1. Resolution Resolution

2. Landsat ETM+ image

4. Learning Objectives Be able to name and define the four types of data resolution. Be able to calculate the number of pixels in a given area. Understand the trade-offs between different types of resolution. Understand the relationship between SNR and resolution.

5. Understand binary data and the relationship between radiometric resolution and data storage space. Understand the differences between types of orbits. Learning Objectives (cont.)

6. What are the four types of resolution? SpatialSpectralRadiometricTemporal

7. Spatial Resolution Usually reported as the length of one side of a single pixel In analog imagery, the dimension (e.g. width) of the smallest object on the ground that can be distinguished in the imagery Determined by sensor characteristics (for digital imagery), film characteristics (for air photos), field of view, and altitude.

8. IFOV 1 pixel

9. Group Problem If you have a study area that covers 1 km 2, how many 30 m Landsat pixels does it take to cover it (nearest whole number)? If you have a study area that covers 1 km 2, how many 30 m Landsat pixels does it take to cover it (nearest whole number)? How many 15 m Landsat panchromatic pixels would it take to cover the same area? How many 15 m Landsat panchromatic pixels would it take to cover the same area?

10. Raster pixel size Higher resolution Lower resolution

11. Available Spatial Resolution for Land RS Satellites: ~ 0.3 m to1 km Air photos ~ centimeters to meters

12. Satellite data resolution MODIS: 250 - 1000 m Landsat MSS: 80 m Landsat 5, 7, 8: 30 m (15 m panchromatic) IRS MS: 22.5 m (5 m pan) SPOT: 20 m ASTER: 15m WorldView 3: 1.24 m (0.3 m pan!)

13. Quickbird (Digital Globe, Inc.) ~ 2.4 m spatial resolution in multispectral bands.

14. MODIS 500 m spatial resolution

15. Spatial Resolution Trade-offs Data volume Data volume Signal to Noise Ratio Signal to Noise Ratio “Salt and Pepper” “Salt and Pepper” Cost Cost

16. Spectral Resolution Can be described two ways, but they usually go hand in hand. How many spectral “bands” an instrument records How “wide” each band is (the range of wavelengths covered by a single band) How “wide” each band is (the range of wavelengths covered by a single band)

17. Spectral resolution Related to the measured range of EMR Wide range - coarser resolution Narrow range - finer resolution

18. Case 1 Measure the EMR across a wide range E.g., a single panchromatic band covering the entire visible portion of the spectrum Assigns a single DN representing all visible light energy hitting the sensor Analogous to black and white (panchromatic) film

19. bluegreenred 0.40.70.60.5 UVNear-infrared Case 1

20. From USGS Spectral Characteristics ViewerUSGS Spectral Characteristics Viewer

21. Case 2 Measure EMR across narrower ranges Measure EMR across narrower ranges E.g., Separate bands for blue, green and red parts of the spectrum E.g., Separate bands for blue, green and red parts of the spectrum Assign a DN for each of these wavelength ranges to create 3 bands Assign a DN for each of these wavelength ranges to create 3 bands

22. Case 2 bluegreenred 0.40.70.60.5 UVNear-infrared

23. Coarser (lower) Spectral Resolution Finer (higher) Spectral Resolution RGB RedGreenBlue

24. From USGS Spectral Characteristics ViewerUSGS Spectral Characteristics Viewer

25. High Spectral Resolution Low Spectral Resolution Wavelength (nm) Reflectance Spectral reflectance curve for green leaf using 224 bands (high spectral resolution) Spectral reflectance curve for green leaf using 6 bands (lower spectral resolution)

26. Could you distinguish Dolomite from Calcite using Landsat 8 spectral data?

27. Spectral Resolution Trade-Offs Data Volume and processing Data Volume and processing 1 DN for each pixel in EACH BAND Signal to Noise Ratio Signal to Noise Ratio Cost Cost

28. Problem (with partner) Problem (with partner) For your 1 km 2 study area, if you use 7 Landsat 8 bands, how many DNs will your computer have to store? For your 1 km 2 study area, if you use 7 Landsat 8 bands, how many DNs will your computer have to store?

29. Group Exercise (Groups of 4 - 5) Is higher spatial resolution better than lower spatial resolution? Yes/No with reason Yes/No with reason Is higher spectral resolution better than lower spectral resolution? Yes/No with reason Yes/No with reason

30. Radiometric Resolution How finely does the satellite divide up the How finely does the satellite divide up the radiance it receives in each band? radiance it receives in each band? How much light does it take to change How much light does it take to change the DN from one number to the next? the DN from one number to the next? Radiometric resolution is usually expressed as number of bits used to store the maximum possible DN value 8 bits = 2 8 = 256 levels (DNs 0 to 255) 8 bits = 2 8 = 256 levels (DNs 0 to 255) 16 bits = 2 16 = 65,536 levels (0 to 65,535) 16 bits = 2 16 = 65,536 levels (0 to 65,535)

31. 2 6 = 64 levels (6 bit) 2 2 = 4 levels (2 bit)

32. Radiometric resolution 1 bit ( 0 - 1) 8 bit ( 0 - 255 ) (older Landsats, many others) 16 bit ( 0 - 65,535 ) (Landsat 8) 32 bit ( 0 - 4,294,967,295 ) (uncommon) For an 8-bit satellite: DN = 0: No EMR or below some minimum amount of light (threshold) amount of light (threshold) DN = 255: Max EMR or above some maximum amount of light amount of light

33. Converting Base 10 to Binary Base 10Base 2 (Binary) 00 11 210 311 4100 5101 6110 7111 81000 25511111111 256100000000 257100000001 (etc.)

34. Radiometric resolution 8 bit data (e.g., Landsat 5) (256 values) Everything will be scaled from 0 – 255 Everything will be scaled from 0 – 255 Subtle details may not be represented Subtle details may not be represented 16 bit data (e.g., Landsat 8) (65,536 values) Wide range of choices Wide range of choices Required storage space will be twice that of 8 bit Required storage space will be twice that of 8 bit

35. Radiometric Radiation Trade Offs Data volume Data volume Every 8 bits takes 1 byte to store on Every 8 bits takes 1 byte to store on a computer. a computer. One 8-bit DN takes 1 byte One 9-bit DN takes 2 bytes One 16-bit DN takes 2 bytes One 17-bit DN takes 3 bytes Etc.

36. Calculating Image Size Computer hard drives store data in “boxes” called bytes (e.g., 1 Mb = 1 million bytes) 1 byte can hold 8 binary (base 2) digits (0s or 1s or some combination of 0s and 1s) Each “bit” is a single binary digit An 8-bit number is made of of 8 binary digits and fits into 1 byte. A 9-bit number won’t fit in 1 byte and requires 2 bytes.

37. Group Problem If your are using 7-band, 16-bit Landsat 8 data for your 1 km 2 area, how many bytes are needed to store your DNs on your computer? If your are using 7-band, 16-bit Landsat 8 data for your 1 km 2 area, how many bytes are needed to store your DNs on your computer?

38. Temporal resolution Time between two subsequent data Time between two subsequent data acquisitions for an area acquisitions for an area All of the Landsat satellites have a 16-day return time MODIS has a 1-2 day return time.

39. Return Time (Temporal Resolution) Depends on: Depends on: Orbital characteristics Orbital characteristics Swath width Swath width Ability to point the sensor Ability to point the sensor

40. Orbital Characteristics Geosynchronous Polar Sun synchronous

41. Geosynchronous Orbits Satellite orbits the earth at a rate that allows it to match the earth’s rotation—so the satellite is always over the same place Narrow range of altitudes—about 35,786 km above the equator. Useful for communications, weather etc. Example: GOES satellite (weather) Geosynchronous orbiting earth satellite Geosynchronous orbiting earth satellite

42. Polar/Sun Synchronous Orbits Pass roughly over the north and south Pass roughly over the north and south poles poles Fly over the same place on earth at the Fly over the same place on earth at the same time of day same time of day Examples: Landsat, AVHRR Examples: Landsat, AVHRR Good for land remote sensing Good for land remote sensing Return time related to spatial resolution, Return time related to spatial resolution, latitude, swath width, and orbital altitude latitude, swath width, and orbital altitude

43. Return Time Trade Offs Spatial resolution Spatial resolution Viewing geometry effects (off nadir) Viewing geometry effects (off nadir) Clouds and other atmospheric problems Clouds and other atmospheric problems Lack of archival repeat coverage for Lack of archival repeat coverage for pointable satellites pointable satellites

44. In summary, choosing a satellite is often an exercise in weighing the relative trade-offs of resolution against data needs (and budgets!). In summary, choosing a satellite is often an exercise in weighing the relative trade-offs of resolution against data needs (and budgets!).