Remote Sensing-Spatial, Radiometric,Temporal & Spectral Resolution

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Information about Remote Sensing-Spatial, Radiometric,Temporal & Spectral Resolution

Published on April 28, 2012

Author: explore1


Spatial, Temporal, Radiometric & Spatial Resolution : Spatial, Temporal, Radiometric & Spatial Resolution Remote sensing : Remote sensing “ Remote sensing is the acquisition of information about an object or phenomenon, without making physical contact with the object” Background: Background Remote sensors: : Remote sensors : Remote sensors measure and record the magnitude and frequency of reflected energy from an object . Energy’ is generally either electromagnetic radiation (light) or acoustic (sound). The results are often presented as images. PowerPoint Presentation: Imaging sensors PowerPoint Presentation: Imaging sensors Remote sensing Images: Remote sensing Images Analogue format Digital format Fixed and could not be subject to manipulation Made up of numbers represent image attributes. Resolution : Resolution Pixel The smallest sized picture element on an image is called a pixel Raster image . Digital image is made up of pixels arranged in rows and columns commonly known as a raster image . PowerPoint Presentation: Resolution: “The dimensions and the information content of these pixels are both aspects of the resolution of the image” Resolution is the accuracy at which a given map scale can depict the location and shape of map features. The larger the map scale, the higher the possible resolution. As map scale decreases, resolution diminishes. PowerPoint Presentation: Remote sensors measure differences and variations of objects that are often described in terms of three main resolutions These resolution categories include: Spatial resolution, Radiometric resolution, Temporal resolutions . Spectral resolution Sensors Resolutions Spatial resolution: : 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” Spatial resolution’s three main concepts: : Spatial resolution’s three main concepts: Instantaneous field-of-view (IFOV) Pixel: smallest unit of an image/ Pixel size Field of view (FOV), or Area of coverage PowerPoint Presentation: The IFOV determines the area on the Earth's surface which is "seen" from a given altitude at one particular moment in time (B).The size of the area viewed is determined by multiplying the IFOV by the distance from the ground to the sensor (C). Spatial Resolution: Spatial Resolution This area on the ground is called the resolution cell that determines a sensor's maximum spatial resolution. Feature to be detected, its size generally has to be equal to or larger than the resolution cell. PowerPoint Presentation: 30 meter, spatial resolution spatial resolution 1 meter, spatial resolution PowerPoint Presentation: The cell must be small enough to capture the required detail but large enough so computer storage and analysis can be performed efficiently. More features, smaller features, or a greater detail in the extents of features can be represented by a raster with a smaller cell size. Remotely sensed data whose grid cells range from 15 to 80 meters on a side, such as the Landsat ETM+ and MSS sensors, are considered medium resolution.   Coarse or low resolution image :: Coarse or low resolution image : Images where only large features are visible are said to have coarse or low resolution. Fine or high resolution image: In fine or high resolution images, small objects can be detected. Spatial Resolution: Spatial Resolution Higher the spatial resolution of a digital image, the more detail it contains. Detail is valuable for some applications, but it is also costly. Spatial resolution versus scale : Spatial resolution versus scale Spatial resolution refers to the area covered on the ground. If the area covered by a cell is 5 x 5 meters, the resolution is 5 meters. The higher the resolution of a raster, the smaller the cell size and, thus, the greater the detail. This is the opposite of scale . The smaller the scale, the less detail shown. PowerPoint Presentation: For example, photograph displayed at a scale of 1:2,000 shows more details (appears zoomed in) than one displayed at a scale of 1:24,000 (appears zoomed out). Radiometric resolution: : Radiometric resolution: “ The measure of a sensor's ability to discriminate small differences in the magnitude of radiation within the ground area that corresponds to a single raster cell” Radiometric resolution:: Radiometric resolution: It determines how finely a system can represent or distinguish differences of intensity , and is usually expressed as a number of levels or a number of bits , for example 8 bits or 256 levels that is typical of computer image files. Radiometric resolution:: Radiometric resolution: Describes Sensor’s ability to discriminate very slight differences in (reflected or emitted) energy, The finer the radiometric resolution of a sensor, the more sensitive it is to detecting small differences in energy. Often called contrast. The greater the bit depth (number of data bits per pixel) of the images that a sensor records, the higher its radiometric resolution. Basics of Bit:: Basics of Bit: 7 6 5 4 3 2 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 Bits Max num. (2 bits ) 1 2 2 4 3 8 6 64 8 256 11 2048 12 4096 Computer stores everything in 0 or 1 8 bits as an Example Resolution 12 bits Coverage 0-4095 Comparing a 2-bit image with an 8-bit image:: Comparing a 2-bit image with an 8-bit image: Example: : Example: The AVHRR sensor, for example, stores 2 10 bits per pixel, as opposed to the 2 8 bits that the Landsat sensors record. Thus although its spatial resolution is very coarse (~4 km), the Advanced Very High Resolution Radiometer takes its name from its high radiometric resolution. PowerPoint Presentation: The area under the curve represents the magnitude of electromagnetic energy emitted by the Sun at various wavelengths . Sensors with low radiometric resolution are able to detect only relatively large differences in energy magnitude (as represented by the lighter and thicker purple band). Sensors with high radiometric resolution are able to detect relatively small differences (represented by the darker and thinner band). Temporal resolution: : Temporal resolution: “ Temporal resolution is a description of how often a sensor can obtain imagery of a particular area of interest” Temporal Resolution: Temporal Resolution The length of time for a satellite to complete one entire orbit cycle. Temporal coverage is the time period of sensor from starting to ending. Temporal Resolution: Temporal Resolution Actual temporal resolution of a sensor depends on a variety of factors, including the satellite/sensor capabilities, the swath overlap, and latitude. Revisit period, the length of time it takes for a satellite to complete one entire orbit cycle several days. Therefore the absolute temporal resolution of a remote sensing system to image the exact same area at the same viewing angle a second time is equal to this period. Because of some degree of overlap in the imaging swaths of adjacent orbits for most satellites and the increase in this overlap with increasing latitude, some areas of the Earth tend to be re-imaged more frequently. Temporal Resolution: Temporal Resolution The ability to collect imagery of the same area of the Earth's surface at different periods of time is one of the most important elements for applying remote sensing data. Spectral characteristics of features may change over time and these changes can be detected by collecting and comparing multi-temporal imagery. By imaging on a continuing basis at different times we are able to monitor the changes that take place on the Earth's surface, whether they are naturally occurring or induced by humans. The time factor in imaging is important:: The time factor in imaging is important: Persistent clouds offer limited clear views of the Earth's surface (often in the tropics) short-lived phenomena (floods, oil slicks, etc.) need to be imaged multi-temporal comparisons are required (e.g. the spread of a forest disease from one year to the next) Changing appearance of a feature over time can be used to distinguish it from near-similar features (wheat / maize) Examples : Examples LANDSAT needs 16 days, MODIS needs one day, NEXRAD needs 6 minutes. Spectral Resolution:: Spectral Resolution: “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” Spectral Resolution: Spectral Resolution Sensor's spectral resolution specifies the number of spectral bands in which the sensor can collect reflected radiance. Number of bands is not the only important aspect of spectral resolution. Position of bands in the electromagnetic spectrum is important, too. Spectral Resolution: Spectral Resolution High spectral resolution: - 220 bands Medium spectral resolution: 3 - 15 bands Low spectral resolution: - 3 bands PowerPoint Presentation: Electromagnetic Spectrum Spectral Resolution: Spectral Resolution It is the sensitivity of a sensor to respond to a specific frequency range (mostly for satellite and airborne sensors). The frequency ranges covered often include not only visible light but also non-visible light and electromagnetic radiation. Objects on the ground can be identified by the different wavelengths reflected (interpreted as different colours ) but the sensor used must be able to detect these wavelengths in order to see these features. PowerPoint Presentation: Spectral Resolution for Landsat TM7 and ASTER Satellite Sensors Trend and Future of Remote Sensing: : Trend and Future of Remote Sensing : High spatial resolution: IKONOS launched in 1999 by Space Imaging QuickBird launched in 2001 by DIGITALGLOBE High radiometric resolution : 8 bits to 12 bits High temporal resolution: - GOES 15-30 minutes - NEXRAD 6 or 10 minutes ANY QUESTIONS?: ANY QUESTIONS? PowerPoint Presentation: Thank you!

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