Types of resolution

 When working with imaged raster data, there are four types of resolution you might be concerned with: spatial resolution, spectral resolution, temporal resolution, and radiometric resolution.



In a GIS, you are most often concerned with the spatial resolution of a raster dataset, especially when displaying or comparing raster data with other data types, such as vector. In this case, resolution refers to the cell size (the area covered on the ground and represented by a single cell). A higher spatial resolution implies that there are more cells per unit area; therefore, the graphic on the left represents a higher spatial resolution than the graphic on the right.

Spectral resolution describes the ability of a sensor to distinguish between wavelength intervals in the electromagnetic spectrum. The higher the spectral resolution, the narrower the wavelength range for a particular band. For example, a single-band, grayscale, aerial photograph (image) records wavelength data extending over much of the visible portion of the electromagnetic spectrum; therefore, it has a low spectral resolution. A color image (with three bands) basically collects wavelength data from three smaller parts of the visible portion of the electromagnetic spectrum—the red, green, and blue parts. Therefore, each band in the color image has a higher spectral resolution than the single band in the grayscale image. Advanced multispectral and hyperspectral sensors collect data from up to hundreds of very narrow spectral bands throughout portions of the electromagnetic spectrum, resulting in data that has a very high spectral resolution.

Temporal resolution refers to the frequency at which images are captured over the same place on the earth's surface, otherwise known as the revisit period, which is a term most often used when referring to satellite sensors. Therefore, a sensor that captures data once every week has a higher temporal resolution than one that captures data once a month.

Radiometric resolution describes the ability of a sensor to distinguish objects viewed in the same part of the electromagnetic spectrum; this is synonymous with the number of possible data values in each band. For example, a Landsat band is typically 8-bit data, and an IKONOS band is typically 11-bit data; therefore, the IKONOS data has a higher radiometric resolution.


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