Resolution is a broad term commonly used to describe:
- number of pixels you can display on a display device, or
- area on the ground that a pixel represents in an image file
These broad definitions are inadequate when describing remotely sensed data. Four distinct types of resolution must be considered:
- spectral—specific wavelength intervals that a sensor can record
- spatial—area on the ground represented by each pixel
- radiometric—number of possible data file values in each band (indicated by the number of bits into which the recorded energy is divided)
- temporal—how often a sensor obtains imagery of a particular area
These four domains contain separate information that can be extracted from the raw data.
Spectral resolution refers to the specific wavelength intervals in the electromagnetic spectrum that a sensor can record (Simonett et al, 1983). For example, band 1 of the Landsat TM sensor records energy between 0.45 and 0.52 mm in the visible part of the spectrum.
Wide intervals in the electromagnetic spectrum are referred to as coarse spectral resolution, and narrow intervals are referred to as fine spectral resolution. For example, the SPOT panchromatic sensor is considered to have coarse spectral resolution because it records EMR between 0.51 and 0.73 mm. On the other hand, band 3 of the Landsat TM sensor has fine spectral resolution because it records EMR between 0.63 and 0.69 mm (Jensen, 1996).
The spectral resolution does not indicate how many levels the signal is broken into.
Spatial resolution is a measure of the smallest object that can be resolved by the sensor, or the area on the ground represented by each pixel (Simonett et al, 1983). The finer the resolution, the lower the number. For instance, a spatial resolution of 79 meters is coarser than a spatial resolution of 10 meters.
The terms large-scale imagery and small-scale imagery often refer to spatial resolution. Scale is the ratio of distance on a map as related to the true distance on the ground (Star and Estes, 1990).
Large-scale in remote sensing refers to imagery in which each pixel represents a small area on the ground, such as SPOT data, with a spatial resolution of 10 m or 20 m. Small scale refers to imagery in which each pixel represents a large area on the ground, such as Advanced Very High Resolution Radiometer (AVHRR) data, with a spatial resolution of 1.1 km.
This terminology is derived from the fraction used to represent the scale of the map, such as 1:50,000. Small-scale imagery is represented by a small fraction (one over a very large number). Large-scale imagery is represented by a larger fraction (one over a smaller number). Generally, anything smaller than 1:250,000 is considered small-scale imagery.
Scale and spatial resolution are not always the same thing. An image always has the same spatial resolution, but it can be presented at different scales (Simonett et al, 1983).
Instantaneous Field of View
Spatial resolution is also described as the instantaneous field of view (IFOV) of the sensor, although the IFOV is not always the same as the area represented by each pixel. The IFOV is a measure of the area viewed by a single detector in a given instant in time (Star and Estes, 1990). For example, Landsat MSS data have an IFOV of 79 × 79 meters, but there is an overlap of 11.5 meters in each pass of the scanner, so the actual area represented by each pixel is 56.5 × 79 meters (usually rounded to 57 × 79 meters).
Even though the IFOV is not the same as the spatial resolution, it is important to know the number of pixels into which the total field of view for the image is broken. Objects smaller than the stated pixel size may still be detectable in the image if they contrast with the background, such as roads, drainage patterns, and so forth.
On the other hand, objects the same size as the stated pixel size (or larger) may not be detectable if there are brighter or more dominant objects nearby. In he figure below, a house sits in the middle of four pixels. If the house has a reflectance similar to its surroundings, the data file values for each of these pixels reflect the area around the house, not the house itself, since the house does not dominate any one of the four pixels. However, if the house has a significantly different reflectance than its surroundings, it may still be detectable.
Radiometric resolution refers to the dynamic range, or number of possible data file values in each band. This is referred to by the number of bits into which the recorded energy is divided.
For instance, in 8-bit data, the data file values range from 0 to 255 for each pixel, but in 7-bit data, the data file values for each pixel range from 0 to 128.
In he figure below, 8-bit and 7-bit data are illustrated. The sensor measures the EMR in its range. The total intensity of the energy from 0 to the maximum amount the sensor measures is broken down into 256 brightness values for 8-bit data, and 128 brightness values for 7-bit data.
Temporal resolution refers to how often a sensor obtains imagery of a particular area. For example, the Landsat satellite can view the same area of the globe once every 16 days. SPOT, on the other hand, can revisit the same area every three days.
Temporal resolution is an important factor to consider in change detection studies.
The figure below illustrates all four types of resolution:
Landsat TM—Band 2 (Four Types of Resolution)
Source: NASA Landsat