Abstract
It is now clear that both passive and active remote observing systems gain information on the Earth’s environment by essentially capturing the power carried by the electromagnetic waves that interacted with the terrestrial materials in the sense outlined in Sect. 10.1.3 It should be added that the phase of the waves, measurable by coherent radar observations, provides supplemental pieces of knowledge. The information brought by the directly measured wave quantities (power and/or phase) resides in the imprinting that the observed target exerts on the interacting electromagnetic field.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Systems exploiting low-frequency or quasi-static fields are not considered.
- 2.
Indeed, as already noted, it is not even uncommon to find the term “reflection” denoting scattering.
- 3.
Extremely dry scenarios are disregarded.
- 4.
Given the finite dimension of the coherent source, the term diffracted could be more appropriate.
- 5.
- 6.
The reflection coefficients can be alternatively expressed in terms of refractive index.
- 7.
The degree of roughness can be consequence of natural processes, as well as of agricultural practices [28].
- 8.
Clearly apart from targets the surface of which has peculiar orientations, or which include corner reflectors.
- 9.
As said, the second term in (7.65) is further reduced by the effect of the permittivity-dependent attenuation in the surface layer.
- 10.
Lidar returns behave analogously.
- 11.
It is again pointed out that the multi-platform systems such as TanDEM, although named bistatic, actually do not perform this kind of measurements, which should be carried out over an angular range sufficiently wide to observe the complete features of bistatic “scattering”, including specular reflection.
- 12.
Clearly apart from the effect of the frequency-dependent permittivity on \(\mathcal{R}\).
- 13.
As usual, the antenna is assumed collapsed in its phase center.
- 14.
Clearly according to the frequency of the interacting wave.
- 15.
The present simplified approach does not account for polarization.
- 16.
In ground-based observations, the contribution comes from the environment above the observed layer.
- 17.
The upward scattered wave is assumed to emerge almost entirely: this implies that the inner field has negligible stationary component and that total reflection (Sect. 6.4) does not occur.
- 18.
For sufficiently low extinction.
- 19.
Strong fluctuations of scattering intensity about high values are observed because of speckle (Sect. 7.2).
- 20.
The relatively smooth surface of oil-covered water in the slick area considered in Sect. 14.2.2.3 is a typical target yielding reduced backscattered power.
- 21.
Except that when the mean surface is perpendicular to the direction of observation, or when its shape corresponds to the dihedral or trihedral configurations considered in Sect. 6.6
- 22.
Clearly, down to the penetration depth (say, a few micrometers) of the optical radiation.
- 23.
Application details are given in Sect. 14.2.1.1
- 24.
Especially at grazing angles.
- 25.
This concept should be kept distinct from that of permanent scatterer outlined in Sect. 12.3.3.3
References
Alvarez-Perez JL (2009) The Extended Integral Equation Model IEM2M for topographically modulated rough surfaces. In: Ho P-GP (ed) Geoscience and remote sensing. InTech, pp 497–529. ISBN:9789533070032. doi:10.5772/ 8297
Attema EPW, Ulaby FT (1978) Vegetation modeled as a water cloud. Radio Sci 13(2):357–364. doi:10.1029/RS013i002p00357
Beckman P, Spizzichino A (1987) The scattering of electromagnetic waves from rough surfaces. Artech House. ISBN:9780890062388
Canuti P, d’Auria G, Pampaloni P, Solimini D (1992) MAC 91 on Montespertoli: an experiment for agro-hydrology. In: International geoscience and remote sensing symposium (IGARSS ’92), vol 2, pp 1744–1746. doi:10.1109/IGARSS.1992.578869
Chen MF, Fung AK (1988) A numerical study of the regions of validity of the Kirchhoff and small-perturbation rough surface scattering models. Radio Sci 23(2):163–170. doi:10.1029/RS023i002p00163
Cherniakov M (ed) (2008) Bistatic radars: emerging technology. Wiley. ISBN:9780470985748
Davidson M, Le Toan T, Mattia F, Satalino G, Manninen T, Borgeaud M (2000) On the characterization of agricultural soil roughness for radar remote sensing studies. IEEE Trans Geosci Remote Sens 38(2):630–640. doi:10.1109/36.841993
De Roo RD, Ulaby FT (1994) Bistatic specular scattering from rough dielectric surfaces. IEEE Trans Antennas Propag 42(2):220–231. doi:10.1109/8.277216
Eftimiu C (1986) Scattering by rough surfaces: a simple model. IEEE Trans Antennas Propag 34(5):626–630. doi:10.1109/TAP.1986.1143873.
Fung AK, Pan GW (1987) A scattering model for perfectly conducting random surfaces I. Model development. Int J Remote Sens 8(11):1579–1593. doi:10.1080/01431168708954800
Ishimaru A (1978) Wave propagation and scattering in random media. Academic. ISBN:9780123747020
Krieger G, Moreira A (2006) Spaceborne bi- and multistatic SAR: potential and challenges. IEE Proc Radar Sonar Navig 153(3). doi:10.1049/iprsn:20045111
Lang RH (1981) Electromagnetic backscattering from a sparse distribution of lossy dielectric scatterers. Radio Sci 16(1):15–30. doi:10.1029/RS016i001p00015
Ogilvy JA (1991) Theory of wave scattering from random rough surfaces. Taylor & Francis. ISBN:9780750300636
Prakash R, Singh D, Singh KP (2013) Analysis and retrieval of soil parameters with specular scattering data at different incidence angle. In: 2013 IEEE international geoscience and remote sensing symposium (IGARSS), Video TU4.T03.2. pp 755–758. doi:10.1109/IGARSS20136721267. http://www.igarss2013.org/ShowRecording.asp?C=E34B7C42 (visited on 19 Mar 2014)
Prati C, Rocca F, Giancola D, Monti Guarnieri A (1998) Passive geosynchronous SAR system reusing backscattered digital audio broadcasting signals. IEEE Trans Geosci Remote Sens 36(6):1973–1976. doi:10.1109/36.729370
Rytov SM, Kravtsov YuA, Tatarskii VI (1989) Principles of statistical radiophysics 3: elements of random fields. Springer. ISBN:9783540178293
Schooley AH (1962) Upwind-downwind ratio of radar return calculated from facet size statistics of a wind-disturbed water surface. Proc IRE 50(4):456–461. doi:10.1109/JRPROC.1962.288043
Shepard MK, Campbell BA, Bulmer MH, Farr TG, Gaddis LR, Plaut JJ (2001) The roughness of natural terrain: a planetary and remote sensing perspective. J Geophys Res Planets 106(E12):32777–32795. doi:10.1029/2000JE001429
Träger F (ed) (2012) Springer handbook of lasers and optics. Springer. ISBN:9783642194092
Ulaby FT, Dobson C (1989) Handbook of radar scattering: statistics for terrain. Artech House. ISBN:9780890063361
Ulaby FT, Moore RK, Fung AK (1982) Microwave remote sensing: active and passive. Radar remote sensing and surface scattering and emission theory, vol. 2. Addison-Wesley. ISBN:9780890061916
Verhoest N, Lievens H, Wagner W, Alvarez-Mozos J, Moran MS, Mattia F (2008) On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar. Sensors 8(7):4213–4248. doi:10.3390/s8074213
Willis NJ (2005) Bistatic radar. SciTech. ISBN:9781891121456
Willis NJ, Griffiths H (eds) (2007) Advances in bistatic radar. SciTech. ISBN:9781891121487
Woodhouse IH (2005) Introduction to microwave remote sensing. CRC. ISBN: 9780203646526
Yueh SH, Kong JA, Jao JK, Shin RT, Le Toan T (1992) Branching model for vegetation. IEEE Trans Geosci Remote Sens 30(2):390–402. doi:10.1109/36.134088
Zheng B, Campbell JB, Serbin G, Galbraith JM (2014) Remote sensing of crop residue and tillage practices: present capabilities and future prospects. Soil Tillage Res 138:26–34. doi:10.1016/j.still.2013.12.009
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Solimini, D. (2016). Sensing Surface and Underneath Features. In: Understanding Earth Observation. Remote Sensing and Digital Image Processing, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-25633-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-25633-7_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25632-0
Online ISBN: 978-3-319-25633-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)