Remote Sensing Terminology
The Landsat program is a series of American satellites that use the visible and infrared parts of the spectrum to record images of the Earth's surface. It is the longest running enterprise for acquisition of satellite imagery, and started back in 1972. The most recent, Landsat 8, was launched in 2013.
Landsat satellites are located in a polar orbit, which allows them to provide images of almost all of the Earth's geography. As the satellite orbits the Earth from pole to pole, it appears to move from east to west because of the Earth’s rotation. This apparent movement allows the satellite to view a new area with each orbit.
Determining land cover has become one of the most common uses of Landsat Imagery and remotely sensing generated images all around the world.
The LiDAR sensor produces a series of point measurements that consists of geographic location (X & Y) and height (Z) of both natural and man-made features, and can be further processed to produce several different products and integrated into a Geographic Information System (GIS).
Click here to learn more about LiDAR
The amount of energy returning to the sensor (known as backscatter) is dependent upon the topography, roughness, and dielectric properties (moisture). Areas of an image with low backscatter appear dark (such as water), while areas of high backscatter appear as light gray levels approximating white shades. By interpreting the various gray tones, textures and patterns, the user can detect information regarding to the regions geologic lithology and structure.
In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. This is exemplified by the use of imaging systems where the following seven elements are involved. Note, however that remote sensing also involves the sensing of emitted energy and the use of non-imaging sensors. Click here to learn more about Remote Sesning
Submit a term
Download Canadian OpenData from over 100 different Sources
This is a sample of an seamless 1:10000 scale color aerial photograph mosaic of Halifax, Nova Scotia. The actual image was plotted out on a 4 foot by 4 foot poster. The mosaic image was generated using PCI OrthoEngine software to seamlessly combine seven individual ortho photos.
For more information on mosaicking ortho photos with PCI Orthoengine software refer to the following document that I created for a remote sensing course at COGS:
- MacKinnon E (2003) Orthorectification of Aerial Photos with PCI OrthoEngine Middleton, NS: Applied Geomatics Research Group, Centre of Geographic Sciences, 33 pages
Remote sensing is merely the science of acquiring information about a surface without physically being in contact with it. It involves the use of technical instruments or sensors to record reflected or emitted energy and then processing, analyzing, and applying that information to determine the spectral and spatial relations of distance objects and materials.
This is possible due to the fact that the examined objects (such as vegetation, buildings, water, air masses etc.) reflect or emit radiation in different wavelengths and intensities according to their current condition. Modern remote sensing typically involves digital processes but can also be done with non-digital methods.
Probably the most common example of remote sensing is an aerial photograph but there are probably hundreds of applications related to remote sensing ranging from space-borne satellites to under-ground geophysical systems. It has become a major component in the evolving Geomatics industry. In order to generate maps for GIS, most remote sensing systems expect to convert a photograph or other data item to actual measurable distance on the surface. However, this almost always depends on the precision of the instrument that is being used to capture the data. For example, distortion in an aerial photographic lens can cause severe distortions when photographs are used to measure ground distances. Using sophisticated software like PCI OrthoEngine can convert the photograph into an ortho photo which can be used to measure ground distances.
In order to coordinate a series of observations, most sensing systems need to know where they are, what time it is, and the rotation and orientation of the instrument. High-end instruments now often use positional information from satellite navigation systems. The rotation and orientation is often provided within a degree or two with electronic compasses.
The resolution determines how many pixels are available in measurement, but more importantly, higher resolutions are more informative, giving more data about more points. However, large amounts of high resolution data can clog a storage or transmission system with useless data, when a few low resolution images might be a better use of the system.
Like I mentioned earlier examples of remote sensing are very numerous. I have over the past decade and have used the many projects that I have been involved with along with actual examples of my work to help illustrate the principals of the various topics covered on the web site. I have included basic overviews for each along with images, presentations, papers and links to other related resources.
Remote Sensing Links
A Northen Nova Scotia RADARSAT mosaic created using PCI OrthoEngine software. Back then RADARSAT data came unformatted and had to be heavily processed and stitched together to form an image like the one featured here …