1. Introduction to Digital Data and Imagery
Data Models, Pixels, and Satellite Bands

3. Learning Objectives
Understand the differences between raster and vector data.
What are digital numbers (DNs) and what do they represent in remotely sensed data?
What are satellite bands?
Be able to define spatial and spectral resolution.
What are some advantages and disadvantages of high spatial resolution?
What are some advantages and disadvantages of high spectral resolution?

4. Data Models: Raster vs. Vector Data
Raster Data
Images are grids of cells or “pixels”
Each pixel is represented by number called the digital number (DN)
A pixel represents an area on the ground
Vector Data
Points, lines, and areas
Defined by x,y coordinates and info about “connectedness”
Attributes can describe the features they represent

5. Vector Features Point Raster Grid w/ DNs Line or Arc Area or Polygon
100 10
250
122 35 75
255 5 90 92
112 12 11 2 3
200 78 20 93
187
202 87
140
144 52 68 89 23 76 56 62
178
142 24 53 1 57 63
242
137 36 25
Vector Features
Point
Raster Grid w/ DNs
Line or Arc
Area or Polygon

6. Data Model
Imaginary matrix (row & column format) is placed on the feature (e.g., the ground)
Some phenomenon (e.g. amount of light) is measured
A value (digital number) representing the amount of light is assigned to each grid cell (pixel).

7. Somewhere on earth

8. Raster grid is placed

9. Raster data 32 47 67 93 11
105 79 35 23 56 43 89 21
213
245
201
179
136
155 55
203
163 63
211
189
145
109
122
202

10. Real world >>> Raster value
For remote sensing, the total amount of EMR from the area of a pixel on the ground is recorded as a digital number (DN).
Depending on the intensity of the EMR, a numeric value is assigned to each pixel
Low or None - Lowest value (dark)
High - Maximum value (bright)
Others - Scaled in between (gray)

11. Digital Image Data
Digital images are matrices of digital numbers (DNs).
Satellite bands capture light from different wavelength regions.
There is one layer (or matrix) for each satellite band.
Each band covers the same area on the ground
Each DN corresponds to one pixel in one band
If there are 6 bands each pixel will be described by 6 DNs, one for each band
The DNs control how a computer displays an image on your computer screen

13. Images are presented as 2-d grids
Images are presented as 2-d grids. Each pixel (one square) has a location (x,y).
Position of pixel (x,y) often describe in terms of rows and columns but can be translated (projected) into other coordinate systems (e.g., latitude/longitude, UTM, etc.)
F(2,3)
F(4,1)

14. What are digital numbers (DNs)?
DNs are relative measures of radiance
DNs are NOT reflectance
DNs can be converted to ground reflectance if you know atmospheric properties, etc.
The range of DNs depends on the radiometric resolution of the recording instrument
A common range of DNs is 0 – 255.

15. Resolution

17. Types of Resolution
Spatial
Spectral
Radiometric
Temporal

18. Spatial Resolution The dimension of one side of a single pixel
The extent of the smallest object on the ground that can be distinguished in the imagery
Determined by the Instantaneous Field of View of satellite instruments (IFOV)
Determined by altitude, camera (lens), and film characteristics for air photos.

19. Spatial Resolution

20. Raster grid size
finer
Coarser

21. Available Resolution Satellites: ~ .61 m to > 1 km
Air photos ~ <0.6 m to large.

22. Satellite data resolution
MODIS: m
Landsat MSS: 80 m
Landsat TM5, 7, 8: 30 m
SPOT: 20 m
ASTER: 15 m
IRS Pan: 5 m
Worldview 3 Pan: 31 cm (!!)

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

24. MODIS
500 m spatial resolution

25. So…what about in the movies?
Zoom and Enhance! (YouTube)
Group discussion: Can you extract (zoom and enhance!) information from an image when the information is in an area smaller than a pixel?
The Truth!

26. Spectral Resolution
How finely an instrument “divides up” the range of wavelengths in the electromagnetic spectrum
How many spectral “bands” an instrument records
Landsat 8 bands (in red) overlaid on plant spectral reflectance.

27. Case 1 Measure the EMR across a wide range
E.g., the visible portion of EMR
Assign a single DN for sum of all visible light energy hitting the sensor
Analogous to black and white (panchromatic) film
Called a panchromatic band

28. Case 1
blue
green
red
0.4
0.7
0.6
0.5 UV
Near-infrared

29. Case 2 Measure EMR across narrower ranges
E.g., Blue, green and red bands
Assign a DN for each of these wavelength ranges to create 3 bands

30. Case 2
blue
green
red
0.4
0.7
0.6
0.5 UV
Near-infrared

31. Coarser (lower) Spectral Resolution
RGB
Finer (higher) Spectral Resolution
Red
Green
Blue

32. High Spectral Resolution
Reflectance
Wavelength (nm)
Low Spectral Resolution
Reflectance
Wavelength (nm)

33. Spectral Resolution

34. Summary
Remotely sensed imagery are RASTER data composed of grids of pixels organized in bands (layers)
Size of pixels is called spatial resolution of sensor
Number of bands is called spectral resolution of sensor
Digital numbers are associated with pixels and tell you relatively how much light came from that area on the ground to the satellite sensor.