1 / 33

Introduction to Digital Data and Imagery

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

ranae
Download Presentation

Introduction to Digital Data and Imagery

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. 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,ycoordinates and info about “connectedness” • Attributes can describe the features they represent

  3. Vector Features Point Raster Grid w/ DNs Line or Arc Area or Polygon

  4. 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).

  5. Somewhere on earth

  6. Raster grid is placed

  7. 32 47 67 93 11 105 79 136 155 35 23 55 213 179 203 163 63 11 145 245 89 211 189 56 201 43 202 21 122 109 Raster data

  8. Real world >>> Raster value • For remote sensing, the average amount of EMR from the area of a pixel on the ground is recorded as a digital number (DN). • Depending on the average 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)

  9. Digital Image Data • Digital images are matrices of digital numbers (DNs). • 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 renders an image on your computer screen

  10. 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)

  11. 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.

  12. Resolution

  13. Types of Resolution • Spatial • Spectral • Radiometric • Temporal

  14. 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.

  15. Spatial Resolution

  16. Raster grid size finer Coarser

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

  18. Satellite data resolution • MODIS: 250 - 1000 m • Landsat MSS: 80 m • Landsat TM5, 7, 8: 30 m • SPOT: 20 m • ASTER: 15m • IRS Pan: 5 m • Quickbird Pan: 0.6 m

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

  20. MODIS 500 m spatial resolution

  21. 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!

  22. Spectral Resolution • How finely an instrument “divides up” the range of wavelengths in the electromagnetic spectrum • How many spectral “bands” an instrument records

  23. 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

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

  25. 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

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

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

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

  29. Spectral Resolution

  30. 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.

More Related