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Remote Sensing: An Overview


Different Types of Remotely Sensed Images
Examples of Remotely Sensed Data Sets



What is Remote Sensing?

Remote sensing is a technique used to collect data about the earth without taking a physical sample of the earth's surface. A sensor is used to measure the energy reflected from the earth. This information can be displayed as a digital image or as a photograph. Sensors can be mounted on a satellite orbiting the earth, or on a plane or other airborne structure.
There are two basic types of sensors: passive and active sensors. Passive sensors record radiation reflected from, or emitted by, the earth's surface. The source of this radiation must come from outside the sensor; in most cases, this is solar energy. Because of this energy requirement, passive solar sensors can only capture data during daylight hours. The Advanced Very High Resolution Radiometer (AVHRR) sensors on the National Oceanic and Atmospheric Administration's (NOAA) polar orbiting satellites and the Thematic Mapper (TM) sensor system on the Landsat satellite are passive sensors. Example of a Passive Sensor
Example of a Passive Sensor
Example of an Active Sensor
Example of an Active Sensor		 Active sensors, unlike passive sensors, require the energy source to come from within the sensor. For example, a laser remote sensing system is an active sensor that sends out a beam of light with a known wavelength and frequency. This beam of light hits the earth and is reflected back to the sensor, which records the time it took for the beam of light to return.

For more detailed information on how remote sensing works, proceed to Remote Sensing Fundamentals.

What Can You Do with Remotely Sensed Data?

Example of the Digital Shoreline for South Carolina
South Carolina Shoreline
Delineated from
Aerial Photography

Coastal Applications
Remote sensing data can be an asset to coastal resource managers by providing a pictorial representation of coastal processes. For example, remote sensing data can be used to monitor and evaluate shoreline changes both pre- and post-beach renourishment and to study shoreline and bluff erosion. Other coastal applications of remote sensing data include mapping intertidal zones and their features, delineating the shoreline, mapping coastal features (including vegetation), studying sediment transport, developing bathymetric models, extracting building outlines for use in a geographic information system (GIS), and evaluating the effects of human impact.



Example of Sea Surface Temperature for the Carolina Coast
Sea Surface Temperatures
for the Carolina Coast

Oceanic Applications
Large-scale events such as ocean circulation, current systems, upwelling, and eddy formation can be better understood by using satellite imagery. Learning how these events work could provide managers insight into how better to manage ocean resources. Other oceanic properties that satellite imagery can measure include chlorophyll concentrations, water temperature, wave heights, sea surface winds, and sea ice.


Example of How LIDAR Can Be Used to Map Beachfront Property
LIDAR Data Used to Map
Beachfront Property

Hazard Assessment
As more people migrate toward the coast, it is important for coastal resource managers and other planners to understand how hazards could impact coastal communities. Hazard events could include large storms, earthquakes, erosion, and flooding. Remote sensing can be used both to aid in identifying resources prior to an event and also to assess the damage following an event.


North Inlet National Estuarine Research Reserve Boundary Overlaid on Satellite Imagery
North Inlet National Estuarine
Research Reserve Boundary
Overlaid on Satellite Imagery

Natural Resource Management
With the increase in urban sprawl and recreational use of natural areas, habitat assessment and natural resource management are becoming important topics for coastal resource managers. Remote sensing data sets can be used to monitor urban sprawl, map and inventory wetlands, and delineate wildlife habitat. Once the land cover has been mapped, repeated collection of remote sensing data can be used to monitor and study the various types of habitat and vegetation.



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