برآورد پارامترهای روزانه و ماهانه دمای هوا در استان کردستان با بکارگیری تصاویر سنجنده MODIS

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه کردستان

2 دانش آموخته کارشناسی ارشد آبیاری و زهکشی، دانشگاه کردستان

3 دانشجوی دکتری هواشناسی کشاورزی دانشگاه کلگری کانادا

چکیده

هدف از انجام این تحقیق، برآورد توزیع مکانی سه پارامتر دمای هوا شامل دمای کمینه، دمای بیشینه و دمای میانگین در مقیاس­های زمانی روزانه و ماهانه در استان کردستان با بکارگیری تصاویر سنجنده MODIS نصب شده بر روی ماهواره­های Aqua و Terra است. برای این منظور، 8 ایستگاه سینوپتیک در استان کردستان انتخاب شدند و برای سال­های 2013 و 2014 در این 8 ایستگاه، داده­های روزانه کمینه، بیشینه و میانگین دمای هوا و همچنین دمای سطح زمین در 4 زمان مختلف شبانه­روز با انجام پردازش­هایی بر روی تصاویر سنجنده MODIS استخراج شدند. سپس از روش رگرسیون خطی چند متغیره جهت استخراج روابط رگرسیونی بین هر کدام از سه پارامتر دمایی مذکور با دماهای سطح زمین برای کل استان کردستان و جهت سنجش خطا از روش اعتبارسنجی متقابل با بکارگیری سه شاخص میانگین قدر مطلق خطا، میانگین اریبی خطا و ضریب کارایی نش - ساتکلیف استفاده شد. نتایج نشان داد که ارتباطی قوی بین هر سه پارامتر دمایی با دماهای سطح زمین مستخرج از تصاویر ماهواره­ای وجود دارد. نتایج حاصل از اعتبارسنجی متقابل نیز حاکی از تطابق مناسب و قابل قبول بین مقادیر اندازه­گیری­شده سه پارامتر دمایی مذکور با مقادیر برآورد شده توسط روابط رگرسیونی در هر دو مقیاس زمانی روزانه و ماهانه بود به گونه­ای که شاخص میانگین قدر مطلق خطا برای سه پارامتر دمای کمینه، دمای بیشینه و دمای میانگین در مقیاس روزانه به ترتیب با 7/2، 1/2 و 6/1 درجه سانتیگراد و در مقیاس ماهانه به ترتیب 9/1، 1/2 و 1/1 درجه سانتیگراد بدست آمد که نشان­دهنده آن است که مقادیر این پارامترهای دمایی را در نقاطی از استان کردستان که فاقد ایستگاه هواشناسی هستند می­توان با استخراج دماهای سطح زمین از سنجنده MODIS برای این نقاط و بکارگیری این روابط رگرسیونی با دقت مناسب برآورد کرد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Estimating daily and monthly air temperature parameters at Kurdistan province using MODIS sensor images

نویسندگان [English]

  • Younes Khoshkhoo 1
  • Sorour Esmaeili 2
  • Masoud Abdollahi 3
1 Water science and Engineering Department, Agriculture Faculty, University of Kurdistan
2 University of Kurdistan
3 Ph.D. student
چکیده [English]

The object of this research is the estimation of spatial distribution of three air temperature parameters at daily and monthly scales including minimum, maximum and mean temperatures at the Kurdistan province using MODIS sensor images setted on Aqua and Terra satellites. For this object, 8 synoptic stations at Kurdistan province were selected and for these 8 stations at 2013 and 2014, daily minimum, maximum and mean air temperature data and also land surface temperature at 4 daily times at these 8 stations for 2013 and 2014 years were extracted by processing on the MODIS sensor images. Afterwards, the multiple linear regression method was used to extract regional regression models for Kurdistan province between these 3 air temperature parameters and land surface temperature and to assesing the errors, cross validation based on the Mean Absolute Error, Mean Bias Error and Nash-Sutcliffe Efficiency coefficient was adopted. The results showed that it is a powerful relation between all of these 3 air temperture and land surface temperatures extracted by sattelite images. The results of cross validation showed an approperiate and reseanable agreement between the measured and estimated values of these 3 parameters at both daily and monthly scales so that the mean absolute error for minimum, maximum and mean temperatures were 2.7, 2.1 and 1.6 °C at daily scale and 1.9, 2. 1 and 1.1 °C at monthly scale, respectively. These results showed that it is possible to estimate these air temperature parameters at the places witout any meteorological stations with an approperiate and acceptable accuracy by extracting land surface temperatures of MODIS sensor for these places and applying the extracted regression models.

کلیدواژه‌ها [English]

  • Air Temperature
  • Kurdistan province
  • Land surface temperature
  • MODIS
  • Multiple Linear Regression

مراجع

Bazyani, S., Zare-Abyaneh, H. and Akbari, M. (2014). Estmating TVX Index using remote sensing data (A case study: Hamedan Province). Natural Geographic Researchs, 46(3), 333-348. (In Farsi)
Benali, A., Carvalho, A., Nunes, J., Carvalhais, N. and Santos, A. (2012). Estimating air surface temperature in Portugal using MODIS LST data. Remote Sensing Environment, 124, 108–121.
Boudhar, A., Duchemin, B., Hanich, L., Boulet, G. and Chehbouni, A. (2011). Spatial distribution of air temperature in mountainous area using satellite thermal Infra Red data. Comptes Rendus Geoscience, 34, 32-42.
Bustos, E. and 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), 211-226.
Cabrera, H.M. (2002). Ecophysiological responses of plants in ecosys-tems with Mediterranean-like climate and high mountain environ-ments. Rev. Chil. Hist. Nat, 75, 625– 637.
Chuvieco, E., Aguado, I., Yebra, M., Nieto, H., Salas, J., Martın, P., Vilar, L., Martınez, J., Martın, S., Ibarra, P., dela Riva, J., Baeza, J., Rodrıguez, F., Molina, J.R. Herrera, M.A. and Zamora, R. (2010). Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, 221, 46–58.
Colombi, A., DeMichele, C., Pepe, M. and Rampini, A. (2007). Estimation of daily mean air temperature from MODIS LST in Alpine areas. EARSeL eProc, 6, 38–46.
DeVisser, M.H., Messina, J.P., Moore, N.J., Lusch, D.P. and Maitima, J. (2010). A dynamic species distribution model of Glossina subgenus Morsitans: The identification of tsetsereservoirs and refugia. Ecosphere, 1(1), 1-21.
Feizizadeh, B., Didehban, Kh. And Gholamnia, Kh. (2015). Extraction of Land Surface Temperature (LST) based on landsat satellite images and split window algorithm Study area: Mahabad Catchment. Scientific - Research Quarterly of Geographical Data  (SEPEHR), 98, 171-181. (In Farsi)
Fu, G., Shen, Z., Zhang, X., Shi, P., Zhang, Y. and Wu, J. (2011). Estimating air temperature of an alpine meadow on the Northern Tibetan Plateau using MODIS land surface temperature. Acta Ecologica Sinica, 31, 8–13.
House-Peters, L.A. and Chang, H. (2011). Modeling the impact of land use and climate change on neighborhood-scale evaporation and nighttime cooling: A surface energy balance approach. Landsc Urban Plan, 103, 139–155.
IPCC. (2007). Climate Change 2007: The Physical Science Basis. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change. United Kindom, Cambridge.
Ishida, T. and Kawashima, S. 1993. Use of cokriging to estimate surface air temperature from elevation. Theor. Appl. Climatol, 47, 147–157.
Jahanbakhsh, S., Zahedi, M. and Valizadeh, Kh. (2011). Calculationg land surface temperature using SEBAL and tree decision at RS and GIS environment at centeral part of Maragheh. Geograghy and Programming Journal, 16, 19-42. (In Farsi)
Jin, M. and Dickinson R.E. (2010). Land surface skin temperature climatology: Benefitting from the strengths of satellite observations. Environmental Research Letters, 5(4), 1-13.
Kaviani, A., Sohrabi, T. and Daneshkar, P. (2013). Estimation of land surface temperature using NDVI in MODIS and Landsat. Journal of Agricultural Meteorology, 1(1), 14-25. (In Farsi)
Kloog, I., Nordio, F., Coull, B.A. and Schwartz, J. (2014). Predicting spatiotemporal mean air temperature using MODIS satellite surface temperature measurements across the Northeastern USA. Remote Sensing of Environment, 150, 132-139.
Lin, S., Moore, N. J., Messina, J. P., DeVisser, M. H. and 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, 128-140.
Liu, H. and Weng, Q. (2012). Enhancing temporal resolution of satellite imagery for public health studies: A case study of West Nile Virus outbreak in Los Angeles in 2007. Remote Sens Environ, 117, 57–71.
Mildrexler, D.J., Zhao, M. and Running, S.W. (2011). A global comparison between station air temperatures and MODISl and surface temperatures reveals the cooling role of forests. Journal of Geophysical Research, 116, 1–15.
Mostovoy, G. V., King, R. L., Reddy, K. R., Kakani, V. G. and Filippova, M. G. (2006). Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi. GIS science and Remote Sensing, 43(1), 78–110.
Nieto, H., Sandholt, I. and Aguado, A. (2011). Air temperature estimation with MSG-SEVIRI data: calibration and validation of the TVX algorithm for the Iberian Peninsula. Remote Sens. Environ, 115, 107–116.
Parviz, L. and Valizadeh, Kh. (2011). Estimating air temperature using TVX Index. Soil and Water Science Journal, 56, 21-33. (In Farsi)
Peón, J., Recondo, C. and Calleja, J.F. (2014). Improvements in the estimation of daily minimum air temperature in peninsular Spain using MODIS land surface temperature. International Journal of Remote Sensing, 35(13), 5148-5166.
Richard, C. and Gratton, D.J. (2001). The importance of the air temperature variable for the snowmelt runoff modeling using the SRM. Hydrological Processes, 15, 3357-3370.
Shah, D. B., Pandya, M. R., Trivedi, H. J. and Jani, A. R. (2013). Estimating minimum and maximum air temperature using MODIS data over Indo-Gangetic Plain. Journal of Earth System Science, 122(6), 1593-1605.
Shen, S. and Leptoukh, G.G. (2011). Estimation of Surface Air Temperature over Central and Eastern Eurasia from MODIS Land Surface Temperature. Environmental Research Letters, 6, 1-8.
Sohrabinia, M., Zawar-Reza, P. and Rack, W. (2015). Spatio-temporal analysis of the relationship between LST from MODIS and air temperature in New Zealand. Theoretical and Applied Climatology, 119(3-4), 567-583.
Sun, H., Chen, Y., Gong, A., Zhao, X., Zhan, W. and Wang, M. (2014). Estimating mean air temperature using MODIS day and night land surface temperatures. Theoretical and applied climatology, 118(1-2), 81-92.
Urban, M., Eberle, J., H¨uttich, C., Schmullius, C . and Herold, M. (2013). Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the pan-Arctic scale. Remote Sensing, 5, 2348–2367.
Vancutsem, C., Ceccato, P., Dinku, T. and Connor, S.J. (2010). Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Remote Sensing of Environment, 114, 449–465.
Wallach, D., Makowski, D. and Jones, J. W. (2006). Working with dynamic crop models: evaluation, analysis, parameterization, and applications. Elsevier. 447pp.
Wang, K. and Dickinson, R.E. (2012). A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Rev Geophys, 50, 1–54.
Woodard, J. D. and Sherrick, B.J. (2011). Estimation of mixture models using cross-validation optimization: Implications for crop yield distribution modeling. American Journal of Agricultural Economics, 93(4), 968-982.
Xiong, W., Holman, I., Conway, D., Lin, E. and Li, Y. (2008). A crop model cross calibration for use in regional climate impacts studies. Ecological Modelling, 213 (3), 365-380.
Yoo, J.M., Won, YI., Cho, Y.J., Jeong, M.J., Shin, D.B., Lee, S.J., Lee, Y.R., Oh S.M. and Ban, S.J. (2011). Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satelliteand ground measurements. Asia-Pac J Atmos Sci, 47, 439–455.
Zakšek, K. and Schroedter-Homscheidt, M. (2009). Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments. ISPRS J. Photogramm. Remote Sens, 64, 414–421.
Zeng, L., Wardlow, B.D., Tadesse, T., Shan, J., Hayes, M.J., Li, D. and Xiang, D. (2015). Estimation of daily air temperature based on MODIS land surface temperature products over the Corn Belt in the US. Remote Sensing, 7(1), 951-970.
Zhang, W., Huang, Y., Yu, Y. and 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, 9415–9440.
Zhu, W., Lű, A. and Jia, S. (2013). Estimation of daily maximum and minimum air temperature using MODIS land surface temperature products. Remote Sensing of Environment, 130, 62 –73.
 
 
تحقیقات آب و خاک ایران
دوره 49، شماره 2
خرداد و تیر 1397
صفحه 413-423

فایل ها

هم رسانی

ارجاع به این مقاله

آمار