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Optical Spectrum Earth Resource Satellites in Remote Sensing and Their Applications

This chapter explores the pivotal role of Earth resource satellites operating in the optical spectrum, detailing their evolution and significance in remote sensing. It begins with an overview of remote sensing and space exploration applications across various disciplines, highlighting advancements in satellite and sensor technologies. The chapter outlines the history of space imaging technologies, focusing on pivotal missions like Landsat and the NOAA series. It also discusses Landsat's orbit characteristics, sensor capabilities, and data distribution, providing a comprehensive understanding of these essential tools for observing Earth.

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Optical Spectrum Earth Resource Satellites in Remote Sensing and Their Applications

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  1. Chapter 6 Earth resource satellites operating in the optical spectrum Introduction to Remote Sensing Instructor: Dr. Cheng-Chien Liu Department of Earth Sciences National Cheng-Kung University Last updated: 28May 2003

  2. 6.1 Introduction • Remote sensing + space exploration (RS+SE) interest and application over a wider range of disciplines • Current application • New technology  new or improved satellite/sensor  new application • The most important outcome of RS+SE  observing earth  earth system

  3. 6.1 Introduction (cont.) • This chapter  optical range  0.3 m m~14 m m • Landsat • Spot • NOAA series

  4. 6.2 Early history of space imaging • Ludwig Bahrmann (1891): New or improved apparatus for obtaining Bird’s eye photographic views • Alfred Maul (1907): gyrostabilization • Alfred Maul (1912): 41kg, 200mm x 250 mm, 790m • 1946~1950: V2 rockets • 1960~ : TIROS-1, early weather satellite • Not just look at but also look through

  5. 6.2 Early history of space imaging (cont.) • 1960s: Mercury, Gemini, Apollo • Alan Shepard, 1961, 70 mm, 150 photos • John Glenn, 1962, 35 mm, 48 photos. • Later Mercury missions: 70 mm, 80 mm • Gemini GT-4 mission: formal experiment directed at geology • Tectonics, volcanology, geomophology. • 1:2,400 1100 photos • Apollo 9: 4 camera array, electrically triggered. 140 sets of imagery

  6. 6.2 Early history of space imaging (cont.) • Skylab 1973 • Earth Resources Experiment Package (EREP) • 6-camera multi-spectral array • A long focal length “earth terrain” camera • A 13-channel multispectral scanner • A pointable spectroradiometer • Two microwave systems. • 35,000 images • U.S.-USSR Apollo-Soyuz Test Project (ASTP)

  7. 6.3 Landsat satellite program overview • Earth Resources Technology Satellite (ERTS) 1967 • ERTS-1, 1972~1978 • Nimbus weather satellite  modified • Experimental system  test feasibility • Open skies principle • Landsat-2, 1975 (ERTS-2)

  8. 6.3 Landsat satellite program overview (cont.) • Table 6.1: Characteristics of Landsat 1~6 • Return Beam Vidicon (RBV) camera systems • Multispectral Scanner system (MSS) • Thematic Mapper (TM) • Enhanced Thematic Mapper (ETM) • Table 6.2: Sensors used on Landsat 1~6 missions

  9. 6.4 Orbit characteristic of Landsat-1, -2, and –3 • Fig 6.1: Landsat –1, -2, and –3 observatory configuration • 3m x 1.5m, 4m width of solar panels, 815 kg, 900 km • Inclination = 90 • To= 103 min/orbit • Fig 6.2: Typical Landsat-1, -2 and –3 daily orbit pattern • Successive orbits are about 2760km • Swath: 185km • Orbital procession  18 days for coverage repetition 20 times of global coverage per year

  10. 6.4 Orbit characteristic of Landsat-1, -2, and –3 (cont.) • Sun-synchronous orbit • 9:42 am  early morning skies are generally clearer than later in the day • Pros: repeatable sun illumination conditions on the same day in every year • Cons: variable sun illumination conditions with different locations and seasons  variations in atmospheric conditions

  11. 6.5 Sensors onboard Landsat-1, -2 and –3 • 3-Channel RBV • 185km x 185 km • Ground resolution: 80m • Spectral bands: 1: 0.475 mm~0.575 mm (green) 2:0.580 mm~0.680 mm (red) 3: 0.690 mm~0.830 mm (NIR) • Expose  photosensitive surface  scan  video signal • Pros: • Greater cartographic fidelity • Reseau grid  geometric correction in the recording process

  12. 6.5 Sensors onboard Landsat-1, -2 and –3 (cont.) • 3-Channel RBV (cont.) • Landsat-1: malfunction  only 1690 scenes • Landsat-2  only for engineering evaluation  only occasionally RBV imagery was obtained. • Landsat-3 • Single broad band (0.505~0.75 u mm) • 2.6 times of resolution improved: 30m  double f • Two-camera side-by-side configuration with side-lap and end-lap. (Fig 6.4) • Fig 6.5: Landsat-3 RBV image

  13. 6.5 Sensors onboard Landsat-1, -2 and –3 (cont.) • 4 Channel MSS • 185km x 185km • Ground resolution: 79m • Spectral band: • Band 4: 0.5 mm ~ 0.6 mm (green) • Band 5: 0.6 mm ~ 0.7 mm (red) • Band 6: 0.7 mm ~ 0.8 mm (NIR) • Band 7: 0.8 mm ~ 0.9 mm (NIR) • Band 8: 10.4~12.6 um  Landsat-3, failed • Band 4~7  band 1~4 in Landsat-4, -5 • Fig 6.6: Comparison of spectral bands

  14. 6.5 Sensors onboard Landsat-1, -2 and –3 (cont.) • 4 Channel MSS (cont.) • Fig 6.7: Landsat MSS operating configuration • Small TFOV  use an oscillating scan mirror • A-to-D converter (6 bits) • Pixel width: 56m x 79m set by the pixel sampling rate (Fig 6.8) • Each Landsat MSS scene  185km x 185km • 2340 scan lines, 3240 pixels per line, 4 bands • Enormous data • Fig 6.9: Full-frame, band 5, Landsat MSS scene • Parallelogram  earth’s rotation • 15 steps • Tick marks  Lat. Long. • Annotation block • Color composite: band 4 (b), band 5 (g), band 7(r)(Fig 6.6)

  15. 6.5 Sensors onboard Landsat-1, -2 and –3 (cont.) • Data distribution • Experiment  transitional  operational • NASA NOAA NASA USGS EOSAT USGS Landsat-1,-2,-3 Landsat-4,-5,-6 Landsat-7 Department of Interior Department of Commerce Department of Defense • Data receiving station • Data reprocessing • Data catalogue

  16. 6.6 Landsat MSS image interpretation • Applications: • agriculture, botany cartography, civil engineering, environmental monitoring, forestry, geography, geology, geophysics, land resources analysis, land use planning, oceanography, water resource analysis • Comparison of Landsat & airborne image • Table 6.4 • Resolution • Coverage • Complementary not replacement • 2-D, non-stereo mode

  17. 6.6 Landsat MSS image interpretation (cont.) • Characteristics of MSS image • Effective resolution  79m, (30m for Landsat-3) but linear feature with sharp contrast can be seen • 1-D displacement relief (in E-W direction) • Limited area can be viewed in stereo  study topographic • High altitude + low TFOV  little RD  planimeter map • E.g. World Bank, USGS. DMA, petroleum company

  18. 6.6 Landsat MSS image interpretation (cont.) • Characteristics of MSS image (cont.) • Band 5 (red)  better atmospheric penetration  detecting cultural features • Band 4 (green)  deep, clear water penetration • Band 6, 7  lineating water bodies (dark) • The largest single use of Landsat MSS data  geologic studies  band 5.7

  19. 6.6 Landsat MSS image interpretation (cont.) • Fig 6.10 : four Landsat MSS bands • Extent of the urban area (B4, 5, light) • Major road (B4, 5 light, not B6, B7 dark) • Airport • Asphalt-surfaced runways • Four major lakes and connected river (B6, 7 dark) • mid-July  algae  green  B4: similar to the surrounding agricultural land • Agricultural field. (B5, 6, 7) • Forest (B4, 5 dark)  winter images are preferred

  20. 6.6 Landsat MSS image interpretation (cont.) • Fig 6.11: Landsat MSS band 5 • December image • 20 cm snow covered  all water bodies are frozen • Snow covered upland and valley floors  light tone • Steep, tree-covered valley sides  dark tone • September image • Identify forest area

  21. 6.6 Landsat MSS image interpretation (cont.) • A hit-or-miss proposition • Some events leave lingering trace • Fig 6.12: Landsat MSS band 7 • July image  200 m3/sec • March image  1300 m3/sec  once every four years • Fig 6.13: Mississippi River Delta • Silt flow but vague boundary  band 5 • Delineation of the boundary  band 7 • Fig 6.14: short-lived phenomena • Active forest fire in Alaska • Volcanic eruption on Kunashir Island

  22. 6.6 Landsat MSS image interpretation (cont.) • A hit-or-miss proposition (cont.) • Fig 6.15: Extensive geologic features visible on MSS • San Andreas fault, Six solid dots  earthquake > 6.0 • Fig 6.16: Landsat MSS band 6 • 66-km-wide Manicouagan ring  212-million-year-old meteorite impact crater • Fig 6.17: Landsat MSS images of Mt. St. Helens before and after its 1980 eruptions • Fig 6.18: Landsat MSS image of Maritoba, Canada, showing tornado and hail scar • Fig 6.19: Landsat MSS image of East kalimantan, Indonesia, showing tropical deforestation

  23. 6.7 Orbit characteristics of Landsat-4 and -5 • Fig 6.20: Sun-synchronous orbit of Landsat-4 and –5 • Altitude: 900  705km • Retrievable by the space shuttle • Ground resolutions • Inclination 98.20 T=99min  14.5 orbit/day • 9:45 am • Fig 6.21: adjacent orbit space = 2752km • 16-day repeat cycle • 8-day phase between Landsat-4 and –5 (Fig 6.22)

  24. 6.8 Sensors onboard Landsat-4 and -5 • Fig 6.23: Landsat-4 and –5 observatory configuration • MSS, TM • 2000 kg, 1.5x2.3m solar panels x 4 on one side • High gain antenna  Tracking and Data Relay Satellite system (TDRSS) • Direct transmission  X-band and S-band • MSS: 15 Mbps • TM: 85 Mbps

  25. 6.8 Sensors onboard Landsat-4 and –5 (cont.) • MSS • Same as previous except for larger TFOV for keeping the same ground resolution (79m  82m) • Renumber bands • TM • 7 bands (Table 6.4) • DN: 6  8 bits • Ground resolution: 30m (thermal band: 120m) • Geometric correction  Space Oblique Mercator (SOM) cartographic projection

  26. 6.8 Sensors onboard Landsat-4 and –5 (cont.) • TM (cont.) • Bi-directional scan  the rate of oscillation of mirror dwelling time  geometric integrity signal-to-noise • Detector: • MSS: 6x4=24 • TM: 16x6+4x1=100 • Fig 6.24: Thematic Mapper optical path and projection of IFOV on earth surface • Fig 6.25: Schematic of TM scan line correction process

  27. 6.9 Landsat TM Image interpretation • Pros: • Spectral and radiometric resolution • Ground resolution • Fig 6.26: MSS vs TM • Fig 6.27: All seven TM bands for a summertime image of an urban fringe area • Lake, river, ponds: b1,2 > b3 > b4=b5=b7=0 • Road urban streets: b4  min • Agricultural crops: b4  max • Golf courses

  28. 6.9 Landsat TM Image interpretation (cont.) • Fig 6.27 (cont.) • Glacial ice movement: upper right  lower left • Drumlins, scoured bedrock hills • Band 7  resample from 120m to 30m • Plate 12 + Table 6.5: TM band color combinations • (a): normal color  mapping of water sediment patterns • (b): color infrared  mapping urban features and vegetation types • (c)(d): false color

  29. 6.9 Landsat TM Image interpretation (cont.) • Fig 6.28: Landsat TM band 6 (thermal infrared) image • Correlation with field observations  6 gray levels  6T • Plate 13: color-composite Landsat TM image • Extremely hot  blackbody radiation  thermal infrared • TM bands 3, 4 and 7

  30. 6.9 Landsat TM Image interpretation (cont.) • Fig 6.29: Landsat TM band 5 (mid-infrared) image • Timber clear-cutting • Fig 6.30: Landsat TM band 3, 4 and 5 composite • Extensive deforestation. • Fig 6.31: Landsat TM band 4 image map • 13 individual TM scenes + mosaic

  31. 6.10 Landsat-6 planned mission • A failed mission • Enhanced Thematic Mapper (ETM) • TM+ panchromatic band (0.5~0.9 mm) with 15m resolution. • Set 9-bit A-to-D converter to a high or low gain 8-bit setting from the ground. • Low reflectance  water  high gain • Bright region  deserts  low gain

  32. 6.11 Landsat ETM image simulation • Fig 6.32: Landsat ETM images

  33. 6.12 Landsat-7 • Launch: 1999 • Web site: http://landsat.gsfc.nasa.gov • Landsat 7 handbook • Landsat 7 in orbit • Depiction of Landsat 7

  34. 6.12 Landsat-7 (cont.) • Landsat 7 Orbit • Orbital paths • Swath • Swath pattern • Landsat data • http://landsat.gsfc.nasa.gov/main/data.html

  35. 6.12 Landsat-7 (cont.) • Payload • Enhanced Thematic Mapper Plus (ETM+) • Dual mode solar calibrator • Data transmission • TDRSS or stored on board. • GPS  subsequent geometric processing of the data • High Resolution Multi-spectral Stereo Imager (HRMSI) • 5m panchromatic band • 10m ETM bands 1~4 • Pointable  revisit time (<3 days) Stereo imaging. • 00~380 cross-track and 00~300 along-track

  36. 6.12 Landsat-7 (cont.) • Application • Monitoring Temperate Forests • Mapping Volcanic Surface Deposits • Three Dimensional Land Surface Simulations

  37. 6.13 SPOT Satellite Program • Background • French+Sweden+Belgium • 1978 • Commercially oriented program • SPOT-1 • French Guiana, Ariane Rocket • 1986 • Linear array sensor+pushbroom scanning+pointable • Full-scene stereoscopic imaging

  38. 6.13 SPOT Satellite Program (cont.) • SPOT-2 • 1990 • SPOT-3 • 1993

  39. 6.14 Orbit characteristics of SPOT-1, -2 and -3 • Orbit • Circular, near-polar, sun-synchronous orbit • Altitude: 832km • Inclination: 98.70 • Descend across the equator at 10:30AM • Repeat: 26 days • Fig 6.33: SPOT revisit pattern at latitude 450 and 00 • At equator: 7 viewing opportunities exist • At 450: 11 viewing opportunities exist

  40. 6.15 Sensors onboard SPOT-1, -2 and -3 • Configuration (Fig 6.34) • 223.5m, 1750 kg, solar panel: 15.6m • Modular design • High Resolution Visible (HRV) imaging system • 2-mode • 10m-resolution panchromatic mode (0.51~0.73mm) • 20m-resolution color-infrared mode. (0.5~0.59mm, 0.61~0.68mm, 0.79~0.89mm)

  41. 6.15 Sensors onboard SPOT-1, -2 and –3 (cont.) • HRV (cont.) • Pushbroom scanning • No moving part (mirror)  lifespan • Dwell time  • Geometric error  • 4-CCD subarray • 6000-element subarray  panchromatic mode, 10m • Three 3000-element subarrays  multi-spectral mode, 20m • 8-bit, 25 Mbps • Twin-HRV instruments • IFOV (for each instrument)  4.130 • Swath: 60km  2 - 3km = 117km (Fig 3.36) • TFOV (for each instrument)  270=0.6045 (Fig 3.35)

  42. 6.15 Sensors onboard SPOT-1, -2 and –3 (cont.) • HRV (cont.) • Data streams • Although 2-mode can be operated simultaneously, only one mode data can be transmitted  limitation of data stream • Stereoscopic imaging • Off-nadir viewing capability (Fig 6.37) • Frequency  revisit schedule (Fig 6.33) • Base-height ratio  latitude • 0.75 at equator, 0.5 at 450 • Control • Ground control station  Toulouse, France  observation sequence • Receiving station  Tordouse or Kiruna, Sweden • Tape recorded onboard • Transmitted within 2600km-radius around the station

  43. 6.16 SPOT HRV image interpretation • Fig 6.38: SPOT-1 panchromatic image • 10m-resolution • Cf: Landsat MSS 80m • Cf: Landsat TM 30m (Fig 6.26) • Cf: Landsat ETM 15m (Fig 6.32) • Fig 6.39: SPOT-1 panchromatic image • Plate14: merge of multispectral & panchromatic data • Fig 6.40: SPOT-1 panchromatic image stereopair • Plate 15: Perspective view of Alps • SPOT stereopair + parallax calculation • Plate 23 • Fig 6.41: before and after the earthquake

  44. 6.17 SPOT –4 and –5 • SPOT –4 • Launched 1998 • Vegetation Monitoring Instrument (VMI) • Swath: 2000km daily global coverage • Resolution: 1km • Spectral band: b(0.43~0.47mm), g(0.5~0.59mm), r(0.61~0.68mm), N-IR(0.79~0.89mm), mid-IR(1.58~1.75mm)

  45. 6.17 SPOT –4 and –5 (cont.) • SPOT – 5 • Launched 2002 • Vegetation Monitoring Instrument (VMI) • Swath: 2000km daily global coverage • Resolution: 1km • Spectral band: b(0.43~0.47mm), g(0.5~0.59mm), r(0.61~0.68mm), N-IR(0.79~0.89mm), mid-IR(1.58~1.75mm)

  46. 6.18 Meteorological Satellite • Metsats • Coarse spatial resolution  land-oriented system • Very high temporal resolution of global coverage • NOAA satellites  sun-synchronous • GOES  geostationary  36,000km altitude • DMSP

  47. 6.18 Meteorological Satellite (cont.) • NOAA satellites • Advanced Very High Resolution Radiometer (AVHRR) • NOAA –6 ~ -12. (N-S) • Even: 7:30AM crossing time • Odd: 2:30 AM crossing time • Table 6.6: characteristics of NOAA-6 ~ -12 • Fig 6.42: Example coverage of the NOAA AVHRR • Ground resolution: 1.1km at nadir • AVHRR data • LAC • GAC • Fig 6.43: Comparison of Spectral sensitivity

  48. 6.18 Meteorological Satellite (cont.) • NOAA satellites (cont.) • Fig 6.44: AVHRR images • A: distortion  wide angle of view • B: geometric correction • Plate 16: NOAA AVHRR band 4 thermal image of the Great Lakes • Fig 6.45: AVHRR images of the Mississippi Delta • (a): present and past channels, future  Atchafalaya • (b): Channel–1 (red), silky material  visible • (c): Channel–2 (Near-IR), light tone  higher & drier • (d): Channel–4 (thermal –IR) light tone  cooler • Plumes of cooler river water

  49. 6.18 Meteorological Satellite (cont.) • NOAA satellites (cont.) • Plate 17: springtime NOAA-8 AVHRR color composite • Applications of AVHRR in monitoring vegetation • Use Ch-1 (0.58~0.68 mm) and Ch-2 (0.73~1.10 mm) • A simple vegetation index VI=Ch2-Ch1 • Normalized difference vegetation index NDVI = (Ch2-Ch1)/(Ch2+Ch1) • Vegetated areas  large VI Clouds, water, snow  negative VI Rock, Bare soil  VI  0 • For global vegetation  NDVI preferred  compensate the charging illumination conditions • Plate 18: color-coded NDVI • Select the highest NDVI during that period

  50. 6.18 Meteorological Satellite (cont.) • NOAA satellites (cont.) • Applications of AVHRR in monitoring vegetation (cont.) • Applications: vegetation seasonal dynamics at global and continental scale, tropical forest clearance, leaf area index measurement, biomass estimation, percentage ground cover determination, photosynthetically active radiation estimation • Other factors that might influence NDVI • Incident solar radiation • Radiometric response of the sensor • Atmospheric effect and viewing angle  need further research

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