An observing system simulation experiment for the aquarius/SAC-D soil moisture product
An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D mission has been developed for assessing the accuracy of soil moisture retrievals from passive L-band remote sensing. The implementation of the OSSE is based on the following: a 1-km land surface model over the Red-Arkansas Rive...
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
Institute of Electrical and Electronics Engineers Inc.
2014
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
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| LEADER | 10865caa a22010337a 4500 | ||
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| 001 | PAPER-24036 | ||
| 003 | AR-BaUEN | ||
| 005 | 20250428091602.0 | ||
| 008 | 190411s2014 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-84901978232 | |
| 030 | |a IGRSD | ||
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Bruscantini, C.A. | |
| 245 | 1 | 3 | |a An observing system simulation experiment for the aquarius/SAC-D soil moisture product |
| 260 | |b Institute of Electrical and Electronics Engineers Inc. |c 2014 | ||
| 270 | 1 | 0 | |m Bruscantini, C.A.; Instituto de Astronomía y Física Del Espacio, C1428ZAA Buenos Aires, Argentina; email: cintiab@iafe.uba.ar |
| 504 | |a 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 (2001) IEEE Transactions on Geoscience and Remote Sensing, 39 (8), pp. 1622-1631. , DOI 10.1109/36.942540, PII S0196289201066785, Large Scale Passive Microwave Remote Sensing of Soil Moisture | ||
| 504 | |a Crow, W.T., Chan, S.T.K., Entekhabi, D., Houser, P.R., Hsu, A.Y., Jackson, T.J., Njoku, E.G., Zhan, X., An Observing System Simulation Experiment for Hydros radiometer-only soil moisture products (2005) IEEE Trans. Geosci. Remote Sens, 43 (6), pp. 1289-1303. , Jun | ||
| 504 | |a Le Vine, D.M., Dinnat, E.P., Abraham, S., De Matthaeis, P., Wentz, F.J., The aquarius simulator and cold-sky calibration (2011) IEEE Trans. Geosci. Remote Sens, 49 (9), pp. 3198-3210. , Se | ||
| 504 | |a Njoku, E.G., Entekhabi, D., Passive microwave remote sensing of soil moisture (1996) J. Hydrol, 184 (1-2), pp. 101-129. , Oct | ||
| 504 | |a Jackson, T.J., Le Vine, D.M., Hsu, A.Y., Oldak, A., Starks, P.J., Swift, C.T., Isham, J.D., Haken, M., Soil moisture mapping at regional scales using microwave radiometry: The Southern great plains hydrology experiment (1999) IEEE Transactions on Geoscience and Remote Sensing, 37 (5), pp. 2136-2151. , pt1 DOI 10.1109/36.789610 | ||
| 504 | |a Luo, Y., Feng, X., Houser, P., Anantharaj, V., Fan, X., De Lannoy, G., Zhan, X., Dabbiru, L., Potential soil moisture products from the Aquarius radiometer and scatterometer using an Observing System Simulation Experiment (2012) Geosci. Instrum Methods Data Syst. Discuss, 2 (2), pp. 457-476 | ||
| 504 | |a Crow, W.T., Koster, R.D., Reichle, R.H., Sharif, H.O., Relevance of time-varying and time-invariant retrieval error sources on the utility of spaceborne soil moisture products (2005) Geophys. Res. Lett, 32 (24), pp. L24405 | ||
| 504 | |a Konings, A.G., Entekhabi, D., Chan, S.T.K., Njoku, E.G., Effect of radiative transfer uncertainty on L-band radiometric soil moisture retrieval (2011) IEEE Trans. Geosci. Remote Sens, 49 (7), pp. 2686-2698. , Jul | ||
| 504 | |a Peters-Lidard, C.D., Zion, M.S., Wood, E.F., A soil vegetation-atmosphere transfer scheme for modeling spatially variable water and energy balance processes (1997) J. Geophys. Res, 102 (D4), pp. 4303-4324. , Feb | ||
| 504 | |a Jackson, T.J., Schmugge, T.J., Vegetation effects on the microwave emission of soil (1991) Remote Sens. Environ, 36 (3), pp. 203-212. , Jun | ||
| 504 | |a Dobson, M.C., Ulaby, F.T., Hallikainen, M.T., El-Rayes, M.A., Microwave dielectric behavior of wet soil Part II: Dielectric mixing models (1985) IEEE Trans. Geosci. Remote Sens Vol GE-23, (1), pp. 35-46. , Jan | ||
| 504 | |a Zhan, X., Crow, W.T., Jackson, T.J., O'Neill, P.E., Improving spaceborne radiometer soil moisture retrievals with alternative aggregation rules for ancillary parameters in highly heterogeneous vegetated areas (2008) IEEE Geosci. Remote Sens. Lett, 5 (2), pp. 261-265. , Apr | ||
| 504 | |a Le Vine, D.M., Lagerloef, G.S.E., Yueh, S., Pellerano, F., Dinnat, E., Wentz, F., Aquarius mission technical overview (2006) Proc. IGARSS, pp. 1678-1680. , Jul | ||
| 504 | |a Limaye, A.S., Crosson, W.L., Laymon, C.A., Estimating accuracy in optimal deconvolution of synthetic AMSR-E observations (2006) Remote Sens. Environ, 100 (1), pp. 133-142. , Jan | ||
| 504 | |a Chao, Y., L2a Aquarius science requirements (2008) Jet Propulsion Lab, Pasadena, CA, USA, Tech. Rep, , Jul | ||
| 504 | |a Foti, G., Finch, C., Aquarius user guide (2011) Jet Propulsion Lab, , Pasadena, CA, USA, Tech. Rep | ||
| 504 | |a Jackson, T.J., Measuring surface soil moisture using passive microwave remote sensing (1993) Hydrol. Process, 7 (2), pp. 139-152 | ||
| 504 | |a Bruscantini, C.A., Grings, F.M., Perna, P., Karszenbaum, H., Crow, W.T., Jacobo, J.C.A., An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D soil moisture product (2012) Proc. 12th Spec. Meet. MicroRad, Mar, pp. 1-4 | ||
| 504 | |a Lilly, J.M., Lagerloef, G.S.E., Aquarius level 3 processing algorithm theoretical basis document, Part II (2009) Implementation, , Feb | ||
| 504 | |a Calvet, J.-C., Wigneron, J.-P., Walker, J., Karbou, F., Chanzy, A., Albergel, C., Sensitivity of passive microwave observations to soil moisture and vegetation water content: L-band to W-band (2011) IEEE Trans. Geosci. Remote Sens, 49 (4), pp. 1190-1199. , Ar | ||
| 504 | |a Ulaby, F.T., Moore, R.K., Fung, A.K., (1986) Microwave Remote Sensing: Active and Passive. from Theory to Applications, , Norwood, MA, USA: Artech House | ||
| 504 | |a Pellarin, T., Wigneron, J.-P., Calvet, J.-C., Berger, M., Douville, H., Ferrazzoli, P., Kerr, Y.H., Waldteufel, P., Two-year global simulation of L-band brightness temperatures over land (2003) IEEE Trans. Geosci. Remote Sens, 41 (9), pp. 2135-2139. , Sep | ||
| 504 | |a Chen, D., Jackson. F Li., T.J., Cosh, M.H., Walthall, C., Anderson, M., Estimation of vegetation water content for corn and soybeans with a normalized difference water index (ndwi) using landsat thematic mapper data (2003) Proc IEEE IGARSS, 4, pp. 2853-2856 | ||
| 504 | |a Jing, T., Jiancheng, S., Jackson, T.J., Jinyang, D., Bindlish, R., Lixin, Z., Monitoring vegetation water content using microwave vegetation indices (2008) Proc IEEE IGARSS, 1, pp. I197-I200 | ||
| 504 | |a Chen, D., Huang, J., Jackson, T.J., Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands (2005) Remote Sensing of Environment, 98 (2-3), pp. 225-236. , DOI 10.1016/j.rse.2005.07.008, PII S0034425705002373 | ||
| 504 | |a Jackson, T.J., Chen, D., Cosh, M., Li, F., Anderson, M., Walthall, C., Doriaswamy, P., Hunt, E.R., Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans (2004) Remote Sensing of Environment, 92 (4), pp. 475-482. , DOI 10.1016/j.rse.2003.10.021, PII S0034425703003353 | ||
| 506 | |2 openaire |e Política editorial | ||
| 520 | 3 | |a An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D mission has been developed for assessing the accuracy of soil moisture retrievals from passive L-band remote sensing. The implementation of the OSSE is based on the following: a 1-km land surface model over the Red-Arkansas River Basin, a forward microwave emission model to simulate the radiometer observations, a realistic orbital and sensor model to resample the measurements mimicking Aquarius operation, and an inverse soil moisture retrieval model. The simulation implements a zero-order radiative transfer model. Retrieval is performed by direct inversion of the forward model. The Aquarius OSSE attempts to capture the influence of various error sources, such as land surface heterogeneity, instrument noise, and retrieval ancillary parameter uncertainty, all on the accuracy of Aquarius surface soil moisture retrievals. In order to assess the impact of these error sources on the estimated volumetric soil moisture, a quantitative error analysis is performed by comparison of footprint-scale synthetic soil moisture with 'true' soil moisture fields obtained from the direct aggregation of the original 1-km soil moisture field input to the forward model. Results show that, in heavily vegetated areas, soil moisture retrievals have a positive bias that can be suppressed with an alternative aggregation strategy for ancillary parameter vegetation water content (VWC). Retrieval accuracy was also evaluated when adding errors to 1-km VWC (which are intended to account for errors in VWC derived from remote sensing data). For soil moisture retrieval root-mean-square error on the order of 0.05 m3/m3, the error in VWC should be less than 12%. © 1980-2012 IEEE. |l eng | |
| 593 | |a Instituto de Astronomía y Física Del Espacio, C1428ZAA Buenos Aires, Argentina | ||
| 593 | |a Hydrology and Remote Sensing Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, United States | ||
| 690 | 1 | 0 | |a AQUARIUS |
| 690 | 1 | 0 | |a OBSERVING SYSTEM SIMULATION EXPERIMENT (OSSE) |
| 690 | 1 | 0 | |a SOIL MOISTURE |
| 690 | 1 | 0 | |a ERROR ANALYSIS |
| 690 | 1 | 0 | |a EXPERIMENTS |
| 690 | 1 | 0 | |a REMOTE SENSING |
| 690 | 1 | 0 | |a AQUARIUS |
| 690 | 1 | 0 | |a MICROWAVE EMISSION MODELS |
| 690 | 1 | 0 | |a OBSERVING SYSTEM SIMULATION EXPERIMENTS |
| 690 | 1 | 0 | |a QUANTITATIVE ERROR ANALYSIS |
| 690 | 1 | 0 | |a SOIL MOISTURE RETRIEVALS |
| 690 | 1 | 0 | |a SURFACE SOIL MOISTURE RETRIEVAL |
| 690 | 1 | 0 | |a VEGETATION WATER CONTENTS (VWC) |
| 690 | 1 | 0 | |a VOLUMETRIC SOIL MOISTURES |
| 690 | 1 | 0 | |a SOIL MOISTURE |
| 690 | 1 | 0 | |a ACCURACY ASSESSMENT |
| 690 | 1 | 0 | |a AQUARIUS |
| 690 | 1 | 0 | |a DATA ASSIMILATION |
| 690 | 1 | 0 | |a ERROR ANALYSIS |
| 690 | 1 | 0 | |a MICROWAVE RADIATION |
| 690 | 1 | 0 | |a NUMERICAL MODEL |
| 690 | 1 | 0 | |a RADIATIVE TRANSFER |
| 690 | 1 | 0 | |a RADIOMETER |
| 690 | 1 | 0 | |a SATELLITE MISSION |
| 690 | 1 | 0 | |a SOIL MOISTURE |
| 690 | 1 | 0 | |a VEGETATION COVER |
| 690 | 1 | 0 | |a WATER CONTENT |
| 690 | 1 | 0 | |a ARKANSAS BASIN |
| 690 | 1 | 0 | |a RED BASIN [UNITED STATES] |
| 690 | 1 | 0 | |a UNITED STATES |
| 700 | 1 | |a Crow, W.T. | |
| 700 | 1 | |a Grings, Francisco Matías | |
| 700 | 1 | |a Perna, P. | |
| 700 | 1 | |a Maas, M. | |
| 700 | 1 | |a Karszenbaum, H. | |
| 773 | 0 | |d Institute of Electrical and Electronics Engineers Inc., 2014 |g v. 52 |h pp. 6086-6094 |k n. 10 |p IEEE Trans Geosci Remote Sens |x 01962892 |w (AR-BaUEN)CENRE-1633 |t IEEE Transactions on Geoscience and Remote Sensing | |
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