A Comparative Study of Vegetation Indices to Analyze Land Use Patterns and Relationship between Vegetation Indices and Land Surface Temperature in San Kamphaeng District, Chiang Mai Province


Patiya Pattanasak


The objectives of this study including 1) to do a comparative study of vegetation indices to analyze land use patterns 2) to analyze relationship between vegetation indices and land surface temperature (LST). There were 5 different types of vegetation indices in the analysis including Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI), Soil Adjustment Vegetation Index (SAVI), and Transform Vegetation Index (TVI) from Landsat 8 OLI. The classification method used maximum likelihood classifier and the accuracy assessment was done by the confusion matrix. Split –window technique was used to analyze LST from Landsat 8 TIRS. Finally, Pearson product moment correlation coefficient and linear regression were used. The results found that NDVI provided the highest overall accuracy and kappa statistic followed by TVI, NDBI, RVI and SAVI, respectively. Analysis of LST presented urban and built-up areas had the highest LST. The relationship analysis between the LST and the vegetation indices found that LST and NDBI had positive correlation. However, LST and RVI, NDVI, SAVI and TVI had negative correlation, respectively. From the result, high accuracy of vegetation indices could be applied to image classification. The analysis of LST, which was received from each of land use, would be useful for urban planning.

Keywords: Vegetation indices, Land surface temperature, Split – window technique, Land use classification, Spectral index


Dechaphongthana, W., Karnchanasutham, S., Nualchawee, K., & Intarawichian, N. (2016). Estimation of Land Surface Temperature of Land Using Satellite Data. Thai Science and Technology Journal, 25(3), 377–387.
Gao, J. (2009). Digital Analysis of Remotely Sensed Imagery. USA: McGraw-Hill.
Guha, S., Govil, H., Dey, A., & Gill, H. (2018). Analytical Study of Land Surface Temperature with NDVI and NDBI Using Landsat 8 OLI and TIRS data in Florence and Naples City, Italy. Retrieved from https://www.tandfonline.com/doi/full/10.1080/22797254.2018.1474494
Kiyoshi, H. (2005). DN to reflectance. Retrieved from http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/ DN2Reflectance_2p.pdf
Pattanasak, P. (2018). Change Detection of Land Use and Land Cover by Normalized Difference Vegetation Index Differencing in the City of Chiang Mai, Thailand. Retrieved from https://acrs2018.mrsa.
Phengpit, N., Karnchanasutham, S., Nualchawee, K., & Soytong, P. (2017). The study of correlation between Land Surface Temperature with Urban and Built up Areas, A Case Study of Amphoe Mueang Rayong, Rayong Province, Thailand. Journal of Geo – information technology, 2(3), 27–40.
Pratiwi, K. (2018). Effect of Land Use Change on Surface Temperature of Benjamasin City using Landsat Image data. Retrieved from https://drive.google.com/file/d/1vzcwgJtLyrvgkwf-SvHPNaZT0V
Ren, H., Du, C., Liu, R., Qin, Q., Yan, G., Li, Z., & Meng, J. (2015). Atmospheric water vapor retrieval from Landsat 8 thermal infrared images. Retrieved from https://agupubs.onlinelibrary.wiley.com/doi/
Sangawong, S. (2009). Remote Sensing for Land – Use/Land – Cover Monitoring and Application. Bangkok: V. Print company.
Sopa, P., & Chayakul, T. (2019). Enhanced Vegetation Index and Normalized Difference Built – up Index in Bangkok and Metropolitan Region. Journal of Remote Sensing and GIS Association of Thailand, 20, 226–236.
Srivanit, M. & Hokao, K. (2012). Effects of Urban Development and Spatial Characteristics on Urban Thermal Environment in Chiang Mai Metropolitan, Thailand. Retrieved from https://www.researchgate.net/ publication/286138507_Effects_of_urban_development_and_spatial_characteristics_on_urban_thermal_environment_in_chiang_mai_metropolitan_Thailand
Srivanit, M. & Iamtrakul, P. (2019). Spatial Patterns of Greenspace Cool Islands and Their Relationship to Cooling Effectiveness in the Tropical city of Chiang Mai, Thailand. Retrieved from https://link.
Thongtip, U. (2014). Application of Vegetation Index for Exploring Land Use and Its Relationship with Household Livelihood in Khuan Sai Village, Lam Thap Subdistrict, Lam Thap district, Krabi province. Retrieved from http://www.lib.ku.ac.th.
U.S. Geological Survey. (2017). Landsat Mission. Retrieved from https://www.usgs.gov/land-resources/

Research Articles


How to Cite
PATTANASAK, Patiya. A Comparative Study of Vegetation Indices to Analyze Land Use Patterns and Relationship between Vegetation Indices and Land Surface Temperature in San Kamphaeng District, Chiang Mai Province. Naresuan University Journal: Science and Technology (NUJST), [S.l.], v. 30, n. 4, p. 12-23, sep. 2022. ISSN 2539-553X. Available at: <https://www.journal.nu.ac.th/NUJST/article/view/Vol-30-No-4-2022-12-23>. Date accessed: 27 jan. 2023. doi: https://doi.org/10.14456/nujst.2022.32.