Validation of MODIS Land Surface Temperature Products with Ground-Based Measurements: A Case Study in the Bajestan Desert, Iran

Subject Areas : Journal of Radar and Optical Remote Sensing and GIS

Morteza Kaffash ¹ , Seyed Hoseyn Sanaei Nejad ²

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Received: 2020-09-22 Accepted : 2020-10-29 Published : 2024-12-10

Keywords: LST, SMT160, Satellite, Validation, MODIS ,

Abstract :

Objective: Land surface temperature (LST) is a critical parameter for environmental studies, including climate change analysis, soil moisture monitoring, evapotranspiration estimation, and surface energy balance evaluation. This study aims to validate the accuracy of MODIS LST products (MOD11A1 and MYD11A1) from Terra and Aqua satellites in the Bajestan Desert, Iran, by comparing them with ground-based measurements.

Methods:  Ground-based LST measurements were conducted using six thermometers equipped with SMT160 temperature sensors over 15 clear-sky days and nights. MODIS LST products were validated using two approaches: (1) comparison with pixel-level ground-based data and (2) comparison with the average LST values of image windows larger than the pixel size (e.g., 3×3, 5×5). Statistical parameters, including root mean square error (RMSE), coefficient of determination (R²), and standard deviation, were calculated to assess the accuracy of satellite-derived LST.

Results: The results indicate that MODIS LST products systematically underestimate LST in the barren study area. Nocturnal LST exhibited higher accuracy (RMSE = 1.1) compared to diurnal measurements (RMSE = 3.38). Increasing the size of the window used for averaging resulted in higher standard deviations of pixel temperatures, while RMSE and R² values showed negligible changes, demonstrating the homogeneity of the selected study area.

Conclusion: This study validates the applicability of MODIS LST products in arid environments despite their systematic underestimation. The findings highlight the importance of incorporating homogeneous sampling areas and suggest the need for further improvements in MODIS algorithms for arid regions. The methodologies applied in this study provide a robust framework for LST validation in other arid and semi-arid environments.

References:

Alavipanah, S. K. (2006). Thermal remote sensing and its application in earth sciences. University of Tehran press, ISBN, 964-903.
AZIZI, G., Alavipanah, S. K., Goudarzi, N., & Kazemi, M. (2007). An estimation of the temperature of Lut desert using MODIS sensor data.
Bokaie, M., Zarkesh, M. K., Arasteh, P. D., & Hosseini, A. (2016). Assessment of urban heat island based on the relationship between land surface temperature and land use/land cover in Tehran. Sustainable Cities and Society, 23, 94-104. https://doi.org/10.1016/j.scs.2016.03.009
Coll, C., Caselles, V., Galve, J. M., Valor, E., Niclos, R., Sánchez, J. M., & Rivas, R. (2005). Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data. Remote sensing of Environment, 97(3), 288-300. https://doi.org/10.1016/j.rse.2005.05.007
Coll, C., & Caselles, V. (1997). A split‐window algorithm for land surface temperature from advanced very high resolution radiometer data: validation and algorithm comparison. Journal of Geophysical Research: Atmospheres, 102(D14), 16697-16713. https://doi.org/10.1029/97JD00929
Davari, S., Rashki, A., Akbari, M., & Talebanfard, A. (2017). Assessing intensity and risk of desertification and management programs (Case study: Ghasemabad plain of Bajestan, Khorasan Razavi Province). Desert Management, 5(9), 91-106. https://doi.org/10.22034/jdmal.2017.27855
Davies, D. K., Ilavajhala, S., Wong, M. M., & Justice, C. O. (2008). Fire information for resource management system: archiving and distributing MODIS active fire data. IEEE Transactions on Geoscience and Remote Sensing, 47(1), 72-79. https://doi.org/10.1109/TGRS.2008.2002076
Ermida, S. L., Jiménez, C., Prigent, C., Trigo, I. F., & DaCamara, C. C. (2017). Inversion of AMSR‐E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature. Journal of Geophysical Research: Atmospheres, 122(6), 3348-3360. https://doi.org/10.1002/2016JD026148
Ghalamchi, M., Kasaeian, A., & Ghalamchi, M. (2015). Experimental study of geometrical and climate effects on the performance of a small solar chimney. Renewable and Sustainable Energy Reviews, 43, 425-431. https://doi.org/10.1016/j.rser.2014.11.068
Guillevic, P. C., Bork-Unkelbach, A., Göttsche, F. M., Hulley, G., Gastellu-Etchegorry, J. P., Olesen, F. S., & Privette, J. L. (2013). Directional viewing effects on satellite land surface temperature products over sparse vegetation canopies—A multisensor analysis. IEEE Geoscience and Remote Sensing Letters, 10(6), 1464-1468. https://doi.org/10.1109/LGRS.2013.2260319
Justice, C., Belward, A., Morisette, J., Lewis, P., Privette, J., & Baret, F. (2000). Developments in the'validation'of satellite sensor products for the study of the land surface. International Journal of Remote Sensing, 21(17), 3383-3390. https://doi.org/10.1080/014311600750020000
Maimaitiyiming, M., Ghulam, A., Tiyip, T., Pla, F., Latorre-Carmona, P., Halik, Ü., ... & Caetano, M. (2014). Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation. ISPRS Journal of Photogrammetry and Remote Sensing, 89, 59-66. https://doi.org/10.1016/j.isprsjprs.2013.12.010
Olivera-Guerra, L., Mattar, C., Merlin, O., Durán-Alarcón, C., Santamaría-Artigas, A., & Fuster, R. (2017). An operational method for the disaggregation of land surface temperature to estimate actual evapotranspiration in the arid region of Chile. ISPRS Journal of Photogrammetry and Remote Sensing, 128, 170-181. https://doi.org/10.1016/j.isprsjprs.2017.03.014
Orhan, O., Ekercin, S., & Dadaser-Celik, F. (2014). Use of landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey. The Scientific World Journal, 2014(1), 142939. https://doi.org/10.1155/2014/142939
Pahlevani, M., & Mobasheri, M. R. (2009). An Improvement on Land Surface Temperature Determination by Producing Surface Emissivity Maps. Desert, 14(2), 171-184. https://doi.org/10.1080/01431160600702665
Prata, A. J. (2002). Land surface temperature measurement from space: AATSR algorithm theoretical basis document. Contract Report to ESA, CSIRO Atmospheric Research, Aspendale, Victoria, Australia, 2002, 1-34.
Son, N. T., Chen, C. F., Chen, C. R., Chang, L. Y., & Minh, V. Q. (2012). Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18, 417-427. https://doi.org/10.1016/j.jag.2012.03.014
Srivastava, P. K., Han, D., Ramirez, M. R., & Islam, T. (2013). Machine learning techniques for downscaling SMOS satellite soil moisture using MODIS land surface temperature for hydrological application. Water resources management, 27, 3127-3144. https://doi.org/10.1007/s11269-013-0337-9
Wan, Z., & Li, Z. L. (2008). Radiance‐based validation of the V5 MODIS land‐surface temperature product. International Journal of Remote Sensing, 29(17-18), 5373-5395. https://doi.org/10.1080/01431160802036565
Wang, K., Wan, Z., Wang, P., Sparrow, M., Liu, J., & Haginoya, S. (2007). Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground‐based measurements at a semi‐desert site on the western Tibetan Plateau. International Journal of Remote Sensing, 28(11), 2549-2565. https://doi.org/10.1080/01431160600702665
Wang, W., Liang, S., & Meyers, T. (2008). Validating MODIS land surface temperature products using long-term nighttime ground measurements. Remote Sensing of Environment, 112(3), 623-635. https://doi.org/10.1016/j.rse.2007.05.024
Wan, Z. (2014). New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote sensing of Environment, 140, 36-45. https://doi.org/10.1016/j.rse.2013.08.027
Wan, Z. (2008). New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote sensing of Environment, 112(1), 59-74. https://doi.org/10.1016/j.rse.2006.06.026
Wan, Z., Wang, P., & Li, X. (2004). Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA. International journal of remote sensing, 25(1), 61-72. https://doi.org/10.1080/0143116031000115328
Wan, Z., & Dozier, J. (1996). A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on geoscience and remote sensing, 34(4), 892-905. https://doi.org/10.1109/36.508406
Wang, S., Li, X., Ge, Y., Jin, R., Ma, M., Liu, Q., ... & Liu, S. (2016). Validation of regional-scale remote sensing products in China: From site to network. Remote Sensing, 8(12), 980. https://doi.org/10.3390/rs8120980
Wan, Z., Zhang, Y., Zhang, Q., & Li, Z. L. (2002). Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote sensing of Environment, 83(1-2), 163-180.
Zakšek, K., & Oštir, K. (2012). Downscaling land surface temperature for urban heat island diurnal cycle analysis. Remote Sensing of Environment, 117, 114-124. https://doi.org/10.1016/j.rse.2011.05.027