1. Introduction to Remote Sensing
Cons 340

2. Lab Review Connect to a folder
Make sure your default geodatabase is the one you are working on
Save your map document in your workspace (where your geodatabase lives)

3. Project management Be organized
Lots of data from lots of sources – it’s easy to get lost
Develop good habits early on
Verify the validity of your data
Read metadata first
Check GCS and projection
Use a consistent file/directory naming convention

4. The Basics
An “image” is digital as opposed to a “picture” which you take with a camera
Images are made up of Pixels which is short for Picture Elements
Pixels contain values (numbers)
The more Pixels etc. the larger the image file size

5. File Structure Common file formats:
JPEG Joint Photographic Experts Group
TIFF Tag Image File Format
GIF Graphics Interchange Format
BMP Bitmap File
PICT Macintosh Picture File
TGA Targa Image File
Graphics files typically have a header (file format info) and then a table of numbers that represent pixel values as seen on the right

6. Pixels and Color Depth
Each pixel has numerous values associated with it
The # of bits in a value defines the color depth of the image
1 bit = 2 colors
8 bits = 256 colors
16 bits = 65k colors (hi-color)
24 bit = 16 million colors (true-color)
As color depth increases the space required for the image’s storage increases as well

7. Color Spaces RGB (Red-Green-Blue; Additive)
CMY (Cyan-Magenta-Yellow; Subtractive)
CMYK (Cyan-Magenta-Yellow-Black)
HSV (Hue-Saturation-Value)
Grayscale (Shades of Gray)
1-bit (line art; only two colors i.e. Black and White)
Equivalent RGB, CMY, and HSV values

8. Additive vs. Subtractive

9. RGB (Red-Green-Blue) An RGB image is comprised of three layers
RGB is an additive color space, meaning that pixel values are added to black to create new colors

10. CMYK (Cyan-Magenta-Yellow-Black)
A CMYK image is comprised of four layers
CMYK is a subtractive color space, meaning that pixel values are subtracted from white to create new colors

11. Image Dimensions
Referred to as (Horizontal dimension by Vertical dimension)
(200 x 340) or (100 x 170)
Relates to the size of the image in bytes
200 x 300 = 200 Kb
100 x 170 = 50 Kb

12. Resolution (DPI) DPI = Dots per Inch
The greater the DPI per equivalent areas the greater the image’s file size
Average screen resolution is 72 DPI
Typical printer resolution is 300 DPI

13. Spatial Resolution
When an image refers to something in the “real world” we say it has Spatial Resolution
This refers to the unit of measure in the “real world” that a pixel represents in the image
e.g. 30 meter Digital Elevation Models (DEM)

14. Which brings us to Remote Sensing (and a selection of major RS programs)

15. Examples
This one-meter resolution satellite image of Manhattan, New York was collected at 11:43 a.m. EDT on Sept. 12, 2001 by Space Imaging's IKONOS satellite.
IKONOS travels 423 miles above the Earth's surface at a speed of 17,500 miles per hour.

16. Examples – Quickbird

17. Land surface from satellite
Four landsat-5 Thematic Mapper multispectral image mosaic displayed in 4,3,2-RGB (false color)
August 2nd and 27th, 1998, 10:15a.m. pst.
16 day repeat, 30m

18. Ocean Color
SeaWiFs classified ocean color image with unclassified land surface displayed 6,3,2-RGB
August 16th, 1999
Daily, 1km

19. Time series
One year of daily AVHRR at 1km of the Amazon Basin

20. A Remote Sensing System
Energy source
platform
sensor
data recording / transmission
ground receiving station
data processing
expert interpretation / data users

21. A Remote Sensing System

22. Energy

23. Basic Concepts: EM Spectrum
l 1 nm, 1mm, 1m
f 3x1017 Hz, 3x1011 Hz, 3x108 Hz,
Sometime use frequency, f = c / l,
where c = 3x108 m/s (speed of light)

24. You are a remote sensing platform!
And your eyes are the sensors

25. Spectral Signatures

26. Spectral Resolution

27. Platforms

28. Airborne Platforms
Aircraft are often used to collect very detailed images and facilitate the collection of data over virtually any portion of the Earth's surface at any time.
Aerial platforms are primarily stable wing aircraft, although helicopters are occasionally used.

29. Satellite Platforms
In space, remote sensing is sometimes conducted from the space shuttle or, more commonly, from satellites.
Because of their orbits, satellites permit repetitive coverage of the Earth's surface on a continuing basis.
Cost is often a significant factor in choosing among the various platform options.

30. Geostationary Orbit
geostationary ( km altitude)

31. Near-Polar Orbit
polar orbiting ( km altitude)

32. Sensors

33. Cameras versus digital sensors

34. The Business End of RS (and for that matter your Digital Camera or Camcorder)
MERIS (MEdium Resolution Image Spectrometer Instrument)
charge-coupled device (CCD)
Many of these put together in a grid is referred to as a CCD Array

35. Passive Sensor

36. Active Sensor

37. Radar real aperture radar microwave energy emitted across-track
return time measured
amount of energy (scattering)
synthetic aperture radar
higher resolution - extended antenna simulated by forward motion of platform
ERS-1, -2 SAR (AMI), Radarsat SAR, JERS SAR

38. Data

39. The “PIXEL”

40. Visualizing numbers

41. Band Combinations
3,2,1
4,3,2
5,4,3

42. Issues

43. Spatial data resolution problem
trade-off pixel size vs. spatial coverage
quantization and data volume
data merge from different sources
grid displacement in time
information content of different resolutions
raster-vector conversion

44. Multi-resolution merging 20m Multi-spectral + 10m PAN of SPOT

45. Geometric registration

46. Image
Processing

47. Simple IP Techniques
These techniques are accomplished by applying mathematical algorithms to individual pixel values
e.g. Brightness simply adds a constant value to each pixel

48. Convolution Filters
A matrix of multipliers that is applied to each pixel as it is moved across the image
They are typically moved from left to right as you would read a book

49. Examples of Convolution Filters at work
(a) Input image
(b) Laplacian of (a)
(c) sum of (a) and (b)
(d) Sobel gradient of (a) smoothed by a 5x5 box filter
(e) Product of (b) and (d)
(f) sum of (a) and (e)

50. Interpretation

51. Image Interpretation Interpretation: Data Information
Visual Interpretation : Uses visual methods to interpret Analog Data (maps)
Digital Interpretation : Uses computer-based methods to interpret digital data

52. Visual Interpretation
Shape
Size
Pattern
Tone
Texture
Shadows
Site
Association

53. Image Enhancement
Usually done to more effectively display or record the data for subsequent visual interpretation.
Contrast stretching
Filtering
Edge enhancement

54. Image Transformation
Arithmetic operations done to combine and transform the original bands into "new" images which better display or highlight certain features in the scene. e.g Normalized Difference Vegetation Index (NDVI)
These use multiple bands

55. NDVI Image

56. Image Classification
To categorize all pixels in an image into land cover classes or themes
Multi-spectral data are used to perform classification
Spectral patterns present within data used as numerical basis for categorization

57. Classification
                                                                                                                                                                                                                             
                                                                                                                                                                                                                             

58. Unsupervised Classification

59. Supervised Classification
In this type of classification the analyst “supervises” the classification by specifying inputs on various land cover classes to the computer
Analyst identifies representative ‘training areas’ for different categories
These training areas provide numerical spectral attributes of each land cover type.

60. Supervised Classification

61. Classified Product

62. Ground Truthing

63. Integrating Remotely Sensed Data with GIS
What GIS has to offer remote sensing:
- control points
- themes
- training sites
What remote sensing has to offer GIS:
- rapid updates
- change detection
- vegetation indices
What the future may hold:
- fully integrated systems
- transparent data integration

64. Image processing software and portability of formats
ARC/Info GRID various basic raster formats, tif, sun, gis, lan, img, bil, bip, bsq, grass, adrg, rlc
Arcview ERDAS lan, img, grid, tif
ERDAS IMAGINE Arc/info live link, no conversion needed
PCI EASI PACE Arc/Info GeoGateway for multiple formats
ENVI/IDL imports shapefiles, e00, dxf, USGS, SDTS, dlg,
exports ArcView grid, uses own vector format
ERMAPPER various raster formats, import of dxf and SeisWorks, uses own vector format
other packages: TNT, IDRISI, ILWIS...