Research Article
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Year 2019, Volume: 8 Issue: 4, 340 - 350, 01.10.2019
https://doi.org/10.18393/ejss.608005

Abstract

References

  • Ahmadaali, J., Barani, GH.A., Qaderi, K., Hessari, B., 2018. Analysis of the effects of water management strategies and climate change on the environmental and agricultural sustainability of Urmia Lake Basin, Iran. Water 10(2): 160.
  • Albergel, C., de Rosnay, P., Gruhier, C., Munoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., Wagner, W., 2012. Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment 118: 215–226.
  • Al-Yaari, A., Wigneron, J.P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A., Albergel, C., Muñoz-Sabater, J., 2014. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to land data assimilation system estimates. Remote Sensing of Environment 149: 181–195.
  • Al-Yaari, A., Wigneron, J.P., Kerr, Y., de Jeu, R., Rodriguez-Fernandez, N., van der Schalie, R., Al Bitar, A., Mialon, A., Richaume, P., Dolman, A., 2016. Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations. Remote Sensing of Environment 180: 453–464.
  • Barichivich, J., Briffa, K.R., Myneni, R., van der Schrier, G., Dorigo, W., Tucker, C.J.,Osborn, T.J., Melvin, T.M., 2014. Temperature and snow-mediated moisture controls of summer photosynthetic activity in northern terrestrial ecosystems between 1982 and 2011. Remote Sensing 6(2): 1390–1431.
  • Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., Hasenauer, S., 2010. Improving runoff prediction through the assimilation ofthe ASCAT soil moisture product. Hydrology and Earth System Sciences 14(10): 1881–1893.
  • Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martinez-Fernandez, J., Llorens, P., Latron, J., Martin, C., Bittelli, M., 2011. Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe. Remote Sensing of Environment 115(12): 3390–3408.
  • Brocca, L., Ponziani, F., Moramarco, T., Melone, F., Berni, N., Wagner, W., 2012. Improving landslide forecasting using ASCAT-derived soil moisture data: A case study of the Torgiovannetto Landslide in Central Italy. Remote Sensing 4(5): 1232–1244.
  • Brocca, L., Melone, F., Moramarco, T., Wagner, W., Albergel, C., 2013a. Scaling and filtering approaches for the use of satellite soil moisture observations. In: Remote Sensing of Energy Fluxes and Soil Moisture Content. Petropoulos, G.P. (Ed.). CRC Press, Taylor and Francis Group, Boca Raton, New York, USA. pp. 411–426.
  • Brocca, L., Moramarco, T., Melone, F., Wagner, W., 2013b. A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters 40(5): 853–858.
  • Brocca, L., Tarpanelli, A., Moramarco, T., Melone, F., Ratto, S.M., Cauduro, M., Ferraris, S., Berni, N., Ponziani, F., Wagner, W., Melzer, T., 2013c. Soil moisture estimation in alpine catchments through modeling and satellite observations. Vadose Zone Journal 12(3): vzj2012.0102
  • Chen, F., Crow, W.T., Holmes, T.R.H., 2012. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool. Journal of Applied Remote Sensing 6(1): 063604
  • Crow, W.T., Berg, A.A., Cosh, M.H., Loew, A., Mohanty, B.P., Panciera, R., de Rosnay, P., Ryu, D., Walker, J.P., 2012. Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products. Reviews of Geophysics 50(2): RG2002.
  • Das, N.N., Entekhabi, D., Dunbar, R.S., Njoku, E.G., Yueh, S.H., 2016. Uncertainty estimates in the SMAP combined active-passive downscaled brightness temperature. IEEE Transactions on Geoscience and Remote Sensing 54(2): 640–650.
  • Das, N.N., Entekhabi, D., Njoku, E.G., 2011. An algorithm for merging SMAP radiometer and radar data for high-resolution soil-moisture retrieval. IEEE Transactions on Geoscience and Remote Sensing 49(5): 1504–1512.
  • Dorigo, W.A., Scipal, K., Parinussa, R.M., Liu, Y.Y., Wagner, W., de Jeu, R.A.M., Naeimi, V., 2010. Error characterisation of global active and passive microwave soil moisture datasets. Hydrology and Earth System Sciences 14(12): 2605–2616.
  • Dorigo,W.A., Gruber, A., de Jeu, R.A.M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R.M., Kidd, R., 2015. Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sensing of Environment 162: 380–395.
  • Entekhabi, D., Njoku, E.G., O’Neill, P.E., Kellogg, K.H., Crow, W.T., Edelstein, W.N., Entin, J.K., Goodman, S.D., Jackson, T.J., Johnson, J., 2010. The Soil Moisture Active Passive (SMAP) mission. Proceedings of the IEEE 98(5): 704–716.
  • Entekhabi, D., Yueh, S., O’Neill, P.E., Kellogg, K.H., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., Crow, W.T., Das, N., De Lannoy, G., Dunbar, R.S., Edelstein, W.N., Entin, J.K., Escobar, V., Goodman, S.D., Jackson, T.J., Jai, B., Johnson, J., Kim, E., Kim, S., Kimball, J., Koster, R.D., Leon, A., McDonald, K.C., Moghaddam, M., Mohammed, P., Moran, S., Njoku, E.G., Piepmeier, J.R., Reichle, R., Rogez, F., Shi, J.C., Spencer, M.W., Thurman, S.W., Tsang, L., Van Zyl, J., Weiss, B., West, R., 2014. SMAP Handbook–Soil Moisture Active Passive: Mapping Soil Moisture and Freeze/Thaw from Space. Jet Propulsion Laboratory (JPL) Publication. Pasadena, CA. Jackson, T.J., Cosh, M.H., Bindlish, R., Starks, P.J., Bosch, D.D., Seyfried, M., Goodrich, D.C., Moran, M.S., Du, J.Y., 2010, Validation of advanced microwave scanning radiometer soil moisture products. IEEE Transactions on Geoscience and Remote Sensing 48(12): 4256–4272.
  • Kerr, Y., Waldteufel, P., Wigneron, J.P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.J., Font, J., Reul, N., Gruhier, C., Juglea, S.E., Drinkwater, M.R., Hahne, A.,Martin-Neira, M., Mecklenburg, S., 2010. The SMOS mission: new tool formonitoring key elements of the global water cycle. Proceedings of the IEEE 98(5): 666–687.
  • 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., 2012. The SMOS soil moisture retrieval algorithm. IEEE Transactions on Geoscience and Remote Sensing 50(5): 1384–1403.
  • Leroux, D.J., Kerr, Y.H., Al Bitar, A., Bindlish, R., Jackson, T.J., Berthelot, B., Portet, G., 2014. Comparison between SMOS, VUA, ASCAT, and ECMWF soil moisture products over four watersheds in US. IEEE Transactions on Geoscience and Remote Sensing 52(3): 1562–1571.
  • Loew, A., Schlenz, F., 2011. A dynamic approach for evaluating coarse scale satellite soil moisture products. Hydrology and Earth System Sciences 15(1): 75–90.
  • Miralles, D.G., van den Berg, M.J., Teuling, A.J., de Jeu, R.A.M., 2012. Soil moisture-temperature coupling: A multiscale observational analysis. Geophysical Research Letters 39(21): L21707.
  • Owe, M., de Jeu, R., Van de Griend, A., 2001. Estimating long term surface soil moisture from satellite microwave observations in Illinois, USA. Remote Sensing and Hydrology 2000 (Proceedings of a symposium held at Santa Fe, New Mexico, USA, April 2000). IAHS Publication No. 267, 2001.
  • Parinussa, R., Meesters, A.G.C.A., Liu, Y.Y., Dorigo, W.; Wagner, W.; de Jeu, R.A.M., 2011 An analytical solution to estimate the error structure of a global soil moisture data set. IEEE Geoscience and Remote Sensing Letters 8(4): 779–783.
  • Parinussa, R.M., Holmes, T.R.H., Wanders, N., Dorigo,W.A., de Jeu, R.A.M., 2015. A preliminary study toward consistent soil moisture from AMSR2. Journal of Hydrometeorology 16: 932–947.
  • Reichle, R., Koster, R., De Lannoy, G., Crow, W., Kimball, J., 2016. Level 4 Surface and Root Zone Soil Moisture (L4_SM) Data Product. Available at [Access date: 03.10.2018]: https://nsidc.org/sites/nsidc.org/files/technical-references/272_L4_SM_RevA_web.pdf
  • Sanchez, N., González-Zamora, Á., Martínez-Fernández, J., Piles, M., Pablos, M., 2018. Integrated remote sensing approach to global agricultural drought Monitoring. Agricultural and Forest Meteorology 259: 141–153.
  • Seneviratne, S.I., Corti, T., Davin, E.L., Hirschi, M., Jaeger, E.B., Lehner, I., Orlowsky,B., Teuling, A.J., 2010. Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Science Reviews 99(3-4): 125–161.
  • Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P., Dorigo, W.A., 2012. Afternoon rain more likely over drier soils. Nature 489: 423–426.
  • Urmia Lake Restoration National Committee. 2015. Necessity of Lake Urmia Resuscitation, Causes of Drought and Threats; Report No: ULRP-6-4-3-Rep 1; Urmia Lake Restoration National Committee: Tehran, Iran.
  • Wang, S., Mo, X., Liu, S., Lin, Z., Hu, S., 2016. Validation and trend analysis of ECV soil moisture data on cropland in North China plain during 1981–2010. International Journal of Applied Earth Observation and Geoinformation 48: 110–121.
  • Wilson, D. J., Western, A. W., Grayson, R.B., 2004. Identifying and quantifying sources of variability in temporal and spatial soil moisture observations. Water Resources Research 40(2): W02507.
  • Wu, Q.S., Liu, H.X., Wang, L., Deng, C.B., 2016. Evaluation of AMSR2 soil moisture products over the contiguous united states using in situ data from the international soil moisture network. International Journal of Applied Earth Observation and Geoinformation 45: 187–199.
  • Zeng, J.Y., Chen, K.S., Bi, H.Y., Chen, Q., 2016. A preliminary evaluation of the SMAP radiometer soil moisture product over United States and Europe using ground-based measurements. IEEE Transactions on Geoscience and Remote Sensing 54(8): 4929–4940.

Validation of satellite-based soil moisture retrievals from SMAP with in situ observation in the Simineh-Zarrineh (Bokan) Catchment, NW of Iran

Year 2019, Volume: 8 Issue: 4, 340 - 350, 01.10.2019
https://doi.org/10.18393/ejss.608005

Abstract

Soil moisture is an influential parameter in
land surface hydrology and precise soil moisture data that can help researcher
to realize the climate changes and land-atmosphere interactions. A initial
struggle for the utilize of soil moisture data from satellite sensors is their
reliability. It is important to appraise the dependability of those data before
they can be regularly used at a global or local scale. In this study, the satellite soil moisture data was evaluated from the
Soil Moisture Active/Passive (SMAP) over Simineh-Zarrineh Catchment in
Bokan region, NW of Iran. A total of 287 soil samples as ground-based
observations in the time period of 03 April to 03 December 2017 were taken for
SMAP data validation. Results showed
that the satellite data and in situ observation has a good correlation,
with a mean correlation (r) value of 0.63 in total. This correlation level
showed that
,
commonly, the SMAP soil moisture products over Simineh-Zarrineh Catchment (Bokan)
have great quality, and it would be valuable for versatile utilization,
including monitoring of land surface, weather prediction, modeling of
hydrological process, soil loess monitoring, and climate studies. The results
reveal that the remotely sensed data demonstrate the good correlation with in
situ observation across the dry land
with mean correlation (r) values of 0.67 throughout the time period.
Particularly, SMAP soil moisture reveal a constant structure for obtain the
spatial distribution of surface soil moisture.
Additional researches are necessary for well realizing the
SMAP data.

References

  • Ahmadaali, J., Barani, GH.A., Qaderi, K., Hessari, B., 2018. Analysis of the effects of water management strategies and climate change on the environmental and agricultural sustainability of Urmia Lake Basin, Iran. Water 10(2): 160.
  • Albergel, C., de Rosnay, P., Gruhier, C., Munoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., Wagner, W., 2012. Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment 118: 215–226.
  • Al-Yaari, A., Wigneron, J.P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A., Albergel, C., Muñoz-Sabater, J., 2014. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to land data assimilation system estimates. Remote Sensing of Environment 149: 181–195.
  • Al-Yaari, A., Wigneron, J.P., Kerr, Y., de Jeu, R., Rodriguez-Fernandez, N., van der Schalie, R., Al Bitar, A., Mialon, A., Richaume, P., Dolman, A., 2016. Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations. Remote Sensing of Environment 180: 453–464.
  • Barichivich, J., Briffa, K.R., Myneni, R., van der Schrier, G., Dorigo, W., Tucker, C.J.,Osborn, T.J., Melvin, T.M., 2014. Temperature and snow-mediated moisture controls of summer photosynthetic activity in northern terrestrial ecosystems between 1982 and 2011. Remote Sensing 6(2): 1390–1431.
  • Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., Hasenauer, S., 2010. Improving runoff prediction through the assimilation ofthe ASCAT soil moisture product. Hydrology and Earth System Sciences 14(10): 1881–1893.
  • Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martinez-Fernandez, J., Llorens, P., Latron, J., Martin, C., Bittelli, M., 2011. Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe. Remote Sensing of Environment 115(12): 3390–3408.
  • Brocca, L., Ponziani, F., Moramarco, T., Melone, F., Berni, N., Wagner, W., 2012. Improving landslide forecasting using ASCAT-derived soil moisture data: A case study of the Torgiovannetto Landslide in Central Italy. Remote Sensing 4(5): 1232–1244.
  • Brocca, L., Melone, F., Moramarco, T., Wagner, W., Albergel, C., 2013a. Scaling and filtering approaches for the use of satellite soil moisture observations. In: Remote Sensing of Energy Fluxes and Soil Moisture Content. Petropoulos, G.P. (Ed.). CRC Press, Taylor and Francis Group, Boca Raton, New York, USA. pp. 411–426.
  • Brocca, L., Moramarco, T., Melone, F., Wagner, W., 2013b. A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters 40(5): 853–858.
  • Brocca, L., Tarpanelli, A., Moramarco, T., Melone, F., Ratto, S.M., Cauduro, M., Ferraris, S., Berni, N., Ponziani, F., Wagner, W., Melzer, T., 2013c. Soil moisture estimation in alpine catchments through modeling and satellite observations. Vadose Zone Journal 12(3): vzj2012.0102
  • Chen, F., Crow, W.T., Holmes, T.R.H., 2012. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool. Journal of Applied Remote Sensing 6(1): 063604
  • Crow, W.T., Berg, A.A., Cosh, M.H., Loew, A., Mohanty, B.P., Panciera, R., de Rosnay, P., Ryu, D., Walker, J.P., 2012. Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products. Reviews of Geophysics 50(2): RG2002.
  • Das, N.N., Entekhabi, D., Dunbar, R.S., Njoku, E.G., Yueh, S.H., 2016. Uncertainty estimates in the SMAP combined active-passive downscaled brightness temperature. IEEE Transactions on Geoscience and Remote Sensing 54(2): 640–650.
  • Das, N.N., Entekhabi, D., Njoku, E.G., 2011. An algorithm for merging SMAP radiometer and radar data for high-resolution soil-moisture retrieval. IEEE Transactions on Geoscience and Remote Sensing 49(5): 1504–1512.
  • Dorigo, W.A., Scipal, K., Parinussa, R.M., Liu, Y.Y., Wagner, W., de Jeu, R.A.M., Naeimi, V., 2010. Error characterisation of global active and passive microwave soil moisture datasets. Hydrology and Earth System Sciences 14(12): 2605–2616.
  • Dorigo,W.A., Gruber, A., de Jeu, R.A.M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R.M., Kidd, R., 2015. Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sensing of Environment 162: 380–395.
  • Entekhabi, D., Njoku, E.G., O’Neill, P.E., Kellogg, K.H., Crow, W.T., Edelstein, W.N., Entin, J.K., Goodman, S.D., Jackson, T.J., Johnson, J., 2010. The Soil Moisture Active Passive (SMAP) mission. Proceedings of the IEEE 98(5): 704–716.
  • Entekhabi, D., Yueh, S., O’Neill, P.E., Kellogg, K.H., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., Crow, W.T., Das, N., De Lannoy, G., Dunbar, R.S., Edelstein, W.N., Entin, J.K., Escobar, V., Goodman, S.D., Jackson, T.J., Jai, B., Johnson, J., Kim, E., Kim, S., Kimball, J., Koster, R.D., Leon, A., McDonald, K.C., Moghaddam, M., Mohammed, P., Moran, S., Njoku, E.G., Piepmeier, J.R., Reichle, R., Rogez, F., Shi, J.C., Spencer, M.W., Thurman, S.W., Tsang, L., Van Zyl, J., Weiss, B., West, R., 2014. SMAP Handbook–Soil Moisture Active Passive: Mapping Soil Moisture and Freeze/Thaw from Space. Jet Propulsion Laboratory (JPL) Publication. Pasadena, CA. Jackson, T.J., Cosh, M.H., Bindlish, R., Starks, P.J., Bosch, D.D., Seyfried, M., Goodrich, D.C., Moran, M.S., Du, J.Y., 2010, Validation of advanced microwave scanning radiometer soil moisture products. IEEE Transactions on Geoscience and Remote Sensing 48(12): 4256–4272.
  • Kerr, Y., Waldteufel, P., Wigneron, J.P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.J., Font, J., Reul, N., Gruhier, C., Juglea, S.E., Drinkwater, M.R., Hahne, A.,Martin-Neira, M., Mecklenburg, S., 2010. The SMOS mission: new tool formonitoring key elements of the global water cycle. Proceedings of the IEEE 98(5): 666–687.
  • 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., 2012. The SMOS soil moisture retrieval algorithm. IEEE Transactions on Geoscience and Remote Sensing 50(5): 1384–1403.
  • Leroux, D.J., Kerr, Y.H., Al Bitar, A., Bindlish, R., Jackson, T.J., Berthelot, B., Portet, G., 2014. Comparison between SMOS, VUA, ASCAT, and ECMWF soil moisture products over four watersheds in US. IEEE Transactions on Geoscience and Remote Sensing 52(3): 1562–1571.
  • Loew, A., Schlenz, F., 2011. A dynamic approach for evaluating coarse scale satellite soil moisture products. Hydrology and Earth System Sciences 15(1): 75–90.
  • Miralles, D.G., van den Berg, M.J., Teuling, A.J., de Jeu, R.A.M., 2012. Soil moisture-temperature coupling: A multiscale observational analysis. Geophysical Research Letters 39(21): L21707.
  • Owe, M., de Jeu, R., Van de Griend, A., 2001. Estimating long term surface soil moisture from satellite microwave observations in Illinois, USA. Remote Sensing and Hydrology 2000 (Proceedings of a symposium held at Santa Fe, New Mexico, USA, April 2000). IAHS Publication No. 267, 2001.
  • Parinussa, R., Meesters, A.G.C.A., Liu, Y.Y., Dorigo, W.; Wagner, W.; de Jeu, R.A.M., 2011 An analytical solution to estimate the error structure of a global soil moisture data set. IEEE Geoscience and Remote Sensing Letters 8(4): 779–783.
  • Parinussa, R.M., Holmes, T.R.H., Wanders, N., Dorigo,W.A., de Jeu, R.A.M., 2015. A preliminary study toward consistent soil moisture from AMSR2. Journal of Hydrometeorology 16: 932–947.
  • Reichle, R., Koster, R., De Lannoy, G., Crow, W., Kimball, J., 2016. Level 4 Surface and Root Zone Soil Moisture (L4_SM) Data Product. Available at [Access date: 03.10.2018]: https://nsidc.org/sites/nsidc.org/files/technical-references/272_L4_SM_RevA_web.pdf
  • Sanchez, N., González-Zamora, Á., Martínez-Fernández, J., Piles, M., Pablos, M., 2018. Integrated remote sensing approach to global agricultural drought Monitoring. Agricultural and Forest Meteorology 259: 141–153.
  • Seneviratne, S.I., Corti, T., Davin, E.L., Hirschi, M., Jaeger, E.B., Lehner, I., Orlowsky,B., Teuling, A.J., 2010. Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Science Reviews 99(3-4): 125–161.
  • Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P., Dorigo, W.A., 2012. Afternoon rain more likely over drier soils. Nature 489: 423–426.
  • Urmia Lake Restoration National Committee. 2015. Necessity of Lake Urmia Resuscitation, Causes of Drought and Threats; Report No: ULRP-6-4-3-Rep 1; Urmia Lake Restoration National Committee: Tehran, Iran.
  • Wang, S., Mo, X., Liu, S., Lin, Z., Hu, S., 2016. Validation and trend analysis of ECV soil moisture data on cropland in North China plain during 1981–2010. International Journal of Applied Earth Observation and Geoinformation 48: 110–121.
  • Wilson, D. J., Western, A. W., Grayson, R.B., 2004. Identifying and quantifying sources of variability in temporal and spatial soil moisture observations. Water Resources Research 40(2): W02507.
  • Wu, Q.S., Liu, H.X., Wang, L., Deng, C.B., 2016. Evaluation of AMSR2 soil moisture products over the contiguous united states using in situ data from the international soil moisture network. International Journal of Applied Earth Observation and Geoinformation 45: 187–199.
  • Zeng, J.Y., Chen, K.S., Bi, H.Y., Chen, Q., 2016. A preliminary evaluation of the SMAP radiometer soil moisture product over United States and Europe using ground-based measurements. IEEE Transactions on Geoscience and Remote Sensing 54(8): 4929–4940.
There are 36 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Khaled Haji Maleki This is me

Ali Reza Vaezi This is me

Fereydoon Sarmadian This is me

Wade T. Crow This is me

Publication Date October 1, 2019
Published in Issue Year 2019 Volume: 8 Issue: 4

Cite

APA Maleki, K. H., Vaezi, A. R., Sarmadian, F., Crow, W. T. (2019). Validation of satellite-based soil moisture retrievals from SMAP with in situ observation in the Simineh-Zarrineh (Bokan) Catchment, NW of Iran. Eurasian Journal of Soil Science, 8(4), 340-350. https://doi.org/10.18393/ejss.608005