Analyzing Temporal and Spatial Variations of Surface Albedo over Sistan Plain in Eastern Iran using Satellite Remote Sensing Product of MODIS Sensor of Terra Satellite

Document Type : علمی - پژوهشی

Authors

1 University of Sistan and Baluchestan

2 Professor Department of Physical Geography, Geography and Regional Planning Faculty, University of Sistan and Baluchestan, Zahedan, Iran

3 Assistant Professor, Department of Physical Geography, Geography and Regional Planning Faculty, University of Sistan and Baluchestan, Zahedan, Iran

4 Assistant Professor Department of Statistics, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

The radative energy balance received and returned from Earth planet reflects the energy available in each part of the Earth-Atmosphere system. Also, net solar radiation is the most fundamental driving force for evaporation, and all actions and reactions between the Earth's surface and the atmosphere. These reactions significantly affect the climate and its transformations. Hence, the wide-scale cross-sectional estimation of pure net energy is important in terms of global and regional climate models. In this research, in order to study the trend of long-term monthly average changes of surface-Albedo, the Albedo products from the sensors of MODIS Satellite Terra named MCD43B3were used. The spatial resolution of the images taken was 1×1 km for a 15-year statistical period (2000-2014) for April, May, and June. After capturing images by NASA's land processes distributed active archive center, all 45 downloaded images. The next step was to convert the image format to ASCII format; each ASCII includes 30080 pixels. Finally, by using both statistical methods of Sen's slope estimator, and Classic Linear Regression the trends of long-term monthly average Albedo changes were analyzed on a pixel-based scale. The results of these two models showed that these two models did not differ in their estimation of the trends of Albedo's average changes, and acted precisely the same. Also, the results of this research showed that the center of the most slowly declining slope of Albedo changes is located in the northeast, where, due to the flow of the Hirmand River, in this part of the plain the agriculture is widespread. The incremental magnitude of the slope of the change process is also very limited, and there are small and large spots in the north, northeast, and center of the plain. This increasing trend in the values of Albedo's index in the north of the plain was exactly the same as the drying of the Hamoon triple lakes. The rest of the plain area, which has desert landscape and does not have any vegetation, as well as any human population, has not shown any particular trend. In this study, it was also clearly found that, the use of nonparametric method of Sen's slope estimator and parametric method of classic linear regression can be very effective in studying the trend of Albedo changes in the arid regions resulted from satellite products of MADIS sensors

Keywords

References

  1. ادب، ح.، امیراحمدی، ا. و عتباتی، آ.، 1393، ارتباط پوشش گیاهی با دما و آلبدوی سطحی در دوره گرم سال با استفاده از داده های مودیس در شمال ایران، پژوهش های جغرافیای طبیعی، دوره 46، شماره 4، صص 434-419.
  2. افروزه، ف.، موسوی، س.ن.ا. و ترکمانی، ج.، 1390، بررسی نوسانات آب و بهینه کردن مصرف آن در بخش کشاورزی منطقه سیستان: کاربرد رهیافت فازی، تحقیقات اقتصاد کشاورزی، جلد3، شماره3، صص59-37.
  3. اکبرزاده، م.، مباشری، م.ر. و فاطمی، س.ب.، 1392، ارزیابی محصولات آلبیدوی 16 روزه MODIS با استفاده از آلبیدوی ASTER در مناطق نیمه خشک با پوشش همگن، نشریه پژوهش های اقلیم شناسی، سال 4، شماره 13، صص96-85.
  4. بهرامی، م.، مباشری م.ر. و رحیم زادگان، م.، 1393، ارزیابی دقت محصولات گسیل مندی سنجندهASTER و MODIS با استفاده از اندازه گیری‌های میدانی، جغرافیا و توسعه، شماره37، صص 40-29.
  5. جلیلوند، ا.، سیما، س.، سروانی، س.، تجریشی، م.، 1396، بررسی تغییرات آلبیدوی سطح و نواحی ساحلی دریاچه ارومیه، دهمین کنگره ملی مهندسی عمران، صص 12-1
  6. خیرخواه زرکش، م.، محبوبیان، ع. و حصادی، ه.، 1393، مقایسة مقایر برآوردی آلبیدوی سطحی به‌دست آمده از تصاویر لندست و مودیس، سنجش از دور و سامانه اطلاعات جغرافیایی در منابع طبیعی، سال پنجم، شماره دوم، صص 48-39.
  7. علیجانی، ب.، محمودی، پ. و چوگان، ع.، 1390، بررسی روند تغییرات بارش های سالانه و فصلی ایران با استفاده از روش ناپارامتریک، پژوهش های اقلیم شناسی، سال سوم، شماره 9. صص 13-1.
  8. Bonan, G.B., 1996, A Land Surface Model (LSM Version 1.0) for Ecological, Hydrological, and Atmospheric Studies: Technical Description and User’s Guide, NCAR Tech Note, 1:150-417
  9. Cess, R.D., 1978, Biosphere-albedo feedback and climate modeling, Atmos Sci, 35(9): 1765-1768.
  10. Csiszar, I. & Gutman, G., 1999, Mapping global land surface albedo from NOAA AVHRR, Geophysical Research, 104: 6215–6228.
  11. Duke, C. & Guerif, M., 1998, Crop reflectance estimate errors from the SAIL model due to spatial and temporal variability of canopy and soil characteristics, Remote Sens Environ, 66: 286– 297.
  12. Elena, A., Tsvetsinskaya, C.B., Schaaf, F., Gao, A.H., Strahler, R. & Dickinson, E., 2002, Relating MODIS-derived surface albedo to soils and rock types over Northern Africa and the Arabian peninsula, geophysical research letters, 29: 817-840.
  13. Henderson-Sellers, A., 1990, Predicting Generalized Ecosystem Groups with the NCAR CCM: First Steps Towards an Interactive Biosphere, Climate, 3: 917–940.
  14. Henderson-Sellers, A. & Wilson, M.F., 1983, Surface albedo for climate modeling, Reviews of Geophysics, 21:1743–1778.
  15. Hu, Y.Q., Yang, X.L. & Zhang, Q., 1992, The characters of energy budget on the gobi and desert surface in Hexi Region, Acta Meteorologica Sinica, 26: 82–91.
  16. Hulley, G.C., Hook, S.J. & Baldridge, A.M., 2009, Validation of the North American ASTER Land Surface Emissivity Database (NAALSED) version 2.0 using pseudo-invariant sand dune sites, Remote Sensing of Environment, 7: 1-13.
  17. Leroy, M., Deuze, J.L., Breon, F.M., Hautecoeur, O., Herman, M. & Buriez, J.C., 1997, Retrieval of atmospheric properties and surface bidirectional reflectances over the land from POLDER/ADEOS, Geophysical Research, 102: 17023–17 037.
  18. Li, Z., Cribb, M.C., Trishchenko, A.P., 2002, Impact of surface inhomogeneity on solar radiative transfer under overcast conditions, Geophys, 107: 429-440.
  19. Li, Z. & Garand, L., 1994, Estimation of surface albedo from space: A parameterization for global application, Geophysical Research, 99: 8335- 8350.
  20. Liang, S., 2000, Narrowband to broadband conversions of land surface albedo Algorithms, Remote Sens Environ, 76(2): 213-238.
  21. Liang, S., Strahler, A., Walthall, C., 1998, Retrieval of land surface albedo from satellite observations: A simulation study, In Geo science and Remote Sensing Symposium Proceedings, IEEE International, 3: 1286-1288.
  22. Liang, X., Xu, M., Gao, W., Kunkel, K., Slusser, J., Dai,Y., Min, Q., Houser, P.R., Rodell, M., Schaaf, C.B. & Gao, F., 2005, Development of land surface albedo parameterization based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, Geophysical Research, 110: 1-20
  23. Maurer, J., 2002, Retrieval of surface albedo from space, Part of a graduate course ("Remote Sensing Field Methods"), NASA/GSFC/LaRC/JPL, 1: 1-10.
  24. Muller, E. & Decamps, H., 2001, Modeling soil moisture-reflectance, Remote Sens Environ,76: 173– 180.
  25. Nicholson, S.E. & Frouin, R., 2001, Satellite-derived surface radiation budget over the African continent—Part II: Climatologies of the various components, Climate,14: 60–76.
  26. Opoku Duah, S., Donoghue, D. & Burt, T., 2008, Intercomparison of evapotranspiration over the Savannah Volta Basin in West Africa using remote sensing data, Sensors, 8:2736-2761.
  27. Pinty, B., Roveda, F., Verstraete, M.M., Gobron, N., Govaerts, Y. & Martonchik, J.V., 2000, Surface albedo retrieval from Meteosat, Geophysical Research, 18: 99-112.
  28. Robinson, D.A. & Kukla, G.,1985, Maximum surface albedo of seasonally snow-covered lands in the Northern Hemisphere, Clim Appl Meteorol, 24: 402– 411.
  29. Roujean, J.L. & Geiger, B., 2007, Use of a Kalman filter for the retrieval of surface BRDF coefficients with a time-evolving model based on the ECOCLIMAP land cover classification, Remote Sensing of Environment,3: 1-15.
  30. Schaaf, C. B., Gao, F., Strahler, A. H., Lucht,W., Li, X. & Tsang, T., 2002, First operational BRDF albedo and nadir reflectance products from MODIS, Remote Sensing of Environment, 83: 135–148.
  31. Schaaf, C.B., Gao, F., Strahler, A.H., Lucht, W., Li, X., Tsang, T., Strugnell, N.C., Zhang, X., Jin, Y. & Muller, J.P., 2002, First operational BRDF albedo nadir reflectance products from MODIS, Remote Sensing of Environment, 83:135-148.
  32. Strugnell, N.C. & Lucht, W., 2001, An algorithm to infer continental-scale albedo from AVHRR data, land cover class and field observations of typical BRDFs, Climate, 4: 1360–1376.
  33. Taberner, M., Pinty, B., Govaerts, Y., Liang, S., Verstraete, M. M. & Gobron, N., 2010, Comparison of MISR and MODIS land surface albedos: Methodology, Geophysical Research, 115: 29-40.
  34. Thomas, G. & Rowntree, P. R., 1992, The boreal forests and climate, Meteorol Soc, 118: 469–497.
  35. Twine, T.E., Kucharik, C.J. & Foley, J.A., 2004, Effects of land cover change on the energy and water balance of the Mississippi River Basin, Hydrometeorology , 5:640–655.
  36. Van Beek, E. & Meijer, K., 2006, Integrated water resources management for the Sistan closed inland delta, Iran, Delft, Netherlands, Delft hydraulics, www.wldelft.nl/cons/area/rbm/wrpl/pdf/main_report_ sistan_irwm.pdf.
  37. Wang, K., Liang, S., Schaaf, C.L. & Strahler, A.H., 2010, Evaluation of Moderate Resolution Imaging Spectroradiometer land surface visible and shortwave albedo products at FLUXNET sites, J. Geophys. Res, 115, D17107, doi:10.1029/2009JD013101.
  38. Wanner, W., Strahler, A.H., Hu, B. & Lewis, P.,1997, Global retrieval of bidirectional reflectance and albedo over land from MODIS and MISR data: Theory and algorithm, Journal of Geophysical Research, 102: 143-161.
  39. Wielicki, B.A., Wong, T., Loeb, N., Minnis, P., Priestley, K. & Kandel, R., 2005, Changes in Earth's albedo measured by satellite, Sci, 308: 825-825.
Iranian Journal of Remote Sensing & GIS
Volume 10, Issue 4 - Serial Number 4
February 2019
Pages 69-84

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