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A review of downscaling methods for remote sensing-based irrigation management: part I

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Abstract

High-resolution daily evapotranspiration (ET) maps would greatly improve irrigation management. Numerous ET mapping algorithms have been developed to make use of thermal remote sensing data acquired by satellite sensors. However, adoption of remote sensing-based ET maps for irrigation management has not been feasible due to inadequate spatial and temporal resolution of ET maps. Data from a coarse spatial resolution image in agricultural fields often cause inaccurate ET estimation because of a high level of spatial heterogeneity in land use. Image downscaling methods have been utilized to overcome spatial and temporal scaling issues in numerous remote sensing applications. In the field of hydrology, the image downscaling method has been used to improve spatial resolution of remote sensing-based ET maps for irrigation scheduling purposes and thus improves estimation of crop water requirements. This paper (part I) reviews downscaling methods to improve spatial resolution of land surface characteristics such as land surface temperature or ET. Each downscaling method was assessed and compared with respect to their capability of downscaling spatial resolutions of images. The companion paper (part II) presents review of image fusion methods that are also designed to increase spatial resolutions of images by integrating multi-spectral and panchromatic images.

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References

  • Adams JB, Smith MO, Johnson PE (1986) Spectral mixture modeling: a new analysis of rock and soil types at the Viking Lander 1 site. J Geophys Res 91:8098–8112

    Article  Google Scholar 

  • Agam N, Kustas WP, Anderson MC, Li F, Neale CMU (2007) A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sens Environ 107:545–558

    Article  Google Scholar 

  • Aiazzi B, Alparone L, Baronti S, Garzelli A (2002) Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis. IEEE Trans Geosci Remote 40:2300–2312

    Article  Google Scholar 

  • Allen RG, Tasumi M, Trezza R (2007a) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-model. J Irrig Drain Eng ASCE 133:380–394

    Article  Google Scholar 

  • Allen RG, Tasumi M, Morse A, Trezza R, Wright JL, Bastiaanssen W, Kramber W, Lorite I, Robinson CW (2007b) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-applications. J Irrig Drain Eng ASCE 133:395–406

    Article  Google Scholar 

  • An Q, Yang B (2007) A multi-crop identification model based on stepwise removal learning-support vector machine using remote sensing images. New Zeal J Agr Res 50:1013–1019

    Article  Google Scholar 

  • Anderson MC, Norman JM, Mecikalski JR, Torn RD, Kustas WP, Basara JB (2004) A multiscale remote sensing model for disaggregating regional fluxes to micrometeorological scales. J Hydrometeorol 5:343–363

    Article  Google Scholar 

  • Antonini M, Barlaud M, Mathieu P, Daubechies I (1992) Image coding using wavelet transform. IEEE Trans Image Process 1:205–220

    Article  PubMed  CAS  Google Scholar 

  • ASCE Task Committee on Application of Artificial Neural Networks in Hydrology (2000) Artificial neural networks in hydrology, I: preliminary concepts. J Hydrol Eng 5:115–123

    Article  Google Scholar 

  • Asner GP, Lobell DB (2000) A biogeophysical approach for automated SWIR unmixing of soils and vegetation. Remote Sens Environ 74:99–112

    Article  Google Scholar 

  • Atkinson PM, Tatnall ARL (1997) Introduction—neural network in remote sensing. Int J Remote Sens 18:699–709

    Article  Google Scholar 

  • Badeck F-W, Bondeau A, Böttcher K, Doktor D, Lucht W, Schaber J, Sitch S (2004) Responses of spring phenology to climate change. New Phytol 162:295–309

    Article  Google Scholar 

  • Bastiaanssen WGM (2000) SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. J Hydrol 229:87–100

    Article  Google Scholar 

  • Bastiaanssen WGM, Menenti M, Feddes RA, Holtslag AAM (1998) A remote sensing surface energy balance algorithm for land (SEBAL)—1. Formulation. J Hydrol 212–213:198–212

    Article  Google Scholar 

  • Bateson CA, Asner GP, Wessman CA (2000) Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis. IEEE Trans Geosci Remote 38:1083–1094

    Article  Google Scholar 

  • Bischof H, Schneider W, Pinz AJ (1992) Multispectral classification of landsat-imaes using newral networks. IEEE Trans Geosci Remote 30:482–490

    Article  Google Scholar 

  • Blyth EM (1995) Using a simple SVAT scheme to describe the effect of scale aggregation. Bound Lay Meteorol 72:267–285

    Article  Google Scholar 

  • Bocchiola D (2007) Use of scale recursive estimation for assimilation of precipitation data from TRMM (PR and TMI) and NEXTRAD. Adv Water Resour 30:2354–2372

    Article  Google Scholar 

  • Boucher A (2009a) Sub-pixel mapping of coarse satellite remote sensing images with stochastic simulations from training images. Math Geosci 41:265–290

    Article  Google Scholar 

  • Boucher A (2009b) Considering complex training images with search tree partitioning. Comput Geosci 35:1151–1158

    Article  Google Scholar 

  • Boucher A, Kyriakidis PC (2006) Super-resolution land cover mapping with indicator geostatistics. Remote Sens Environ 104:264–282

    Article  Google Scholar 

  • Braswell BH, Hagen SC, Frolking SE, Salas WA (2003) A multivariable approach for mapping sub-pixel land cover distributions using MISR and MODIS: Application in the Brazilian Amazon region. Remote Sens Environ 87:243–256

    Article  Google Scholar 

  • Brown ME, Lary DJ, Vrieling A, Stathakis D, Mussa H (2008) Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS. Int J Remote Sens 29:7141–7158

    Article  Google Scholar 

  • Bruzzone L, Melgani F (2005) Robust multiple estimator systems for the analysis of biophysical parameters from remotely sensed data. IEEE Trans Geosci Remote 43:159–174

    Article  Google Scholar 

  • Burges C (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Disc 2:121–167

    Article  Google Scholar 

  • Burton A, Fowler HJ, Blenkinsop S, Kilsby CG (2010) Downscaling transient climate change using a Neyman-Scott rectangular pulses stochastic rainfall model. J Hydrol 381:18–32

    Article  Google Scholar 

  • Chou KC (1991) A stochastic modeling approach to multiscale signal processing. Dissertation, Massachusetts Institute of Technology

  • Chou KC, Willsky AS, Benveniste A (1994a) Multiscale recursive estimation, data fusion, and regularization. IEEE Trans Autom Control 39:464–478

    Article  Google Scholar 

  • Chou KC, Willsky AS, Nikoukhah R (1994b) Multiscale systems, Kalman filters, and Riccati equations. IEEE Trans Autom Control 39:479–492

    Article  Google Scholar 

  • Das NN, Mohanty BP (2008) Temporal dynamics of PSR-based soil moisture across spatial scales in an agricultural landscape during SMES02: a wavelet approach. Remote Sens Environ 112:522–534

    Article  Google Scholar 

  • Dibike YB, Velickov S, Solomatine D, Abbott MB (2001) Model induction with support vector machines: introduction and applications. J Comput Civil Eng 15:208–216

    Article  Google Scholar 

  • Dozier J (1981) A method for satellite identification of surface temperature fields of subpixel resolution. Remote Sens Environ 11:221–229

    Article  Google Scholar 

  • Dumic E, Grgic S, Grgic M (2007) The use of wavelets in image interpolation: possibilities and limitations. Radioeng 16:101–109

    Google Scholar 

  • Foody GM, Cox DP (1994) Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions. Int J Remote Sens 15:619–631

    Article  Google Scholar 

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modeling. Int J Climatol 27:157–1578

    Article  Google Scholar 

  • Ghosh S, Mujumdar PP (2008) Statistical downscaling of GCM simulations to streamflow using relevance vector machine. Adv Water Resour 31:132–146

    Article  Google Scholar 

  • Gillespie AR (1992) Spectral mixture analysis of multispectral thermal infrared images. Remote Sens Environ 42:137–145

    Article  Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley Professional, Boston, MA, USA

    Google Scholar 

  • Gorenburg PI, McLaughlin D, Entekhabi D (2001) Scale-recursive assimilation of precipitation data. Adv Water Resour 24:941–953

    Article  Google Scholar 

  • Gowda PH, Chávez JL, Colaizzi PD, Evett SR, Howell TA, Tolk JA (2008) ET mapping for agricultural water management: present status and challenges. Irrig Sci 26:223–237

    Article  Google Scholar 

  • Guardiano F, Srivastava RM (1993) Multivariate geostatistics: beyond bivariate moments. In: Soares A (ed) Geostatistics-Troia, vol 1. Kluwer Academic, Dordrecht, pp 133–144

    Chapter  Google Scholar 

  • Gupta R, Venugopal V, Foufoula-Georgiou E (2006) A methodology for merging multisensor precipitation estimates based on expectation-maximization and scale-recursive estimation. J Geophys Res 111:D02102. doi:10.1029/2004JD005568

    Article  Google Scholar 

  • Hapke B (1981) Bidirectional reflectance spectroscopy: 1. Theory. J Geophys Res 86:3039–3054

    Article  Google Scholar 

  • Harvey JT (2002) Population estimation models based on individual TM pixels. Photogramm Eng Rem Sens 68:1181–1192

    Google Scholar 

  • Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, Upper Saddle River, NJ, USA

    Google Scholar 

  • Hewitson BC, Crane RG (1996) Climate downscaling: techniques and application. Clim Res 7:85–95

    Article  Google Scholar 

  • Immerzeel WW, Rutten MM, Droogers P (2009) Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula. Remote Sens Environ 113:362–370

    Article  Google Scholar 

  • Inamdar AK, French A (2009) Disaggregation of GOES land surface temperatures using surface emissivity. Geophys Res Lett 36:L02408. doi:10.1029/2008GL036544

    Article  Google Scholar 

  • Inamdar AK, French A, Hook S, Vaughan G, Luckett W (2008) Land surface temperature retrieval at high spatial and temporal resolutions over the southwestern United States. J Geophys Res 113:D07107. doi:10.1029/2007JD009048

    Article  Google Scholar 

  • Ines AVM, Mohanty BP (2008a) Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithm: 1. Conceptual modeling. Water Resour Res 44:W06422. doi:10.1029/2007WR005990

    Google Scholar 

  • Ines AVM, Mohanty BP (2008b) Parameter conditioning with a noisy Monte Carlo genetic algorithm for estimating effective soil hydraulic properties from space. Water Resour Res 44:W08441. doi:10.1029/2007WR006125

    Google Scholar 

  • Ines AVM, Mohanty BP (2008c) Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties under different hydroclimatic conditions. Vadose Zone J 7:39–52

    Article  Google Scholar 

  • Kaheil YH, Gill MK, McKee M, Bastidas LA, Rosero E (2008a) Downscaling and assimilation of surface soil moisture using ground truth measurements. IEEE Trans Geosci Remote 46(5):1375–1384

    Article  Google Scholar 

  • Kaheil YH, Rosero E, Gill MK, McKee M, Bastidas LA (2008b) Downscaling and forecasting of evapotranspiration using a synthetic model of wavelets and support vector machines. IEEE Trans Geosci Remote 46(9):2692–2707

    Article  Google Scholar 

  • Kannan A, Ostendorf M, Karl WC, Castañon DA, Fish RK (2000) ML parameter estimation of a multiscale stochastic process using the EM algorithm. IEEE Trans Signal Process 48:1836–1840

    Article  Google Scholar 

  • Karnieli A, Bayasgalan M, Bayarjargal Y, Agam N, Khudulmur S, Tucker CJ (2006) Comments on the use of the vegetation health index over Mongolia. Int J Remote Sens 27:2017–2024

    Article  Google Scholar 

  • Khlopenkov KV, Trishchenko AP (2008) Implementation and evaluation of concurrent gradient search method for reprojection of MODIS level 1B imagery. IEEE Trans Geosci Remote 46:2016–2027

    Article  Google Scholar 

  • Kohonen T (1988) An introduction to neural computing. Neural Netw 1:3–16

    Article  Google Scholar 

  • Koster RD, Suarez MJ (1992) A comparative analysis of two land surface heterogeneity representations. J Clim 5:1379–1390

    Article  Google Scholar 

  • Kustas WP, Norman JM (1999) Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover. Agric Forest Meteorol 94:13–29

    Article  Google Scholar 

  • Kustas WP, Norman JM, Anderson MC, French AN (2003) Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship. Remote Sens Environ 85:429–440

    Article  Google Scholar 

  • Kustas WP, Li F, Jackson TJ, Prueger JH, MacPherson JI, Wolde M (2004) Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa. Remote Sens Environ 92:535–547

    Article  Google Scholar 

  • Lafferty J, McCallum A, Pereira F (2001) Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Brodley CE, Danyluk AP (eds) Proceedings of the 18th international conference on machine learning. Morgan Kaufmann, San Francisco, CA, USA, pp 282–289

  • Liu D, Pu R (2008) Downscaling thermal infrared radiance for subpixel land surface temperature retrieval. Sensors 8:2695–2706

    Article  Google Scholar 

  • Lucas NS, Shanmugam S, Barnsley M (2002) Sub-pixel habitat mapping of a coastal dune ecosystem. Appl Geogr 22:253–270

    Article  Google Scholar 

  • Luo Y, Trishchenko AP, Khlopenkov KV (2008) Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America. Remote Sens Environ 112:4167–4185

    Article  Google Scholar 

  • Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal 11:674–693

    Article  Google Scholar 

  • McMillin LM (1975) Estimation of sea surface temperatures from two infrared window measurements with different absorption. J Geophys Res 80:5113–5117

    Article  Google Scholar 

  • Merlin O, Walker JP, Chehbouni A, Kerr Y (2008) Toward deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency. Remote Sens Environ 112:3935–3946

    Article  Google Scholar 

  • Moriondo M, Bindi M (2006) Comparison of temperatures simulated by GCMs, RCMs and statistical downscaling: potential application in studies of future crop development. Clim Res 30:149–160

    Article  Google Scholar 

  • Murphy J (1999) An evaluation of statistical and dynamical techniques for downscaling local climate. J Clim 12:2256–2284

    Article  Google Scholar 

  • Norman JM, Anderson MC, Kustas WP, French AN, Mecikalski J, Torn R, Diak GR, Schmugge TJ, Tanner BCW (2003) Remote sensing of surface energy fluxes at 101-m pixel resolution. Water Resour Res 39:1221. doi:10.1029/2002WR001775

    Article  Google Scholar 

  • Perica S, Foufoula-Georgiou E (1996) Model for multiscale disaggregation of spatial rainfall based on coupling meteorological and scaling descriptions. J Geophys Res 101:26347–26361

    Article  Google Scholar 

  • Price JC (1990) Using spatial context in satellite data to infer regional scale evapotranspiration. IEEE Trans Geosci Remote 28:940–948

    Article  Google Scholar 

  • Primus I (1996) Scale-recursive estimation of precipitation using remote sensing data. Thesis, Massachusetts Institute of Technology

  • Prudhomme C, Reynard N, Crooks S (2002) Downscaling of global climate models for flood frequency analysis: where are we now? Hydrol Process 16:1137–1150

    Article  Google Scholar 

  • Rahman S, Bagtzoglou AC, Hossain F, Tang L, Yarbrough LD, Easson G (2009) Investigating spatial downscaling of satellite rainfall data for streamflow simulation in a medium-sized basin. J Hydrometeorol 10:1063–1079

    Article  Google Scholar 

  • Raje D, Mujumdar PP (2009) A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin. Water Resour Res 45:W10404. doi:10.1029/2008WR007487

    Article  Google Scholar 

  • Robinson GD, Gross HN, Schott JR (2000) Evaluation of two applications of spectral mixing models to image fusion. Remote Sens Environ 71:272–281

    Article  Google Scholar 

  • Rosenblatt F (1958) The perceptron: a probabilistic model for information storage and organization in the brain. Psychol Rev 65:386–408

    Article  PubMed  CAS  Google Scholar 

  • Senay GB, Budde M, Verdin JP, Melesse AM (2007) A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields. Sensors 7:979–1000

    Article  Google Scholar 

  • Sentlinger GI, Hook SJ, Laval B (2008) Sub-pixel water temperature estimation from thermal-infrared imagery using vectorized lake features. Remote Sens Environ 112:1678–1688

    Article  Google Scholar 

  • Settle JJ, Drake NA (1993) Linear mixing and the estimation of ground cover proportions. Int J Remote Sens 14:1159–1177

    Article  Google Scholar 

  • Shouse PJ, Mohanty BP (1998) Scaling of near-saturated hydraulic conductivity measured using disc infiltrometers. Water Resour Res 34:1195–1205

    Article  Google Scholar 

  • Smith MO, Johnson PE, Adams JB (1985) Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis. J Geophys Res 90(Supplement):C797–C804

    Article  Google Scholar 

  • Strebelle S (2002) Conditional simulation of complex geological structures using multiple-point statistics. Math Geol 34:1–21

    Article  Google Scholar 

  • Su L (2009) Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis. ISPRS J Photogramm 64:407–413

    Article  Google Scholar 

  • Suykens JAK (2001) Nonlinear modeling and support vector machines. In: Proceedings of IEEE instrumentation and measurement technology conference (IMTC) 2001, Budapest, Hungary, pp 287–294

  • Tasumi M, Allen RG, Trezza R (2006) Calibrating satellite-based vegetation indices to estimate evapotranspiration and crop coefficients. In: Wichelns D, Anderson SS (eds) Proceedings of the 2006 USCID water management conference, ground water and surface water under stress: competition, interaction, solutions, published by USCID, Denver, CO, USA

  • Tatem AJ, Lewis HG, Atkinson PM, Nixon MS (2003) Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network. Int J Geogr Inf Sci 17:647–672

    Article  Google Scholar 

  • Timmermans WJ, Kustas WP, Anderson MC, French AN (2007) An intercomparison of the surface energy balance algorithm for land (SEBAL) and the two-source energy balance (TSEB) modeling schemes. Remote Sens Environ 108:369–384

    Article  Google Scholar 

  • Tripathi S, Srinivas VV, Nanjundiah RS (2006) Downscaling of precipitation for climate change scenarios: a support vector machine approach. J Hydrol 330:621–640

    Article  Google Scholar 

  • Trishchenko AP, Khlopenkov KV, Luo Y (2004) Retrieval of BRDF for pure landcover types from MODIS and MISR using an angular unmixing approach. Proc SPIE Int Soc Opt Eng 5549:167–175

    Article  Google Scholar 

  • Trishchenko AP, Luo Y, Khlopenkov KV (2006) A method for downscaling MODIS land channels to 250 m spatial resolution using adaptive regression and normalization. Proc SPIE Int Soc Opt Eng 6366, Art. No. 636607

  • Tustison B, Foufoula-Georgiou E, Harris D (2003) Scale-recursive estimation for multisensor quantitative precipitation forecast verification: a preliminary assessment. J Geophys Res 108(D8):8377. doi:10.1029/2001JD001073

    Article  Google Scholar 

  • van de Vyver H, Roulin E (2009) Scale-recursive estimation for merging precipitation data from radar and microwave cross-track scanners. J Geophys Res 114:D08104. doi:10.1029/2008JD010709

    Article  Google Scholar 

  • van der Meer F, de Jong SM (2000) Improving the results of spectral unmixing of Landsat thematic mapper imagery by enhancing the orthogonality of end-members. Int J Remote Sens 21:2781–2797

    Article  Google Scholar 

  • Vapnik VN (1995) The nature of statistical learning theory. Springer, New York, NY, USA

    Book  Google Scholar 

  • Vapnik VN (1998) Statistical learning theory. Wiley, New York, NY, USA

    Google Scholar 

  • Wan Z, Dozier J (1996) A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote 34:892–905

    Article  Google Scholar 

  • Wang W, Liang S (2009) Estimation of high-spatial resolution clear-sky longwave downward and net radiation over land surfaces from MODIS data. Remote Sens Environ 113:745–754

    Article  Google Scholar 

  • Wang W, Liang S, Augustine JA (2009) Estimating high spatial resolution clear-sky land surface upwelling longwave radiation from MODIS data. IEEE Trans Geosci Remote 47(5):1559–1570

    Article  Google Scholar 

  • Wieringa J (1986) Roughness-dependent geographic interpolation surface wind speed averages. Q J R Meteorol Soc 112:867–889

    Article  Google Scholar 

  • Wilby RL, Wigley TML (1997) Downscaling general circulation model output: a review of methods and limitations. Prog Phys Geog 21:530–548

    Article  Google Scholar 

  • Wu C, Murray AT (2007) Population estimation using Landsat enhanced thematic mapper imagery. Geogr Anal 39:26–43

    Article  Google Scholar 

  • Wu H, Li Z-L (2009) Scale issues in remote sensing: a review on analysis, processing and modeling. Sensors 9:1768–1793

    Article  PubMed  Google Scholar 

  • Yang F, White MA, Michaelis AR, Ichii K, Hashimoto H, Votava P, Zhu A-X, Nemani RR (2006) Prediction of continental-scale evapotranspiration by combining MODIS and AmeriFlux data through support vector machine. IEEE Trans Geosci Remote 44:3452–3461

    Article  Google Scholar 

  • Yang G, Pu R, Huang 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

    Article  Google Scholar 

  • Yocky DA (1996) Multiresolution wavelet decomposition image merger of Landsat thematic mapper and SPOT panchromatic data. Photogramm Eng Rem Sens 62:1067–1074

    Google Scholar 

  • Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12:2474–2489

    Article  Google Scholar 

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Acknowledgments

Funding for this study was provided by USDA-ARS and NASA Terrestrial Hydrology Program (Proposal No. 08-THP07-0053). Authors are grateful to reviewers who provided valuable comments.

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  1. Conservation and Production Research Laboratory, USDA-ARS, P.O. Drawer 10, Bushland, TX, 79012, USA

    Wonsook Ha, Prasanna H. Gowda & Terry A. Howell

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  1. Wonsook Ha
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Correspondence to Wonsook Ha.

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Communicated by I. Dodd.

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Ha, W., Gowda, P.H. & Howell, T.A. A review of downscaling methods for remote sensing-based irrigation management: part I. Irrig Sci 31, 831–850 (2013). https://doi.org/10.1007/s00271-012-0331-7

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