GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision

Transcription

1 UCL DEPARTMENT OF GEOGRAPHY GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel:

2 RECAP

3

4 Observations of forests... C-band (cm-tens of cm) low penetration depth, leaves / needles / twigs L-band leaves / branches P-band can propagate through canopy to branches, trunk and ground C-band quickly saturates (even at relatively low biomass, it only sees canopy); P-band maintains sensitivity to higher biomass as it sees trunks, branches, etc Low biomass behaviour dictated by ground properties

5 Surfaces - scattering depends on moisture and roughness Note - we could get penetration into soils at longer wavelengths or with dry soils (sand) Surfaces are typically bright if wet and rough dark if dry and smooth What happens if a dry rough surface becomes wet? Note similar arguments apply to snow or ice surfaces. Note also, always need to remember that when vegetation is present, it can act as the dominant scatterer OR as an attenuator (of the ground scattering)

6 Eastern Sahara desert Landsat SIR-A Penetration 1 4 m

7 Safsaf oasis, Egypt Penetration up to 2 m Landsat SIR-C L-band 16 April 1994

8 Single channel data Many applications are based on the operationally-available spaceborne SARs, all of which are single channel (ERS, Radarsat, JERS) As these are spaceborne datasets, we often encounter multitemporal applications (which is fortunate as these are only single-channel instruments!) When thinking about applications, think carefully about where the information is:- scattering physics spatial information (texture, ) temporal changes

9

10 Multi-temporal data Temporal changes in the physical properties of regions in the image offer another degree of freedom for distinguishing them but only if these changes can actually be seen by the radar for example - ERS-1 and ERS-2:- wetlands, floods, snow cover, crops implications for mission design? ALOS-PALSAR ( ) revisits

11 Wetlands in Vietnam - ERS Oct 97 Jan Mar May 99 Sept 99 Dec 99 Jan 00 Feb 00

12 Wetlands...

13 SIR-C (mission 1 left, mission 2 centre, difference in blue on right)

14 Floods... Maastricht A two date composite of ERS SAR images 30/1/95 (red/green) 21/9/95 (blue)

15 Snow cover... Glen Tilt - Blair Atholl ERS-2 composite red = 25/11/96 cyan=19/5/97 Scott Polar Research Institute

16 Agriculture " Gt. Driffield Composite of 3 ERS SAR images from different dates

17 OSR - Oil seed rape WW - Winter wheat

18 ERS SAR East Anglia

19

20

21 Radar modelling Surface roughness Volume roughness Dielectric constant ~ moisture Models of the vegetation volume, e.g. water cloud model of Attema and Ulaby, RT2 model of Saich Multitemporal SHAC radar image Barton Bendish

22 Water cloud model σ , * ( () & 2BL # & 2BL # $! = % cosθ " θ Acosθ 1 exp + ( ) $! % cos C + Dm.exp " s A vegetation canopy backscatter at full cover B canopy attenuation coefficient C dry soil backscatter D sensitivity to soil moisture σ 0 = scattering coefficient m s = soil moisture θ = incidence angle L = leaf area index Vegetation

23 Values of A, B, C, D Parameter Value Units / description A db B Fractional canopy moisture C db D Fractional soil moisture

24 Simulated backscatter Actual backscatter (db) r 2 = 0.81 r 2 = 0.81 σ , * ( () & 2BL # $! % cos ( C + Dm ).exp " & 2BL # $! = % cosθ " θ Acosθ 1 exp + s CHIPS simulated backscatter (db)

25

26

27

28 Canopy moisture 1 Simulated fractional canopy moisture r 2 = 0.96 r 2 = Measured fractional canopy moisture

29 Applications Irrigation fraud detection Irrigation scheduling Crop status mapping, e.g. disease, water stress

30 Multi-parameter radar More sophisticated instruments have multi-frequency, multi-polarisation radars, with steerable beams (different incidence angle) Also, different modes combinations of resolutions and swath widths SIR-C / X-SAR ENVISAT ASAR, ALOS PALSAR,...

31 Flevoland April 1994 (SIR-C/X-SAR) (L/C/X composite) L-total power (red) C-total power (green) X-VV (blue)

32 Thetford, UK AIRSAR (1991) C-HH

33 Thetford, UK AIRSAR (1991) multi-freq composite

34 Coherent RADAR modelling Thetford, UK SHAC (SAR and Hyperspectral Airborne Campaign) neodc.nerc.ac.uk ATOM dataent _ Disney et al. (2006) combine detailed structural models with optical AND RADAR models to simulate signal in both domains Drat optical model + CASM (Coherent Additive Scattering Model) of Saich et al. (2001)

35 Coherent RADAR modelling Thetford, UK SHAC (SAR and Hyperspectral Airborne Campaign) neodc.nerc.ac.uk ATOM dataent _ Disney et al. (2006) combine detailed structural models with optical AND RADAR models to simulate signal in both domains Drat optical model + CASM (Coherent Additive Scattering Model) of Saich et al. (2001)

36 Optical signal with age for different tree density (HyMAP optical data)

37 Coherent (polarised) modelled RADAR signal (CASM)

38 OPTICAL RADAR

39 An ambitious list of Applications... Flood mapping, Snow mapping, Oil Slicks Sea ice type, Crop classification, Forest biomass / timber estimation, tree height Soil moisture mapping, soil roughness mapping / monitoring Pipeline integrity Wave strength for oil platforms Crop yield, crop stress Flood prediction Landslide prediction

40 CONCLUSIONS ALOS (RIP) Radar is very reliable because of cloud penetration and day/ night availability Major advances in interferometric SAR Should radar be used separately or as an adjunct to optical Earth observation data?

41 Revision Exam: 3 hrs, answer 4 from 7 (2 from Dietmar, 5 from me) Types of question based on PREVIOUS material be similar each year (not surprisingly!) Planck function, orbital calculations, definitions of terms, preprocessing stages Factors controlling measured signal from vegetation across vis/ SWIR, or angular behaviour RADAR principles eg RADAR equation, resolutions Principles of SAR interferometry and applications General questions - systems to address a given problem KEY: address that problem Does Q give scope for moving beyond one platform or wavelength? If so then DO SO

42 Revision Types of question based on NEW material for 2011 LiDAR Principles of lidar remote sensing? What is it good for and limitations? Example applications Radiative Transfer modelling Basis of RT model building blocks? Structure, leaf scattering, soil scattering Scalar RT equation what do terms mean? How can we go about solving?

43 Revision problems: Planck s Law Fractional energy from 0 to λ F 0 λ? Integrate Planck function Note E bλ (λ,t), emissive power of bbody at λ, is function of product λt only, so... Radiant energy from 0 to λ F 0 λ ( λ, T ) E 0 λ = σt ( λ, T ) 4 = λt 0 d ( λ, T ) E bλ ( λ, T ) σt 5 Total radiant energy for λ =0 to λ = 43

44 Revision: Planck s Law example Q: what fraction of the total power radiated by a black body at 5770 K fall, in the UV (0 < λ 0.38µm)? Need table of integral values of F 0 λ So, λt = 0.38µm * 5770K = 2193µmK Or 2.193x10 3 µmk i.e. between 2 and 3 Interpolate between F 0 λ (2x10 3 ) and F 0 λ (3x10 3 ) F F F 3 ( λ, T ) F0 0.38( 2x10 ) 3 3 ( 3x10 ) F ( 2x10 ) = = ( λ, T ) = Finally, F = 0.193*( ) = 0.11 i.e. ~11% of total solar energy lies in UV between 0 and 0.38µm λ T ( µ mk x10 3 ) F 0 λ ( λ T) (dimensionless)

45 Orbital period for a given instrument and height? Gravitational force F g = GM E m s /R se 2 where G is universal gravitational constant (6.67x10-11 Nm 2 kg 2 ); M E is Earth mass (5.983x10 24 kg); m s is satellite mass (?) and R se is distance from Earth centre to satellite i.e. 6.38x h where h is satellite altitude Centripetal (not centrifugal!) force F c = m s v s2 /R se where v s is linear speed of satellite (=ω s R se where ω is the satellite angular velocity, rad s -1 ) for stable (constant radius) orbit F c = F g GM E m s /R se 2 = m s v s2 /R se = m s ω s2 R se 2 /R se so ω s 2 = GM E /R se 3 Orbits: examples From: 45

46 Orbits: examples Orbital period T of satellite (in s) = 2π/ω (remember 2π = one full rotation, 360, in radians) and R se = R E + h where R E = 6.38x10 6 m So now T = 2π[(R E +h) 3 /GM E ] 1/2 Example: geostationary altitude? T =?? Rearranging: h = [(GM E /4π 2 )T 2 ] 1/3 - R E So h = [(6.67x10-11 *5.983x10 24 /4π 2 )(24*60*60) 2 ] 1/3-6.38x10 6 h = 42.2x x10 6 = 35.8km 46

47 Example: polar orbiter period, if h = 705x10 3 m T = 2π[(6.38x x10 3 ) 3 / (6.67x10-11 *5.983x10 24 )] 1/2 T = s = 98.8mins Orbits: examples Example: show separation of successive ground tracks ~3000km Earth angular rotation = 2π/24*60*60 = 7.27x10-5 rads s -1 So in 98.8 mins, point on surface moves 98.8*60*7.27x10-5 =.431 rads Remember l =r*θ for arc of circle radius r & θ in radians So l = (Earth radius + sat. altitude)* θ = (6.38x x10 3 )* = 3054km 47