被动微波反演土壤水分的L波段新发展及未来展望

doi:10.18306/dlkxjz.2018.02.003

Abstract

Abstract:

Soil moisture is an important boundary condition of land-atmosphere interactions and plays a major role in the Earth's water and energy cycles. It directly affects the hydrological processes such as precipitation, runoff, infiltration, and evapotranspiration, and can provide direct information for flood and drought monitoring. Accompanied by the continuous development of space science and technology, especially the successful launching of the first L-band satellite mission of Soil Moisture and Ocean Salinity (SMOS) using passive microwave interference imaging technology, L-band passive microwave remote sensing has become a key tool in large-scale soil moisture mapping. New issues regarding L-band application including "detection and mitigation of radio frequency interference", "vegetation optical depth retrieval and vegetation effects correction", and "soil roughness parameterization" have been studied extensively. In this article, we summarize the latest research results of the project "Vegetation effects on soil moisture estimation using multi-angle observations at L-band" funded by the National Natural Science Foundation of China, and review the research progress made regarding the above issues. The future development of soil moisture microwave remote sensing is also prospected. The review of the research progress and the prospect of the cutting-edge issues will be helpful for the demonstration and implementation of China's future satellite missions, and promote the microwave remote sensing of soil moisture and application in eco-hydrology studies at the global and regional scales.

Key words: passive microwave remote sensing, soil moisture, vegetation optical depth, soil roughness, L-band

Tianjie ZHAO. Recent advances of L-band application in the passive microwave remote sensing of soil moisture and its prospects[J].PROGRESS IN GEOGRAPHY, 2018, 37(2): 198-213.

Figures/Tables 6

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Soil roughness parameterization schemes in L-band (from Peng et al, 2017)"

类别	名称	参数化方案	参数设置	文献
基于试验数据	C79	$r s, p = Γ s, h H p$ $H p = exp - hco s N p (θ i)$	$h = 2 kσ) 2$ , $N p = 2$	Choudhury等(1979)
	W83		$h = 2 kσ) 2$ , $N p = 0$	Wang等(1983)
	W01		$h = 1.3972 m 0.5879$ , $N p = 0$ , $m = σ L c$	Wigneron等(2001)
	W01sm		$h = 0.5761 w s - 0.3475 m 0.4230$ , $N p = 0$ , $m = σ L c$	Wigneron等(2001)
	E07		$h = 2 kσ) 2$ , $N p = 1 p = h - 1 p = v$	Escorihuela等(2007)
	E07sm		$N p = 2 kσ) 2 - 4.4 w s - w FC, if w s ≤ w FC 2 kσ) 2, if w s ≤ w FC$ , $N p = 1 p = h - 1 p = v$	Escorihuela等(2007)
	W11		$h = 0.9437 σ 0.8865 σ + 2.2913 6$ , $N p = 0$	Wigneron等(2011)
	SMOS		$h = 0.10, if w s ≤ w t 0.10 - 0.05 (w s - w t) w FC - w t, if w t ≤ w s ≤ w FC 0.05, if w s ≥ w FC$ , $N p = 1 p = h - 1 p = v$	Kerr等(2012)
	W99	$r s, h = Γ s, h H h$ $r s, v = r s, h co s N θ i$ $H h = exp - h 0.1 cos θ i$	$h = kσ$ , $N = 0.655, for θ i ≤ 60$	Wegmuller等(1999)
	S06	$r s, h = Γ s, h H p$ $H p = exp (- h ? G (ε r, θ i, p))$	$h = σ λ 2 2$ , $G (ε r, θ i, p) = a - 2 (ε r, θ i, p)$ , $a (ε r, θ i, p) = k 1 θ i, p + k 2 θ i, p ε r$	Schwank等(2006)
	L13	$r s, p = 1 - Q Γ s, p + Q Γ s, q H p$ $H p = exp - hco s N p (Q i)$	$h = 2.265 1 - exp - Z s 2.023, Z s ≤ 1.253 1.046, Z s > 1.253$ , $Z s = σ 2 L c$ $Q = 0.253 h$ , $N v = 0.999 h - 0.54$ , $N h = N v + ? N$ $? N = 2.029 - 0.7457 Z s$	Lawrence等(2013)
	G14	$T b p = T s, eff + a eff, p T a - T s, eff + r s, p (T b DN - T s, eff)$ $r s, p = 1 - Q) Γ s, p G p + Q Γ s, q G q$ $a eff, p = 1 - Q A s, p + Q A s, Q$	$G p = exp - δ R 2 (c 0 + c 1 Γ s, p) co s c 2 (θ i) 103$ $Q = 0.5 1.0 - sin (2 β R) 2 β R)$ $A s, p = 1.0 - exp - δ R 1.5 (c 3 + c 4 Γ s, p) co s c 5 (θ i) 102$	Goodberlet等(2014)
基于理论模型	S02	$r s, p = Γ s, p ? exp - 2 kσ 2 cso θ i 2 + A p Γ s, p B p$	$A p or B p = exp a θ i, p, ρ + b θ i, p, ρ ? log kσ + c θ i, p, ρ ? kσ + d θ i, p, ρ ? W$ $a, b, c, d θ i, p, ρ = e p, ρ + g p, ρ θ i + h (p, ρ) θ i 2$	Shi等(2002)
	C10	$r s, p = A p m B p Γ s, p$	$A p, B p, C p = a p θ i 3 + b p θ i 2 + c p θ i + d p$ , $m = σ L c$	Chen等(2010)
	Z15	$r s, p = Γ s, p H p$ $H p = A p exp (B p Z s 2 + C p Z s)$	$A p, B p, C p = a p θ i 2 + b p θ i + c p,$ $Z s = σ 2 L c$	Zhao, Shi et al. (2015b)

Tab.1

Fig.5

References 72

[1]	赵天杰. 2012. 被动微波遥感土壤水分[D]. 博士论文, 北京师范大学.
	[Zhao T J.2012. Passive microwave remote sensing of soil moisture[D]. Beijing: Beijing Normal University.]
[2]	赵天杰, 张立新, 蒋玲梅, 等. 2009. 利用主被动微波数据联合反演土壤水分[J]. 地球科学进展, 24(7): 769-775. doi: 10.3321/j.issn:1001-8166.2009.07.010
	[Zhao T J, Zhang L X, Jiang L M, et al.2009. Joint inversion of soil moisture using active and passive microwave data[J]. Advances in Earth Science, 24(7): 769-775.] doi: 10.3321/j.issn:1001-8166.2009.07.010
[3]	Al Bitar A, Leroux D, Kerr Y H, et al.2012. Evaluation of SMOS soil moisture products over continental U.S. using the scan/SNOTEL network[J]. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1572-1586. doi: 10.1109/TGRS.2012.2186581
[4]	Bindlish R, Jackson T, Cosh M, et al.2015. Global soil moisture from the Aquarius/SAC-D satellite: Description and initial assessment[J]. IEEE Geoscience and Remote Sensing Letters, 12(5): 923-927. doi: 10.1109/LGRS.2014.2364151
[5]	Bindlish R, Jackson T, Zhao T J.2011. A MODIS-based vegetation index climatology[C]//Proceedings of SPIE 8156, remote sensing and modeling of ecosystems for sustainability VIII. San Diego, CA: SPIE, 8156: 815603.
[6]	Chan S K, Bindlish R, O'Neill P E, et al.2016. Assessment of the SMAP passive soil moisture product[J]. IEEE Transactions on Geoscience and Remote Sensing, 54(8): 4994-5007. doi: 10.1109/TGRS.2016.2561938
[7]	Chen K S, Wu T-D, Tsang L, et al.2003. Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations[J]. IEEE Transactions on Geoscience and Remote Sensing, 41(1): 90-101. doi: 10.1109/TGRS.2002.807587
[8]	Chen L, Shi J C, Wigneron J-P, et al.2010. A parameterized surface emission model at L-band for soil moisture retrieval[J]. IEEE Geoscience and Remote Sensing Letters, 7(1): 127-130. doi: 10.1109/LGRS.2009.2028443
[9]	Chen Y Y, Yang K, Qin J, et al.2017. Evaluation of SMAP, SMOS, and AMSR2 soil moisture retrievals against observations from two networks on the Tibetan Plateau[J]. Journal of Geophysical Research: Atmospheres, 122(11): 5780-5792. doi: 10.1002/2016JD026388
[10]	Choudhury B J, Schmugge T J, Chang A, et al.1979. Effect of surface roughness on the microwave emission from soils[J]. Journal of Geophysical Research: Oceans, 84(C9): 5699-5706. doi: 10.1029/JC084iC09p05699
[11]	Cosh M H, Jackson T J, Bindlish R, et al.2004. Watershed scale temporal and spatial stability of soil moisture and its role in validating satellite estimates[J]. Remote Sensing of Environment, 92(4): 427-435. doi: 10.1016/j.rse.2004.02.016
[12]	Cosh M H, Jackson T J, Starks P, et al.2006. Temporal stability of surface soil moisture in the Little Washita River watershed and its applications in satellite soil moisture product validation[J]. Journal of Hydrology, 323(1-4): 168-177. doi: 10.1016/j.jhydrol.2005.08.020
[13]	Crow W T, Koster R D, Reichle R H, et al.2005. Relevance of time-varying and time-invariant retrieval error sources on the utility of spaceborne soil moisture products[J]. Geophysical Research Letters, 32(24): L24405. doi: 10.1029/2005GL024889
[14]	Cui Q, Shi J C, Du J Y, et al.2015. An approach for monitoring global vegetation based on multiangular observations from SMOS[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(2): 604-616. doi: 10.1109/JSTARS.2015.2388698
[15]	Dall'Amico J T, Schlenz F, Loew A, et al.2012. First results of SMOS soil moisture validation in the upper danube catchment[J]. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1507-1516. doi: 10.1109/TGRS.2011.2171496
[16]	Entekhabi D, Njoku E G, O'Neill P E, et al.2010. The soil moisture active passive (SMAP) mission[J]. Proceedings of the IEEE, 98(5): 704-716. doi: 10.1109/JPROC.2010.2043918
[17]	Escorihuela M J, Kerr Y H, De Rosnay P, et al.2007. A simple model of the bare soil microwave emission at L-band[J]. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 1978-1987. doi: 10.1109/TGRS.2007.894935
[18]	Fernandez-Moran R, Al-Yaari A, Mialon A, et al.2017. SMOS-IC: An alternative SMOS soil moisture and vegetation optical depth product[J]. Remote Sensing, 9(5): 457. doi: 10.3390/rs9050457
[19]	Fernandez-Moran R, Wigneron J-P, De Lannoy G, et al.2016. Calibrating the effective scattering albedo in the SMOS algorithm: Some first results[C]//Proceedings of 2016 IEEE international geoscience and remote sensing symposium. Beijing, China: IEEE, 826-829.
[20]	Goodberlet M A, Mead J B.2014. A model of surface roughness for use in passive remote sensing of bare soil moisture[J]. IEEE Transactions on Geoscience and Remote Sensing, 52(9): 5498-5505. doi: 10.1109/TGRS.2013.2289979
[21]	Houser P R, Shuttleworth W J, Famiglietti J S, et al.1998. Integration of soil moisture remote sensing and hydrologic modeling using data assimilation[J]. Water Resources Research, 34(12): 3405-3420. doi: 10.1029/1998WR900001
[22]	Imaoka K, Kachi M, Shibata A, et al.2007. Five years of AMSR-E monitoring and successive GCOM-W1/AMSR2 instrument[C]//Proceedings of SPIE 6744, sensors, systems, and next-generation satellites XI. Florence, Italy: SPIE, 6744: 67440J .
[23]	Jackson T J, Bindlish R, Cosh M H, et al.2012. Validation of soil moisture and ocean salinity (SMOS) soil moisture over watershed networks in the U.S[J]. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1530-1543. doi: 10.1109/TGRS.2011.2168533
[24]	Jackson T J, Cosh M H, Bindlish R, et al.2010. Validation of advanced microwave scanning radiometer soil moisture products[J]. IEEE Transactions on Geoscience and Remote Sensing, 48(12): 4256-4272. doi: 10.1109/TGRS.2010.2051035
[25]	Jackson T J, Le Vine D M, Hsu A Y, et al.1999. Soil moisture mapping at regional scales using microwave radiometry: The Southern Great Plains hydrology experiment[J]. IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2136-2151. doi: 10.1109/36.789610
[26]	Jackson T J, Schmugge T J.1991. Vegetation effects on the microwave emission of soils[J]. Remote Sensing of Environment, 36(3): 203-212. doi: 10.1016/0034-4257(91)90057-D
[27]	Kerr Y H, Waldteufel P, Richaume P, et al.2012. The SMOS Soil Moisture Retrieval Algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1384-1403. doi: 10.1109/TGRS.2012.2184548
[28]	Kerr Y H, Waldteufel P, Wigneron J-P, et al.2010. The SMOS mission: New tool for monitoring key elements of the global water cycle[J]. Proceedings of the IEEE, 98(5): 666-687. doi: 10.1109/JPROC.2010.2043032
[29]	Konings A G, Piles M, Das N, et al.2017. L-band vegetation optical depth and effective scattering albedo estimation from SMAP[J]. Remote Sensing of Environment, 198(1): 460-470. doi: 10.1016/j.rse.2017.06.037
[30]	Konings A G, Piles M, Rötzer K, et al.2016. Vegetation optical depth and scattering albedo retrieval using time series of dual-polarized L-band radiometer observations[J]. Remote Sensing of Environment, 172: 178-189. doi: 10.1016/j.rse.2015.11.009
[31]	Kurum M.2013. Quantifying scattering albedo in microwave emission of vegetated terrain[J]. Remote Sensing of Environment, 129: 66-74. doi: 10.1016/j.rse.2012.10.021
[32]	Kurum M, Lang R H, O'Neill P E, et al.2011. A first-order radiative transfer model for microwave radiometry of forest canopies at L-band[J]. IEEE Transactions on Geoscience and Remote Sensing, 49(9): 3167-3179. doi: 10.1109/TGRS.2010.2091139
[33]	Lawrence H, Wigneron J-P, Demontoux F, et al.2013. Evaluating the semiempirical H-Q model used to calculate the L-band emissivity of a rough bare soil[J]. IEEE Transactions on Geoscience and Remote Sensing, 51(7): 4075-4084. doi: 10.1109/TGRS.2012.2226995
[34]	Le Vine D M, Lagerloef G S E, Colomb F R, et al.2007. Aquarius: An instrument to monitor sea surface salinity from space[J]. IEEE Transactions on Geoscience and Remote Sensing, 45(7): 2040-2050. doi: 10.1109/TGRS.2007.898092
[35]	Li D Y, Zhao T J, Shi J C, et al.2015. First evaluation of Aquarius soil moisture products using in situ observations and GLDAS model simulations[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(12): 5511-5525. doi: 10.1109/JSTARS.2015.2452955
[36]	Li L, Gaiser P W, Gao B C, et al.2010. WindSat global soil moisture retrieval and validation[J]. IEEE Transactions on Geoscience and Remote Sensing, 48(5): 2224-2241. doi: 10.1109/TGRS.2009.2037749
[37]	Li L, Njoku E G, Im E, et al.2004. A preliminary survey of radio-frequency interference over the U.S. in Aqua AMSR-E data[J]. IEEE Transactions on Geoscience and Remote Sensing, 42(2): 380-390. doi: 10.1109/TGRS.2003.817195
[38]	Mialon A, Wigneron J-P, De Rosnay P, et al.2012. Evaluating the L-MEB model from long-term microwave measurements over a rough field, SMOSREX 2006[J]. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1458-1467. doi: 10.1109/TGRS.2011.2178421
[39]	Mo T, Choudhury B J, Schmugge T J, et al.1982. A model for microwave emission from vegetation-covered fields[J]. Journal of Geophysical Research: Oceans, 87(C13): 11229-11237. doi: 10.1029/JC087iC13p11229
[40]	Njoku E G, Ashcroft P, Chan T K, et al.2005. Global survey and statistics of radio-frequency interference in AMSR-E land observations[J]. IEEE Transactions on Geoscience and Remote Sensing, 43(5): 938-947. doi: 10.1109/TGRS.2004.837507
[41]	Njoku E G, Chan S K.2006. Vegetation and surface roughness effects on AMSR-E land observations[J]. Remote Sensing of Environment, 100(2): 190-199. doi: 10.1016/j.rse.2005.10.017
[42]	Njoku E G, Jackson T J, Lakshmi V, et al.2003. Soil moisture retrieval from AMSR-E[J]. IEEE Transactions on Geoscience and Remote Sensing, 41(2): 215-229. doi: 10.1109/TGRS.2002.808243
[43]	O'Neill P, Chan S, Njoku E, et al.2016. Algorithm theoretical basis document level 2 & 3 soil moisture (passive) data products[R]. JPL D-66480. Pasadena, CA: Jet Propulsion Laboratory.
[44]	Pan M, Sahoo A K, Wood E F.2014. Improving soil moisture retrievals from a physically-based radiative transfer model[J]. Remote Sensing of Environment, 140: 130-140. doi: 10.1016/j.rse.2013.08.020
[45]	Parrens M, Al Bitar A, Mialon A, et al.2017. Estimation of the L-band effective scattering albedo of tropical forests using SMOS observations[J]. IEEE Geoscience and Remote Sensing Letters, 14(8): 1223-1227. doi: 10.1109/LGRS.2017.2703637
[46]	Parrens M, Wigneron J-P, Richaume P, et al.2016. Global-scale surface roughness effects at L-band as estimated from SMOS observations[J]. Remote Sensing of Environment, 181: 122-136. doi: 10.1016/j.rse.2016.04.006
[47]	Peng B, Zhao T J, Shi J C, et al.2017. Reappraisal of the roughness effect parameterization schemes for L-band radiometry over bare soil[J]. Remote Sensing of Environment, 199: 63-77. doi: 10.1016/j.rse.2017.07.006
[48]	Qin J, Yang K, Lu N, et al.2013. Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia[J]. Remote Sensing of Environment, 138: 1-9. doi: 10.1016/j.rse.2013.07.003
[49]	Saatchi S S, Harris M L, Brown S, et al.2011. Benchmark map of forest carbon stocks in tropical regions across three continents[J]. Proceedings of the National Academy of Sciences of the United States of America, 108(24): 9899-9904. doi: 10.1073/pnas.1019576108
[50]	Sánchez N, Martínez-Fernández J, González-Piqueras J, et al.2012. Water balance at plot scale for soil moisture estimation using vegetation parameters[J]. Agricultural and Forest Meteorology, 166-167: 1-9. doi: 10.1016/j.agrformet.2012.07.005
[51]	Schlenz F, Dall'Amico J T, Mauser W, et al.2012. Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany[J]. Hydrology and Earth System Sciences Discussions, 16(10): 3517-3533. doi: 10.5194/hessd-9-5389-2012
[52]	Schwank M, Matzler C.2006. Air-to-soil transition model[M]//Mätzler C, Rosenkranz P W, Battaglia A, et al. Thermal microwave radiation: Applications for remote sensing. Stevenage, England: Institute of Engineering and Technology.
[53]	Schwank M, Volksch I, Wigneron J-P, et al.2010. Comparison of two bare-soil reflectivity models and validation with L-band radiometer measurements[J]. IEEE Transactions on Geoscience and Remote Sensing, 48(1): 325-337. doi: 10.1109/TGRS.2009.2026894
[54]	Shi J C, Chen K S, Li Q, et al.2002. A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer[J]. IEEE Transactions on Geoscience and Remote Sensing, 40(12): 2674-2686. doi: 10.1109/TGRS.2002.807003
[55]	Shi J C, Dong X L, Zhao T J, et al.2014. WCOM: The science scenario and objectives of a global water cycle observation mission[C]//Proceedings of 2014 IEEE international geoscience and remote sensing symposium. Quebec City, QC, Canada: IEEE, 3646-3649.
[56]	Shi J C, Jackson T, Tao J, et al.2008. Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E[J]. Remote Sensing of Environment, 112(12): 4285-4300. doi: 10.1016/j.rse.2008.07.015
[57]	Shi J C, Yang D, Du J Y, et al.2012. Progresses on microwave remote sensing of land surface parameters[J]. Science China Earth Sciences, 55(7): 1052-1078. doi: 10.1007/s11430-012-4444-x
[58]	Van Der Schalie R, Kerr Y H, Wigneron J P, et al.2016. Global SMOS soil moisture retrievals from the land parameter retrieval model[J]. International Journal of Applied Earth Observation and Geoinformation, 45(Pt B): 125-134. doi: 10.1016/j.jag.2015.08.005
[59]	Wang J R, Choudhury B J.1981. Remote sensing of soil moisture content, over bare field at 1.4 GHz frequency[J]. Journal of Geophysical Research: Oceans, 86(C6): 5277-5282. doi: 10.1029/JC086iC06p05277
[60]	Wang J R, O'Neill P E, Jackson T J, et al.1983. Multifrequency measurements of the effects of soil moisture, soil texture, and surface roughness[J]. IEEE Transactions on Geoscience and Remote Sensing, GE-21(1): 44-51. doi: 10.1109/TGRS.1983.350529
[61]	Wegmuller U, Matzler C.1999. Rough bare soil reflectivity model[J]. IEEE Transactions on Geoscience and Remote Sensing, 37(3): 1391-1395. doi: 10.1109/36.763303
[62]	Wigneron J-P, Chanzy A, Kerr Y H, et al.2011. Evaluating an improved parameterization of the soil emission in L-MEB[J]. IEEE Transactions on Geoscience and Remote Sensing, 49(4): 1177-1189. doi: 10.1109/TGRS.2013.2253972
[63]	Wigneron J-P, Kerr Y, Waldteufel P, et al.2007. L-band microwave emission of the biosphere (L-MEB) model: Description and calibration against experimental data sets over crop fields[J]. Remote Sensing of Environment, 107(4): 639-655. doi: 10.1016/j.rse.2006.10.014
[64]	Wigneron J-P, Laguerre L, Kerr Y H.2001. A simple parameterization of the L-band microwave emission from rough agricultural soils[J]. IEEE Transactions on Geoscience and Remote Sensing, 39(8): 1697-1707. doi: 10.1109/36.942548
[65]	Wigneron J-P, Parde M, Waldteufel P, et al.2004. Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band[J]. IEEE Transactions on Geoscience and Remote Sensing, 42(2): 416-425. doi: 10.1109/TGRS.2003.817976
[66]	Yang H, Weng F Z, Lv L Q, et al.2011. The FengYun-3 microwave radiation imager on-orbit verification[J]. IEEE Transactions on Geoscience and Remote Sensing, 49(11): 4552-4560. doi: 10.1109/TGRS.2011.2148200
[67]	Zeng J Y, Li Z, Chen Q, et al.2015. Method for soil moisture and surface temperature estimation in the Tibetan Plateau using spaceborne radiometer observations[J]. IEEE Geoscience and Remote Sensing Letters, 12(1): 97-101. doi: 10.1109/LGRS.2014.2326890
[68]	Zhang Z J, Lan H M, Zhao T J.2017. Detection and mitigation of radiometers radio-frequency interference by using the local outlier factor[J]. Remote Sensing Letters, 8(4): 311-319. doi: 10.1080/2150704X.2016.1266408
[69]	Zhao T J, Jackson T J, Bindlish R, et al.2012. Potential use of aquarius scatterometer observations to estimate vegetation water content[C]. Barc Poster Day. 2012 CDROM.
[70]	Zhao T J, Shi J C, Bindlish R, et al.2015a. Refinement of SMOS multiangular brightness temperature toward soil moisture retrieval and its analysis over reference targets[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(2): 589-603. doi: 10.1109/JSTARS.2014.2336664
[71]	Zhao T J, Shi J C, Bindlish R, et al.2015b. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval[J]. Physics and Chemistry of the Earth, Parts A/B/C, 83-84: 65-74. doi: 10.1109/URSIGASS.2014.6929685
[72]	Zhao T J, Zhang L X, Shi J C, et al.2011. A physically based statistical methodology for surface soil moisture retrieval in the Tibet Plateau using microwave vegetation indices[J]. Journal of Geophysical Research: Atmospheres, 116(D8): D08116. doi: 10.1029/2010JD015229

Recent advances of L-band application in the passive microwave remote sensing of soil moisture and its prospects

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[10]	ZhANG Caixia, YANG Qinke, LI Rui. Advancement in Topographic Wetness Index and Its Application [J]. PROGRESS IN GEOGRAPHY, 2005, 24(6): 116-123.
[11]	SHAO Xiaomei, YAN Changrong, XU Zhenjian. Progress in Monitoring and Simulation of Soil Moisture [J]. PROGRESS IN GEOGRAPHY, 2004, 23(3): 58-66.
[12]	GAO Lu, CHEN Su ying, HU Chun sheng, HUO Xi liang . A Study on Spatial Variability of Soil Moisture in Wheat Field Under Sprinkling Irrigation Condition [J]. PROGRESS IN GEOGRAPHY, 2002, 21(6): 609-615.