بهبود قدرت تفکیک زمانی-مکانی داده های تبخیر-تعرق واقعی با استفاده از ترکیب داده های مادیس و لندست-8

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد / مهندسی آبیاری و زهکشی، شرکت آب منطقه‌ای تهران.

2 استادیار / گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشگاه تربیت مدرس.

3 دانشیار / گروه مهندسی آبیاری و زهکشی، دانشگاه تربیت مدرس.

چکیده

هدف این مطالعه تولید نقشه‌های تبخیر- تعرق روزانه با قدرت تفکیک مکانی 30 متر و به صورت روزانه برای اراضی کشت و صنعت امیرکبیر با استفاده از دو سناریو می باشد. در سناریوی اول پارامترهای ورودی مورد نیاز الگوریتم سبال حاصل از تصاویر مادیس به قدرت تفکیک مکانی لندست-8 ریزمقیاس شد، سپس با استفاده از الگوریتم سبال و پارامترهای ورودی ریزمقیاس شده، تبخیر- تعرق واقعی محاسبه شد. در سناریوی دوم تبخیر- تعرق واقعی‌ بدست آمده از سنجنده مادیس به قدرت تفکیک مکانی لندست-8 ریزمقیاس شد. در سناریوهای اول و دوم ریزمقیاس کردن داده‌ها با سه روش نسبت، رگرسیون و شبکه‌ عصبی مصنوعی و با دو رویکرد مختلف انجام شد. در رویکرد اول فاصله زمانی بین تصویر پایه و تصویر ریزمقیاس شده از 1 روز تا 15 روز متغیر می‌باشد ولی در رویکرد دوم فاصله زمانی بین دو تصویر پایه و ریزمقیاس شده 1 روز می‌باشد. با مقایسه تبخیر- تعرق‌های واقعی ریزمقیاس شده با مقادیر تبخیر- تعرق واقعی بدست آمده از تصویر لندست-8 روش رگرسیون در سناریوی دوم با رویکرد اول با مجذور میانگین مربعات خطا 87/0 میلیمتر در روز دارای بهترین نتیجه و روش شبکه عصبی مصنوعی در سناریوی دوم با رویکرد دوم با مجذور میانگین مربعات خطا 25/2 میلیمتر در روز دارای بدترین نتیجه بود. اگرچه نتایج محاسبه تبخیر-تعرق واقعی حاصل از ریزمقیاس نمایی در تمامی روشها در هر دو سناریو و با هر دو رویکرد، نسبت به تبخیر- تعرق واقعی بدست آمده از تصویر مادیس با مجذور میانگین مربعات خطا 19/3 میلیمتر در روز دارای صحت بهتری بود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Spatio-temporal resolution improvement of actual evapotranspiration using MODIS and Landsat-8 data fusion

نویسندگان [English]

  • Hamid Salehi 1
  • Ali Shamsoddini 2
  • Seyed Majid Mirlatifi 3
1 Master of Agricultural Engineering (Irrigation), Regional Water Company of Tehran.
2 Assistant professor, Department of Remote Sensing and GIS, Tarbiat Modares University.
3 Associate professor, Department of Irrigation and Drainage, Tarbiat Modares University.
چکیده [English]

Recently, downscaling algorithms have been developed to obtain ET images with high temporal-spatial resolution. The purpose of the present study is to produce daily ET maps with spatial resolution of 30 m for farmlands of Amirkabir Agriculture & Industry. To reach this goal, two different scenarios were used. In the first scenario, SEBAL algorithm input parameters (surface albedo coefficient, normalized difference vegetation index [NDVI], leaf area index [LAI] and land surface temperature [LST]) calculated from MODIS data were downscaled to spatial resolution of Landsat-8, and then actual ET was calculated. In the second scenario, ET data estimated by MODIS data and SEBAL algorithm was downscaled to Landsat-8 spatial resolution. In the first and second scenarios, downscaling was conducted by applying three methods including ratio, regression and neural network. Also, two approaches were applied in this study. In the first approach, the time lag between the base image (image with higher spatial resolution) and MODIS image varies from 1 to 15 days, whereas in the second approach the time lag was 1 day. Comparing downscaled actual ET with actual ET calculated from Landsat-8 data, the regression method applied in the second scenario and first approach indicated the best result with RMSE=0.87 mm/day and neural network used in the second scenario and second approach showed the worst result with RMSE=2.25 mm/day. However downscaled actual ETs derived from different methods were more accurate than actual ET resulted from MODIS data with RMSE= 3.19 mm/day.

کلیدواژه‌ها [English]

  • evapotranspiration
  • MODIS
  • Landsat-8
  • Downscaling
  • SEBAL
Agam N, Kustas W P, Anderson M C, Li F, Neale C M U (2007a) A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sensing of Environment 107:545–558
Allen RG, Tasumi M, Trezza R, (2007) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-model. Journal of Irrigation and Drainage Engineering 133:380–394
Bastiaanssen W (2000) SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology 229:87-100
Bastiaanssen W, Menenti M, Feddes R, and Holtslag A (1998a) A remote sensing surface energy balance algorithm for land (SEBAL). Part 1, Formulation, Journal of Hydrology 212:198-212
Bastiaanssen W G M, Waters R, Allen R G, Tasumi M, and Terzza R (2002) Advanced training and user's manual of surface energy balance algorithms for Land. Nasa EOSDIS/Synergy Grant from the Raythoen Company through the Idaho Department of Water Resources.1:1-98
Brindhu V M, Narasimhan B, Sudheer K P (2013) Development and verification of a non-linear disaggregation method (NL-DisTrad) to downscale MODIS land surface temperature to the spatial scale of Landsat thermal data to estimate evapotranspiration. Remote Sensing of Environment 135:118-129
Brisco B, Brown R J, Hirose T, McNairn H, Staenz K (2014) Precision agriculture and the role of remote sensing, a review. Canadian Journal of Remote Sensing 24:315–327
Chandrapala L and Wimalasuriya M (2003) Satellite measurements supplemented with meteorological data to operationally estimate evaporation in Sri Lanka. Agricultural Water Management 58:89-107
Gao B C, Montes M J, Ahmad Z, Davis C O (2000) Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. Applied Optics 39(6):887-896
Ha W, Gowda P H, Howell T A (2012a) A review of downscaling methods for remote sensing-based irrigation management: part I. Irrig. Sci. 31, 831–850
Ha W, Gowda P.H, Howell T.A, (2012b) A review of potential image fusion methods for remote sensing-based irrigation management:part II. Irrigation Science 31:851–869
Hafeez M, Chemin Y, Van De Giesen N and Bouman B (2002) Field evapotranspiration estimation in central Luzon, Philippines using different sensors: Landsat 7 ETM+, Terra MODIS and ASTER. ISPRS/CIG conference July. P. 2002
Hong S, Hendrickx J M H, Borchers B (2011) Down-Scaling of SEBAL derived evapotranspiration maps from MODIS (250m) to LANDSAT (30m) scale. International Journal of Remote Sensing 32(21):6457-6477
Goshehgir AS, Golabi M, and Naseri AA (2018) Comparison of actual evapotranspiration estimated using Gram-Schmidt method and SEBAL algorithm with lysimetric data (Case study: Amir Kabir sugarcane argo-industry company). Iran- Water Resources Research 14(1):125-139 (In Persian)
Kaufman Y J, Tanre D, Gordon H R, Nakajima T, Lenoble J, Frouin R (1997) Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect. Journal of Geophysical Research: Atmospheres 102(D14):16815-16830
Kim J, Hogue T S (2012) Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions. Journal of Applied Remote Sensing, doi:10.1117/1.JRS.6.063569
Li H, Zheng L, Lei Y, Li C, Liu Z and Zhang S (2008) Estimation of water consumption and crop water productivity of winter wheat in North China Plain using remote sensing technology. Agricultural Water Management 95:1271-1278
Luo Y, Liu R, Feng Zhu Y (2008) Fusion of remote sensing image base on The PCA + ATROUS wavelet transform. The International Archives of the Pho- togrammetry, Remote Sensing and Spatial Information Sciences XXXVII (Part B7) 1155–1158
Mahour M, Tolpekin V, Stein A, Sharifi A (2017) A comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration. ISPRS Journal of Photogrammetry and Remote Sensing 126:56–67
McCabe M F, Wood E F (2006) Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors. Remote Sensing of Environment 105:271–285
Ramosa J G, Cratchley C, Kay J A, Casterad M A, Martinez-Cob A, and Dominguez Z (2008) Evaluation of satellite evapotranspiration estimates using ground-meteorological data available for the Flumen District into the Ebro Valley of N.E, Spain. Agricultural Water Management Journal AGWAT-2701:15-26
Salehi H, Shamsoddini A, Mirlatifi SM (2018) MODIS image downscaling using STARFM and SADFAT algorithms for daily Landsat-like spatial resolution evapotranspiration mapping. Iranian Remote Sensing & GIS 10(3) (In Persian)
Shamsoddini A, Trinder J C, and Turner R (2013) Non-linear methods for inferring lidar metrics using spot-5 textural data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W2
Senay G B, Budde M, Verdin J P, Melesse A M (2007) A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields. Sensors 7:979–1000
Singh R K, Senay G B, Velpuri N M, Bohms S, Verdin J P (2014) On the downscaling of actual evapotranspiration maps based on combination of MODIS and Landsat-based actual evapotranspiration estimates. Remote Sensing 6:10483-10509
Spiliotopoulos M, Adaktilou N, Toulios L (2013) A spatial downscaling procedure of MODIS derived actual evapotranspiration using Landsat images at central Greece. Conference Paper in Proceedings of SPIE - The International Society for Optical Engineering
Su Z (2002) The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Science 6:85–100
Hong S H, Hendrickx J M H, Borchers B (2011) Down-Scaling of SEBAL derived evapotranspiration maps from MODIS (250m) to LANDSAT (30m) scale. International Journal of Remote Sensing 32: 6437-6456
Tasumi M, Allen R G, Trezza R (2008) Atsurface reflectance and albedo from satellite for operational calculation of land surface energy balance. Journal of Hydrologic Engineering 13(2):51-63
Varvani H, Farhadi Bansouleh B, Sharifi M A (2019) Integration of Landsat 8 satellite images and MODIS sensor to estimate actual crop evapotranspiration of maize during the growing period (Case Study: Mahidasht, Kermanshah Province).  Iran-Water Resources Research 15(1):257-266 (In Persian)
 
Yang G, PU R, Hung W, Wang J, Zhao C (2010) A novel method to estimate subpixel temperature by fusing solar-reflective and thermal-infrared remote-sensing data with an artificial neural network. IEEE Trans Geosci Remote 48:2170-2178