Fundamentals of Satellite Remote Sensing – Chapter 2

1. Fundamentals of Satellite Remote Sensing – Chapter 2 Emilio Chuvieco and Alfredo Huete

2. Main types of radiation processes in remote sensing: (i) reflection, (ii) emission, and (iii) emission- reflection (iii) (ii) (i)

3. Transmission of energy Convection Radiation Conduction

4. The oscillating electric and magnetic components of electromagnetic radiation propagation (the wave theory of light) l Electric field = Wavelength frequency n = Magnetic field Transmission direction Amplitude

5. Theories to explain electromagnetic radiation Wave Quantum

6. Frequency (MHz) 14 13 12 11 10 9 8 7 6 5 4 3 2 10 10 10 10 10 10 10 10 10 10 10 10 10 INFRARED MICROWAVES GAMMA RADAR X RAYS ULTRA-VIOLET NEAR RAYS MIDDLE THERMAL RADIO, TV. UHF VHF 0.01 0.1 1 10 100 0.1 1 10 100 0.1 1 10 1 10 l Wavelength ( ) Micrometers Centimetres Meters Angstroms VISIBLE SPECTRUM BLUE GREEN RED 0.4 0.5 0.6 0.7 µ m The electromagnetic spectrum (the visible spectrum highlighted)

7. Radiometric quantities commonly used in remote sensing sr, steradian, measure of the solid angle mm, micrometer or micron (10-6 meter) Mn, exitance of a black body at the same temperature fi , incident flux fr , reflected flux fa , absorbed flux ft , transmitted flux q, angle formed by the energy flux direction and the normal

8. Concept of Radiance and Radiant Intensity, the rates of energy transfer per unit solid angle. Reference Line Flux q Zenith Angle W Solid Angle q Projected Surface = A cos Surface of detected object (A)

9. Electromagnetic radiation Laws (1/2) Mn,l Radiant exitance H, Planck constant (6.626 x 10-34 W s²); k, Boltzmann constant (1.38 x 10-23 W s² K-1); c, Speed of light; l, Wavelength, T, Black body temperature (in Kelvin, K). c1 = 3.741 x 108 W m-2µm4 c2 = 1.438 x 104 µm K. Planck:

10. Electromagnetic radiation Laws (2/2) • Wien: max = 2898 m K/ T (K) • Stefan-Boltzmann: Mn = s T4 s is the Stefan-Boltzmann constant (5.67 x 10-8 W m-2 K-4 ),T is temperature in Kelvin. • For a real body: M = e Mn

11. Blackbody spectral radiant exitance curves at various temperatures

12. Comparisons of the spectral exitance from a 6000 K blackbody with top of the atmosphere solar irradiance and direct and diffuse irradiance the Earth’s surface

13. Interactions of Solar energy with the Earth’s surface f f r i f Incident energy i f f Reflected energy a r f f Transmitted energy t t f Absorbed energy a

14. Factors affecting surface reflectance • Absorption features (water, pigments, minerals). • Surface roughness (lambertian or specular reflectance). • Observation and illumination angles.

15. 70 60 50 40 30 20 10 0 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 (m) Spectral reflectance signatures for representative Earth surface materials 80 % reflectance water vegetation sand concrete snow B G RNIRSWIR

16. Types of reflections according to surface roughness Incidence angle Reflectance angle Lambertian reflector Specular reflector

17. Factors affecting spectral signatures • Solar elevation • Aspect • Slope • Atmosphere • Phenology • Soil background

18. How to obtain spectral signatures • Spectral libraries. • Spectro-radiometers. • Simulation Models. • Hyperspectral images.

19. Examples of spectral libraries • USGS (http://speclab.cr.usgs.gov). • ASTER (http://speclib.jpl.nasa.gov). • Purdue (http://shay.ench.purdue.edu/~frdata/FRDATA/Index.html). • Espectra (www.geogra.uah.es/espectra)

20. Measuring with radiometers Filter radiometers Continuous-band spectro-radiometers.

21. Models for reflectance simulation • For Vegetation: • Leaf level (Prospect) • Canopy level (SAIL) • Plot (GEOSAIL, FLIGHT) • Atmosphere (Modtran, 6S).

22. 60 50 40 30 20 10 0 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 (m) Leaf optical properties within the solar domain Leaf Cell Water content Pigments structure % reflectance Red edge

23. Basic components of a leaf and cellular structure Cuticule Epidermis Chloroplasts Palisade Mesophyll Xylem Phloem Spongy Mesophyll Air Cavity Guard cell Stomata (adapted from http://library.thinkquest.org/22016/photo/leaf.html).

24. Tessa Traeger, 1997, Sight reflected absorbed transmitted T.R. Sinclair, M.M. Schreiber & R.M. Hoffer, 1973, Agron. J., 65:276-283.

25. Absorption spectra for the Prospect model http://www.diderotp7.jussieu.fr/Led/

26. Leaf spectral signatures as a function of moisture content (FMC) 60 50 40 % reflectance 30 20 FMC (%) 142.1 10 48.9 0.0 0 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 (m)

27. 100 SLW EWT 90 Cab N 80 70 60 Sensitivity (%) 50 40 30 20 10 0 400 505 610 715 820 925 1030 1135 1240 1345 1450 1555 1660 1765 1870 1975 2080 2185 2290 2395 2500 Wavelength (nm) Relative importance of different factors in leaf reflectance (from Prospect) (Danson and Bowyer, 2004)

28. Factors affecting plant canopy reflectance • Leaf reflectance. • Leaf area index. • Leaf geometry. • Live/Dead leaves proportion. • Soil reflectance.

29. Variations of reflectance with Leaf Area Index Short, 2000

30. Combined effects of leaf and canopy factors (PROSPECT+SAIL) Danson and Boyer, 2004

31. Effects of bidirectional reflectance Spruce Soybean (http://crsa.bu.edu/~nstrug/brdf/BRDF Explained.htm).

32. Anisotropy effects (Sandmeier e Itten, 1999)

33. Factors affecting soil reflectance • Soil Minerals. • Organic matter. • Iron oxides. • Water content. • Texture y structure. • Observation and illumination angles.

34. 0,.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 (m) Spectral reflectance for different soil types: Molisol (grey silt); Vertisol (brown clay) and Entisol (white yeast 80 Mollisol 70 Vertisol Entisol 60 50 40 % reflectance 30 20 10 0 http://speclib.jpl.nasa.gov/

35. Effects of surface roughness of soil reflectance Differences in land use - Physical compacity (after Metternich, 2004)

36. Factors affecting water reflectance • Chlorophyll content: • Absorption in the visible bands. • Reflection in the NIR. • Turbidity. • Surface roughness.

37. MODIS-Aqua image of South Florida, showing different sediment concentrations in shallow waters. Source: http://visibleearth.nasa.gov/

38. Terra-MODIS image of Mexico and Central America, showing Sun glint effects. Notice the white colors of lake Chapala (located at the NW of the image) and the Pacific ocean (Source: http://visibleearth.nasa.gov/)

39. Differences in water turbidity near Manaos, Brazil (Source: http://visibleearth.nasa.gov/)

40. Reflectance curves for different types of snow and ice (adapted from Hall and Martinec 1985).

41. Differences between snow and clouds using the NIR/SWIR/R band combination (Landsat-TM image near Quito, Ecuador).

42. Thermal inertia for different land covers Dry Soils and rocks Sunrise Sunset Vegetation Water Radiant Temperature Wet soil Metalic objects 0 4 8 12 16 20 24 Time of the day (adapted from Short and Stuart, 1982)

43. Vegetation • Vegetation absorbs heat during daylight hours and emits at nightime. • ET (Rn net radiation, G ground heat, H sensible heat, latent heat LE): • Rn = G + H + LE • LE = (Rn-G) -H • LE = (Rn-G)- (Ts-Ta) Cp/ra • High thermal inertia.

44. Soils • The more moisture, the more thermal inertia. • The more organic matter, the less thermal inertia. • The emissivity is very dependent on bedrock.

45. Water • High thermal inertia. • Critical applications: • Sea currents. • Fisheries. • Impact on climatic characteristics.

46. Detection of El Niño events from sea temperature La Nina, December, 1988 Normal, December, 1990 El Nino, December, 1997

47. 100 80 60 40 20 0 1 2 3 4 5 6 7 8 9 Cloud transmisivity in the microwave region Ice clouds Atmospheric transmissivity Water clouds X C L Bands (adapted from ESA, 1995)

48. Micro-wave versus optical observation Right: JERS-1 red reflectance. Left: JERS-1 RADAR image of the same area. Images acquired simultaneously. Manaos, 1993. Source: NASDA.

49. Bands frequently used in micro-wave remote sensing

50. Factors in the RADAR signal • Surface properties: • Dialectric constant. • Roughness. • Observation characteristics: • Wavelenght. • Incidence angle. • Polarization.