Satellite Imagery Primer
Digital data, in an imaging sense, can apply to quite a broad range of products.
In WorldSat's case we deal with four basic sets of digital data, these being:
It is important that the first time user of digital data be aware of the differences and the limitations of each of these types of data.
In our terms of reference, the Cartographic data is traditional map data comprised of line drawings and shaded backgrounds.
Digital Elevation Data (DEM) is used to model satellite imagery or to create grayscale shaded-relief imagery of the Earth's surface. Finally, the Satellite Imagery is an actual picture of the surface of our Earth.
Scales and Resolutions:
DETAIL and COVERAGE is determined by the scale and resolution of the imagery.
Know what you're looking for but don't know how much detail you need?
Use our VISUAL GUIDE to help you determine the detail and coverage that is suitable for your needs.
Since our imagery is available at various scales and resolutions, we understand that it can be difficult to visualize what the imagery looks like. Our VISUAL GUIDE takes the guesswork out of the process.
Starting with the Satellite Imagery:
Satellite imagery can be defined by two major criteria:
1) Its resolution
2) Its band, or colour, content
RESOLUTION
15 Meter Resolution
An overview of Salt Lake City
A satellite's resolution is defined as the size of the smallest individual component or dot (called a pixel) from which the image is constituted.
If a satellite's resolution is stated as "5 meters", this means that each pixel in the imagery is 5 meters by 5 meters in size. While there are cases where objects smaller than 5 meters in a given dimension can be identified by such a satellite the general rule of thumb is that objects smaller than the resolution of the satellite in the largest dimension are not readily or reliably distinguishable in such imagery.
5 Meter Resolution
A close-up shot of Salt Lake City Airport
Current satellites provide data at resolutions ranging from 0.6 meters per pixel to 1 kilometer per pixel. At 0.6 meters per pixel people are visible in the imagery, not distinguishable from each other, but identifiable as people. At 1 km per pixel you wouldn't want to be looking at anything much smaller than the state of California.
We have provided image samples at resolutions of 160 meters, 60 meters, 30 meters, 15 meters, 10 meters, 5 meters and 1 meter. We have created a table that relates the pixel resolution to map scales for those of you more familiar with traditional mapping.
COLOUR BANDS
Panchromatic Antarctica
In the case of colour, a satellite's colour content is defined by the number of "bands"of data that are available within the imagery provided.
Each band of data is acquired separately and filtered so that only the information for a specific colour range, or defined portion of the electromagnetic spectrum, is recorded.
In simple terms, a three band image consisting of "red", "green" and "blue" bands of data (RGB) would, when combined, represent a natural colour image. In fact most satellites acquire their imagery in four or more "bands", many of which are outside the visible colour spectrum.
It is this characteristic of certain satellites that allows the data to be used to extract information that is not normally visible in the imagery. This process is called "classification" or "discrimination".
25m Raw Imagery Antarctica
Not all satellites, however, collect their data in multiple bands. All things being equal, higher resolution imagery can be acquired more easily in black and white than in colour. In satellite terms, black and white imagery is referred to as "panchromatic" data.
Obviously the ideal situation would be to have both the resolution of the panchromatic data but with the colour content of the lower resolution data.
WorldSat has developed a proprietary process that allows us to use colour imagery from a lower resolution satellite and combine it with higher resolution panchromatic imagery to create a colour image at the higher resolution. Samples of this can be seen in the 5 meter imagery which was originally a "panchromatic" image.
25m Processed Imagery Antarctica
While on the subject of colour, it should be noted that unprocessed satellite images rarely represent "true" or "natural" colours as we see them in day to day life. Some amount of processing is required to generate a "natural colour" image.
This is not an overly complex issue but the problem becomes considerably more difficult when more than one "scene" is involved.
Raw Mosaic Scenes
Kashmir
All satellite imagery is delivered as discrete "scenes" at some predefined size.
Not always, but in general, the size of a scene is defined as the square area of the satellite's "across track" dimension (swath width), where the "across track" dimension is the distance on the earth that the satellite sees, or scans, from side to side.
If the satellite's swath width is 60 km then a scene will usually be delivered as a 60 km x 60 km image.Few applications are fortunate enough to fall within this very limited constraint and so will normally require that we paste together two or more images (mosaicking) to meet application demands.
In this process of "mosaicking" we are often faced with the problem of matching adjacent scenes from different seasons and years so, if we are producing a natural colour image of an area, not only do we have to process the data to create a natural colour scene but we must also adjust each scene to match, or "balance", to the adjacent scenes if we are to avoid a patchwork quilt effect in the imagery.
WorldSat has spent considerable time and effort in refining the process of colour balancing and we believe that our mosaics are second to none.
There is yet a third issue in colour balancing and that is to balance imagery of one resolution to that of another resolution.
If one is to zoom from a shot of the world from space to a local farm you will need to transit through at least five (5) separate image layers. If these layers are not colour balanced the transitions will be quite obvious and the semblance of reality in the process will be lost.
WorldSat has expended considerable effort in colour balancing its data sets at different resolutions; all of this towards offering a set of imagery that can take the user from beyond the far reaches of our atmosphere down to local city streets in a single, seamless zoom that more closely approximates reality than alternative options.
DEM Guide
DEM of Kashmir
Using DEMs, you can create Shaded Relief maps, a grayscale topographical representation of the Earth.
Digital elevation data, variously referred to as DEM, DTED, terrain data,elevation data and relief data (among other possibilities), refers to a file that, digitally, defines the variations in the earth's terrain.
It describes what the elevation, above sea level, is of any point in the image, where each point represents a specific geographic location on the earth's surface.
This data can be used to make models of the surface variations of the earth but does not represent any other surface features such as vegetation, roads, deserts, etc.
Shaded Relief of the State of Colorado
When combined with satellite imagery, very realistic models of the earth can be produced and, with appropriate software, you can fly through the virtual valleys and mountains of our world.
Digital elevation data is also available at varying resolutions and in a multitude of formats. Resolutions are chosen for the scale of mapping or imagery that it will be associated with.
WorldSat offers elevation data for the world at 1 km spacing, matching the 1 km/pixel imagery. Selected areas of the world are offered at other resolutions varying from 250 meter spacing to as close as 10 meter spacing.
As there are numerous and widely different formats for elevation data it is important that the user know exactly what format the data should be delivered in or at least the name of the software that will use the data.
Cartography
This cartographic sample features vector data such as cities, roads, airport, and etc.
This is the base for traditional mapping as seen in most atlases and road maps.
In digital form it consists of vector data that defines lines, points and polygons.
Lines can represent features such as roads and political boundaries. Points can represent the location of items of interest without significant dimension, such as the location of a town,a building or a monument on small scale maps.
And polygons which are used to define areas of consistent classification such as a state, park or municipality on a map of appropriate scale.
These lines, points and polygons all have a specific location on the surface of the earth directly or indirectly indicated by latitude and longitude coordinates. This is referred to as "geocoded" data.
In addition to being "geocoded" these lines, points and polygons typically have attribute data associated with them. Such attribute information can be a name, such as the name of a town or highway, a population in the case of cities and towns, a definition of its general properties indicating whether the item is a state, a park, a forest or some other feature, to mention but a few of the possibilities.
The fact that the data is geocoded allows very different sets of data, derived from different sources and at different times, to be overlaid one on the other and matched with other data sets such as satellite imagery and digital elevation data.
Cartography is generally referred to as having a particular scale, where the scale is defined as a ratio of the map unit to the same area or distance on the ground.
If a map is said to have a scale of "one to fifty thousand", written 1:50,000, then one inch on the map would be equivalent to fifty thousand (50,000) inches on the actual surface of the earth (or 1 cm = 500 meters for those of us in a metric world).
This scale generally defines the level of detail that will be available in the data.
This sample features a satellite image overlaid with cartographic data such as cities, roads, etc.
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A map at a scale of 1:16,000,000 would equate to a double page spread with dimensions of 24" x 18" (61 cm x 45.7 cm) encompassing all of North America.
1:2,000,000 would cover all of California on the same double page spread.
Salt Lake City is represented on a double page spread of 18" x 13" would be at a scale of 1:25,000. At this scale individual streets are well defined and such maps would likely include street names.
