The radiometric resolution and the spatial resolution are the most important measure for characterisation of digital spectral. The radiometric resolution stands for the ability of a digital sensor to distinguish between grey-scale values while acquiring an image. Now, what does this mean?
Humans see the nature in colour. However, a satellite perceives different wavelengths in different intensities only. He can only distinguish between bright and dark. But he can do this a great deal better than humans. A spectral image is not less than a raster consisting of different grey-scale values.
The swipe below contains two spectral images of Bonn: The first has a radiometric resolution of 2 and the second has a radiometric resolution of 8 bit. It becomes clear that surfaces can be distinguished much better in the 8-bit image than in the 2-bit image.
The swipe shows two spectral images with different radiometric resolutions. Which image is the 8-bit image with 256 grey-scale values and which image has only 4 bit and 15 grey-scale values to offer? (Images of USGS/NASA Landsat Program)
What is a "bit", then?
In remote sensing, a bit stands for the number of grey-scale values a spectral sensor can tell apart. The greater the bit number, the greater the number of grey-scale values a spectral sensor can distinguish, and, therefore, the higher the radiometric resolution of a spectral sensor. One bit stands for a sensor that knows only black and white. 2 bit equals 4 grey-scale values and 4 bit 16 values. The equation is as follows:
2 to the power of bit = number of grey-scale values
The higher the bit, the more grey-scale values can be differentiated by a sensor.
The radiometric resolution of image data in remote sensing stands for the ability of the sensor to distinguish different grey-scale values. It is measured in bit. The more bit an image has, the more grey-scale values can be stored, and, thus, more differences in the reflection on the land surfaces can be spotted.