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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Summary poster created to show GPS validation data collected for 2003 LIDAR survey of the Annapolis Valley. Poster was one of several presented at the Geomatics Atlantic 2003 Conference held at Acadia University in Wolfville, Nova Scotia and posted at the Applied Geomatics Research Group seminar room in Middleton, Nova Scotia.
The following co-authored paper featuring my graduate LiDAR research work at the AGRG was published in the Canadian Journal of Remote Sensing in 2006. Airborne light detection and ranging (LiDAR) has the spatial density and vertical precision required to map coastal areas at risk of flooding from water levels typically 1–2 m higher than predicted tides during storm surges. In this study …
While doing my graduate LIDAR research work at the AGRG we were often tasked with writing user guides for the equipment that we purchased to help others in the group know how to use it. Here is a user guide for the Leica Total Station (TCR1105) that covers the basic information about the unit itself and the equipment found in the case, how to prepare for the survey in the office, details about the user interface, how to operate the unit, and how to export the data after the survey.
Map created showing New Brunswick high precision monuments within and around 2003 AGRG LIDAR project study areas used to help plan LIDAR validation surveys.
Here is a summer GIS project that I worked on for Parks Canada.
The PDF technical report details the methodologies and issues that were encountered with a Spatial GIS vegetation database and GIS Spatial modeling project at the Applied Geomatics Research Group (AGRG) during the summer of 2004 that involved generating a spatial geographic database for Jeremy’s Bay Campground of Kejimkujik National Park and Historic Site. High resolution aerial photography acquired from a previous AGRG aerial photography mission was used along with extensive data collected during a Rapid Vegetation Assessment survey and a detailed forest stand interpretation.
salamanders; Kejimkujik has more amphibians and reptiles than anywhere else in the Atlantic Provinces. The park is also home to many birds, especially common loons, and fish which include brook trout and white and yellow perch. In Canada, National Parks are considered places where ecosystems and ecological integrity should be maintained and Kejimkujik National Park is no exception.
The project was divided into two main sections that were indirectly related to one other. The first major part of the project was the compilation of digital line work and the creation of a Geographic Information System (GIS) Spatial database of forest stands found within the campground. The second part of the project was focused on generating a GIS spatial database of the vegetation found within each campsite that was collected during a Rapid Vegetation Assessment (RVA) Survey.
Here is a poster generated with ESRI ArcGIS for a summer GIS project that I worked on for Parks Canada. [The PDF technical report details the methodologies and issues that were encountered with a Spatial GIS vegetation database and GIS Spatial modeling project at the Applied Geomatics Research Group (AGRG) during the summer of 2004 that involved generating a spatial geographic database for Jeremy’s Bay Campground of Kejimkujik National Park and Historic Site. High resolution aerial photography acquired from a previous AGRG (COGS) aerial photography mission was used along with extensive data collected during a Rapid Vegetation Assessment survey and a detailed forest stand interpretation.]
Color Shaded Relief (CSR) image generated from Bald Earth LIDAR points on the left, Middle image is of a Digital Surface Model generated with “All the LIDAR points” and on the right is an air photo for the same area. The area shown in the data samples are of Bouctouche in New Brunswick at a scale of 1:6000. Data sets were part of my gradute research work at the AGRG / COGS in 2003.