Resolution A sensor's various resolutions are very important characteristics. These resolution categories include: spatial spectral temporal radiometric.

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Presentation transcript:

Resolution A sensor's various resolutions are very important characteristics. These resolution categories include: spatial spectral temporal radiometric

Spatial resolution Spatial resolution is a measure of the smallest object that can be resolved by the sensor, or the linear dimension on the ground represented by each pixel or grid cell in the image. The spatial resolution specifies the pixel size of satellite images covering the earth surface.

Spatial resolution High spatial resolution: m » GeoEye-1 » WorldView-2 » WorldView-1 » QuickBird » IKONOS » SPOT-5 Medium spatial resolution: m » ASTER » LANDSAT 7 » CBERS-2 Low spatial resolution: 30 - > 1000 m

1 m 2 m 5 m 20 m 10 m 50 m

Spectral Spectral resolution describes the specific wavelengths that the sensor can record within the electromagnetic spectrum. For example, the “photographic infrared” band covers from about 0.7 – 1.0 micrometers. A sensor's spectral resolution specifies the number of spectral bands in which the sensor can collect reflected radiance. But the number of bands is not the only important aspect of spectral resolution. The position of bands in the electromagnetic spectrum is important, too. High spectral resolution: bands Medium spectral resolution: bands Low spectral resolution: - 3 bands

Electromagnetic spectrum

Panchromatic images Panchromatic images are obtained by recording radiation in a single wide bandwidth within the visible part of the spectrum, i.e. between 0.4 and 0.7 µm. Because the data are stored in one single channel, only black and white images can be produced (for images coded in 8 bits, 256 greytones can be visualised). The spectral information contained in a panchromatic image is rather limited, but such images generally have a higher spatial resolution.

Panchromatic images

Multispectral images Multispectral data are acquired by simultaneously recording 3 to 8 different spectral bands that may or may not be contiguous. To visualise this information as a colour image, primary colours (red-green-blue) are paired with spectral bands. The relative brightness (which depends on its digital value) of each pixel in each primary colour band determines the resulting colour in the combined bands.

SPOT Image Visualisation of a SPOT image as an infrared false colors composite Source:

For example, the spectral bands covered by the The Thematic Mapper (TM) sensor aboard Landsat 5 records seven spectral bands in the 0.45 to 12,5 µm portion of the spectrum (three in visible light, one in near infrared, two in mid infrared and one in thermic infrared). The HRV sensor on board Spot 1 to 3 satellites generates three spectral bands in multispectral mode: - the green band B1 registers the part of the spectrum between 0,50 and 0,59µm, - the red band B2 between 0,61 and 0,68 µm, - the (NIR) near infrared band B3 between 0,79 and 0,89 µm, and one single band in panchromatic mode (0,51 - 0,73 µm ).

Hyperspectral images (imaging spectroscopy) Hyperspectral imagery is acquired by sensors which can sample a multitude (often more than 200) of spectral bands in the visible, near infrared and mid infrared range. In comparison with multispectral data, the bands are much narrower (a couple of nm order of magnitude) and are often contiguous. Hyperspectral data provide more detailed information (a finer spectral signature) about an object thus allowing a more precise identification and discrimination. Each pixel in a hyperspectral image contains the information sampled over wide windows within the visible and infrared parts of the electromagnetic spectrum.

Hyperspectral images

Temporal Temporal resolution is a description of how often a sensor can obtain imagery of a particular area of interest. High temporal resolution : 16 days For example, the Landsat satellite revisits an area every 16 days as it orbits the Earth, while the SPOT satellite can image an area every 1 to 4 days.

IKONOS Temporal Resolution

Radiometric Radiometric resolution refers to the number of possible brightness values in each band of data and is determined by the number of bits into which the recorded energy is divided. Radiometric resolution is often called contrast. It describes the ability of the sensor to measure the signal strength (acoustic reflectance) or brightness of objects. The more sensitive a sensor is to the reflectance of an object as compared to its surroundings, the smaller an object that can be detected and identified. In 8-bit data, the brightness values can range from 0 to 255 for each pixel (256 total possible values). In 7-bit data, the values range from 0 to 127, or half as many possible values.

8-bit quantization (256 levels)6-bit quantization (64 levels) 3-bit quantization (8 levels) 4-bit quantization (16 levels) 1-bit quantization (2 levels) 2-bit quantization (4 levels)