L-band vegetation optical depth and effective scattering albedo estimation from SMAP

Remote Sensing of Environment

Volumn 198, Issue , 2017, Pages 460-470

  Konings, Alexandra G ^a   Piles, Maria ^b   Das, Narendra ^c   Entekhabi, Dara ^d  

^a STANFORD UNIVERSITY   (United States)

^b UNIVERSITY OF VALENCIA   (Spain)

^c CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Effective scattering albedo; L band radiometry; Vegetation optical depth

Indexed keywords

ATMOSPHERIC HUMIDITY; FREQUENCY BANDS; INTERFERENCE SUPPRESSION; LUMINANCE; MOISTURE; NASA; OPTICAL PROPERTIES; RADIOMETRY; SOIL MOISTURE; SOILS; SOLAR RADIATION; SPACE FLIGHT; TEMPERATURE; VEGETATION;

L-BAND RADIOMETRY; MICROWAVE BRIGHTNESS TEMPERATURE; RADIO FREQUENCY INTERFERENCE; SCATTERING ALBEDOS; SOIL MOISTURE ACTIVE PASSIVE (SMAP); SOIL MOISTURE AND OCEAN SALINITY (SMOS); SOIL MOISTURE RETRIEVALS; VEGETATION OPTICAL DEPTH;

VIDEO ON DEMAND;

ALBEDO; ALGORITHM; BIOME; BRIGHTNESS TEMPERATURE; DATA SET; ESTIMATION METHOD; LAND COVER; OPTICAL DEPTH; RADIOMETER; SCATTERING; SMOS; SOIL EMISSION; SOIL MOISTURE; VEGETATION COVER;

EID: 85021741892     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.06.037     Document Type: Article

References (70)

1. Andela, N., Liu, Y.Y., van Dijk, A.I.J.M., de Jeu, R.A.M., McVicar, T.R., Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data. Biogeosciences 10:10 (2013), 6657–6676, 10.5194/bg-10-6657-2013.
2. Arino, O., Arino, O., Gross, D., Gross, D., Ranera, F., Ranera, F., GlobCover: ESA service for global land cover from MERIS. Processing, 2000, 2412–2415.
3. 2 at high northern latitudes from 1950 to 2011. Glob. Chang. Biol. 19:10 (2013), 3167–3183, 10.1111/gcb.12283.
4. Chan, S., SMAP Ancillary Data Report: Static Water Fraction. 2013, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, JPLD-53059.
5. Chan, S., SMAP Ancillary Data Report: Vegetation Water Content. 2013, Jet Propuls. Lab. Calif. Inst. Technol., JPL, D047.
6. Chan, S.K., et al. Assessment of the SMAP passive soil moisture product. IEEE Trans. Geosci. Remote Sens. 54:8 (2016), 4994–5007, 10.1109/TGRS.2016.2561938.
7. Chaubell, J., Yueh, S., Entekhabi, D., Peng, J., Resolution enhancement of SMAP radiometer data using the Backus Gilbert optimum interpolation technique. 2016 IEEE Int. Geosci. Remote Sens. Symp, 2016, 284–287, 10.1109/IGARSS.2016.7729065.
8. Chaubell, M.J., Chan, S., Dunbar, R.S., Peng, J., Yueh, S., SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures, Version 1. 2016, 10.5067/2C9O9KT6JAWS.
9. Choudhury, B., Schmugge, T., Mo, T., A parameterization of effective soil temperature for microwave emission. J. Geophys. Res. 87 (1982), 1301–1304.
10. Crow, W.T., Chan, S.T.K., Entekhabi, D., Houser, P.R., Hsu, A.Y., Jackson, T.J., Njoku, E.G., O'Neill, P.E., Shi, J., Zhan, X., An observing system simulation experiment for Hydros radiometer-only soil moisture products. IEEE Trans. Geosci. Remote Sens. 43:6 (2005), 1289–1303, 10.1109/TGRS.2005.845645.
11. Das, N., O'Neill, P., Selection of Soil Attributes Datasets for the SMAP Mission, SMAP Science Document #D-53058, 1.1, JPL, Dec., 2010. 2010.
12. De Lannoy, G.J.M., Reichle, R.H., Vrugt, J.A., Uncertainty quantification of GEOS-5 L-band radiative transfer model parameters using Bayesian inference and SMOS observations. Remote Sens. Environ. 148 (2014), 146–157.
13. Du, J., Kimball, J.S., Jones, L.A., Member, S., Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E. IEEE Trans. Geosci. Remote Sens., 1–12, 2015.
14. Entekhabi, D., Reichle, R.H., Koster, R.D., Crow, W.T., Performance metrics for soil moisture retrievals and application requirements. J. Hydrometeorol. 11:3 (2010), 832–840, 10.1175/2010JHM1223.1.
15. Entekhabi, D., Yueh, S., O'Neill, P., Kellogg, K.H., Al, E., SMAP Handbook. 2014.
16. Fernandez-Moran, R., Al-Yaari, A., Mialon, A., Mahmoodi, A., Al Bitar, A., De Lannoy, G., Rodriguez-Fernandez, N., Lopez-Baeza, E., Kerr, Y., Wigneron, J.-P., SMOS-IC: an alternative SMOS soil moisture and vegetation optical depth product. Remote Sens., 9, 2017, 457, 10.3390/rs9050457.
17. Grant, J.P., Wigneron, J.-P., De Jeu, R.A.M., Lawrence, H., Mialon, A., Richaume, P., Al Bitar, A., Drusch, M., Van Marle, M.J.E., Kerr, Y., Comparison of SMOS and AMSR-E vegetation optical depth to four MODIS-based vegetation indices. Remote Sens. Environ. 172 (2016), 87–100.
18. Gruber, A., Su, C.-H., Zwieback, S., Crow, W., Dorigo, W., Wagner, W., Recent advances in (soil moisture) triple collocation analysis. Int. J. Appl. Earth Obs. Geoinf., 2015, 10.1016/j.jag.2015.09.002.
19. Guan, K., Wolf, A., Medvigy, D., Caylor, K.K., Pan, M., Wood, E.F., Seasonal coupling of canopy structure and function in {A}frican tropical forests and its environmental controls. Ecosphere, 4(3), 2013 (art35–, doi:10.1890/ES12-00232.1).
20. Guan, K., Wood, E.F., Medvigy, D., Kimball, J., Pan, M., Caylor, K.K., Sheffield, J., Xu, X., Jones, M.O., Terrestrial hydrological controls on land surface phenology of African savannas and woodlands. J. Geophys. Res. Biogeosci. 119 (2014), 1652–1669, 10.1002/2013JG002572.
21. Guanter, L., et al. Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc. Natl. Acad. Sci. 111:14 (2014), E1327–E1333, 10.1073/pnas.1320008111.
22. Hellkvist, J., R., G.P., J., P.G., Vertical gradients of water potential and tissue water relations in sitka spruce trees measured with the pressure chamber. J. Appl. Ecol., 11(2), 1974, 637.
23. Jackson, T., Schmugge, T., Vegetation effects on the microwave emission of soils. Remote Sens. Environ. 36:3 (1991), 203–212.
24. Jiménez-Muñoz, J.C., Mattar, C., Barichivich, J., Santamaría-Artigas, A., Takahashi, K., Malhi, Y., Sobrino, J.A., van der Schrier, G., Record-breaking warming and extreme drought in the Amazon rainforest during the course of El Niño 2015–2016. Sci Rep, 6(May), 2016, 33130, 10.1038/srep33130.
25. Jones, L.A., Ferguson, C.R., Kimball, J.S., Zhang, K., Chan, S.T.K., McDonald, K.C., Njoku, E.G., Wood, E.F., Satellite microwave remote sensing of daily land surface air temperature minima and maxima from AMSR-E. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 3:1 (2010), 111–123, 10.1109/JSTARS.2010.2041530.
26. Jones, M.O., Jones, L.A., Kimball, J.S., McDonald, K.C., Satellite passive microwave remote sensing for monitoring global land surface phenology. Remote Sens. Environ. 115:4 (2011), 1102–1114, 10.1016/j.rse.2010.12.015.
27. Jones, M.O., Kimball, J.S., Jones, L.A., McDonald, K.C., Satellite passive microwave detection of North America start of season. Remote Sens. Environ. 123:0 (2012), 324–333, 10.1016/j.rse.2012.03.025.
28. Kerr, Y.H., Njoku, E.G., A semiempirical model for interpreting microwave emission from semiarid land surfaces as seen from space. IEEE Geosci. Remote Sens. Lett. 28:3 (1990), 384–393.
29. Kerr, Y.H., et al. The SMOS mission: new tool for monitoring key elements of the global water cycle. Proc. IEEE 98:5 (2010), 666–687, 10.1109/JPROC.2010.2043032.
30. Kerr, Y.H., Waldteufel, P., Richaume, P., Wigneron, J.-P., Ferrazzoli, P., Mahmoodi, A., Al Bitar, A., Cabot, F., Gruhier, C., Juglea, S.E., Leroux, D., Mialon, A., Delwart, S., The SMOS soil moisture retrieval algorithm. IEEE Trans. Geosci. Remote Sens. 50 (2012), 1384–1403.
31. Kerr, Y.H., Waldteufel, P., Richaume, P., Ferrazzoli, P., Wigneron, J.-P., SMOS level 2 processor soil moisture algorithm theoretical basis document (ATBD): SO-TN-ARR-L2PP-0037 v3.9. Toulouse, SM-ESL (CBSA). https://earth.esa.int/web/guest/-/data-processors-7632, 2015.
32. Kim, S., SMAP Ancillary Data Report on Landcover Classification. 2013, Jet Propuls. Lab. Calif. Inst. Technol., JPL, D-53057.
33. Konings, A.G., Gentine, P., Global variations in ecosystem-scale isohydricity. Glob. Chang. Biol. 23 (2017), 891–905, 10.1111/gcb.13389.
34. Konings, A.G., Entekhabi, D., Chan, S.K., Njoku, E.G., Effect of radiative transfer uncertainty on L-band radiometric soil moisture retrieval. IEEE Trans. Geosci. Remote Sens. 49:7 (2011), 2686–2698, 10.1109/TGRS.2011.2105495.
35. Konings, A.G., McColl, K.A., Piles, M., Entekhabi, D., How many parameters can be maximally estimated from a set of measurements?. IEEE Geosci. Remote Sens. Lett., 12(5), 2015, 10.1109/LGRS.2014.2381641.
36. Konings, A.G., Piles, M., Rotzer, K., McColl, K.A., Chan, S.K., Entekhabi, D., Vegetation optical depth and scattering albedo retrieval using time series of dual-polarized L-band radiometer observations. Remote Sens. Environ. 172 (2016), 178–189, 10.1016/j.rse.2015.11.009.
37. Konings, A.G., Williams, A.P., Gentine, P., Sensitivity of grassland productivity to aridity controlled by stomatal and xylem regulation. Nat. Geosci. 10 (2017), 284–288, 10.1038/ngeo2903.
38. Kurum, M., Quantifying scattering albedo in microwave emission of vegetated terrain. Remote Sens. Environ. 129:0 (2013), 66–74.
39. Kurum, M., O'Neill, P.E., Lang, R.H., Joseph, A.T., Cosh, M.H., Jackson, T.J., Effective tree scattering and opacity at L-band. Remote Sens. Environ. 118:0 (2012), 1–9.
40. Lawrence, H., Wigneron, J.-P., Richaume, P., Novello, N., Grant, J., Mialon, A., Al Bitara, A., Merlin, O., Guyon, D., Leroux, D., Comparison between SMOS vegetation optical depth products and MODIS vegetation indices over crop zones of the USA. Remote Sens. Environ. 140:0 (2014), 396–406, 10.1016/j.rse.2013.07.021.
41. Le Vine, D.M., Lagerloef, G.S., Torrusio, S., Aquarius and remote sensing of sea surface salinity from space. Proc. IEEE 98:5 (2010), 688–703.
42. Liu, Y.Y., de Jeu, R.A.M., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M., Global long-term passive microwave satellite-based retrievals of vegetation optical depth. Geophys. Res. Lett., 38(18), 2011, L18402.
43. Liu, Y.Y., Evans, J.P., McCabe, M.F., de Jeu, R.A.M., van Dijk, A.I.J.M., Dolman, A.J., Saizen, I., Changing climate and overgrazing are decimating Mongolian steppes. PLoS One 8:2 (2013), 4–9, 10.1371/journal.pone.0057599.
44. Liu, Y.Y., van Dijk, A.I.J.M., de Jeu, R.A.M., Canadell, J.G., McCabe, M.F., Evans, J.P., Wang, G., Recent reversal in loss of global terrestrial biomass. Nat. Clim. Chang. 5:May (2015), 470–474, 10.1038/nclimate2581.
45. Matzler, C., Microwave transmissivity of a forest canopy: experiments made with a beech. Remote Sens. Environ. 48:2 (1994), 172–180, 10.1016/0034-4257(94)90139-2.
46. McColl, K.A., Vogelzang, J., Konings, A.G., Entekhabi, D., Piles, M., Stoffelen, A., Extended triple collocation: estimating errors and correlation coefficients with respect to an unknown target. Geophys. Res. Lett., 41(17), 2014, 10.1002/2014GL061322.
47. McColl, K.A., Entekhabi, D., Piles, M., Uncertainty analysis of soil moisture and vegetation indices using aquarius scatterometer observations. IEEE Trans. Geosci. Remote Sens. 52:7 (2014), 4259–4272.
48. Meesters, A.G.C.A., de Jeu, R.A.M., Owe, M., Analytical derivation of the vegetation optical depth from the microwave polarization difference index. IEEE Geosci. Remote Sens. Lett. 2:2 (2005), 121–123.
49. Mironov, V.L., Dobson, M.C., Kaupp, V.H., Komarov, S.a., Kleshchenko, V.N., Generalized refractive mixing dielectric model for moist soils. IEEE Trans. Geosci. Remote Sens. 42:4 (2004), 773–785, 10.1109/TGRS.2003.823288.
50. Mohammed, P.N., Aksoy, M., Piepmeier, J.R., Johnson, J.T., Bringer, A., SMAP L-band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations. IEEE Trans. Geosci. Remote Sens. 54:10 (2016), 6035–6047, 10.1109/TGRS.2016.2580459.
51. Njoku, E.G., Ashcroft, P., Chan, T.K., Li, L., Global survey and statistics of radio-frequency interference in AMSR-E land observations. IEEE Trans. Geosci. Remote Sens. 43:5 (2005), 938–946, 10.1109/TGRS.2004.837507.
52. Oliva, R., Daganzo, E., Richaume, P., Kerr, Y.H., Cabot, F., Soldo, Y., Anterrieu, E., Reul, N., Gutierrez, A., Barbosa, J., Lopes, G., Status of radio frequency interference (RFI) in the 1400–1427 MHz passive band based on six years of SMOS mission. Remote Sens. Environ. 180 (2016), 64–75.
53. O'Neill, P.E., Njoku, E.G., Jackson, T.J., Chan, S., Bindlish, R., SMAP Algorithm Theoretical Basis Document: Level 2 & 3 Soil Moisture (Passive) Data Products. 2015, Jet Propuls. Lab. Calif. Inst. Technol., JPL, D-66480.
54. O'Neill, P.E., Chan, S., Njoku, E.G., Jackson, T., Bindlish, R., SMAP Enhanced L3 Radiometer Global Daily 9 km EASE-Grid Soil Moisture, Version 1. 2016, NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado USA, 10.5067/ZRO7EXJ8O3XI (February 2017).
55. Owe, M., de Jeu, R., Holmes, T., Multisensor historical climatology of satellite-derived global land surface moisture. J. Geophys. Res. Earth Surf., 113(F1), 2008, 10.1029/2007JF000769.
56. Parrens, M., Wigneron, J.-P., Richaume, P., Mialon, A., Al Bitar, A., Fernandez-Moran, R., Al-Yaari, A., Kerr, Y.H., Global-scale surface roughness effects at L-band as estimated from SMOS observations. Remote Sens. Environ. 181 (2016), 122–136.
57. Patton, J., Hornbuckle, B., Initial validation of SMOS vegetation optical thickness in Iowa. IEEE Geosci. Remote Sens. Lett. 10:4 (2013), 647–651, 10.1109/LGRS.2012.2216498.
58. Piles, M., McColl, K.A., Entekhabi, D., Das, N., Pablos, M., Sensitivity of aquarius active and passive measurements temporal covariability to land surface characteristics. IEEE Trans. Geosci. Remote Sens. 53:8 (2015), 4700–4711.
59. Simard, M., Pinto, N., Fisher, J.B., Baccini, A., Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res. Biogeosci. 116:November (2011), 1–12, 10.1029/2011JG001708.
60. SMAP Algorithm Development Team and Science Team, Ancillary Data Report on Surface Temperature. 2016, Jet Propuls. Lab. Calif. Inst. Technol., JPL, D-53064.
61. Tian, F., Brandt, M., Liu, Y.Y., Rasmussen, K., Fensholt, R., Mapping gains and losses in woody vegetation across global tropical drylands. Glob. Chang. Biol., 1–13, 2016, 10.1111/gcb.13464.
62. Tian, F., Brandt, M., Liu, Y.Y., Verger, A., Tagesson, T., Diouf, A.A., Rasmussen, K., Mbow, C., Wang, Y., Fensholt, R., Remote sensing of vegetation dynamics in drylands: evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel. Remote Sens. Environ. 177 (2016), 265–276, 10.1016/j.rse.2016.02.056.
63. Ulaby, F.T., Long, D.G., Microwave Radar and Radiometric Remote Sensing. 2014, The Univerity of Michigan Press, Ann Arbor.
64. Van de Griend, A.A., Owe, M., Microwave vegetation optical depth and inverse modeling of soil emissivity using nimbus SMMR satellite-observations. Meteorog. Atmos. Phys. 54:1–4 (1994), 225–239.
65. Van der Schalie, R., Parinussa, R.M., Renzullo, L.J., van Dijk, A.I.J.M., Su, C.-H., de Jeu, R.a.M., SMOS soil moisture retrievals using the land parameter retrieval model: evaluation over the Murrumbidgee Catchment, southeast Australia. Remote Sens. Environ. 163 (2015), 70–79, 10.1016/j.rse.2015.03.006.
66. Vittucci, C., Ferrazzoli, P., Kerr, Y., Richaume, P., Guerriero, L., Rahmoune, R., Vaglio Laurin, G., SMOS retrieval over forests: exploitation of optical depth and tests of soil moisture estimates. Remote Sens. Environ. 180 (2016), 115–127.
67. Vrieling, A., De Leeuw, J., Said, M.Y., Length of growing period over africa: variability and trends from 30 years of NDVI time series. Remote Sens. 5:2 (2013), 982–1000, 10.3390/rs5020982.
68. Wigneron, J.-P., Parde, M., Waldteufel, P., Chanzy, A., Kerr, Y., Schmidl, S., Skou, N., Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band. IEEE Trans. Geosci. Remote Sens. 42 (2004), 416–425, 10.1109/TGRS.2003.817976.
69. Wigneron, J.-P., Jackson, T.J., O'Neill, P., Lannoy, De, de Rosnay, P., Walker, J.P., Ferrazzoli, P., Mironov, V., Bircher, S., Grant, J.P., Kurum, M., Schwank, M., Munoz-Sabater, J., Das, N., Royer, A., Al-Yaari, A., Al Bitar, A., Fernandez-Moran, R., Lawrence, H., Mialon, A., Parrens, M., Richaume, P., Delwart, S., Kerr, Y., Modelling the passive microwave signature from land surfaces: a review of recent results and application to the L-band SMOS and SMAP soil moisture retrieval algorithms. Remote Sens. Environ. 192 (2017), 238–262.
70. Yilmaz, M.T., Crow, W.T., Evaluation of assumptions in soil moisture triple collocation analysis. J. Hydrometeorol. 15:3 (2014), 1293–1302, 10.1175/JHM-D-13-0158.1.