Navegar

Colección

Datos Estadísticas

Artículo

Bruscantini, C.A.; Konings, A.G.; Narvekar, P.S.; McColl, K.A.; Entekhabi, D.; Grings, F.M.; Karszenbaum, H. "L-Band Radar Soil Moisture Retrieval Without Ancillary Information" (2015) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(12):5526-5540
Estamos trabajando para incorporar este artículo al repositorio
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor

Abstract:

A radar-only retrieval algorithm for soil moisture mapping is applied to L-band scatterometer measurements from the Aquarius. The algorithm is based on a nonlinear relation between L-band backscatter and volumetric soil moisture and does not require ancillary information on the surface, e.g., land classification, vegetation canopy, surface roughness, etc. It is based on the definition of three limiting cases or end-members: 1) smooth bare soil; 2) rough bare soil; and 3) maximum vegetation condition. In this study, an estimation method is proposed for the end-member parameters that is iterative and only uses space-borne measurements. The major advantages of the algorithm include an analytic formulation (direct inversion possible), and the fact that there is no requirement for ancillary information. Ancillary data often misclassify the surface and the parameterizations linking surface classification to model parameter values are often highly uncertain. The retrieval algorithm is tested using 3 years of space-borne scatterometer observations from the Aquarius/SAC-D. Retrieved soil moisture accuracy is assessed in several ways: comparison of global spatial patterns with other available soil moisture products (two reanalysis modeling products and retrievals based on the Aquarius radiometer), extended triple collocation (ETC) and time series analysis over selected target areas. In general, low bias and standard deviation are observed with levels comparable to independent radiometer-based retrievals. The errors, however, increase across areas with high vegetation density. The results are promising and applicable to forthcoming L-band radar missions such as SMAP-NASA (2015) and SAOCOM-CONAE (2016). © 2015 IEEE.

Registro:

Documento: Artículo
Título:L-Band Radar Soil Moisture Retrieval Without Ancillary Information
Autor:Bruscantini, C.A.; Konings, A.G.; Narvekar, P.S.; McColl, K.A.; Entekhabi, D.; Grings, F.M.; Karszenbaum, H.
Filiación:Department of Remote Sensing, Institute of Astronomy and Space Physics (IAFE), Ciudad de Buenos Aires, 1428, Argentina
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02143, United States
Palabras clave:Aquarius/SAC-D; microwave remote sensing; radar; radar roughness; radar vegetation index (RVI); scatterometer; soil moisture; Algorithms; Classification (of information); Iterative methods; Meteorological instruments; Moisture; NASA; Radar; Radar measurement; Radiometers; Soil moisture; Soils; Space-based radar; Surface roughness; Time series analysis; Uncertainty analysis; Vegetation; Nonlinear relations; Retrieval algorithms; Scatterometer measurements; Soil moisture mapping; Soil moisture retrievals; Surface Classification; Vegetation condition; Volumetric soil moistures; Soil surveys; algorithm; Aquarius; microwave imagery; radar; remote sensing; satellite data; soil moisture
Año:2015
Volumen:8
Número:12
Página de inicio:5526
Página de fin:5540
DOI: http://dx.doi.org/10.1109/JSTARS.2015.2496326
Título revista:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Título revista abreviado:IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.
ISSN:19391404
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19391404_v8_n12_p5526_Bruscantini

Referencias:

  • Narvekar, P., Entekhabi, D., Kim, S., Njoku, E., Soil moisture retrieval using L-band radar observations (2015) IEEE Trans. Geosci. Remote Sens., 53 (6), pp. 3492-3506. , Jun
  • Kornelsen, K.C., Coulibaly, P., Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications (2013) J. Hydrol., 476, pp. 460-489
  • Kim, S.-B., Tsang, L., Johnson, J.T., Huang, S., Van Zyl, J.J., Njoku, E.G., Soil moisture retrieval using time-series radar observations over bare surfaces (2012) IEEE Trans. Geosci. Remote Sens., 50 (5), pp. 1853-1863. , May
  • Zhou, L., Tsang, L., Jandhyala, V., Li, Q., Chan, C.H., Emissivity simulations in passive microwave remote sensing with 3-D numerical solutions of maxwell equations (2004) IEEE Trans. Geosci. Remote Sens., 42 (8), pp. 1739-1748. , Aug
  • Rahmoune, R., Ferrazzoli, P., Kerr, Y.H., Richaume, P., SMOS level 2 retrieval algorithm over forests: Description and generation of global maps (2013) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., 6 (3), pp. 1430-1439. , Jun
  • Wickel, J., Jackson, T.J., Woo, A.E.F., Multitemporal monitoring of soil moisture with RADARSAT SAR during the 1997 Southern Great Plains hydrology experiment (2001) Int. J. Remote Sens., 22 (8), pp. 1571-1583. , May
  • Holah, N., Baghdadi, N., Zribi, M., Bruand, A., King, C., Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields (2005) Remote Sens. Environ., 96 (1), pp. 78-86
  • Oh, Y., Sarabandi, K., Ulaby, F.T., An empirical model and an inversion technique for radar scattering from bare soil surfaces (1992) IEEE Trans. Geosci. Remote Sens., 30 (2), pp. 370-381. , Mar
  • Dubois, P.C., Van Zyl, J., Engman, T., Measuring soil moisture with imaging radars (1995) IEEE Trans. Geosci. Remote Sens., 33 (4), pp. 915-926. , Jul
  • Shi, J., Wang, J., Hsu, A.Y., O'Neill, P.E., Engman, E.T., Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data (1997) IEEE Trans. Geosci. Remote Sens., 35 (5), pp. 1254-1266. , Sep
  • Santi, E., Paloscia, S., Pettinato, S., Fontanelli, G., A prototype ann based algorithm for the soil moisture retrieval from L-band in view of the incoming SMAP mission (2014) Proc. 13th Spec. Meeting Microw. Radiom. Remote Sens. Environ. (MicroRad), pp. 5-9. , Mar
  • Kim, Y., Van Zyl, J.J., A time-series approach to estimate soil moisture using polarimetric radar data (2009) IEEE Trans. Geosci. Remote Sens., 47 (8), pp. 2519-2527. , Aug
  • Arii, M., Van Zyl, J.J., Kim, Y., A general characterization for polarimetric scattering from vegetation canopies (2010) IEEE Trans. Geosci. Remote Sens., 48 (9), pp. 3349-3357. , Sep
  • Yueh, S., Dinardo, S., Chan, S., Njoku, E., Jackson, T., Bindlish, R., Passive and active L-band system and observations during the 2007CLASIC campaign (2008) Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), 2, pp. 241-244. , Jul
  • McColl, K.A., Entekhabi, D., Piles, M., Uncertainty analysis of soil moisture and vegetation indices using aquarius scatterometer observations (2014) IEEE Trans. Geoscience Remote Sens., 52 (7), pp. 4259-4272. , Jul
  • Huang, S., Tsang, L., Njoku, E.G., Chan, K.S., Backscattering coefficients, coherent reflectivities, and emissivities of randomly rough soil surfaces at L-band for SMAP applications based on numerical solutions of maxwell equations in three-dimensional simulations (2010) IEEE Trans. Geosci. Remote Sens., 48 (6), pp. 2557-2568. , Jun
  • Ulaby, F.T., Moore, R.K., Fung, A.K., (1986) Microwave Remote Sensing: Active and Passive, 3. , Reading, MA, USA: Addison-Wesley
  • Du, Y., Ulaby, F.T., Dobson, M.C., Sensitivity to soil moisture by active and passive microwave sensors (2000) IEEE Trans. Geosci. Remote Sens., 38 (1), pp. 105-114. , Jan
  • Oh, Y., Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces (2004) IEEE Trans. Geosci. Remote Sens., 42 (3), pp. 596-601. , Mar
  • Wang, J.R., Engman, E.T., Mo, T., Schmugge, T.J., Shiue, J.C., The effects of soil moisture, surface roughness, and vegetation on Lband emission and backscatter (1987) IEEE Trans. Geosci. Remote Sens., GE-25 (6), pp. 825-833. , Nov
  • Ulaby, F.T., Batlivala, P.P., Optimum radar parameters for mapping soil moisture (1976) IEEE Trans. Geosci. Electron., 14 (2), pp. 81-93. , Apr
  • Bindlish, R., Jackson, T., (2013) Aquarius l2 Swath Single Orbit Soil Moisture. Version 2, , NASA DAAC at the National Snow and Ice Data Center, Boulder, CO, USA
  • Reichle, R., (2014) The SMAP Nature v03 Data Product, , personal communication
  • Reichle, R.H., Assessment and enhancement of MERRA land surface hydrology estimates (2011) J. Clim., 24 (24), pp. 6322-6338
  • Reichle, R.H., (2014) Observation-corrected Precipitation Estimates in GEOS-5, 35. , Goddard Space Flight Center, NASA, Greenbelt, MD, USA, Tech. Rep. TM-2014-104606
  • De Lannoy, G.J.M., Koster, R.D., Reichle, R.H., Mahanama, S.P.P., Liu, Q., An updated treatment of soil texture and associated hydraulic properties in a global land modeling system (2014) J. Adv. Model. Earth Syst., 6, pp. 957-979
  • Stoffelen, A., Toward the true near-surface wind speed: Error modeling and calibration using triple collocation (1998) J. Geophys. Res. Oceans, 103 (C4), pp. 7755-7766
  • 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 (2014) Geophys. Res. Lett., 41, pp. 6229-6236
  • Davidson, M., Toan, T.L., Mattia, F., Satalino, G., Manninen, T., Borgeaud, M., On the characterization of agricultural soil roughness for radar remote sensing studies (2000) IEEE Trans. Geosci. Remote Sens., 38 (2), pp. 630-640. , Mar
  • Jackson, T.J., Kostov, K.G., Saatchi, S.S., Rock fraction effects on the interpretation of microwave emission from soils (1992) IEEE Trans. Geosci. Remote Sens., 30 (3), pp. 610-616. , May
  • Miralles, D.G., Crow, W.T., Cosh, M.H., Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations (2010) J. Hydrometeorol., 11 (6), pp. 1423-1429
  • Wagner, W., Lemoine, G., Borgeaud, M., Rott, H., A study of vegetation cover effects on ERS scatterometer data (1999) IEEE Trans. Geosci. Remote Sens., 37 (2), pp. 938-948. , Mar

Citas:

---------- APA ----------
Bruscantini, C.A., Konings, A.G., Narvekar, P.S., McColl, K.A., Entekhabi, D., Grings, F.M. & Karszenbaum, H. (2015) . L-Band Radar Soil Moisture Retrieval Without Ancillary Information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(12), 5526-5540.
http://dx.doi.org/10.1109/JSTARS.2015.2496326
---------- CHICAGO ----------
Bruscantini, C.A., Konings, A.G., Narvekar, P.S., McColl, K.A., Entekhabi, D., Grings, F.M., et al. "L-Band Radar Soil Moisture Retrieval Without Ancillary Information" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8, no. 12 (2015) : 5526-5540.
http://dx.doi.org/10.1109/JSTARS.2015.2496326
---------- MLA ----------
Bruscantini, C.A., Konings, A.G., Narvekar, P.S., McColl, K.A., Entekhabi, D., Grings, F.M., et al. "L-Band Radar Soil Moisture Retrieval Without Ancillary Information" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 12, 2015, pp. 5526-5540.
http://dx.doi.org/10.1109/JSTARS.2015.2496326
---------- VANCOUVER ----------
Bruscantini, C.A., Konings, A.G., Narvekar, P.S., McColl, K.A., Entekhabi, D., Grings, F.M., et al. L-Band Radar Soil Moisture Retrieval Without Ancillary Information. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015;8(12):5526-5540.
http://dx.doi.org/10.1109/JSTARS.2015.2496326