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http://dx.doi.org/10.7780/kjrs.2014.30.2.13

Analysis of Land Surface Temperature from MODIS and Landsat Satellites using by AWS Temperature in Capital Area  

Jee, Joon-Bum (Weather Information Service Engine, Center for Atmospheric and Earthquake Research)
Lee, Kyu-Tae (Dept. of Atmospheric and Environmental Sciences, Gangneung-Wonju National University)
Choi, Young-Jean (Weather Information Service Engine, Center for Atmospheric and Earthquake Research)
Publication Information
Korean Journal of Remote Sensing / v.30, no.2, 2014 , pp. 315-329 More about this Journal
Abstract
In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.
Keywords
Landsat; MODIS; Land Surface Temperature; AWS temperature; Urban;
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Times Cited By KSCI : 9  (Citation Analysis)
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1 Prihodko, L. and S.N. Goward, 1997. Estimation of air temperature from remotely sensed surface observations, Remote Sensing of Environment, 60(3): 335-346.   DOI   ScienceOn
2 Suga, Y., H. Ogawa, K. Ohno and K. Yamada, 2003. Detection of Surface Temperature from Landsat-7/ETM+, Advances in Space Research, 32(11): 2235-2240.   DOI   ScienceOn
3 Teillet, P.M., J.L. Barker, B.L. Markham, R.R. Irish, G. Fedosejevs, and J.C. Storey, 2001. Radiometric cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM sensors based on tandem data sets, Remote Sensing of Environment, 78(1-2): 39-54.   DOI   ScienceOn
4 Walawender, J.P., M. Szymanowski, M.J. Hajito, and A. Bokwa, 2013. Land Surface Temperature Patterns in the Urban Agglomeration of Krakow (Poland) Derived from Landsat-7/ETM+ Data, Pure and Applied Geophysics, doi:10.1007/s00024-013-0685-7.   DOI   ScienceOn
5 Wan, Z. and Z.L. Li, 2008. Radiance-based validation of the V5 MODIS land-surface temperature product, International Journal of Remote Sensing, 29 (17-18): 5373-5395.   DOI   ScienceOn
6 World Meteorological Organization (WMO), 2007. RGB Composite Satellite Imagery Workshop, Final Report. Boulder, Co, 5-7.
7 Yoo, B.M., 1999. Introduction to Geospatial Information, DongMyung, 511pp (in Korean).
8 Yoon, M.H. and D.M. Ahn, 2009. An Application of Satellite Image Analysis to Visualize the Effects of Urban Green Areas on Temperature, Journal of the Korean Institute of Landscape Architecture, 37(3): 46-53(in Korean with English abstract).   과학기술학회마을
9 Mallick, J., Y. Kant, and B.D. Bharath, 2008. Estimation of land surface temperature over Delhi using Landsat-7 ETM+, Journal Indian Geophysical Union, 12(3): 131-140.
10 Lee, K.K. and W.H. Hong, 2008. A Study on the Urban Heat Environment Pattern Analysis and Alleviation Plan, Journal of Architectural Institute of Korea, 24(9): 253-260 (in Korean with English abstract).   과학기술학회마을
11 Lee, S.H., J.S. Ahn, H.D. Kim, and S.J. Hwang, 2009. Comparison Study on the Estimation Algorithm of Land Surface Temperature for MODIS Data at the Korean Peninsula, Journal of the Environmental Sciences, 18(4): 355-367 (in Korean with English abstract).   과학기술학회마을   DOI   ScienceOn
12 Liu, L. and Y. Zhang, 2011. Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong, Remote Sensing, 3(7): 1535-1552.   DOI
13 Mishra, N., D.L. Helder, A. Angal, J. Choi, and X. Xiong, 2014. Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site, Remote Sens, 6(2): 1327-1346.   DOI
14 Nasa Landsat Project Science Office, 2004. Landsat 7 Science Data Users Handbook, 184, http://landsathandbook.gsfc.nasa.gov/pdfs/Landsat7_Handbook.pdf.
15 Na, S.I., J.H. Park, and H.S. Shin, 2008. Change Detection of NDVI, Surface Temperature and VTCI in Saemangeum Area using Satellite Imagery, Korean National Committee on Irrigation and Drainage Journal, 15(1): 28-38.
16 Nikolopoulou, M. and S. Lykoudis, 2007. Use of Outdoor Spaces and Microclimate in a Mediterranean Urban Area, Building and Environment, 42(10): 3691-3707.   DOI   ScienceOn
17 Jin, M. and S. Liang, 2006. An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations, Journal of Climate, 19(12): 2867-2881.   DOI   ScienceOn
18 Nikolopoulou, M. and S. Lykoudis, 2006. Thermal comfort in outdoor urban spaces: analysis across different European countries, Building and Environment, 41(11): 1455-1470.   DOI   ScienceOn
19 Park, M.H., 2001. A Study on the Urban Heat Island Phenomenon Using LANDSAT TM Thermal Infrared Data-In the Case of Seoul-, Korean Society Civil Engineering, 21(6-D): 861-874 (in Korean with English abstract).   과학기술학회마을
20 Kim, H.O. and J.M. Yeom, 2012. Effect of the Urban Land Cover Types on the Surface Temperature: Case Study of Ilsan New City, Korean Journal of Remote Sensing, 28(2): 203-214 (in Korean with English abstract).   과학기술학회마을   DOI
21 Jo, M.H., K.J. Lee, and W.S. Kim, 2001. A Study on the Spatial Distribution Characteristic of Urban Surface Temperature using Remotely Sensed Data and GIS, Journal of the Korean Association of Geographic Information Studies, 4(1): 57-66 (in Korean with English abstract).   과학기술학회마을
22 Karnieli, A., 2010. Use of NDVI and Land surface Temperature for Drought Assessment, Jourrnal of Climate, 23(3): 618-633.   DOI   ScienceOn
23 Kim, J.I. and J.H. Kwon, 2005. Identifying Urban Spatial Structure through GIS and Remote Sensing Data: The Case of Daegu Metropolitan Area, The Korean Association of Geographic Information Studies, 12(4): 44-51 (in Korean with English abstract).   과학기술학회마을
24 Lee, J.Y., D.Y. Yang, J.Y. Kim, and G.S. Chung, 2004. Application of Landsat ETM Image to Estimate the Distribution of Soil Types and Erosional Pattern in the Wildfire Area of Gangneung, Gangweon Province, Korea, Journal Korean Earth Science Society, 25(8): 764-773 (in Korean with English abstract).   과학기술학회마을
25 Kim, T.G., K.E. Kim, K.S. Jo, and K.H. Kim, 1996. Monitoring of Lake Water Quality Using LANDSAT TM Imagery Data, Journal of The Korean Society for Geo-Spatial Information System, 4(2): 23-33 (in Korean with English abstract).   과학기술학회마을
26 Landsberg, H.E, 1981. The Urban Climate, New York, Academic press. 275pp.
27 Lee, C.S., K.S. Han, J.M. Yeom, B.G. Song, and Y.S. Kim, 2007. Thermal Spatial Representativity of Meteorological Stations using MODIS Land Surface Temperature, Journal of the Korean Association of Geographic Information Studies, 10(3): 123-133 (in Korean with English abstract).   과학기술학회마을
28 National Geological Information Institute: www.ngi.go.kr
29 NASA LAADS(Level 1 and Atmosphere Archive and distribution system): ladsweb.nascom.nasa.gov
30 Landsat EarthExplorer : earthexploerer.usgs.org
31 Boo, K.O., Y.S. Chun, J.Y. Park, H.M. Cho, and W.T. Kwon, 1999. The Horizontal Distribution of Air Temperature in Seoul using Automatic Weather Station data, Journal of the Korean Meteorological Society, 35(3): 335-343 (in Korean with English abstract).
32 Chander, G., B.L. Markham, and D.L. Helder, 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors, Remote Sensing of Environment, 113(5): 893-903.   DOI   ScienceOn
33 Steve, K.J., N.H. Wong, H. Emlyn, A. Roni, and Y. Hong, 2007. The influence of land use on the urban heat island in Singapore, Habitat International, 31(1): 232-242.   DOI   ScienceOn
34 Choi, S.P. and I.T. Yang, 1998. Extraction of Land Surface Change Information by Using Landsat TM Images, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography, 21(3): 261-267 (in Korean with English abstract).   과학기술학회마을
35 Jeong, J.C., 2009. Comparison of Land Surface Temperatures Derived from Surface Emissivity with Urban Heat Island Effect, Journal of Environmental Impact Assessment, 18(4): 219-277 (in Korean with English abstract).   과학기술학회마을
36 Wan, Z.M., 2008. New refinements and validation of the MODIS Land-Surface Temperature/Emissivity products, Remote Sensing of Environment, 112(1): 59-74.   DOI   ScienceOn