摘要
The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean(i.e.,arithmetic mean)of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error(RMSE)values of our product were 0.06 and 0.09 m~3/m~3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1%and 57.7%in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.
The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean(i.e.,arithmetic mean)of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error(RMSE)values of our product were 0.06 and 0.09 m~3/m~3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1%and 57.7%in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.
引文
Aires,F.,Aznay,O.,Prigent,C.,Paul,M.,Bernardo,F.,2012.Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products:Application for the retrieval of atmospheric profiles using MetOp-A.J.Geophys.Res.:Atmosphere 117(D18).https://doi.org/10.1029/2011JD017188.
Berg,A.,Lintner,B.R.,Findell,K.L.,Malyshev,S.,2014.Impact of soil moisture-atmosphere interactions on surface temperature distribution.J.Clim.27(21),7976-7993.https://doi.org/10.1175/jcli-d-13-00591.1.
Chan,S.K.,Bindlish,R.,O'Neill,P.E.,Njoku,E.,2016.Assessment of the SMAP passive soil moisture product.IEEE Trans.Geosci.Remote Sens.54(8),1-14.https://doi.org/10.1109/TGRS.2016.256193 8.
Choudhury,B.J.,Schmugge,T.J.,Chang,A.,Newton,R.W.,1979.Effect of surface roughness on the microwave emission from soil.J.Geophys.Res.84(C9),5699-5706.https://doi.org/10.1029/JC084iC09p05699.
Choudhury,B.J.,Schmugge,T.J.,Mo,T.,1982.A parameterization of effective soil temperature for microwave emission.J.Geophys.Res.87(C2),1301-1304.https://doi.org/10.1029/JC087iC02p01301.
Crow,W.T.,Ryu,D.,2009.A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals.Hydrol.Earth Syst.Sci.13(1),1-16.https://doi.org/10.5194/hess-13-1-2009.
Dorigo,W.A.,Wanger,W.,Roland,H.,Sebastian,H.,Christoph,P.,Matthias,D.,Mecklenburg,S.,Peter,V.O.,Robock,A.,Tj,J.,2011.The International Soil Moisture Network:A data hosting facility for global insitu soil moisture measurements.Hydrol.Earth Syst.Sci.15(5),1675-1698.https://doi.org/10.5 194/hessd-8-1609-2011.
Dorigo,W.A.,Gruber,A.,De Jeu,R.A.M.,Wanger,W.,Stacke,T.,Loew,A.,Albergel,C.,Brocca,L.,Chung,D.,Parinussa,R.M.,et al.,2015.Evaluation of the ESA CCI soil moisture product using ground-based observations.Remote Sens.Environ.162,380-395.https://doi.Org/10.1016/j.rse.2014.07.023.
Du,J.Y.,Kimball,J.S.,Jones,L.A.,2016.Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E.IEEE Trans.Geosci.Remote Sens.54(1),597-608.https://doi.org/10.1109/TGRS.2015.246275 8.
Enenkel,M.,Reimer,C.,Dorigo,W.,Wanger,W.,Pfeil,I.,Parinussa,R.,Jeu,R.D.,2016.Combining satellite observations to develop a global soil moisture product for near-real-time applications.Hydrol.Earth Syst.Sci.20(10),4191-4208.https://doi.org/10.5194/hess-20-4191-2016.
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.,et al.,2010.The soil moisture active passive(SMAP1)mission.Proc.IEEE98(5),704-716.https://doi.org/10.1109/jproc.2010.2043918.
Fischer,G.,Nachtergaele,F.,Prieler,S.,Van Velthuizen,H.T.,Verelst,L.,Wiberg,D.,2008.Global Agro-Ecological Zones Assessment for Agriculture(GAEZ 2008).Laxenburg.
Flanagan,L.B.,Johnson,B.G.,2005.Interacting effects of temperature,soil moisture and plant biomass production on ecosystem respiration in a northern temperate grassland.Agric.For.Meteorol.130(3-4),237-253.https://doi.org/10.101 6/j.agrformet.2005.04.002.
Ford,T.W.,Quiring,S.M.,Frauenfeld,O.W.,Rapp,A.D.,2015.Synoptic conditions related to soil moisture-atmosphere interactions and unorganized convection in Oklahoma.J.Geophys.Res.:Atmosphere 120(22),11519-1153 5.https://doi.org/10.1002/2015JD023975.
Friedl,M.A.,Menashe,D.S.,Tan,B.,Schneider,A.,Ramankutty,N.,Sibley,A.,Huang,X.M.,2010.MODIS Collection 5 global land cover:Algorithm refinements and characterization of new datasets.Remote Sens.Environ.1 14(1),168-1 82.https://doi.org/10.1016/j.rse.2009.08.016.
Gallego-Elvira,B.,Taylor,C.M.,Harris,P.P.,Ghent,D.,Veal,K.L.,Folwell,S.S.,2016.Global observational diagnosis of soil moisture control on the land surface energy balance.Geophys.Res.Lett.43(6),2623-263 1.https://doi.org/10.1002/2016GL068 178.
He,M.,Kimball,J.S.,Running,S.,Ballantyne,A.,Guan,K.,Huemmrich,F.,2016.Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index.Remote Sens.Environ.186,173-1 83.https://doi.org/10.1016/j.rse.2016.08.019.
Huang,Y.Y.,Gerber,S.,Huang,T.Y.,Lichstein,J.W.,2016.Evaluating the drought response of CMIP5 models using global gross primary productivity,leaf area,precipitation,and soil moisture data.Glob.Biogeochem.Cycles 30(12),1827-1846.https://doi.org/10.1002/2016GB005480.
Jackson,T.J.,Schmugge,T.J.,1991.Vegetation effects on the microwave emission of soils.Remote Sens.Environ.36(3),203-212.https://doi.org/10.1016/0034-4257(91)90057-D.
Jackson,T.J.,1993.III.Measuring surface soil moisture using passive microwave remote sensing.Hydrol.Process.7(2),139-152.
Jia,X.,Zha,T.S.,Gong,J.N.,Wang,B.,Zhang,Y.Q.,Wu,B.,Qin,S.G.,Peltola,H.,2016.Carbon and water exchange over a temperate semi-arid shrubland during three years of contrasting precipitation and soil moisture patterns.Agric.For.Meteorol.(228-229),120-129.https://doi.org/10.1016/j.agrformet.2016.07.007.
Juszak,I.,Eugster,W.,Heij mans,M.M.,Schaepman-Strub,G.,2016.Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra.Biogeosciences 13(13),4049-4064.http s://doi.org/10.5194/bg-13-4049-2016.
Kerr,Y.H.,Waldteufel,P.,Richaume,P.,Wigneron,J.P.,Ferrazzoli,P.,Mahmoodi,A.,Al,B.A.,Cabot,F.,Gruhier,C.,Juglea,S.E.,et al.,2012.The SMOS soil moisture retrieval algorithm.IEEE Trans.Geosci.Remote Sens.50(5),13 84-1403.https://doi.org/10.1109/TGRS.2012.2184548.
Koike,T.,2013.Description of the GCOM-W1 AMSR2 Soil Moisture Algorithm.Japan Aerospace Exploration Agency Earth Observation Research Center.
Kolassa,J.,Gentine,P.,Prigent,C.,Aires,F.,2016.Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy,Part 1:Satellite data analysis.Remote Sens.Environ.173,1-14.https://doi.org/10.1016/j.rse.2015.11.011.
Kolassa,J.,Reichle,R.H.,Draper,C.S.,2017.Merging active and passive microwave observations in soil moisture data assimilation.Remote Sens.Environ.19 1,1 17-130.https://doi.org/10.1016/j.rse.2017.01.015.
Li,T.,Cui,Y.,Liu,A.,2017.Spatiotemporal dynamic analysis of forest ecosystem services using“big data”:A case study of Anhui Province,central-eastern China.J.Clean.Prod.142,589-599.https://doi.org/10.1016/j.jclepro.2016.09.118.
Lin,T.-S.,Cheng,F.-Y.,2016.Impact of soil moisture initialization and soil texture on simulated land-atmosphere interaction in Taiwan.J.Hydrometeorol.17(5),1337-1355.
Lindell,D.B.,Long,D.G.,2016.High-resolution soil moisture retrieval with ASCAT.IEEE Geosci.Remote Sens.Lett.13(7),972-976.https://doi.org/10.1109/LGRS.2016.2557321.
Liu,S.,Rouj ean,J.-L.,Tchuente,A.T.K.,Ceamanos,X.,Calvet,J.-C.,2014.A parameterization of SEVIRI and MODIS daily surface albedo with soil moisture:Calibration and validation over southwestern France.Remote Sens.Environ.144,137-151.https://doi.org/10.1016/j.rse.2014.01.016.
Liu,Y.Y.,Dorigo,W.A.,Parinussa,R.M.,de Jeu,R.A.M.,Wagner,W.,McCabe,M.F.,Evan,J.P.,van Dijk,A.I.J.M.,2012.Trend-preserving blending of passive and active microwave soil moisture retrievals.Remote Sens.Environ.123,280-297.https://doi.org/10.1016/j.rse.2012.03.014.
McInerney,E.,Helton,A.M.,2016.The effects of soil moisture and emergent herbaceous vegetation on carbon emissions from constructed wetlands.Wetlands 36(2),275-284.https://doi.org/10.1007/s13 157-016-0736-9.
Mironov,V.L.,Kosolapova,L.G.,Fomin,S.V.,2009.Physically and mineralogically based spectroscopic dielectric model for moist soils.IEEE Trans.Geosci.Remote Sens.47(7),2059-2070.https://doi.org/10.1109/TGRS.2008.2011631.
Morbidelli,R.,Saltalippi,C.,Flammini,A.,Corradini,C.,Brocca,L.,Govindaraju,R.S.,2016.An investigation of the effects of spatial heterogeneity of initial soil moisture content on surface runoff simulation at a small watershed scale.J.Hydrol.539,589-598.https://doi.org/10.1016/j.jhydrol.2016.05.067.
Njoku,E.G.,Li,L.,1999.Retrieval of land surface parameters using passive microwave measurements at 6-18 GHz.IEEE Trans.Geosci.Remote Sens.37(1),79-93.https://doi.org/10.1109/36.739125.
Njoku,E.G.,Jackson,T.J.,Lakshmi,V.”Chan,T.K.,Nghiem,S.V,2003.Soil moisture retrieval from AMSR-E.IEEE Trans.Geosci.Remote Sens.41(2),215-229.https://doi.org/10.1109/TGRS.2002.808243.
O'Neill,P.,Chan,S.,Njoku,E.,Jackson,T.,Bindlish,R.,2015.Soil Moisture Active Passive(SMAP)Algorithm Theoretical Basis Document Level 2&3Soil Moisture(Passivel)Data Products.Jet Propulsion Laboratory,Pasadena.
Paloscia,S.,Macelloni,G.,Santi,E.,Koike,T.,2001.A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites.IEEE Trans.Geosci.Remote Sens.39(8),1655-1661.https://doi.org/10.1109/36.942543.
Parinussa,R.M.,Wang,G.,Holmes,T.R.H.,Liu,Y.,Dolman,A.J.,de Jeu,R.,Jiang,T.,Zhang,P.,Shi,J.,2014.Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite.Int.J.Remote Sens.35(19),7007-7029.
Parinussa,R.M.,Holmes,T.R.,Wanders,N.,Dorigo,W.A.,de Jeu,R.A.,2015.A preliminary study toward consistent soil moisture from AMSR2.J.Hydrometeorol.16(2),932-947.https://doi.org/10.1175/JHM-D-13-0200.1.
Piles,M.,Petropoulos,G.P.,Sanchez,N.,Gonzalez-Zamora,A.,Ireland,G.,2016.Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MS G SEVIRI spaceborne observations.Remote Sens.Environ.1 80,403-417.https://doi.org/10.10 16/j.rse.2016.02.048.
Reichle,R.,De Lannoy,G.,Liu,Q.,Ardizzone,J.,Kimball,J.,Koster,R.,2016.SMAP Level 4 surface and root zone soil moisture.In:Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium(IGARSS).IEEE,Beijing,pp.136-138.
Rodriguez-Fernandez,N.J.,Aires,F.,Richaume,P.,Kerr,Y.H.,Prigent,C.,Kolassa,J.,Cabot,F.,Jimenez,C.,Mahmoodi,A.,Drusch,M.,2015.Soil moisture retrieval using neural networks:Application to SMOS.IEEETrans.Geosci.Remote Sens.53(1 1),5991-6007.https://doi.org/10.1 109/TGRS.2015.2430845.
Rodrfguez-Fernandez,N.J.,Aires,F.,Richaume,P.,Kerr,Y.H.,Prigent,C.,Kolassa,J.,Cabot,F.,Jimenez,C.,Mahmoodi,A.,Drusch,M.,2016.Long term global surface soil moisture fields using an SMOS-trained neural network applied to AMSR-E data.Rem.Sens.8(11),959.https://doi.org/10.1109/TGRS.2015.2430845.
Shi,J.C.,Jiang,L.,Zhang,L.,Chen,K.S.,Wigneron,J.P.,Chanzy,A.,Jackson,T.J.,2006.Physically based estimation of bare-surface soil moisture with the passive radiometers.IEEE Trans.Geosci.Remote Sens.44(11),3 145-3 153.https://doi.org/10.1109/TGRS.2006.876706.
Song,C.,Jia,L.,2016.A method for downscaling FengYun-3B soil moisture based on apparent thermal inertia.Rem.Sens.8(9).https://doi.org/10.3390/rs8090703.
Suarez,A.,Mahmood,R.,Quintanar,A.I.,Beltran-Przekurat,A.,Pielke Sr,R.,2014.A comparison of the MM5 and the Regional Atmospheric Modeling System simulations for land-atmosphere interactions under varying soil moisture.Tellus Dyn.Meteorol.Oceanogr.66(1),21486.
Sugathan,N.,Biju,V.,Renuka,G.,2014.Influence of soil moisture content on surface albedo and soil thermal parameters at a tropical station.J.Earth Sys.Sci.123(5),1115-1128.
Ulaby,F.T.,Moore,R.K.,Fung,A.K.,1981.Microwave Remote Sensing Active and Passive:Volume 1 Microwave Remote Sensing Fundamentals and Radiometry.Artech House,Norwood,p.456.
Van der Schalie,R.,De Jeu,R.,Parinussa,R.,Rodriguez-Fernandez,N.,Kerr,Y.,Al-Yaari,A.,Wigneron,J.-P.,Drusch,M.,2018.The effect of three different data fusion approaches on the quality of soil moisture retrievals from multiple passive microwave sensors.Rem.Sens.10(1),107.https://doi.org/10.33 90/rs10010107.
Wigneron,J.-P.,Jackson,T.J.,Neill,P.O.,Lannoy,G.D.,de Rosnay,P.,Walker,J.P.,Ferrazzoli,P.,Mironov,V.,Bircher,S.,Grant,J.P.,et al.,2017.Modelling the passive microwave signature from land surfaces:A review of recent results and application to the L-band SMOS&SMAP soil moisture retrieval algorithms.Remote Sens.Environ.192,238-262.https://doi.Org/10.101 6/j.rse.2017.01.024.
Xia,J.,Zhao,Z.,Sun,J.,Liu,J.,Zhao,Y.,2017.Response of stem sap flow and leaf photosynthesis in Tamarix chinensis to soil moisture in the Yellow River Delta,China.Photosynthetica 55(2),368-377.
Xu,L.K.,Baldocchi,D.D.,Tang,J.W.,2004.How soil moisture,rain pulses,and growth alter the response of ecosystem respiration to temperature.Glob.Biogeochem.Cycles 18(4).https://doi.org/10.1029/2004GB002281.
Xu,Z.Z.,Zhou,G.S.,2005.Effects of soil moisture on gas exchange,partitioning of fed L4C02 and stable carbon isotope composition(613C)of Leymus chinensis under two different diurnal temperature variations.J.Agron.Crop Sci.191(1),27-34.https://doi.Org/10.1111/j.1439-037X.2004.00119.x.
Yang,K.,Qin,J.,Zhao,L.,Chen,Y.Y.,Tang,W.J.,Han,M.L.,La,Z.,Chen,Z.Q.,Li,N.,Ding,B.H.,et al.,2013.A multiscale soil moisture and freeze-thaw monitoring network on the third pole.Bull.Am.Meteorol.Soc.94(12),1907-1916.https://doi.org/10.1175/Bams-D-12-00203.1.
Yao,P.P.,Shi,J.C.,Zhao,T.J.,Lu,H.,Al-Yaari,A.,2017.Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index.Rem.Sens.9(1),35.https://doi.org/10.33 90/rs901003 5.
Zeng,J.Y.,Li,Z.,Chen,Q.,Bi,H.Y.,Qiu,J.X.,Zou,P.F.,2015.Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations.Remote Sens.Environ.163,91-110.https://doi.org/10.101 6/j.rse.2015.03.008.
Zhang,K.”Kimball,J.S.,Nemani,R.R.,Running,S.W.,Hong,Y.,Gourley,J.J.,Yu,Z.B.,2015.Vegetation greening and climate change promote multidecadal rises of global land evapotranspiration.Sci.Rep.5,15956.https://doi.org/10.103 8/srep15956.
Zhang,Y.F.,Wang,X.P.,Hu,R.,Pan,Y.X.,Zhang,H.,2014.Variation of albedo to soil moisture for sand dunes and biological soil crusts in arid desert ecosystems.Environ.Earth Sci.71(3),1281-1288.
Zhao,L.,Yang,K.,Qin,J.,Chen,Y.Y.,Tang,W.J.,Lu,H.,Yang,Z.L.,2014.The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau.Remote Sens.Environ.152,345-355.https://doi.org/10.1016/j.rse.2014.07.005.