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
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Most imagery (and/or spatial data) that we view in geomatics is typically viewed vertically downwards from the source toward the map or image. This typical aerial view that we are accustomed to using, allows an abundant amount of information to be represented spatially within a two dimensional cartesian representation. However, occasionally it is useful for us to change our focus from the default traditional view and use a more complex three dimensional visualization view of the data.
This type of terrain model is commonly referred to as a perspective view and often reveals additional information by allowing us to observe the same data obliquely.. In order to do this each location of the image needs to be transformed from the traditional 2-D to a 3-D projection coordinate system.
A perspective view is not really a new tool as it has been around for centuries, but it has become a popular component of most geomatics projects. “A Perspective is a rational demonstration by which experience confirms that the images of all things are transmitted to the eye by pyramidal lines. Those bodies of equal size will make greater or lesser angles in their pyramids according to the different distances between the one and the other. By a pyramid of lines, means those which depart from the superficial edges of bodies and converge over a distance to be drawn together in a single point” (Leonardo da Vinci)¹.
Data integration and overlays are very common with perspective views because it allows traditional flat images to become new products by incorporating an elevation component and providing a new look at the same data. It is also probably used more so for visual appeal then as another method of extracting data.
Sample image on the right is a 3D perspective view of Cape George, Nova Scotia (just north of Antigonish), created with LandSat imagery drapped over a digital elevation model (DEM).
[* quote 1 is from – O’Connor and Robertson (2003) Mathematics and art – perspective www-groups.dcs.st-and.ac.uk/~history/HistTopics/Art.htmlJanuary]
3D Perspective View Related Links
The following images are a few enhanced LandSAT images of Trout Lake, Nova Scotia (popular fishing place on the South Mountain – south of the town of Middleton) created using PCI Geomatica.
This poster is of a mosaic of multi-temporal infra red LandSat imagery of the Annapolis Valley in Nova Scotia. The top image is a false color composite (FCC) using LandSat bands 7,4 and 3. The bottom image image is a true color composite using LandSat bands 3,2 and 1. It was one of the first image mosaics that I ever created with PCI orthoengine while studying remote sensing at COGS in 1999.