Remote Sensing Exam 2 Study Guide Resolution Analog – to – digital • Instantaneous field of view (IFOV) – f ( cone angle of optical system ) – Everything in that area contributes to spectral response • “mixels” • Sampling rate – Determines horizontal resolution – # of sampling levels determines bits • Instantaneous field of view (IFOV) – f ( cone angle of optical system ) – Everything in that area contributes to spectral response • “mixels” – Dwell time – the time a sensor spends “looking” at any area • Analog-Digital conversion process – Photons strike detector, electrons flow proportional to the # photons • # photons related to reflectance characteristics, • λ (recall that shorter wavelengths carry more energy) • Area viewed (more photons come from a larger area (at any λ)) • Spectral region width (wider region = more photons) • Sampling rate – Determines horizontal resolution – # of sampling levels determines bit • Spatial resolution • Spectral resolution • Radiometric resolution • There are tradeoffs – If you increase the spatial resolution (i.e. smaller area of coverage), detector is receiving energy from a smaller area (less total energy received at detector at some λ) • So, the spectral range needs to be increased to receive enough energy (or design a better detector) – If you increase the spectral resolution (i.e. more bands each representing a smaller range of the EMS) detectors are receiving energy in a narrower range of the spectrum (less total energy received at the detector at some λ) • So, the DWELL time needs to be increased to compensate, resulting in lower spatial resolution (or design a better detector) • Coverage area (altitude and field of view) • Off-nadir capabilities (point sensor to side or front/aft)

Pushbroom System Advantages Fewer moving parts Less energy drain Less weight Longer dwell time Better geometric fidelity Disadvantages More sensors to calibrate Limited spectral range Orbital characteristics of satellites • Altitude • Period • Inclination • Equatorial crossing – Sun synchronous • Combination of orbital period and inclination that cause the satellite to cross the equator at the same time (keeps pace with the sun’s westward progress – Geostationary • Equatorial orbit of an altitude that results in an orbital period of 24 hours. • 36,000km Earth resources space imaging • ERTS-1 Earth Resources Technology Satellite – A feasibility test – First launched 7/23/1972 • But design began 1967 – Planned to launch six satellites • Pre-launch designated as ERTS A,B,C,D,E,F • Post-launch redesignated as ERTS 1,2,3,4,5,6 – “Open-sky” principle • All countries may evaluate – Just before ERTS-B launch, NASA renamed the program to LANDSAT • To differentiate it from a future program launch Seasat – ERTS1 renamed Landsat1 retroactively

Landsat 1,2, 3 • Similar characteristics – 185km swath width – Sun synchronous orbit • 9oinclination to equator • Successive orbits 2760km apart • 104 minutes orbital period • Crosses equator at 9:42AM local time – Takes advantage of normally better atm. cond early in day • Also provides same illumination conditions for comparing images • Large gaps between orbits on a given day (14/day) • 18 day temporal resolution – Overlap at equator 14%, at poles 84%

Return-beam Vidicon (RBV) system RBV sensed in 3 bands equivalent to CIR film G,R,IR Bands 1,2,3 Television camera-like Used a photosensitive surface with shutter, then scanned Instant image (like camera) better geometric fidelity Spatial resolution 80m Landsat 3 changed to improve spatial resolution (30m) also single band (0.5-0.75um) 2 cameras (side-side) MSS • G, R, NIR, NIR – .5.-6, .6-.7, .7-.8,.8-1.1um – Bands 4,5,6,7 • Landsat 3 and B8 10.4-12.6 – Failed • 6 contiguous lines scanned • IFOV = 79m • A-D on-board 0-63 (6-bit) – B4-6 rescaled to 0-127 (7-bit) • On ground • Sampling rate = 100000/s – Results in 56m horizontal spacing

Landsat 4,5 7 – 16 day orbital return period (i.e. the temporal resolution) – Altitude 705km – 185km swath width – Sun synchronous orbit • 98.2oinclination to equator • Crosses at 9:45Am • Successive orbits 2760km apart • 104 minutes orbital period • Also provides same illumination conditions for comparing images • Orbits (14.5/day) • Overlap at equator 14%, at poles 84% • 8 bit resolution – Except band 6 is 7 bit • 30m IFOV – Except band 6 is 120m on TM4,5…60m on TM7 – 15m Pan on TM7 • 16 detectors for all bands (4 for B6) totaling 100 detectors Note: Landsat 7 Added a pan Band 8’ 15m res0.4 to 0.9um

SPOT satellite • French satellite (Toulouse, France) • SPOT 1,2,3 • 26 day repeat period • 20 m res. MSS – 3 bands (G,R, NIR) • 10 m res. Pan • SPOT 4 – launched March 1998 • HRVIR – Includes Mid-IR band (20m) – Pan band replaced by red band • Vegetation instrument – 2250 km swath, 1 km IFOV, same bands as HRVIR but blue used instead of green • For oceanographic appllications • SPOT 5 - launched May 2002 • 5 m res. (pan HRGeometric) – May be resampled to 2.5 m • 10 m res G,R,NIR • 20 m res MIR (due to CCD limitations) • HRStereoscopic instrument – Fore-aft instruments for DEM generation – Global 10 m AVHRR – Advanced Very High Resolution Radiometer

EOS ESE Science Objectives • Provide the first state distribution of the main Earthatmosphere coupled parameters • Improve our ability to detect human impacts on climate, identify “fingerprints” of human activity on climate, and predict climate change • Provide observations that will improve forecasts of the timing and geographical extent of transient climatic anomalies • Improve seasonal and inter-annual predictions • Develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts. • Start long-term monitoring of the change in global climate and environmental change. EOS (ESE) AM-1 Mission Overview “Terra” and “Aqua” Launch date: December 1999 Terra May 2002 Aqua Orbit: 705 km altitude, polar Orbit period: 98.8 minutes Equator crossing: 10:30 AM descending Terra 1:30 PM Ascending Aqua Ground track repeat cycle: 16 days Terra Instruments: • Moderate Resolution Imaging Spectroradiometer (MODIS) • Advanced Spaceborne Thermal Emission Radiometer (ASTER) • Multi-angle Imaging Spectroradiometer (MISR) • Measurement of Pollution in the Troposphere (MOPITT) • Clouds and the Earth Radiant Energy System (CERES)

MODIS 12-bit radiometric Resolution for all Bands 2-day global coverage Excellent band-band Registration and Radiomertric accuracy

Aster • 3 unique instruments (has off-nadir capabilities) – Visible and Near Infrared (VNIR) • 3 bands on nadir (bands 1-3) – G, R, NIR • 1 band 27.5º rear-looking (NIR & same as B3 on nadir) – Capable of DEM generation • 15m res – Short Wave Infrared (SWIR) • 6 bands (bands 4-9) • 30m res – Thermal Infrared (TIR) • 5 bands (bands 10-14) • 90m res

DIGITAL IMAGE PROCESSING Image rectification & restoration • Correct distortions and degradations to imagery – Geometric distortions – Radiometric distortions – Sensor dependent – Together, called “preprocessing techniques” Image Enhancement • More effectively portray image data for visual interpretation • Many techniques – No set “best” way – Trial and error – Sometimes several enhancements to a single image are the best way

Image classification • Quantitative techniques for automating the identification of features in a scene – Multispectral data – Statistical based decision rules – Spectral pattern recognition – LULC mapping Data merging / GIS • Change detection • Merging with GIS (LULC) w/zoning, topo, etc • Multisensor merging • Multitemporal data merging • Hyperspectral image analysis – Dozens to hundreds of bands • Biophysical modeling – Crop yield, water depth, insect infestation, pollution, etc • Image compression Statistics • Mean • Standard Deviation • Histograms – Graphical distribution of values in single band

• Used for interpretation • And for enhancements

• Scatterplot & Ellipses – Used for interpretation of band-pairs Enhancements • Process of making an image more interpretable – Technique used f(dataset, desired result) • Must know characteristics of dataset • Have an objective – Ex. Sharpening a dataset to better delineate boundaries – Ex. Reducing the number of bands • May be permanent or on-screen only • Spectral enhancements – Deals with pixels in different bands • Spatial enhancements – Deals with surrounding pixels in a single band

• Derive a new value based on values in surrounding pixels – Moving window concept

Image enhancements • Contrast enhancements – Gray-level thresholding – Level slicing – Contrast stretching • Spatial feature manipulation – Filtering – Edge enhancement – Fourier analysis • Multi-image manipulation – Band ratioing – Principle components – IHS color space transforms – Vegetation components Contrast enhancements • A form of spectral enhancements • Increases the contrast in certain spectral ranges of the image – Likely at the expense of others – Goal – to make image more interpretable or features more identifiable – Application in one band may not be appropriate for others (each band handled separately)

Contrast Stretching • Linear contrast stretch – Simple • Sinusoidal stretch – Divides histogram into several user-defined parts

• Doesn’t eliminate detail in some parts of image • Histogram Equaliztion – LUT values assigned based on frequency of occurrence – Large regions of LUT reserved for common DN – Small regions of LUT reserved for infrequent DN – Concept based upon information yield

• Greatest information in most frequent pixels • Special stretches – Enhance whatever you’re interested in

• Water, veg, etc Contrast enhancements • Grey-level thresholding – Segment image into 2 classes – One above/below some user-defined value – Often used to prepare a binary mask • Level slicing – Divide histogram into segments – Each segment receives the same DN

• Each coded (colors) • Elevations, Thermal imagery

Destriping • “Sixth line striping” or … • Variations in calibration (sensitivity) of same sensor on different lines • Produces contrast variation parallel to scan • Fix – Averaging – Histogram Normalization • MUST be done prior to geometric correction