Comparison of surface soil moisture from SMOS satellite and ground measurements

• Autorzy: Usowicz B. , Marczewski W. , Usowicz J. B. , Lukowski M. I. , Lipiec J.
• Języki publikacji: EN

Abstrakty

EN

Soil moisture datasets at various scales are needed for sustainable land use and water management. The aim of this study was to compare soil moisture ocean salinity satellite and in situ soil moisture data for the Podlasie and Polesie regions in Eastern Poland. Both regions have similar climatic and topo- graphic conditions but are different in land use, vegetation, and soil cover. The test sites were located on agricultural fields on sandy soils and natural vegetation on marshy soils that prevail in the Podlasie and Polesie regions, respectively. The soil moisture ocean salinity soil moisture data were obtained from radiometric measurements (1.4 GHz) and the ground soil moisture from sensors at a depth of 5 cm during the years 2010-2011. In general, temporal patterns of soil moisture from both satellite and ground measurements followed the rainfall trend. The regression coeffi- cients, Bland-Altman analysis, concordance correlation coefficient, and total deviation index showed that the agreement between ground and soil moisture ocean salinity derived soil moisture data is better for the Podlasie than the Polesie region. The lower agre- ement in Polesie was attributed mostly to the presence of the widespread natural vegetation on the wetter marsh soil along with minor contribution of agriculturally used drier coarse-textured soils.

Słowa kluczowe

EN

comparison; soil surface; soil moisture; SMOS satellite; ground; measurement; correlation coefficient

• Wydawca: -
• Czasopismo: International Agrophysics
• Rocznik: 2014
• Tom: 28
• Numer: 3
• Opis fizyczny: p.359-369,fig.,ref.

Twórcy

autor

Usowicz B.

• Institute of Agrophysics, Polish Academy of Sciences in Lublin, Doswiadczalna 4, 20-290 Lublin, Poland

autor

Marczewski W.

• Space Research Centre, Polish Academy of Sciences in Warsaw, Bartycka 18A, 00-716 Warsaw, Poland

autor

Usowicz J. B.

• Torun Centre of Astronomy, Nicolaus Copernicus University, Gagarina 11, 87-100 Torun, Poland

autor

Lukowski M. I.

• Institute of Agrophysics, Polish Academy of Sciences in Lublin, Doswiadczalna 4, 20-290 Lublin, Poland

autor

Lipiec J.

• Institute of Agrophysics, Polish Academy of Sciences in Lublin, Doswiadczalna 4, 20-290 Lublin, Poland

Bibliografia

• Al Bitar A., Leroux D., Kerr Y.H., Merlin O., Richaume P., Sahoo A., and Wood E.F., 2012. Evaluation of SMOS Soil moisture products over continental U.S. using the SCAN/ SNOTELnetwork. IEEE T. Geosci.Remote, 50, 1572-1586.
• Bircher S., Balling J.E., Skou N., and Kerr Y., 2012. Validation of SMOS brightness temperatures during the HOBE Airborne Campaign, Western Denmark. IEEE T. Geosci. Remote, 50, 1468-1482.
• Bland J.M. and Altman D.G., 1986. Statistical method for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307-310.
• Bland J.M. and Altman D.G., 1999. Measuring agreement in method comparison studies. Statistical Methods in Medical Res., 8, 135-160.
• Borg I., Groenen P.J.F., and Mair P., 2012. Applied Multidimensional Scaling – Springerbriefs in Statistics. Springer-Verlag Berlin-Heidelberg, Germany.
• Dall'Amico J.T., Schlenz F., Loew A., and Mauser W., 2012. First results of SMOS soil moisture validation in the upper Danube catchment. IEEE T. Geosci. Remote, 50, 1507-1516.
• Deming W.E., 1943. Statistical adjustment of data. Wiley Press, NY, USA.
• Dente L., Su Z., and Wen J., 2012. Validation of SMOS soil moisture products over the Maqu and Twente regions. Sensors, 12, 9965-9986.
• Gherboudj I., Magagi R., Goita K., Berg A.A., Toth B., and Walker A., 2012. Validation of SMOS data over agricultural and boreal forest areas in Canada. IEEE T. Geosci. Remote, 50, 1623-1635.
• International Soil Moisture Network, 2012. http://ismn.geo.tuwien.ac.at/networks/swex-poland/
• Juglea S., Kerr Y., Mialon A., Lopez-Baeza E., Braithwaite D., and Hsu K., 2010. Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station. Hydrol. Earth Syst. Sci., 14, 1509-1525.
• 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., and Delwart S., 2012.The SMOS soilmoisture retrieval algorithm. IEEE Trans. Geosci. Remote Sens., 50, 5, 1384-1403.
• Kerr Y.H., Waldteufel P., Wigneron J., Delwart S., Cabot F., Boutin J.,EscorihuelaM.J.,Font J.,ReulN., andGruhierC., 2010. The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle. Proc. IEEE, 98, 666-687.
• Kerr Y.H., Waldteufel P., Wigneron J., Martinuzzi J.M., Font J., and Berger M., 2001. Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission. IEEE T. Geosci. Remote, 39, 1729-1735.
• Krouwer J.S., 2008. Why Bland-Altman plots should use X, not (Y+X)/2 when X is a reference method. Statistics in Medicine, 27, 778-780.
• Lacava T., Matgen P., Brocca L., Bittelli M., Pergola N., Moramarco T., and Tramutoli V., 2012. A first assessment of the SMOS soil moisture product with in situ and modelled data in Italy and Luxembourg. IEEE Trans. Geosci. Remote Sens., 50, 5, 1612-1622.
• Lin L.I-K., 1989.Aconcordance correlation coefficient to evaluate reproducibility. Biometrics, 45, 255-268.
• Lin L.I-K., 2000. Total deviation index for measuring individual agreement with applications in laboratory performance and bioequivalence. Statistics in Medicine, 19, 255-270.
• Lipiec J., Doussan C., Nosalewicz A., and Kondracka K., 2013. Effect of drought and heat stresses on plant growth and yield: a review. Int. Agrophys., 27, 463-477.
• Marczewski W., Slominski J., Slominska E., Usowicz B., Usowicz J.,Romanov S., Maryskevych O.,Nastula J., and Zawadzki J., 2010. Strategies for validating and directions for employing SMOS data, in the Cal-Val project SWEX 3275) for wetlands. Hydrol. Earth Syst. Sci. Discuss., 7, 7007-7057.
• Patton J.C. and Hornbuckle B.K., 2013. Initial validation of SMOS vegetation optical thickness in Iowa. IEEE Geosci. Remote Sensing Lett., 10(4), 647-651.
• Pinori S., Crapolicchio R., and Mecklenburg S., 2008. Preparing the ESA-SMOS (Soil Moisture and Ocean Salinity) mission – Overview of the User Data Products and Data Distribution Strategy. Microwave Radiometry and Remote Sensing of the Environment, doi:10.1109/ MICRAD.2008.4579480.
• Seneviratne S.I., Corti T., Davin E.L., Hirschi M., Jaeger E.B., Lehner I., Orlowsky B., and Teuling A.J., 2010. Investigating soil moisture-climate interactions in a changing climate – a review. Earth-Sci. Reviews, 99(3-4), 125-161.
• Smith A.B., Walker J.P., Western A.W., Young R.I., Ellett K.M., Pipunic R.C., Grayson R.B., Siriwidena L., Chiew F.H.S., and Richter H., 2012. The Murrumbidgee soil moisture monitoring network data set. Water Res. Res., 48, W07701, doi:10.1029/2012WR011976.
• Usowicz B., Marczewski W., Lipiec J., Usowicz J.B., SokołowskaZ., Dąbkowska-Naskręt H., Hajnos M., and Łukowski M.I., 2009. Water in the soil – ground and satellite measurements in studies on climate change (in Polish). Foundation for the Development of Agrophysical Sciences, Committee for Agrophysics PAS, Monograph, Lublin, Poland.
• Wagner W., Naeimi V., Scipal K., de Jeu R., and Martinez- Fernandez J., 2007. Soil moisture from operational meteorological satellites. Hydrogeology J., 15(1), 121-131.