SAR Remote Sensing. Introduction into SAR. Data characteristics, challenges, and applications.
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1 SAR Remote Sensing Introduction into SAR. Data characteristics, challenges, and applications. PD Dr. habil. Christian Thiel, Friedrich-Schiller-University Jena
2 DLR-HR Jena & Friedrich-Schiller-University 2
3 DLR-HR Sentinel-1a Image of Thuringia 3
4 DLR-HR Jena & Friedrich-Schiller-University 4
5 DLR-HR Jena & Friedrich-Schiller-University 5
6 DLR-HR Dept. of Earth Observation Basic Research - E.g. SAR coherence & Forestry Applied Earth Observation - E.g. landcover mapping using multitemporal SAR data Project Coordination - Coordination of many international projects Education - BSc Geography - MSc Geoinformatics - Various PhD Projects - SAR-EDU 6
7 DLR-HR Dept. of Earth Observation 7
8 Contents What is Remote Sensing/Earth Observation? Active Radar Remote Sensing Summary SAR-EDU>SAR Remote Sensing>An Introduction>
9 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Remote sensing (RS), also called earth observation, refers to obtaining information about objects or areas at the Earth s surface without being in direct contact with the object or area. SAR-EDU>SAR Remote Sensing>An Introduction>
10 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Components of the remote sensing process 1 2 Source of electromagnetic energy Interaction with the object 1 2 SAR-EDU>SAR Remote Sensing>An Introduction>
11 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Components of the remote sensing process 5 green tree, 5 m high, healthy, Source of electromagnetic energy Interaction with the object Radiation back to sensor Reception of radiation by sensor 1 5 Interpretation and analysis SAR-EDU>SAR Remote Sensing>An Introduction>
12 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Components of the remote sensing process Source of electromagnetic energy Interaction with the object 5 SPOT Radiation back to sensor Reception of radiation by sensor Interpretation and analysis 1 Optical satellite visible part of the spectrum energy scattered off the leaf is dependent on: The greenness of the leaf as a function of the amount of chlorophyll, which absorbs the energy that is needed for photosynthesis 3 2 SAR-EDU>SAR Remote Sensing>An Introduction>
13 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Components of the remote sensing process 1 Source of electromagnetic energy 2 Interaction with the object Radiation back to sensor Reception of radiation by sensor Interpretation and analysis TerraSAR-X 3 Radar satellite microwave part of the spectrum 2 energy scattered off the leaf is dependent on: size shape orientation dielectric properties SAR-EDU>SAR Remote Sensing>An Introduction>
14 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy 1. Sun 2. Earth Emitted Energy 3. fewer 3. Active Source of Energy (e.g. Satellite Sensor) Source: SAR-EDU>SAR Remote Sensing>An Introduction>
15 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy passive active SPOT 5 (optical satellite) TerraSAR-X (radar satellite) Further Examples: Non-imaging: radiometer, magnetic sensor Imaging: cameras, optical mechanical scanner, spectrometer, radiometer Further Examples: Non-imaging: radiometer, altimeter, laser Imaging: Real Aperture Radar, Synthetic Aperture Radar SAR-EDU>SAR Remote Sensing>An Introduction>
16 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy Passive remote sensing systems: Detect the reflected or emitted EM radiation from natural sources Some of the images represent reflected solar radiation in the visible and the near infrared regions of the EM spectrum others are the measurements of the energy emitted by the earth surface itself i.e. in the thermal infrared wavelength region Active remote sensing systems: Detect reflected responses from objects irradiated by artificiallygenerated energy sources energy is transmitted from the remote sensing platform measurement of relative return from the earth s surface SAR-EDU>SAR Remote Sensing>An Introduction>
17 What is Remote Sensing/Earth Observation? Source of electromagnetic energy - active FSU JENA
18 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy atmospheric transmissibility radiation energy sun 6000 K earth 300 K (ALBERTZ 2001:11) x-ray ultraviolet near IR intermediate and far infrared microwaves radio waves thermal scanner radar techniques multispectral scanner visible light infrared photogrammetry multispectral scanner FSU JENA SAR-EDU>SAR Remote Sensing>An Introduction>
19 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy atmospheric transmissibility radiation energy sun 6000 K earth 300 K (ALBERTZ 2001:11) x-ray ultraviolet near IR intermediate and far infrared microwaves radio waves thermal scanner radar techniques multispectral scanner visible light infrared photogrammetry multispectral scanner FSU JENA SAR-EDU>SAR Remote Sensing>An Introduction>
20 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Source of electromagnetic energy atmospheric transmissibility radiation energy sun 6000 K earth 300 K (ALBERTZ 2001:11) x-ray ultraviolet near IR intermediate and far infrared microwaves radio waves thermal scanner radar techniques multispectral scanner visible light infrared photogrammetry multispectral scanner FSU JENA SAR-EDU>SAR Remote Sensing>An Introduction>
21 Synthetic Aperture Radar - SAR Kazuo Ouchi (2013): Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics, Remote Sensing 2013, 5(2), ; doi: /rs
22 Synthetic Aperture Radar - SAR Kazuo Ouchi (2013): Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics, Remote Sensing 2013, 5(2), ; doi: /rs
23 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Interaction with the object Wave Theory and Polarization (David P. Lusch, 1999). SAR-EDU>Basics>SAR FSU JENA Remote Sensing>An Introduction 26
24 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Interaction with the object The Radar Concept (after ROSEN 2004:o.S.). SAR-EDU>SAR Remote Sensing>An Introduction>
25 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Characteristics of microwaves/sar sensors 1. Active remote sensing sensors generate EM-waves no sunlight required (night time acquisitions possible), no problems due to bad illumination 2. Microwaves are capable to penetrate into/through objects. This effect is depending on wavelength and dielectric characteristics of objects (almost) no problems with clouds, dust, fog. Sensing of hidden objects 3. Magnitude and characteristics of backscatter depend on geometric and dielectric properties of objects SAR-EDU>SAR Remote Sensing>An Introduction>
26 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages / Example subsurface penetration Landsat Thematic Mapper shows the desert s surface Safsaf Oasis, Eygpt SIR-C/X-SAR shows what the landscape might look like if stripped bare of sand Safsaf Oasis, Eygpt SAR-EDU>SAR Remote Sensing>An Introduction>
27 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages / Example subsurface penetration SAR-EDU>SAR Remote Sensing>An Introduction>
28 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages / Example all weather These images were acquired over the city of Udine (I), by ERS-1 on the 4th of July 1993 at 9.59 a.m. (GMT) and Landsat-5 on the same date at 9.14 a.m. (GMT) respectively. The clouds that are clearly visible in the optical image, are not appearing in the SAR image. SAR-EDU>SAR Remote Sensing>An Introduction>
29 Heavy Clouds and Rain Cells in X-Band SAR Images Only visible at short wavelengths and extreme conditions 32
30 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Characteristics of microwaves/sar sensors 1. Active remote sensing sensors generate EM-waves no sunlight required (night time acquisitions), no problems caused by weak illumination 2. Microwaves are capable to penetrate into/through objects depending on wavelength and dielectric characteristics of objects (almost) no problems with clouds, dust, fog; sensing of hidden objects 3. Magnitude and characteristics of backscatter depend on geometric and dielectric properties of objects SAR-EDU>SAR Remote Sensing>An Introduction>
31 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 SAR Data Examples TerraSAR-X DLR TerraSAR-X, 9. July 2010, Mediterranean Sea SAR-EDU>SAR Remote Sensing>An Introduction>
32 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages / Example dielecric properties SAR-EDU>SAR Remote Sensing>An Introduction> Irrigated fields: Higher backscatter 35
33 F-SAR Airborne SAR System of DLR - fully polarimetric X-Band Mode (R=HH, G= HV, B=VV) Copyright Subset DLR-HR Neu-Gablonz, Bavaria, Germany 36
34 Subset of Neu-Gablonz Area - River, Fields and (R=HH, G= HV, B=VV) Copyright a purification plant DLR-HR 37
35 Crop monitoring with several observations 19/04/06 06/06/06 05/07/06 Copyright DLR-HR DLR R: HH G: HV B: VV E-SAR, L-band DLR R: HH G: HV B: VV E-SAR, L-band DLR R: HH G: HV B: VV E-SAR, L-band 38 38
36 Frequency and Polarisation Diversity Kalimantan - Indonesia Copyright DLR-HR E-SAR, C-band R: HH G: HV B: VV E-SAR, L-band R: HH G: HV B: VV E-SAR, P-band R: HH G: HV B: VV DLR DLR DLR 39 39
37 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Interaction with the object optical radar SPOT 5 Optical satellite visible part of the spectrum energy scattered off the leaf is dependent on: The greenness of the leaf as a function of the amount of chlorophyll, which absorbs the energy that is needed for photosynthesis TerraSAR-X Radar satellite microwave part of the spectrum energy scattered off the leaf is dependent on: size shape orientation dielectric properties SAR-EDU>SAR Remote Sensing>An Introduction>
38 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 What is Remote Sensing/Earth Observation? Interaction with the object optical radar SPOT 5 Optical satellite visible part of the spectrum energy scattered off the leaf is dependent on: The greenness of the leaf as a function of the amount of chlorophyll, which absorbs the energy that is needed for photosynthesis TerraSAR-X Radar satellite microwave part of the spectrum energy scattered off the leaf is dependent on: size shape orientation dielectric properties SAR-EDU>SAR Remote Sensing>An Introduction>
39 What is Remote Sensing/Earth Observation? Source of electromagnetic energy - active FSU JENA
40 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Interaction with the object Side-looking SAR geometry. 44
41 What is Remote Sensing/Earth Observation? Synthetic Aperture Radar Length of synthetic aperture depending on distance between antenna and target Azimuth resolution independent on range distance FSU JENA
42 What is Remote Sensing/Earth Observation? Synthetic Aperture Radar Is side looking really necessary? FSU JENA
43 SAR Imaging Geometry V S / C radar Radar transmits pulses and receives echoes at the rate of the pulse repetition frequency: Hz range: radar principle = scanning at speed of light azimuth: scanning in flight direction swath width for this lecture: straight flight path Fig. 3: DLR V B VS / C V B V 47
44 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 SAR Data Examples Andreas R. Brenner and Ludwig Roessing, Radar Imaging of Urban Areas by Means of Very High-Resolution SAR and Interferometric SAR, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 46, NO. 10, OCTOBER 2008 (X-band) SAR-EDU>SAR Remote Sensing>An Introduction>
45 DLR-HR Effects of side-looking geometry GEO 312 Radarfernerkundung Übungen 51
46 DLR-HR Effects of side-looking geometry Effekte der Schrägsicht-Aufnahmegeometrie (1/2) 1. Radarshadow GEO 312 Radarfernerkundung Übungen 52
47 DLR-HR Effects of side-looking geometry Effekte der Schrägsicht-Aufnahmegeometrie (1/2) 1. Radarshadow 2. Foreshortening GEO 312 Radarfernerkundung Übungen 53
48 DLR-HR Effects of side-looking geometry Effekte der Schrägsicht-Aufnahmegeometrie (1/2) 1. Radarshadow 2. Foreshortening 3. Layover GEO 312 Radarfernerkundung Übungen 54
49 SAR Image Examples azimuth Sensor: ERS-1 range Mojave Desert CA, USA Size 40 km x 40 km ERS-1 ESA 55
50 Geometry of SAR Images - Foreshortening foreshortening A B range C A B C ground range Slopes oriented to the SAR appear compressed 23 deg ERS-1 ESA Fig. 33: DLR 56
51 Geometry of SAR Images - Layover lay-over A C B D range A B C D Steep slopes oriented to the SAR lead to ghost images 23 deg ERS-1 ESA Fig. 34: DLR 57
52 Layover Mask Computed from DEM 100m DEM DLR DLR simulated ERS-Image white: lay-over 58
53 Geometry of SAR Images - Shadow Steep slopes oriented away from the SAR return no signal radar shadow Fig. 35: DLR azimuth range SRTM/X-SAR 54 deg SRTM DLR 59
54 Active Radar Remote Sensing Parameters measured by SAR 61
55 Active Radar Remote Sensing Parameters measured by SAR 1. Amplitude 62
56 Parameters Influencing Radar Brightness Sensor Parameters wavelength (e.g. penetration through canopy) polarization look angle resolution (texture) Scene Parameters surface roughness (e.g. Bragg scattering at ocean surfaces) local slope and orientation geomorphology scatterer density, e.g. biomass, leaf density 3-D distribution of scatterers and scattering mechanism, e.g. surface, volume, or double bounce (canopy, trunks, buildings) dielectric constant e scattering material soil moisture vegetation status 63
57 Overview Introduction Methods Sensors Applications Copyright DLR-HR Backscattering Coefficient o Levels of Radar backscatter Very high backscatter (above -5 db) High backscatter (-10 db to 0 db) Moderate backscatter (-20 to -10 db) Low backscatter (below -20 db) Typical scenario Man-Made objects (urban) Terrain Slopes towards radar very rough surface radar looking very steep rough surface dense vegetation (forest) medium level of vegetation agricultural crops moderately rough surfaces smooth surface calm water road very dry soil (sand) SAR-EDU> Module 2300: SAR Polarimetry >
58 Calibration of SAR Systems Instrument parameters to be calibrated: transmit power receiver gain elevation antenna pattern (satellite roll angle) Calibration objects: corner reflectors active radar calibrators (ARCs) rain forest 65
59 Corner Reflectors for SAR End-to-End Calibration L radar cross section of a trihedral corner reflector: 4 4 L 2 3 m 2 DLR L DLR 66
60 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Interaction with the object Radar bands and transmission of Radar through the atmosphere (WICKS 2006:o.S.). TerraSAR-X ENVISAT, RADARSAT, ERS1&2 FSU JENA SAR-EDU>SAR Remote Sensing>An Introduction> ALOS, JERS1 67
61 Synthetic Aperture Radar - SAR active independent of sun illumination microwave penetrates clouds and (partially) canopy, soil, snow wavelengths: X-band: 3 cm C-band: 6 cm L-band: 23 cm coherent interferometry, speckle polarization can be exploited spatial resolution: space-borne: 0.5 m m (TerraSAR-X: 1 m) air-borne: > 0.2 m 68
62 Penetration of Microwaves X C L vegetation dry soil glacier ice X-Band λ=3 cm C-Band λ=6 cm L-Band λ=23 cm Fig. 30: DLR 69
63 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Impact of SAR Frequency L-band X-band FSU JENA
64 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Interaction with the object Wave Theory and Polarization (David P. Lusch, 1999). SAR-EDU>Basics>SAR FSU JENA Remote Sensing>An Introduction 71
65 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Use of polarized waves Polarisation (Jensen, 2000). FSU JENA
66 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Use of polarized waves Sender H Receiver H V V RGB-Composite H V FSU JENA
67 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Examples of satellite based radar sensors ERS-1, 2 JERS-1 Radarsat 1, 2 ALOS (PALSAR) Envisat (ASAR) TerraSAR-X FSU JENA
68 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Examples of satellite based radar sensors Sentinel-1A (launch: April 2014) FSU JENA
69 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing A brief history of Missions FSU JENA SAR-EDU>SAR Remote Sensing>An Introduction>
70 Current and Future Civil Spaceborne SARs satellite owner band resolution look angle swath lifetime ERS-1 ESA C 25 m km ERS-2 ESA C 25 m km Radarsat-1 Canada C 10 m m km ENVISAT ESA C 25 m - 1 km km ALOS Japan L 10 m -100 m km Cosmo Italy X ca. 1 m - 16 m TerraSAR-X Germany X 1 m - 16 m km 2007/2010- & TanDEM-X Radarsat-2 Canada C 3 m m km ALOS-2 Japan L 3 m 100 m km Sentinel-1A ESA C 5 m 50 m km
71 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages all weather capability (small sensitivity of clouds, light rain) day and night operation (independence of sun illumination, active instruments, they have their own source of energy) no effects of atmospheric constituents (multitemporal analysis) sensitivity to dielectric properties (water content, biomass, ice) sensitivity to surface roughness (ocean wind speed) accurate measurements of distance (interferometry) sensitivity to man made objects sensitivity to target structure (use of polarimetry) subsurface penetration (the longer the wavelength, the higher the transmission through a medium) SAR-EDU>SAR Remote Sensing>An Introduction>
72 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 SAR-EDU>SAR Remote Sensing>An Introduction>
73 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Active Radar Remote Sensing Advantages / Example all weather SAR-EDU>SAR Remote Sensing>An Introduction> TS-X, Brazil 80
74 DLR-HR Speckle Noise Salt and Pepper 81
75 DLR-HR Speckle Noise Salt and Pepper 82
76 Active Radar Remote Sensing Parameters measured by SAR 1. Amplitude 83
77 Active Radar Remote Sensing Parameters measured by SAR 1. Amplitude 2. Phase [0, 2 ] 0 bzw. 2 0 bzw. 2 0,5 84
78 Sensor Sensor Copyright Active Radar Remote Sensing Phase depends on: 1. Distance between sensor und target target target 85
79 Sensor Sensor Copyright Active Radar Remote Sensing Phase depends on: 2. Characteristics of target target target 86
80 DLR-HR Speckle Noise 87
81 Speckle Noise u Q r i u I Fig. 28: DLR scatt arg A e i 4 j r i ERS ESA Random positive and negative interference of wave contributions from the many individual scatterers within one resolution cell varying brightness from pixel to pixel even for constant σ 0 granular appearance even of homogenous surfaces 88
82 Example for Bayesian Speckle Reduction original SAR image SAR data AeroSensing GmbH AeroSensing GmbH AeroSensing GmbH speckle filtered Bayesian algorithm 89
83 Speckle Reduction by Temporal Multilooking (ERS) +10dB ESA ESA/DLR -10dB 5 spatial looks 20 x 20 m ground resolution 2 db radiometric resolution 320 spatio-temporal looks 20 x 20 m ground resolution 0.3 db radiometric resolution 90
84 Applications - Examples ca. 10 x 3 km E-SAR (L-HH, L-HV, X-VV), Zeulenroda, Germany 93
85 Applications - Examples Classification of Land Cover 94
86 Applications - Examples Detection of Change ASAR APP (HH, HV, HV/HH), Siberia 2006 Landsat (4, 5, 3), Siberia
87 Applications - Examples Rapid situation analysis 96
88 Tab 1 Tab 2 Tab 3 Tab 4 Tab 5 Summary Applications of radar remote sensing systems SAR s ability to pass relatively unaffected through clouds, illuminate the Earth s surface with its own signals, and precisely measure distances makes it especially useful for the following applications: Sea ice monitoring Cartography Surface deformation detection Glacier monitoring Crop production forecasting Forest cover mapping Ocean wave spectra Urban planning Coastal surveillance (erosion) Monitoring disasters such as forest fires, floods, volcanic eruptions, and oil spills etc. SAR-EDU>SAR Remote Sensing>An Introduction>
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