Document Type : Original Article

Authors

1 M.Sc. Student, Dep. of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Noor, Mazandaran

2 Prof. of Dep. of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Noor, Mazandaran

3 Assistant Prof., Dep. of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modarres University, Noor, Mazandaran

Abstract

Due to the importance of meteorological data and limitations of data gathering from ground stations, remote sensing can play an important role in the preparation of these data. The purpose of this study was to quantitatively evaluate the Land Surface Temperature (LST) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images for estimating the maximum and minimum daily air temperature in the Taleghan watershed. For this purpose, the maximum and minimum daily air temperature data of three existing ground stations for the period 2009 to 2015 were obtained. Day and night LST and Normalized Difference Vegetation Index (NDVI) values ​​of MODIS were also prepared. The relationships between each of the effective variables and maximum and minimum daily air temperature in ground stations have been extracted using multiple linear regression method. The results showed that there was a significant correlation between maximum and minimum daily temperature of ground stations with day and night LST and NDVI from MODIS sensor. Therefore, these variables were used in regression relationships. The results of validation showed that the established relationships with all effective variables had the most accuracy. Therefore, the best model for estimating the maximum daily air temperature had , NSE and RMSE values ​​of 0.74, 0.74, and +4.7, respectively and for estimating the minimum daily air temperature had 0.71, 0.72 and +2.9, respectively. Therefore, by converting the surface temperature obtained from MODIS sensor images, the air temperature can be estimated with high accuracy on a daily and monthly scales for various studies.

Keywords

Ahmadi, M., Dadashi Roudbari, A. & Ahmadi, H. 2018a, Analysis of Daytime Land Surface Temperature in Iran Based on the MODIS Sensor Output, Environmental Sciences, 16(1), PP. 47-68.
Ahmadi, M., Kaviani, A., Daneshkar, P. & Faraji, Z., 2018b, Estimation of Air Temperature and Land Surface Using GLDAS and NCEP/NCAR, Iranian Irrigation and Drainage Journal, 13(4), PP. 931-944.
Benali, A., Carvalho, A.C., Nunes, J.P., Carvalhais, N. & Santos, A., 2012, Estimating Air Surface Temperature in Portugal Using MODIS LST Data, Remote Sensing of Environment, 124, PP. 108-121.
Bustos, E. & Meza, F.J., 2015, A Method to Estimate Maximum and Minimum Air Temperature Using MODIS Surface Temperature And Vegetation Data: Application to the Maipo Basin, Chile, Theoretical and Applied Climatology, 120(1-2), PP. 211-226.
Chen, Y., Sun, H. & Li, J., 2016, Estimating Daily Maximum Air Temperature with MODIS Data and a Daytime Temperature Variation Model in Beijing Urban Area, Remote Sensing Letters, 7(9), PP. 865-874.
Czajkowski, K.P., Goward, S.N., Stadler, S.J. & Walz, A., 2000, Thermal Remote Sensing of Near Surface Environmental Variables: Application over the Oklahoma Mesonet, The Professional Geographer, 52(2), PP. 345-357.
Didari, S., Norouzi, H., Zand-Parsa, S. & Khanbilvardi, R., 2017, Estimation of Daily Minimum Land Surface Air Temperature Using MODIS Data in Southern Iran, Theoretical and Applied Climatology, 130(3-4), PP. 1149-1161.
 
 
 
Fattahi, A. & Vazifehdoust, M., 2011, Estimation of Snow Cover Area and Land Surface Temperature Using MODIS Satellite (A Case Study of Golestan Watershed), Geographical Research, 26(102), PP. 149-168.
Georgiou, A.M. & Varnava, S.T., 2019, Evaluation of Modis-Derived Lst Products With Air Temperature Measurements in Cyprus. Geoplanning, Journal of Geomatics and Planning, 6(1), P. 1.
Goldblatt, R., Addas, A., Crull, D., Maghrabi, A., Levin, G.G. & Rubinyi, S., 2021, Remotely Sensed Derived Land Surface Temperature (Lst) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale, Land, 10(4), P. 410.
Hatami Jarabad, C., Erfanian, M. & Babaei Hessar, S., 2018, Estimation of Daily Net Radiation in the Urmia Lake Basin under Clear-Sky Conditions Based on MODIS Data, Physical Geography Research Quarterly, 50(4), PP. 669-684.
Hereher, M.E., 2019, Estimation of Monthly Surface Air Temperatures from MODIS LST Time Series Data: Application to the Deserts in the Sultanate of Oman, Environmental Monitoring and Assessment, 191(9).
Höskuldsson, A., 1988, PLS Regression Methods, Journal of Chemometrics, 2(3), PP. 211-228.
Huang, F., Ma, W., Wang, B., Hu, Z., Ma, Y., Sun, G., Xie, Z. & Lin, Y., 2017, Air Temperature Estimation with MODIS Data over the Northern Tibetan Plateau, Advances in Atmospheric Sciences, 34(5), PP. 650-662.
Huang, R., Zhang, C., Huang, J., Zhu, D., Wang, L. & Liu, J., 2015, Mapping of Daily Mean Air Temperature in Agricultural Regions Using Daytime and Nighttime Land Surface Temperatures Derived from Terra and Aqua MODIS Data, Remote Sensing, 7, PP. 8728-8756.
Ismaili, S., Khoshkho, Y. & Abdolhi, M., 2017, Estimation of Daily and Monthly Air Temperature Parameters in Kurdistan Province Using MODIS Sensor Images, Iran Water and Soil Research (Agricultural Sciences of Iran), 49(2), PP. 423-413.
Janatian, N., Sadeghi, M., Sanaeinejad, S.H., Bakhshian, E., Farid, A., Hasheminia, S.M. & Ghazanfari, S., 2017, A Statistical Framework for Estimating Air Temperature Using MODIS Land Surface Temperature Data, International Journal of Climatology, 37(3), PP. 1181-1194.
Jang, K., Kang, S., Kim, J., Lee, C.B., Kim, T., Kim, J., Hirata, R. & Saigusa, N., 2010, Mapping Evapotranspiration Using MODIS and MM5 Four-Dimensional Data Assimilation, Remote Sensing of Environment, 114(3), PP. 657-673.
Jin, M. & Dickinson, R.E., 2010, Land Surface Skin Temperature Climatology: Benefitting from the Strengths of Satellite Observations, Environmental Research Letters, 5(4), P. 044004.
Kazempour Choursi, S., Erfanian, M. & Ebadi Nehari, Z., 2019, Evaluation of MODIS and TRMM Satellite Data for Drought Monitoring in the Urmia Lake Basin, Geography and Environmental Planning, 30(2), PP. 17-34.
Kutner, M.H., Kutner, M.H., Nachtsheim, C. & Neter, J., 2004, Student Solutions Manual for Use with Applied Linear Regression Models, McGraw-Hill/Irwin.
Lin, S., Moore, N.J., Messina, J.P., DeVisser, M.H. & Wu, J., 2012, Evaluation of Estimating Daily Maximum and Minimum Air Temperature with MODIS Data in East Africa, International Journal of Applied Earth Observation and Geoinformation, 18, PP. 128-140.
Lin, X., Zhang, W., Huang, Y., Sun, W., Han, P., Yu, L. & Sun, F., 2016, Empirical Estimation of Near-Surface Air Temperature in China from MODIS LST Data by Considering Physiographic Features, Remote Sensing, 8(8), PP. 1-15.
Marzban, F., 2020, Estimation of Near-Surface Air Temperature during Day and Night-Time from MODIS over Different LC/LU Using Machine Learning Methods in Berlin, PQDT - Global, June, 167.
Misslin, R., Vaguet, Y., Vaguet, A. & Daudé, É., 2018, Estimating Air Temperature Using MODIS Surface Temperature Images for Assessing Aedes Aegypti Thermal Niche in Bangkok, Thailand, Environmental Monitoring and Assessment, 190(9).
Mohammadi, Ch., Farajzadeh, M., Qavidel Rahimi, Y. & Ali Akbar Bidakhti, A., 2017, Estimation of Air Temperature Based on Environmental Parameters Using Remote Sensing Data, Applied Research Journal of Geographical Sciences, 18(48), PP. 131-152.
Nabizadeh Balkhanloo, A., hejazizadeh, Z. & Zeaiean Firoozabadi, P., 2018, Assessment of Vegetation Temperature Status (VTCI) for Monitoring Drought in the Watershed of Lake Urmia by Using MODIS Satellite Imagery, Journal of Geographical Sciences, 18(50), PP. 129-139.
Nieto, H., Sandholt, I., Aguada, I., Chuvieco, E. & Stisen, S., 2011, Air Temperature Estimation with MSG-SEVIRI Data: Calibration and Validation of the TVX Algorithm for the Iberian Peninsula, Remote Sensing of Environment, 115, PP. 107-116
Noi, P.T., Kappas, M. & Degener, J., 2016, Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam, Remote Sensing, 8(12), P. 1002.
Noor H., Vafakhah, M. & Moghadasi, M., 2016, Backup Tool to Determine the Optimal Spatial Pattern of Watershed Management Measures (Case Study: Taleghan Dam Watershed), Watershed Researches, 113, PP. 70-80.
Nosrati, K., Mohseni Saravi, M., Ahmadi, H. & Aghighi, H., 2015, Evapo-Transpiration Estimation in Taleghan Drainage Basin Using MODIS Images and SEBAL Model, Journal of Range and Watershed Managment, 68(2), PP. 385-398.
Parviz, L., Kholghi, M. & Valizadeh, K.H., 2011, Estimation of Air Temperature Using Temperature-Vegetation Index (TVX) Method, Iranian Journal of Water and Soil Science, 15(56), PP. 21-34.
Phan, T.N., Kappas, M., Nguyen, K.T., Tran, T.P., Tran, Q.V. & Emam, A.R, 2019, Evaluation of MODIS Land Surface Temperature Products for Daily Air Surface Temperature Estimation in Northwest Vietnam, International Journal of Remote Sensing, 40(14), PP. 5544-5562.
Prihodko, L. & Goward, S.N., 1997, Estimation of Air Temperature from Remotely Sensed Surface Observations, Remote Sensing of Environment, 60(3), PP. 335-346.
Rajani, S.V., 2021, Estimation and Validation of Land Surface Temperature by Using Remote Sensing & GIS for Chittoor District, Andhra Pradesh, Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(5), PP. 607-617.
Ruiz-Álvarez, M., Alonso-Sarria, F. & Gomariz-Castillo, F., 2019, Interpolation of Instantaneous Air Temperature Using Geographical and MODIS Derived Variables with Machine Learning Techniques, ISPRS International Journal of Geo-Information, 8(9).
Serra, C., Lana, X., Martínez, M.D., Roca, J., Arellano, B., Biere, R., Moix, M. & Burgueño, A., 2020, Air Temperature in Barcelona Metropolitan Region from MODIS Satellite and GIS Data, Theoretical and Applied Climatology, 139(1-2), PP. 473-492.
Shamir, E. & Georgakakos, K.P., 2014, MODIS Land Surface Temperature as an Index of Surface Air Temperature for Operational Snowpack Estimation, Remote Sensing of Environment, 152, PP. 83-98.
Sheather, S.J., 2009, Multiple Linear regression, In A Modern Approach to Regression with R (PP. 125-149), Springer, New York, NY.
Vancutsem, C., Ceccato, P., Dinku, T. & Connor, S.J., 2010, Evaluation of MODIS Land Surface to Estimate Air Temperature in Different Ecosystems over Africa, Remote Sensing of Environment, 114, PP. 449-465.
Wang, K., Li, Z. & Cribb, M., 2006, Estimation of Evaporative Fraction from a Combination of Day and Night Land Surface Temperatures and NDVI: A New Method to Determine the Priestley-Taylor Parameter, Remote Sensing of Environment, 102(3-4), PP. 293-305.
Willmott, C.J. & Robeson, S.M., 1995, Climatologically Aided Interpolation (CAI) of Terrestrial Air Temperature, International Journal of Climatology, 15(2), PP. 221-229.
Xu, Y., Qin, Z. & Shen, Y., 2012, Study on the Estimation of Near-Surface Air Temperature from MODIS Data by Statistical Methods, International Journal of Remote Sensing, 33(24), PP. 7629-7643.
Yang, Y.Z., Cai, W.H. & Yang, J., 2017, Evaluation of MODIS Land Surface Temperature Data to Estimate Near-Surface Air Temperature in Northeast China, Remote Sensing, 9(5), PP. 1-19.
Yoo, C., Im, J., Park, S. & Quackenbush, L.J., 2018, Estimation of Daily Maximum and Minimum Air Temperatures in Urban Landscapes Using MODIS Time Series Satellite Data, ISPRS Journal of Photogrammetry and Remote Sensing, 137, PP. 149-162.
Zhang,Y. & Wegehenkel, M., 2006, Integration of MODIS Data into a Simple Model for the Spatial Distributed Simulation of Soil Water Content and Evapotranspiration, Remote Sensing of Environment, 104, PP. 393-408.
Zhang, W., Huang, Y., Yu, Y. & Sun, W., 2011, Empirical Models for Estimating Daily Maximum, Minimum and Mean Air Temperatures with MODIS Land Surface Temperatures, International Journal of Remote Sensing, 32, PP. 9415-9440.
Zhu, W., Lu, A. & Jia, S., 2013, Estimation of Daily Maximum and Minimum Air Temperature Using MODIS Land Surface Temperature Products, Remote Sensing of Environment, 130, PP. 62-73.