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Year 2022, Volume: 9 Issue: 2, 54 - 59, 02.06.2022
https://doi.org/10.30897/ijegeo.820906

Abstract

References

  • Avdan, U., & Jovanovska, G. (2016). Algorithm for Avdan, U., & Jovanovska, G. (2016). Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data. 2016.
  • Department of the Interior U.S. Geological Survey. (2016). Landsat 8 Data Users Handbook. Nasa, 8(June),97.Retrieved from https://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf
  • Guillevic, P., Göttsche, F., Nickeson, J., Hulley, G., Ghent, D., Yu, Y., … Camacho, F. (2018). Land surface temperature product validation best practice protocol version 1.1. Best Practice for Satellite-Derived Land Product Validation (p. 60): Land Product Validation Subgroup (WGCV/CEOS), doi(January), 58. https://doi.org/10.5067/doc/ceoswgcv/lpv/lst.001.
  • Ibrahim, M., & Abu-mallouh, H. (2018). Estimate Land Surface Temperature in Relation to Land Use Types and Geological Formations Using Spectral Remote Sensing Data in Northeast Jordan. 2018, 174–185. https://doi.org/10.4236/ojg.2018.82011.
  • Jeevalakshmi, D., Narayana Reddy, S., & Manikiam, B. (2017). Land surface temperature retrieval from LANDSAT data using emissivity estimation. International Journal of Applied Engineering Research, 12(20), 9679–9687.
  • OGUZ, H. (2017). Automated Land Surface Temperature Retrieval From Landsat 8 Satellite Imagery: a Case Study of Diyarbakir - Turkey. Turkish Journal of Forest Science, 1(1), 33–43. https://doi.org/10.32328/turkjforsci.296845.
  • Orhan, O., & Yakar, M. (2016). Investigating land surface temperature changes using Landsat data in Konya, Turkey. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 285–289. https://doi.org/10.5194/isprsarchives-XLI-B8-285-2016.
  • Sun, Y. (2008). Retrieval and Application of Land Surface Temperature. Geo.Utexas.Edu, 1(1), 1–27. Retrieved from http://www.geo.utexas.edu/courses/387H/PAPERS/Term paper-Sun.pdf.
  • Zaharaddeen, I., Ibrahim, B., & Zachariah, A. (2016). Estimation of land surface temperature of kaduna metropolis, nigeria using landsat images. Journal of Chemical and Pharmaceutical Sciences, 11(3), 36–42.

Development of Modeler for Automated Mapping of Land Surface Temperature Using GIS and LANDSAT-8 Satellite Imagery

Year 2022, Volume: 9 Issue: 2, 54 - 59, 02.06.2022
https://doi.org/10.30897/ijegeo.820906

Abstract

Land surface temperature (LST) can be described as the temperature of the earth’s surface and it is most important parameters in climate change, evapotranspiration, urban climate, vegetation monitoring and environmental studies. LST, calculated from remote sensing data, is used in many areas of science such as; hydrology, agriculture, forestry, oceanography etc. The main objective of this study was to develop a model making the LST retrieval process quite simple and automated. This model developed using the ArcGIS Desktop 10.3.1 with the Model Building. Without the model, the process of retrieving LST is very long, and it is susceptible to many mistakes. In this model when user inputs required bands (4,5 and 10) of Landsat-8 data then the model calculate automatically LST and display output. The model first makes the conversions to top of atmosphere (TOA) spectral radiance. Then NDVI is calculated based on band 4 and 5 (NIR and RED) reflectance. Then using the TOA and NDVI model calculates brightness temperature (BT) and Proportion of Vegetation respectively. After that it calculate Land Surface Emissivity with the help of NDVI and Proportion of Vegetation and finally, the model calculates land surface temperatures in degrees Celsius. The findings highlight the capabilities of GIS modelers for such spatial estimation. The developed model can be helpful to field engineers and researchers for using Landsat-8 images for direct estimation of LST, to be used for different other studies to derive LST based products.

References

  • Avdan, U., & Jovanovska, G. (2016). Algorithm for Avdan, U., & Jovanovska, G. (2016). Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data. 2016.
  • Department of the Interior U.S. Geological Survey. (2016). Landsat 8 Data Users Handbook. Nasa, 8(June),97.Retrieved from https://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf
  • Guillevic, P., Göttsche, F., Nickeson, J., Hulley, G., Ghent, D., Yu, Y., … Camacho, F. (2018). Land surface temperature product validation best practice protocol version 1.1. Best Practice for Satellite-Derived Land Product Validation (p. 60): Land Product Validation Subgroup (WGCV/CEOS), doi(January), 58. https://doi.org/10.5067/doc/ceoswgcv/lpv/lst.001.
  • Ibrahim, M., & Abu-mallouh, H. (2018). Estimate Land Surface Temperature in Relation to Land Use Types and Geological Formations Using Spectral Remote Sensing Data in Northeast Jordan. 2018, 174–185. https://doi.org/10.4236/ojg.2018.82011.
  • Jeevalakshmi, D., Narayana Reddy, S., & Manikiam, B. (2017). Land surface temperature retrieval from LANDSAT data using emissivity estimation. International Journal of Applied Engineering Research, 12(20), 9679–9687.
  • OGUZ, H. (2017). Automated Land Surface Temperature Retrieval From Landsat 8 Satellite Imagery: a Case Study of Diyarbakir - Turkey. Turkish Journal of Forest Science, 1(1), 33–43. https://doi.org/10.32328/turkjforsci.296845.
  • Orhan, O., & Yakar, M. (2016). Investigating land surface temperature changes using Landsat data in Konya, Turkey. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 285–289. https://doi.org/10.5194/isprsarchives-XLI-B8-285-2016.
  • Sun, Y. (2008). Retrieval and Application of Land Surface Temperature. Geo.Utexas.Edu, 1(1), 1–27. Retrieved from http://www.geo.utexas.edu/courses/387H/PAPERS/Term paper-Sun.pdf.
  • Zaharaddeen, I., Ibrahim, B., & Zachariah, A. (2016). Estimation of land surface temperature of kaduna metropolis, nigeria using landsat images. Journal of Chemical and Pharmaceutical Sciences, 11(3), 36–42.
There are 9 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Sachin Sutariya 0000-0001-7912-9824

Hirapara Ankur 0000-0002-1963-7197

Mukesh Tiwari 0000-0003-0385-4426

Publication Date June 2, 2022
Published in Issue Year 2022 Volume: 9 Issue: 2

Cite

APA Sutariya, S., Ankur, H., & Tiwari, M. (2022). Development of Modeler for Automated Mapping of Land Surface Temperature Using GIS and LANDSAT-8 Satellite Imagery. International Journal of Environment and Geoinformatics, 9(2), 54-59. https://doi.org/10.30897/ijegeo.820906