A remote sensing system comprises two basic components: a sensor and a platform. The sensor is the instrument used to record data; a platform is the vehicle used to deploy the sensor. Lesson 2 will discuss imaging sensors and platforms in much greater detail. Every sensor is designed with a unique field of view which defines the size of the area instantaneously imaged on the ground. The sensor field of view combined with the height of the sensor platform above the ground determines the sensor footprint. A sensor with a very wide field of view on a high-altitude platform may have an instantaneous footprint of hundreds of square kilometers; a sensor with a narrow field of view at a lower altitude may have an instantaneous footprint of ten of square kilometers.
Resolution, as a general term, refers to the degree of fineness with which an image can be produced and the degree of detail that can be discerned. In remote sensing, there are four relevant types of resolution:
Spatial resolution is a measure of the finest detail distinguishable in an image. Spatial resolution depends on the sensor design and is often inversely related to the size of the image footprint. Sensors with very large footprints tend to have low spatial resolution; and sensors with very high spatial resolution tend to have small footprints. Spatial resolution will determine whether individual houses can be distinguished in a scene and to what degree detailed features of the house or damage to the house can be seen. For imaging satellites of potential interest to the housing inspection program, spatial resolution varies from tens of kilometers per pixel to sub-meter. Spatial resolution is closely tied to Ground Sample Distance (GSD) which is the nominal dimension of a single side of a square pixel in ground units.
Temporal resolution refers to the frequency at which data are captured for a specific place on the earth. The more frequently data they are captured by a particular sensor, the better, or finer, is the temporal resolution of that sensor. Temporal resolution is often quoted as a “revisit time” or “repeat cycle.” Temporal resolution is relevant when using imagery or elevations datasets captured successively over time to detect changes to the landscape. For sun-synchronous satellites of interest to the housing inspection program, revisit times vary from about 2 weeks to 1 day.
Spectral resolution describes the way an optical sensor responds to various wavelengths of light. High spectral resolution means that the sensor distinguishes between very narrow bands of wavelengths; a “hyperspectral” sensor can discern and distinguish between many shades of a color, recording many gradations of color across the infrared, visible, and ultraviolet wavelengths. Low spectral resolution means the sensor records the energy in a wide band of wavelengths as a single measurement; the most common “multispectral” sensors divide the electromagnetic spectrum from infrared to visible wavelengths into four generalized bands: infrared, red, green, and blue. The way a particular object or surface reflects incoming light can be characterized as a spectral signature and can be used to classify objects or surfaces within a remotely sensed scene. For example, an asphalt parking lot, a corn field, and a stand of pine trees will have all have different spectral signatures. Automated techniques can be used to separate various types of objects within a scene; these techniques will be discussed in Section III below.
Radiometric resolution refers to the ability of a sensor to detect differences in energy magnitude. Sensors with low radiometric resolution are able to detect only relatively large differences in the amount of energy received; sensors with high radiometric resolution are able to detect relatively small differences. The range of possible values of brightness that can be assigned to a pixel in an image file or band is determined by the file format and is also related to radiometric resolution. In an 8-bit image, values can range from 0 - 255; in a 12-bit image, values can range from 0 - 4096; in a 16-bit image, values can range from 0 - 65536; and so on.