Stand-alone error characterisation of microwave satellite soil moisture using a Fourier method

Remote Sensing of Environment

Volumn 154, Issue 1, 2014, Pages 115-126

  Su, Chun Hsu ^a   Ryu, Dongryeol ^a   Crow, Wade T ^b   Western, Andrew W ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

Author keywords

AMSR E; ASCAT; Error estimation; Principal component analysis; Remote sensing; Soil moisture; Spectral analysis; Triple collocation

Indexed keywords

PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING; SOIL MOISTURE; SPECTRUM ANALYSIS;

AMSR-E; ASCAT; ERROR CHARACTERISATION; FOURIER METHODS; SATELLITE SOIL MOISTURE; STAND -ALONE; TRIPLE COLLOCATION;

ERROR ANALYSIS;

AMSR-E; ASCAT; ERROR ANALYSIS; RAINFALL; SATELLITE DATA; SEASONALITY; SIGNAL-TO-NOISE RATIO; SOIL MOISTURE; SPECTRAL ANALYSIS;

AUSTRALIA;

EID: 84908155531     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.08.014     Document Type: Article

References (58)

1. Albergel C., de Rosnay P., Gruhier C., Muñoz Sabater J., Hasenauer S., Isaksen, et al. Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment 2012, 118:215-226.
2. Barlow B.A. Phytogeography of the Australian region. Australian vegetation 1994, Cambridge University Press, Cambridge. 2nd ed. R.H. Groves (Ed.).
3. Bindlish R., Barros A.P. Subpixel variability of remotely sensed soil moisture: An inter-comparison study of SAR and ESTAR. IEEE Transactions on Geoscience and Remote Sensing 2002, 40(2):326-337.
4. Bound J., Jaeger D.A., Baker R.M. Problems with instrumental variables estimation when the correlation between instruments and the endogeneous explanatory variable is weak. Journal of the American Statistical Association 1995, 90(430):443-450.
5. Brocca L., Hasenauer S., Lacava T., Melone F., Moramarco T., Wagner W., et al. Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe. Remote Sensing of Environment 2011, 115:3390-3408.
6. Cowpertwait P.S.P. A generalized point process model for rainfall. Proceedings of the Royal Society A 1994, 447:23-37.
7. Crow W.T., Drusch M., Wood E.F. An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval. IEEE Transactions on Geoscience and Remote Sensing 2001, 39(8):1622-1631.
8. Crow W.T., van den Berg M.J. An improved approach for estimating observation and model error parameters in soil moisture data assimilation. Water Resources Research 2010, 46(12):W12519.
9. Danielson J.J., Gesch D.B. Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). U.S. Geological Survey Open-File Report 2011-1073 2011, (accessed online http://pubs.usgs.gov/of/2011/1073/pdf/of2011-1073.pdf).
10. Dorigo W.A., Scipal K., Parinussa R.M., Liu Y.Y., Wagner W., de Jeu R.A.M., et al. Error characterisation of global active and passive microwave soil moisture datasets. Hydrology and Earth System Sciences 2010, 14:2605-2616.
11. Dorigo W.A., Wagner W., Hohensinn R., Hahn S., Paulik C., Xaver A., et al. The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements. Hydrology and Earth System Sciences 2011, 15:1675-1698.
12. Draper C.S., Reichle R.R., de Jeu R.A., Naeimi V., Parinussa R.M., Wagner W. Estimating root mean square errors in remotely sensed soil moisture over continental scale domains. Remote Sensing of Environment 2013, 137:288-298.
13. Dunn P.K. Occurrence and quantity of precipitation can be modeled simultaneously. International Journal of Climatology 2004, 24:1231-1239.
14. Famiglietti J.S., Wood E.F. Multiscale modeling of spatially variable water and energy balance processes. Water Resource Research 1994, 11:3061-3078.
15. Garcia D. Robust smoothing of gridded data in one and higher dimensions with missing values. Computational Statistics and Data Analysis 2010, 54:1167-1178.
16. Hollmann R., Merchant C.J., Saunders R., Downy C., Buchwitz M., Cazenave A., et al. The ESA Climate Change Initiative: Satellite data records for essential climate variables. Bulletin of the American Meteorological Society 2013, 94:1541-1552.
17. Huffman G.J., Bolvin D.T., Nelkin E.J., Wolff D.B., Adler R.F., Gu G., et al. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology 2007, 8:38-55.
18. Jackson T.J., Cosh M.H., Bindlish R., Starks P.J., Bosch D.D., Seyfried M., et al. Validation of Advanced Microwave Scanning Radiometer soil moisture products. IEEE Transactions on Geoscience and Remote Sensing 2010, 48(12):4256-4263.
19. Jolliffe I.T. Principal component analysis 1989, Springer-Verlag, New York.
20. Katul G.G., Porporato A., Daly E., Oishi A.C., Kim H.-S., Stoy P.C., et al. On the spectrum of soil moisture from hourly to interannual scales. Water Resource Research 2007, 43:W05428.
21. Loew A. Impact of surface heterogeneity on surface soil moisture retrievals from passive microwave data at the regional scale: The Upper Danube case. Remote Sensing of Environment 2008, 112(1):231-248.
22. Loew A., Schlenz F. A dynamic approach for evaluating coarse scale satellite soil moisture product. Hydrology and Earth System Sciences 2011, 15:75-90.
23. Lymburner L., Tan P., Mueller N., Thackway R., Lewis A., Thankappan M., et al. 250 metre dynamic land cover dataset of Australia 2010, Geoscience Australia, Canberra. 1st ed.
24. McKenzie N.J., Jacquier D.W., Ashton L.J., Cresswell H.P. Estimation of soil properties using the Atlas of Australian Soils. CSIRO Land and Water Technical Report 11/00 2000, (Available Online at http://www.clw.csiro.au/aclep/documents/tr11-00.pdf).
25. Menke W. Geophysical data analysis: Discrete inverse theory 2012, Elsevier Science, Burlington.
26. Miralles D.G., Crow W.T., Cosh M.H. Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations. Journal of Hydrometeorology 2010, 11:1423-1429.
27. Mladenova I.E., Jackson T.J., Njoku E., Bindlish R., Chan S., Cosh M.H., et al. Remote monitoring of soil moisture using passive microwave-based techniques - Theoretical basis and overview of selected algorithms for AMSR-E. Remote Sensing of Environment 2014, 144:197-213.
28. Mo T., Choudhury B.J., Schmugge T.J., Wang J.R., Jackson T.J. A model for microwave emission from vegetation-covered fields. Journal of Geophysical Research 1982, 87(C13):11229-11237.
29. Naeimi V., Scipal K., Bartalis Z., Hasenauer S., Wagner W. An improved soil moisture retrieval algorithm for ERS and METOP scatterometer observations. IEEE Transanctions on Geoscience and Remote Sensing 2009, 47:1999-2013.
30. Northcote K.H., Beckmann G.G., Bettenay E., Churchward H.M., Van Dijk D.C., Dimmock G.M., et al. Atlas of Australian Soils, Sheets 1 to 10. With explanatory data 1960-1968, CSIRO Aust. and Melbourne University Press, Melbourne.
31. Owe M., de Jeu R., Holmes T. Multisensor historical climatology of satellite-derived global land surface moisture. Journal of Geophysical Research 2008, 113:F01002.
32. Paget M.J., King E.A. MODIS land data sets for the Australian region. CSIRO Marine and Atmospheric Research Internal Report 004 (Canberra, Australia) 2008, (last accessed online on 1 September 2014, https://remote-sensing.nci.org.au/u39/public/html/modis/lpdaac-mosaics-cmar/doc/ModisLand_PagetKing_20081203-final.pdf).
33. Parinussa R., Meesters A., Liu Y., Dorigo W., Wagner W., de Jeu R. Error estimates for near-real-time satellite soil moisture as derived from the Land Parameter Retrieval Model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2011, 8:779-783.
34. Peel M.C., Finlayson B.L., McMahon T.A. Updated world map of the Köppen-Geiger climate classification. Hydrological and Earth System Science 2007, 11:1633-1644.
35. Reichle R.H., Koster R.D., De Lannoy G.J.M., Forman B.A., Liu Q., Mahanama S.P.P., et al. Assessment and enhancement of MERRA land surface hydrology estimates. Journal of Climate 2011, 24(24):6322-6338.
36. Reiersøl O. Confluence analysis by means of lag moments and other methods of 640 confluence analysis. Econometrica 1941, 9(1):1-24.
37. Rienecker M., Suarez M.J., Gelaro R., Todling R., Bacmeister J., Liu E., et al. MERRA - NASA's modern-era retrospective analysis for research and applications. Journal of Climate 2011, 24(14):3624-3648.
38. Salvucci G.D. Estimating the moisture dependence of root zone water loss using conditionally averaged precipitation. Water Resource Research 2001, 37:1357-1365.
39. Scipal K., Holmes T., de Jeu R., Naeimi V., Wagner W. A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters 2008, 35:L24403.
40. Stoffelen A. Towards the true near-surface wind speed: Error modelling and calibration using triple collocation. Journal of Geophysical Research 1998, 103:7755-7766.
41. Su C.-H., Ryu D., Crow W.T., Western A.W. Beyond triple collocation: Applications to soil moisture monitoring. Journal of Geophysical Research: Atmosphere 2014, 119(11):6419-6439.
42. Su C.-H., Ryu D., Western A.W., Wagner W. De-noising of passive and active microwave soil moisture timeseries. Geophysical Research Letters 2013, 40:3624-3630.
43. Su C.-H., Ryu D., Young R.I., Western A.W., Wagner W. Inter-comparison of microwave satellite soil moisture retrievals over southeast Australia. Remote Sensing of Environment 2013, 134:1-11.
44. Ulaby F.T., Moore R.K., Fung A.K. Microwave remote sensing. Active and passive, Volume I, Reading 1981, Addison Wesley, MA.
45. Van Etten W.C. Introduction to random signals and noise 2005, John Wiley & Sons, West Sussex. England.
46. Verhoest N.E.C., Lievens H., Wagner W., Alverez-Mozos J., Moran M.S., Mattia F. On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from Synthetic Aperture Radar. Sensors 2008, 8(7):4213-4248.
47. Wagner W., Brocca L., Naeimi V., Reichle R., Draper C., de Jeu R., et al. Clarifications on the "Comparison between SMOS, VUA, ASCAT, and ECMWF soil moisture products over four watersheds in U.S.". IEEE Transactions on Geoscience and Remote Sensing 2014, 52(3):1901-1907.
48. Wagner W., Hahn S., Kidd R., Melzer T., Bartalis Z., Hasenauer S., et al. The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications. Meteorologische Zeitschrift 2013, 22:5-33.
49. Wagner W., Lemoine G., Rott H. A method for estimating soil moisture from ERS scatterometer and soil data. Remote Sensing of Environment 1999, 70:191-207.
50. Wang G., Garcia D., Liu Y., de Jeu R., Dolman A.J. A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations. Environmental Modelling and Software 2012, 30:139-142.
51. Welch P.D. The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified, periodograms. IEEE Transactions on Audio and Electroacoustics 1967, 15(2):70-73.
52. Western A.W., Grayson R.B., Blöschl G. Scaling of soil moisture: A hydrologic perspective. Annual Review of Earth and Planetary Sciences 2002, 30:149-180.
53. Wright P.G. The tariff on animal and vegetable oils 1928, Macmillan, New York.
54. Yilmaz M.T., Crow W.T. The optimality of potential rescaling approaches in land data assimilation. Journal of Hydrometeorology 2013, 14:650-661.
55. Yilmaz M.T., Crow W.T. Evaluation of assumptions in soil moisture triple collocation analysis. Journal of Hydrometeorology 2014, 15:1293-1302.
56. Yilmaz M.T., Crow W.T., Anderson M.C., Hain C. An objective methodology for merging satellite- and model-based soil moisture products. Water Resources Research 2012, 48:W11502.
57. Zwieback S., Dorigo W., Wagner W. Temporal error variability of coarse scale soil moisture products - Case study in central Spain. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International 2012, 722-725.
58. Zwieback S., Scipal K., Dorigo W., Wagner W. Structural and statistical properties of the collocation technique for error characterisation. Nonlinear Processes in Geophysics 2012, 19:69-80.