and Alavipanah S K. 2020. Estimation of Ardabil land surface temperature using Landsat images and accuracy assessment of land surface temperature estimation methods with ground truth data. Journal of RS and GIS for Natural Resources, 11(4): 114-136, doi dorl.net/dor/20.1001.1.26767082.1399.11.4.6.6. (In Persian).
8. Guo A, Yang J, Sun W, Xiao X, Xia Cecilia J, Jin C and Li X. 2020. Impact of urban morphology and landscape characteristics on spatiotemporal heterogeneity of land surface temperature. Sustainable Cities and Society, 63: 102443, doi https://doi.org/10.1016/j.scs.2020.102443.
9. Isaya Ndossi M and Avdan U. 2016. Application of Open Source Coding Technologies in the Production of Land Surface Temperature (LST) Maps from Landsat: A PyQGIS Plugin. Remote Sensing, 8(5), doi 10.3390/rs8050413.
10. Jimenez-Munoz J and Sobrino J A. 2008. Split-Window Coefficients for Land Surface Temperature Retrieval From Low-Resolution Thermal Infrared Sensors. IEEE Geoscience and Remote Sensing Letters, 5(4): 806-809, doi 10.1109/LGRS.2008.2001636.
11. Jiménez-Muñoz J C, Sobrino J A, Skoković D, Mattar C and Cristóbal J. 2014. Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data. IEEE Geoscience and Remote Sensing Letters, 11(10): 1840-1843, doi 10.1109/LGRS.2014.2312032.
12. Malakar N K, Hulley G C, Hook S J, Laraby K, Cook M and Schott J R. 2018. An Operational Land Surface Temperature Product for Landsat Thermal Data: Methodology and Validation. IEEE Transactions on Geoscience and Remote Sensing, 56(10): 5717-5735, doi 10.1109/TGRS.2018.2824828.
13. Meng X, Cheng J, Zhao S, Liu S and Yao Y. 2019. Estimating Land Surface Temperature from Landsat-8 Data using the NOAA JPSS Enterprise Algorithm. Remote Sensing, 11(2), doi 10.3390/rs11020155.
14. Nugraha A S, Gunawan T and Kamal M. 2019. Comparison of Land Surface Temperature Derived From Landsat 7 ETM+ and Landsat 8 OLI/TIRS for Drought Monitoring. IOP Conference Series: Earth and Environmental Science, 313: 012041, doi 10.1088/1755-1315/313/1/012041.
15. Parvar Z, Mohammadzadeh M and Saeidi S. 2022. Effects of Land Use and Land Morphology on Land Surface Temperature: A Case Study for Bojnourd City, North Khorasan. Journal of RS and GIS for Natural Resources, doi 10.30495/girs.2022.1973023.2021 . (In Persian).
16. Qin Z, Karnieli A and Berliner P. 2001. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22(18): 3719-3746, doi 10.1080/01431160010006971.
17. Rongali G, Keshari A K, Gosain A and Khosa R. 2017. A Mono-Window Algorithm for Land Surface Temperature Estimation from Landsat 8 Thermal Infrared Sensor Data.
18. Rongali G, Keshari A K, Gosain A K and Khosa R. 2018. Split-Window Algorithm for Retrieval of Land Surface Temperature Using Landsat 8 Thermal Infrared Data. Journal of Geovisualization and Spatial Analysis, 2(2): 14, doi 10.1007/s41651-018-0021-y.
19. Sekertekin A and Bonafoni S. 2020. Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sensing, 12(2), doi 10.3390/rs12020294.
20. Soydan O. 2020. Effects of landscape composition and patterns on land surface temperature: Urban heat island case study for Nigde, Turkey. Urban Climate, 34: 100688, doi https://doi.org/10.1016/j.uclim.2020.100688.
21. Tanjina Hasnat G N. 2022. Assessment of spatiotemporal distribution pattern of land surface temperature with incessant urban sprawl over Khulna and Rajshahi City Corporations. Environmental Challenges, 9: 100644, doi https://doi.org/10.1016/j.envc.2022.100644.
22. Wang M, He G, Zhang Z, Wang G, Wang Z, Yin R, Cui S, Wu Z and Cao X. 2019. A radiance-based split-window algorithm for land surface temperature retrieval: Theory and application to MODIS data. International Journal of Applied Earth Observation and Geoinformation, 76: 204-217, doi https://doi.org/10.1016/j.jag.2018.11.015.
23. Xu X, Pei H, Wang C, Xu Q, Xie H, Jin Y, Feng Y, Tong X and Xiao C. 2023. Long-term analysis of the urban heat island effect using multisource Landsat images considering inter-class differences in land surface temperature products. Science of The Total Environment, 858: 159777, doi https://doi.org/10.1016/j.scitotenv.2022.159777.
24. Yang J, Zhou J, Göttsche F-M, Long Z, Ma J and Luo R. 2020. Investigation and validation of algorithms for estimating land surface temperature from Sentinel-3 SLSTR data. International Journal of Applied Earth Observation and Geoinformation, 91: 102136, doi https://doi.org/10.1016/j.jag.2020.102136.
25. Yeneneh N, Elias E and Feyisa G L. 2022. Detection of land use/land cover and land surface temperature change in the Suha Watershed, North-Western highlands of Ethiopia. Environmental Challenges, 7: 100523, doi https://doi.org/10.1016/j.envc.2022.100523.
26. Yu X, Guo X and Wu Z. 2014. Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method. Remote Sensing, 6(10), doi 10.3390/rs6109829.
