Document Type : Research Paper
Authors
Abstract
The purpose of this paper was to make the preparation of soil surface moisture map applied in arid and semi-arid regions using satellite imagery of OLI and TIRS along with the calculated values for spectral reflectance, principal component analysis and Tasseled Cap transformation.Twenty-four predictor variables were used and the most correlated ones were identified at three moisture levels of 4 to 5 percent, more than 5 percent and less than 4 percent by exploratory regression and bivariate correlation method through calculating the inflation factor of variance, Pearson coefficient and coefficient of explanation. The Moran'sI index was used for geo-spatial autocorrelation. Forty-seven soil samples were collected randomly by creating 1800-meter networks in a systematic algorithm and the soil moisture was calculated by W-thermal method. The estimation functions of soil surface moisture were derived in the form of partial least square regression (PLSR), enter regression and stepwise regression. All models had acceptable calibration. Our results clearly showed that the Landsat 8 data could be useful in estimating soil surface moisture and the accuracy of the functions extracted with stepwise regression method was more than that of other methods (RMSE=0.585 to 1.425 %). The models introduced for a moisture level of ≤5%, tend to over estimate (MBE= 0.788) and for other moisture levels tend to underestimate.
Keywords
بداق جمالی، ج.، احمدیان، ج.، جوانمرد، س.، گلمکانی، ت. و ملکی‌زاده، ص.، 1382. ضرورت پایش وضعیت رطوبت خاک در افزایش بهره‌وری آب کشاورزی، مجموعه مقالات یازدهمین همایش کمیته ملی آبیاری و زهکشی ایران، 3 و 4 دی ماه 1382، تهران: 375-389.
خسروشاهی، م. 1387. نقش دوگانه‌ی آب در بیابانزایی و مهار آن. جنگل و مرتع، 78: 26-31.
خسروشاهی، م.، سید اخلاقی، س.ج.، عباسی، ح.ر.، شفیعی، ش.، رهبر، ا.، روحی‌پور، ح.، مومن‌زاده، م.، انصافی مقدم، خ.، فتاحی، م.، جعفریان، و.، بدری‌پور، ح. و حقانی، ق.، 1394. چالش‌ها و راهبرد‌های مقابله با ریزگرد‌ها در ایران (سند راهبردی آب و ریزگرد)، جنگل و مرتع، 104: 7-12.
زهتابیان، غ.، رفیعی امام، ع. و اسماعیل‌زاده، ح.، 1383. معیارها و شاخص های موثر در بیابان زایی با تاکید بر نقش آب. جنگل و مرتع، 62: 16-23.
Babaeyan, A., Homaee, M. and Noroozi, A. A., 2013. Estimating topsoil moisture from ENVISAT/ASAR. Journal of Water Research in Agriculture, 27(4): 611-622.
Babazadeh, H., Norouzi Aghdam, E., Aghighi, H., Shamsnia, S.A. and Khodadadi dehkordi, D., 2012. Estimation of soil surface moisture in arid and semi arid rangelands using remotely sensed Temperature/Vegetation Index measurements (TVX), (Case Study: Khorasan Province). Iranian journal of Range and Desert Reseach, 19(1): 120-132.
Champagne, C., McNairn, H. and Berg, A. A., 2011. Monitoring agricultural soil moisture extremes in Canada using passive microwave remote sensing. Remote Sensing of Environment, 115(10): 2434–2444.
Chen, C. F., Son, N. T., Chang, L. U. and Chen, C. C., 2011. Monitoring of soil moisture variability in relation to rice cropping systems in the Vietnamese Mekong Delta using MODIS data. Applied Geography, 31(2): 463–475.
Dodge, Y., 2003. The Oxford Dictionary of Statistical Terms. Oxford University Press. ISBN 0-19-850994-4, 506 pages.
Ebrahimi, Z., Valli, A., Ghazavi, R. and Haghparast. H., 2013. The effect of the components of soil texture and geometric mean particle diameter on topsoil spectral response, Case study: a part of the Khatam-e-Kavir Yazd. Journal of Quantitative Geomorphological Researches, 1(3): 115-128.
Fang, B. and Lakshmi, V., 2014. Soil moisture at watershed scale: Remote sensing techniques. Journal of Hydrology, 516: 258–272.
Feiznia, S., Ghauomian, J. and Khadjeh, M., 2005. The study of the effect of physical, chemical, and climate factors on surface erosion sediment yield of loess soils (Case study in Golestan province). Journal of Pajouhesh & Sazandegi,. 66: 14-24.
Gao, B. C., 1996. NDWI-a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3): 257–266.
Gringof, I. G. and Nabiev, Kh R., 1987. Modern methods of soil moisture measurement: problems and discussion. Soviet Meteorology and Hydrology, (10): 79-84.
Huete, A. R., 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, (25) 3: 295-309.
Karnieli, A. and Ben-Asher, J., 1993. A Daily Runoff Simulation in Semi-arid Watersheds Based on Deficit Calculations, Journal of Hydrology, 149: 9-25.
Kauth, R.J. and Thomas, G. S., 1976. The tasseled Cap – A graphic description of the spectral-temporal development of agricultural crops as seen by LANDSAT. Proceedings of the Symposium on Machine Processing of Remotely Sensed Data, Purdue University of West Lafayette, Indiana, (4B): 41-51.
Keshavarz, M. R., Vazifedoust, M., Alizadeh, A and Asadi, A., 2011. Soil Moisture Routing Using Moderate Spatial Resolution of MODIS Satellite Data, A case Study: Esfahan Province. Iranian Journal of lrrigation and drainage, 5(2): 209-219.
Keshavarzi, M., Nazemi, A. M., Ashraf Sadradini, S. A., Nayshabori. M. R. and Naseri, A., 2013. Effect of soil texture on accuracy of time domain reflectometry methods for measurement of soil moisture content. Journal of Irrigation and Water Engineering, 3(11): 14-23.
Legates, D. R., 2000. Remote sensing hydro climatology: An introduction. The professional Geographer, 52(2): 233-234.
Liu, H. Q. and Huete, A. R., 1995. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 33(2): 457-465.
Lu, H., Koike, T, Yang, K., Hu, Z., Xu, X., Rasmy, M., Kuria, D. and Tamagawab, K., 2012. Improving land surface soil moisture and energy flux simulations over the Tibetan plateau by the assimilation of the microwave remote sensing data and the GCM output into a land surface model. International Journal of Applied Earth Observation and Geoinformation, 17: 43-54.
National Aeronautics and Space Administration (NASA), 2015. SMAP, in: http://smap.jpl.nasa.gov/.
Noroozi, A. A., Homaee, M. and Farshad, A., 2014. Estimating topsoil salinity from LANDST data: A comparison between classic and spatial statistic. Journal of Range and Watershed Management, 66(4):609-620.
Norouzi Aghdam, E., Behbahani, M.R., Rahimikhob, A. and Aghighi, H., 2009. Surface soil moisture model with NDVI (Case study: rangeland of Khorasan. province). Journal of Environmental Studies, 34(48): 127-36.
Orsham, A., Akhund ali, A.M. and Behnia, A., 2010. Effect of soil antecedent moisture contents on runoff and sedimentation values with simulated rainfall method. Iranian journal of Range and Desert Reseach, 16(4): 445-55.
Pearson, K.,1901. "On Lines and Planes of Closest Fit to Systems of Points in Space" (PDF). Philosophical Magazine, 2 (11): 559–572.
Qi, J., Chehbouni, A., Huete, A.R. and Kerr, Y.H., 1994. "A modified soil adjusted vegetation index", Remote Sensing of Environment, 48(2): 119–126.
Rahimzadeh B., P., Berg, A. A., Champagne, C. and Omasa, K., 2013. Estimation of soil moisture using optical/thermal infrared remote sensing in the Canadian Prairies. ISPRS Journal of Photogrammetry and Remote Sensing, 83: 94–103.
Rosenbaum, U., Bogena, H. R., Herbst, M., Huisman, J. A., Peterson, T. J., Weuthen, A., Western, A. W. and Vereecken, H., 2012. Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale, Water Resources Research, 48, W10544: 1-22.
Rouse, J. W., Haas, R. H., Schell, J.A. and Deering, D. W., 1973. Monitoring vegetation systems in the great plainswith ERTS (Earth Resources Technology Satellite). Proceedings of 3rd Earth Resources Technology Satellite SymposiumGreenbelt, 10-14 December, SP-351: 309-317.
Russell, C. A., 2003. Sample preparation andprediction of soil organic matter properties by nearinfra-red reflectance spectroscopy. Soil Scienceand Plant Analaysis, 34(11-12): 1557–1572..
Sanchez R., S., Piles, M., Sánchez, N., M.Fernández, J. M., V.llossera, M. V. and Camps, A., 2014. Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates. Journal of Hydrology, 516: 273–283.
Sharifi, F., Safarpour, Sh., Ayoubzadeh, S. A. and Vakilpour, J., 2004. An investigation of factors affecting runoff generationi in arid and semi-arid area using simulation and rainfall runoff data. Iranian Journal of Natural Resources, 57(1): 33-45.
Shaun, R. S., Wulder, M. A. and Franklin, S. E., 2003. Sensitivity of thematicmapper enhanced wetness difference index to detect mountain pine beetle red-attract damage. Remote Sens. of Environ.,86.: 433-443.
Wang, H., Li, X., Long, H., Xu. X. and Bao, Y., 2010. Monitoring the effects of landuse and cover type changes on soil moisture using RS data: A case study in China's Yongding River basin. CATENA, 82(3): 135-145.
Xu, H., 2006. Modification of normalized difference water Index (NDWI) to enhance open water features in Remotely Sensed Imagery. International Journal of Remote Sensing, 80(3): 3025-3033.
Ziaee, D. and Khajedin, S. J., 2013. Mapping of soil texture and saturated soil surface moisture using remote sensing, (Case study: Esfahan). Iranian Journal of Range and Desert Reseach, 20(4): 795-808.
)