Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations
Abstract
:1. Introduction
2. Datasets
2.1. Field Experiment and Study Domain
Site Name | Latitude (Degree) | Longitude (Degree) |
---|---|---|
NINW | 40.700 | −106.261 |
NINE | 40.700 | −106.249 |
NICT | 40.696 | −106.255 |
NISW | 40.691 | −106.260 |
NISE | 40.691 | −106.249 |
NPNE | 40.672 | −106.317 |
NPNW | 40.672 | −106.329 |
NPCT | 40.668 | −106.323 |
NPSW | 40.663 | −106.330 |
NPSE | 40.663 | −106.317 |
NMNW | 40.650 | −106.189 |
NMNE | 40.650 | −106.177 |
NMCT | 40.645 | −106.181 |
NMSW | 40.641 | −106.188 |
NMSE | 40.641 | −106.177 |
2.2. In Situ Measurements
2.3. Radar Imagery
3. Theoretical Modeling
4. Results and Discussion
4.1. Model Comparisons
Case 1 | ||
Parameter | First layer | Second layer |
kh | π/5 | π/10 |
Kl | 2 π | π |
Dielectric constant | 5.4 + 0.44i | 11.27 + i |
Depth | 0.8λ | N/A |
Correlation function | Gaussian | |
Case 2 | ||
kh | π/25 | π/25 |
Kl | π | π |
Dielectric constant | 5.4 + 0.44i | 11.27 + i |
Depth | λ / 5 | N/A |
Correlation function | Gaussian |
4.2. Effects of Soil Volume Scattering
L-Band (1.26 GHz) | |||||
---|---|---|---|---|---|
VV (dB) | HH (dB) | VH (dB) | HV (dB) | Particle Diameter (mm) | |
σs1 | −14.9 | −17.1 | −31.8 | −31.8 | |
σv1 | −41.6 | −43.4 | −68.4 | −68.4 | 5 |
σv1 | −27.3 | −29.1 | −54.1 | −54.1 | 15 |
σv1 | −18.4 | −20.2 | −45.2 | −45.2 | 30 |
P-Band (0.43 GHz) | |||||
σs1 | −20.1 | −24.1 | −39.7 | −39.7 | |
σv1 | −59.0 | −60.8 | −85.7 | −85.7 | 5 |
σv1 | −44.6 | −46.4 | −71.4 | −71.4 | 15 |
σv1 | −35.6 | −37.4 | −62.4 | −62.4 | 30 |
4.3. Effects of Soil Profile Heterogeneity
4.4. Detection of Soil Dielectric Profile Inhomogeneity Using AIRSAR
From | To | Interval | |
---|---|---|---|
Incidence Angle | 30° | 60° | 1° |
RMS height | 0.5 cm | 3.0 cm | 0.25 cm |
Correlation Length | 5 cm | 25 cm | 2.5 cm |
Volumetric Soil Moisture | 0.05 m3/m3 | 0.45 m3/m3 | 0.025 m3/m3 |
Frequencies: L-band (1.26 GHz) and P-band (0.43 GHz); Exponential Correlation Function |
5. Discussion
6. Conclusions
Supplementary Files
Supplementary File 1Acknowledgments
Author Contributions
Conflicts of Interest
References
- Vaganov, E.A.; Hughes, M.K.; Kirdyanov, A.V.; Schweingruber, F.H.; Silkin, P.P. Influence of snowfall and melt timing on tree growth in subarctic Eurasia. Nature 1999, 400, 149–151. [Google Scholar]
- Nemani, R.R.; Keeling, C.D.; Hashimoto, H.; Jolly, W.M.; Piper, S.C.; Tucker, C.J.; Myneni, R.B.; Running, S.W. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 2003, 300, 1560–1562. [Google Scholar] [CrossRef] [PubMed]
- Kimball, J.S.; McDonald, K.C.; Zhao, M. Spring thaw and its effect on terrestrial vegetation productivity in the western Arctic observed from satellite microwave and optical remote sensing. Earth Interact. 2006, 10, 1–22. [Google Scholar] [CrossRef]
- Rawlins, M.A.; McDonlad, K.C.; Frolking, S.; Lammers, R.B.; Fahnestock, M.; Kimball, J.S.; Vorosmarty, C.J. Remote sensing of snow thaw at the pan-Arctic scale using the SeaWinds scatterometer. J. Hydrol. 2005, 312, 294–311. [Google Scholar] [CrossRef]
- Betts, A.K.; Viterbo, P.; Beljaars, A.C.M.; den Hurk, B.J.J.M. Impact of BOREAS on the ECMWF forecast model. J. Geophys. Res. 2001, 106, 33593–33604. [Google Scholar] [CrossRef]
- Betts, A.K.; Desjardins, R.; Worth, D.; Wang, S.; Li, J. Coupling of winter climate transitions to snow and clouds over the Prairies. J. Geophys. Res.: Atmos. 2014, 119, 1118–1139. [Google Scholar] [CrossRef]
- McDonald, K.C.; Kimball, J.S.; Njoku, E.; Zimmermann, R.; Zhao, M. Variability in springtime thaw in the terrestrial high latitudes: Monitoring a major control on the biospheric assimilation of atmospheric CO2 with spaceborne microwave remote sensing. Earth Interact. 2004, 8, 1–23. [Google Scholar] [CrossRef]
- Delbart, N.; Picard, G.; Le Toans, T.; Kergoat, L.; Quegan, S.; Woodward, I.; Dye, D.; Fedotova, V. Spring phenology in boreal Eurasia in a nearly century time-scale. Glob. Chang. Biol. 2008, 14, 603–614. [Google Scholar] [CrossRef]
- Kim, Y.; Kimball, J.S.; Zhang, K.; McDonald, K.C. Satellite detection of increasing Northern Hemisphere non-frozen seasons from 1979 to 2008: Implications for regional vegetation growth. Remote Sens. Environ. 2012, 121, 472–487. [Google Scholar] [CrossRef]
- Oechel, W.C.; Vourlitis, G.L.; Hastings, S.J. Acclimation of ecosystem CO2 exchange in the Alaskan Arctic in response to decadal climate warming. Nature 2000, 406, 978–981. [Google Scholar] [CrossRef] [PubMed]
- DeConto, R.M.; Galeotti, S.; Pagani, M.; Tracy, D.; Schaefer, K.; Zhang, T.J.; Pollard, D.; Beerling, D.J. Past extreme warming events linked to massive carbon release from thawing permafrost. Nature 2012, 484, 87–91. [Google Scholar] [CrossRef] [PubMed]
- Bartsch, A.; Kidd, R.; Wagner, W.; Bartalis, Z. Temporal and spatial variability of the beginning and end of daily spring freeze/thaw cycles derived from scatterometer data. Remote Sens. Environ. 2007, 106, 360–374. [Google Scholar] [CrossRef]
- Kimball, J.S.; McDonald, K.C.; Keyser, A.R.; Frolking, S.; Running, S.W. Application of the NASA scatterometer (NSCAT) for determining the daily frozen and nonfrozen landscape of Alaska. Remote Sens. Environ. 2001, 75, 113–126. [Google Scholar] [CrossRef]
- Zwieback, S.; Paulik, C.; Wagner, W. Frozen soil detection based on advanced scatterometer observations and air temperature data as part of soil moisture retrieval. Remote Sens. 2015, 7, 3206–3231. [Google Scholar] [CrossRef]
- Durand, M.; Fu, L.L.; Lettenmaier, D.P.; Alsdorf, D.E.; Rodriguez, E.; Esteban-Fernandez, D. The surface water and ocean topography mission: Observing terrestrial surface water and oceanic submesoscale eddies. Proc. IEEE 2010, 98, 766–779. [Google Scholar] [CrossRef]
- Du, J.Y.; Shi, J.C.; Tjuatja, S.B.; Chen, K.S. A combined method to model microwave scattering from a forest medium. IEEE Trans. Geosci. Remote Sens. 2006, 44, 815–824. [Google Scholar]
- Du, J.Y.; Shi, J.C.; Rott, H. Comparison between a multi-scattering and multi-layer snow scattering model and its parameterized snow backscattering model. Remote Sens. Environ. 2010, 114, 1089–1098. [Google Scholar] [CrossRef]
- Entekhabi, D.; Njoku, E.G.; ONeill, P.E.; Kellogg, K.H.; Crow, W.T.; Edelstein, W.N.; Entin, J.K.; Goodman, S.D.; Jackson, T.; Johnson, J.; et al. The Soil Moisture Active and Passive (SMAP) mission. Proc. IEEE 2010, 98, 704–716. [Google Scholar] [CrossRef]
- Rautiainen, K.; Lemmetyinen, J.; Schwank, M.; Kontu, A.; Ménard, C.B.; Mätzler, C.; Drusch, M.; Wiesmann, A.; Ikonen, J.; Pulliainen, J. Detection of soil freezing from L-band passive microwave observations. Remote Sens. Environ. 2014, 147, 206–218. [Google Scholar]
- Du, J.Y.; Kimball, J.S.; Azarderakhsh, M.; Dunbar, R.S.; Moghaddam, M.; McDonald, K.C. Classification of Alaska spring thaw characteristics using satellite L-band radar remote sensing. IEEE Trans. Geosci. Remote Sens. 2014, 53, 542–556. [Google Scholar]
- Podest, E.; McDonald, K.C.; Kimball, J.S. Multi-sensor microwave sensitivity to freeze-thaw dynamics across a complex boreal landscape. IEEE Trans. Geosci. Remote Sens. 2014, 52, 6818–6828. [Google Scholar] [CrossRef]
- Short, N.; Brisco, B.; Couture, N.; Pollard, W.; Murnaghan, K.; Budkewitsch, P. A comparison of TerraSAR-X, RADARSAT-2 and ALOS-PALSAR interferometry for monitoring permafrost environments—Case study from Herschel Island, Canada. Remote Sens. Environ 2011, 115, 3491–3506. [Google Scholar] [CrossRef]
- Du, J.Y.; Shi, J.C.; Sun, R.J. The development of HJ SAR soil moisture retrieval algorithm. Int. J. Remote Sens. 2010, 31, 3691–3705. [Google Scholar] [CrossRef]
- Bird, R.; Whittaker, P.; Stern, B.; Angli, N.; Cohen, M.; Guida, R. NovaSAR-S: A low cost approach to SAR applications. In Proceedings of IEEE 2013 Asia-Pacific Conference of Synthetic Aperture Radar (APSAR), Tsukuba, Japan, 23–27 September 2013; pp. 84–87.
- Rautiainen, K.; Lemmetyinen, J.; Pulliainen, J.; Vehviläinen, J.; Drusch, M.; Kontu, A.; Kainulainen, J.; Seppanen, J. L-band radiometer observations of soil processes at boreal and sub-Arctic environments. IEEE Trans. Geosci. Remote Sens. 2012, 50, 1483–1497. [Google Scholar] [CrossRef]
- Moghaddam, M.; Rahmat-Samii, Y.; Rodriguez, E.; Entekhabi, D.; Hoffman, J.; Moller, D.; Pierce, L.E.; Saatchi, S.; Thomson, M. Microwave Observatory of Subcanopy and Subsurface (MOSS): A mission concept for global deep soil moisture observations. IEEE Trans. Geosci. Remote Sens. 2007, 45, 2630–2643. [Google Scholar] [CrossRef]
- Tabatabaeenejad, A.; Burgin, M.; Duan, X.; Moghaddam, M. P-band radar retrieval of subsurface soil moisture profile as a second-order polynomial: First AirMOSS results. IEEE Trans. Geosci. Remote Sens. 2015, 53, 645–658. [Google Scholar] [CrossRef]
- Le Toan, T.; Quegan, S.; Davidson, M.W.J.; Balzter, H.; Paillou, P.; Papathanassiou, K.; Plummer, S.; Rocca, F.; Saatchi, S.; Shugart, H.; et al. The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle. Remote Sens. Environ. 2011, 115, 2850–2860. [Google Scholar] [CrossRef]
- Cline, D.; Yueh, S.; Chapman, B.; Stankov, B.; Gasiewski, A.; Masters, D.; Elder, K.; Kelly, R.; Painter, T.H.; Miller, S.; et al. NASA Cold Land Processes Experiment (CLPX 2002/03): Airborne remote sensing. J. Hydrometeor 2009, 10, 338–346. [Google Scholar] [CrossRef]
- Houser, P.; Kunera, D. CLPX-Ground: ISA Corner Site Meteorological Data. Available online: http://nsidc.org/data/docs/daac/nsidc0173_clpx_ISA_corner_met (accessed on 1 May 2014).
- Elder, K.; Cline, D. CLPX-Ground: ISA Snow Depth Transects and Related Measurements, Version 2; Parsons, M., Brodzik, M., Eds.; Available online: http://nsidc.org/data/nsidc-0175 (accessed on 1 May 2014).
- Chapman, B.; Shi, J. CLPX-Airborne: Airborne Synthetic Aperture Radar (AIRSAR) imagery. Available online: http://nsidc.org/data/nsidc-0153 (accessed on 1 May 2014).
- Chen, K.S.; Wu, T.D.; Tsang, L.; Li, Q.; Shi, J.C.; Fung, A.K. Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations. IEEE Trans. Geosci. Remote Sens. 2003, 41, 90–101. [Google Scholar] [CrossRef]
- Schwank, M.; Stähli, M.; Wydler, H.; Leuenberger, J.; Mätzler, C.; Flühler, H. Microwave L-band emission of freezing soil. IEEE Trans. Geosci. Remote Sens. 2004, 42, 1252–1261. [Google Scholar] [CrossRef]
- Onier, C.; Chanzy, A.; Chambarel, A.; Rouveure, R.; Chanet, M.; Bolvin, H. Impact of soil structure on microwave volume scattering evaluated by a two-dimensional numerical model. IEEE Trans. Geosci. Remote Sens. 2011, 49, 415–425. [Google Scholar] [CrossRef]
- Tsang, L.; Kong, J.A.; Ding, K.H. Scattering of Electromagnetic Waves: Theories and Applications; Wiley-Interscience: New York, NY, USA, 2000. [Google Scholar]
- Peplinski, N.R.; Ulaby, F.T.; Dobson, M.C. Dielectric properties of soils in the 0.3–1.3 GHz range. IEEE Trans. Geosci. Remote Sens. 1995, 33, 803–807. [Google Scholar] [CrossRef]
- Shi, J.C.; Dozier, J. Estimation of snow water equivalence using SIR-C/X-SAR. II. Inferring snow depth and particle size. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2475–2488. [Google Scholar]
- Kuo, C.H.; Moghaddam, M. Scattering from multilayer rough surfaces based on the extended boundary condition method and truncated singular value decomposition. IEEE Trans. Antennas Propag. 2006, 54, 2917–2929. [Google Scholar] [CrossRef]
- Pinel, N.; Johnson, J.T.; Bourlier, C. A geometrical optics model of three dimensional scattering from a rough layer with two rough surfaces. IEEE Trans. Antennas Propag. 2010, 58, 809–816. [Google Scholar] [CrossRef]
- Fuks, I.M.; Voronovich, A.G. Wave diffraction by rough interfaces in an arbitrary plane-layered medium. Waves Random Media 2000, 10, 253–272. [Google Scholar] [CrossRef]
- Duan, X.; Moghaddam, M. Bistatic vector 3-D scattering from layered rough surfaces using stabilized extended boundary condition method. IEEE Trans. Geosci. Remote Sens. 2013, 51, 2722–2733. [Google Scholar] [CrossRef]
- Lu, H.; Koike, T.; Yang, K.; Ohta, T.; Kuria, D.; Yang, K.; Fujii, H.; Tsutsui, H.; Tamagawa, K. Monitoring surface soil moisture with spaceborne passive microwave remote sensing: Algorithm developments and applications to AMSR-E and SSM/I. In Advances in Geoscience and Remote Sensing; Jedlovec, G., Ed.; In-Tech: Vukovar, Croatia, 2009; Chapter 17; pp. 371–390. [Google Scholar]
- Mladenova, I.E.; Jackson, T.J.; Bindlish, R.; Hensley, S. Incidence angle normalization of radar backscatter data. IEEE Trans. Geosci. Remote Sens 2013, 51, 1791–1804. [Google Scholar] [CrossRef]
- Shi, J.; Chen, K.S.; Li, Q.; Jackson, T.J.; O’Neill, P.E.; Tsang, L. A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer. IEEE Trans. Geosci. Remote Sens. 2002, 40, 2674–2686. [Google Scholar]
- Lou, Y.; Imel, D.A.; Chu, A.; Miller, T.W.; Moller, D.; Skotnicki, W. Progress report on the NASA/JPL airborne synthetic aperture radar system. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2001 (IGARSS’01), Sydney, Australia, 9–13 July 2001; pp. 2046–2048.
- Stiles, W.H.; Ulaby, F.T. The active and passive microwave response to snow parameters: Wetness. J. Geophys. Res.: Oceans. 1980, 85, 1037–1044. [Google Scholar] [CrossRef]
- Entekhabi, D.; Nakamura, H.; Njoku, E.G. Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations. IEEE Trans. Geosci. Remote Sens. 1994, 32, 438–448. [Google Scholar] [CrossRef]
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Du, J.; Kimball, J.S.; Moghaddam, M. Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations. Remote Sens. 2015, 7, 9450-9472. https://doi.org/10.3390/rs70709450
Du J, Kimball JS, Moghaddam M. Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations. Remote Sensing. 2015; 7(7):9450-9472. https://doi.org/10.3390/rs70709450
Chicago/Turabian StyleDu, Jinyang, John S. Kimball, and Mahta Moghaddam. 2015. "Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations" Remote Sensing 7, no. 7: 9450-9472. https://doi.org/10.3390/rs70709450