Glossary
3D Visual Simulation
A realistic three dimensional representation of the real world that can include fly-throughs and drive-throughs.
See the 3D Visual Simulation for more information.
Digital Elevation Model (DEM)
A Digital Elevation Model is a representation of the terrain using point elevation information.
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A gridded DEM is one in which the elevation points are spaced at regular intervals to create a grid or lattice. A triangulated DEM comprises of irregularly shaped triangles that model the Earth’s surface. These grids can be directly observed or, more generally, they are computed from other elevation information such as contours or irregularly spaced spot heights. DEM’s are used to create 3D views, which in turn can have data draped over them to make them more realistic. Digital Terrain Model (DTM) is another term that has the same meaning.
Geo-Code
Geo-coding is the process of taking a normal textual record from a database or spreadsheet and finding its position on a map. To do this, the record must have a “spatial key” such as a postcode number or street address. For instance, a listing of survey results that includes postcodes can be mapped to the position of those postcodes. If the same survey included street addresses, then the database records could be mapped to the position of the actual houses.
Geo-coding is often the first step in loading data into a GIS, so
that it can be integrated with other mapping data and spatially analysed.
Geo-PDF
Geo-PDF images are intelligent maps that can be viewed by the free software Adobe Reader. By using Adobe Reader to display Geo-PDF maps one can perform the following functions:
Display, pan, zoom, layer control, attribute attachment, query, search, geo-measure, geo-reference, GPS track, markup, redline annotate, comment, create forms and print.
Geo-reference
Aligning spatial data to a known coordinate system, so that it can be viewed, queried, and analyzed in relation to other spatial data. Geo-referencing may involve shifting, rotating, scaling, skewing, and in some cases warping (or rubber sheeting) the data.
Geo-processing
Geo-processing is a GIS operation used to manipulate spatial data. A typical geo-processing operation takes an input dataset, performs an operation on that dataset, and returns the result of the operation as an output dataset. Geo-processing allows for definition, management, and analysis of information used to form decisions.
Geo-spatial Modelling
Geo-spatial Modelling uses geo-processing to develop models that are:
- An abstraction and description of reality used to represent objects, processes, or events.
- A set of clearly defined analytical procedures used to derive new information from input data.
- A set of rules and procedures for representing a phenomenon or predicting an outcome.
Geographic Information System (GIS)
In a generic sense, GIS is a "smart map" tool that allows users to create interactive queries, and analyse and edit map information. In a more rigorous sense a GIS can be described as a system for managing map data and associated attributes. It is a computer system capable of integrating, storing, editing, analyzing, and displaying geographically-referenced information.
LiDAR
A LiDAR (Light Detection and Ranging) system rapidly transmits pulses of light that reflect off the terrain and other landscape features. The return pulse is converted from photons to electrical impulses and collected by a high-speed data recorder. Because the formula for the speed of light is known, time intervals from transmission to collection can be derived.
Time intervals are then converted to distance based on positional information obtained from ground/aircraft GPS receivers, and the on-board Inertial Measurement Unit (IMU) that continually records the attitude (pitch, roll, and heading) of the aircraft. LiDAR systems collect positional (x,y) and elevation (z) data at pre-defined intervals. The resulting LiDAR data is a very dense network of elevation postings. The accuracy of LiDAR data is a function of flying height, laser beam diameter (system dependent), the quality of the GPS/IMU data, and post-processing procedures. Accuracies of ±15cm (horizontal) and ±15cm (vertical) can be achieved.
Map Projection
Map Projections display the curved surface of the Earth as a flat surface. This generally requires a systematic mathematical transformation of the Earth's graticule of lines of longitude and latitude onto a plane. This can be visualized as a transparent globe with a central light bulb that casts lines of latitude and longitude onto a sheet of paper. Generally, the paper is either flat and placed tangential to the globe (a planar or azimuthal projection) or formed into a cone or cylinder and placed over the globe (cylindrical and conical projections). Every map projection distorts distance, area, shape, direction, or some combination thereof.
Mosaic
- Maps of adjacent areas with the same projection and scale, whose boundaries have been matched and dissolved.
- A raster dataset that is composed of two or more merged raster datasets, for example, one image created by merging several individual images or photographs of adjacent areas.
Multi-spectral
Infrared imaging is one method of using wavelengths other than visible light to gather information about Earth. Most satellites and airborne sensors measure energy at many wavelengths, which is called multi-spectral imaging. Images taken at different wavelengths can be combined to make composite images by displaying the image for each wavelength as red, green, or blue in the final image. These composite images result in color patterns that can be used to identify features invisible to the normal visible wavelengths of light.
Ortho-rectify
A digital ortho-rectified image is a satellite or aerial photographic image that has been digitally corrected to ensure ground features are depicted in their correct geographic location. While satellite or aerial photographic images are produced as accurately as possible, misrepresentations do occur due to factors such as the position of the sensor or camera at the time of capture. These misrepresentations are rectified through this technique, resulting in a true depiction of the terrain that enables precise distance and area measurements to be taken from the image.
A digitally ortho-rectified image offers all the benefits of the original image, and delivers a feature-rich picture of the Earth's surface, combined with the highly accurate spatial data of a map. Many users overlay ortho-rectified images with traditional data, such as zoning, utilities or property ownership maps, in order to comprehensively view and analyse this data in the context of the surrounding landscape.
Photogrammetry
Photogrammetry is the science of making reliable measurements of physical objects and the environment, by measuring and plotting data from aerial photographs and remote-sensing systems against land features identified in ground control surveys. Generally, this is performed in order to produce planimetric, topographic, and contour maps.
Remote Sensing Sensors
Remote Sensing satellites carry two types of sensor systems known as “active” and “passive”. A “passive” system generally consists of an array of small sensors or detectors that record (as digital numbers) the amount of electro-magnetic radiation reflected and emitted from the Earth's surface. SPOT is an example of a passive system. An “active” system propagates its own electro-magnetic radiation and measures (as digital numbers) the intensity of the return signal. Synthetic Aperture Radar (SAR) is an example of an active system.
Resolution
The smallest unit of information in a satellite image or raster map is a pixel, which is usually square or rectangular in shape. The term pixel is often used synonymously with the term, cell. Pixel size in a given image correlates to the degree of detail or resolution of that image.
Images with different resolution are complementary to one another. Some users require highly detailed imagery, while others need only large-area coverage. Higher resolution images, showing more detail, are ideal for applications such as transportation network mapping, disaster preparedness, urban planning, precision farming, and telecommunications. Lower resolution images are useful for environmental assessment, regional mapping, forestry management, widespread disaster assessment, and urban monitoring.
The following images show the San Francisco International Airport, and illustrate how much detail can be seen in satellite images with different resolutions.
As you look from left to right, these aerial and satellite images show a decreasing amount of detail, as the resolution reduces. That is, one-meter resolution imagery shows significantly more detail than 25-meter resolution imagery. In the one-meter image you can see planes on the tarmac and cars in the parking lot. In the lowest resolution image on the far right, you can only see the vague outline of the airport jutting out into San Francisco Bay.
Simulated resolution comparison of San Francisco Airport at the same scale. The images below show what you would see if you were looking at a single object, for instance an airplane, at exactly the same scale but at different resolutions.
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One-meter This image was collected by an airplane camera and has a resolution of one meter. It simulates IKONOS satellite imagery. |
Five-meter This image was collected by the Indian Remote Sensing (IRS) satellite and has a resolution of five meters. |
25-meter This image was collected by the U.S. Landsat satellite and has a resolution of 25 meters. |
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One-Meter This one-meter resolution picture simulates an IKONOS satellite image. It is zoomed-in to focus on two airplanes parked at the concourse. |
Five-Meter This is the same picture, but it has been altered to simulate what you would see in a five-meter resolution image. The airplanes appear blurry at this resolution. |
25-Meter At 25-meter resolution, this same picture is unreadable. The airplanes are not recognisable; however, for large-area analysis, this level of detail is satisfactory. |
Scale
Commonly expressed as a ratio or a number, scale refers to the ratio or relationship between a distance or area on a map and the corresponding distance or area on the ground. A map scale of 1:100,000 or 100K means that one unit of measure on the map equals 100,000 of the same unit on the earth i.e. 1cm on the map is equal to 100m on the ground.
The description of scale is somewhat counter-intuitive. A large-scale map is detailed and covers a relatively small area. A small-scale map covers a wide area and is quite general in the level of detail.
Detailed or large-scale mapping is typically in the range of 1:1,000 to 1:25,000 (25K).
Medium-scale mapping is typically in the range of 1:50,000 to 1:250,000 (250K).
Broad-coverage or small-scale mapping is generally described as smaller than 1:250,000 (250K), for example 1:1,000,000.
Spatial
Spatial is a contemporary term used to describe the field of mapping; other terms with similar meaning include geo-spatial, location-based and geographic. Spatial Technologies is a generic term used to describe technologies that capture, process, store, access, and analyse spatial information.
Spatial Data
Spatial data refers to any data that can be mapped. There are two fundamental types of digital spatial data, Raster and Vector.
Raster data is a digital image made up of pixels. Satellite images or scanned maps are examples of raster data.
Vector data represents spatial features as points, lines, and boundaries (polygons). Cadastral boundaries and road centerlines are examples of vector data.
Attribute data is tabular or textual data that describes the geographic characteristics of map features. In vector data, attributes are associated with each feature. For instance, the attribute data of a census boundary might include the population of people living within that boundary. In raster data, attributes are associated with each pixel. For instance a group of dark green pixels could signify an area of dense vegetation.
Meta data are the parameters that describe a dataset. Typical meta-data includes the source, scale, accuracy, and currency of a particular dataset.
See the Spatial Data Section for the wide range of off-the-shelf spatial data available from Terranean.