Earth observation guideKinds of data

Radar imaging

A radar satellite brings its own illumination, so it images the ground at any hour and through cloud.

The basics

A radar satellite carries its own torch. It sends out pulses of microwaves, listens for the echo, and builds a picture from the strength and the timing of what comes back. Since it supplies its own illumination and microwaves pass through cloud, smoke and darkness, it can image the ground at any hour in any weather. The pictures look unfamiliar. Calm water is dark because the pulse skates off it and away from the satellite, while a city is bright because walls and pavements form corners that throw the pulse straight back. Rough ground, wet soil and standing trees all return more. A radar image is therefore a measure of roughness, moisture and structure, not of colour, and it takes some practice to read.

Why it matters

Radar is the data to reach for when cloud, smoke or darkness would block a camera, which makes it the dependable source in places that are often cloudy and in the hours after a storm. It also measures things a camera does not, such as roughness, wetness and the structure of forests and buildings.

Radar satelliteCalm water: the echo goesaway, so it looks darkA corner throws itback, so it looks bright
Calm water sends the pulse away and looks dark. A corner, where a wall meets the ground, throws it straight back and looks bright.

In depth

The radar looks to one side of the flight path and measures the delay tt between sending a pulse and receiving its echo. The slant range to the target follows from the speed of light.

R=c t2R = \frac{c\,t}{2}
(1)

where RR is the slant range, the distance along the line of sight from the antenna to the target, in m\mathrm{m}; cc is the speed of light, 2.998×108 m s−12.998\times 10^{8}\ \mathrm{m\,s^{-1}}; and tt is the round-trip delay of the echo, in s\mathrm{s}, halved because the pulse travels out and back.

Figure 1 shows the geometry, with the incidence angle θ\theta at the ground. Two targets can be told apart in range if their echoes do not overlap in time. A pulse with bandwidth BB resolves a slant range of c/2Bc/2B, and projecting that onto the ground gives the ground-range resolution [1].

δr=c2Bsin⁡ θ\delta_{r} = \frac{c}{2B\sin\,\theta}
(2)

where δr\delta_r is the ground-range resolution, in m\mathrm{m}; cc is the speed of light; BB is the bandwidth of the transmitted pulse, in Hz\mathrm{Hz}; and θ\theta is the incidence angle, between the radar beam and the vertical at the ground.

Along the flight direction a real antenna of length LaL_a has a beam of angular width λ/La\lambda/L_a, which at the range of a satellite would cover many kilometres. Synthetic aperture processing combines the echoes recorded as the satellite moves, so that the data behave as if they came from an antenna as long as the distance flown while the target stays in the beam. The resulting azimuth resolution depends on neither range nor wavelength, and a shorter antenna gives a finer result [1].

δaz=La2\delta_{az} = \frac{L_a}{2}
(3)

where δaz\delta_{az} is the azimuth resolution, along the flight direction, in m\mathrm{m}; and LaL_a is the length of the real antenna in that direction, in m\mathrm{m}.

(a) Side-looking geometry

SatellitenadirRnear rangefar rangeSwath on the groundflight directionθ

(b) What steep ground does

layovershadowRadar looksfrom the left
  • R slant range
  • θ incidence angle
  • The satellite flies out of the page (azimuth)
  • In (b) the summit is imaged at the blue dot, nearer than its foot
Figure 1. Side-looking radar geometry. (a) Slant range, incidence angle and swath. (b) Effects of steep terrain, layover on the slope facing the radar and shadow behind it.

The brightness of a pixel is the backscatter coefficient σ0\sigma^0, usually quoted in decibels. It depends on the roughness of the surface compared with the wavelength, on its dielectric constant (which rises sharply with moisture), and on the geometry. The wavelength matters because radar sees structure at about its own scale. The Sentinel-1 satellites use C band at 5.405 GHz, a wavelength of 5.55 cm [2]. Shorter X band waves, near 3 cm, are scattered mainly by the top of a canopy, while longer L band waves, about 24 cm, reach further down to the branches and ground. Transmitting and receiving in horizontal (H) and vertical (V) polarisation gives channels such as HH, VV and VH that respond differently to surface structure [3, 4].

Two characteristics of radar images surprise newcomers. Because the signal is coherent, neighbouring pixels of a uniform surface fluctuate randomly, an effect known as speckle that is modelled as multiplicative noise [5]. It is reduced by averaging several looks at the cost of resolution. And the side-looking geometry distorts steep terrain, as panel (b) of Figure 1 shows. Slopes facing the sensor are compressed (foreshortening) and can fold over the ground in front (layover), and slopes facing away can be left without any signal (shadow) [1].

Optical and radar together

Optical and radar data record different things. Optical bands give spectral information about pigments, minerals and water, and are blocked by cloud. Radar gives structure and moisture and keeps working under cloud. Combining them, at the level of pixels, extracted features or final decisions, often improves land cover mapping over either alone, and the literature reviews the methods and their pitfalls [6, 7].

References

  1. Moreira, A., Prats-Iraola, P., Younis, M. et al. (2013) A tutorial on synthetic aperture radar. IEEE Geoscience and Remote Sensing Magazine, 1(1), 6-43. https://doi.org/10.1109/MGRS.2013.2248301
  2. Torres, R., Snoeij, P., Geudtner, D. et al. (2012) GMES Sentinel-1 mission. Remote Sensing of Environment, 120, 9-24. https://doi.org/10.1016/j.rse.2011.05.028
  3. Woodhouse, I. H. (2017) Introduction to Microwave Remote Sensing. CRC Press. https://doi.org/10.1201/9781315272573
  4. Ulaby, F. and Long, D. (2014) Microwave Radar and Radiometric Remote Sensing. University of Michigan Press. https://doi.org/10.3998/0472119356
  5. Goodman, J. W. (1976) Some fundamental properties of speckle. Journal of the Optical Society of America, 66(11), 1145. https://doi.org/10.1364/JOSA.66.001145
  6. Joshi, N., Baumann, M., Ehammer, A. et al. (2016) A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring. Remote Sensing, 8(1), 70. https://doi.org/10.3390/rs8010070
  7. Kulkarni, S. C. and Rege, P. P. (2020) Pixel level fusion techniques for SAR and optical images: A review. Information Fusion, 59, 13-29. https://doi.org/10.1016/j.inffus.2020.01.003