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

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?

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

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

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).

Somewhere on earth

Raster grid is placed

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

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)

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

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)

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.

Resolution

Types of Resolution Spatial Spectral Radiometric Temporal

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.

Spatial Resolution

Raster grid size finer Coarser

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

Satellite data resolution MODIS: 250 - 1000 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 (!!)

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

MODIS 500 m spatial resolution

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!

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. https://landsat.usgs.gov/tools_spectralViewer.php

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

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

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

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

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

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

Spectral Resolution

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.