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 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 Thematic Mapper (TM) sensor system on the Landsat satellite is a passive sensor. The land cover and change analysis data provided on this CD-ROM were classified using Landsat TM imagery. For more information about the land cover and change analysis data, click here.

Example of a Passive Sensor

Example of an Active Sensor

Active sensors are different from passive sensors. Unlike passive sensors, active sensors require the energy source to come from within the sensor. For example, a laser-beam 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. Topographic LIDAR laser beach mapping data included on this CD-ROM were collected with an active sensor. For more information about LIDAR data, please visit the LIDAR Beach Mapping Introduction.

What Can You Do with Remotely Sensed Data?

A 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 used 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.

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 to better manage ocean resources. Other oceanic properties satellite imagery can measure include chlorophyll concentrations, water temperature, wave heights, sea surface winds, and sea ice.

LIDAR Data Used to Map Beach Front 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. A hazard event 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 asses the damage following an event.

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.

Incorporating Remote Sensing Data into a GIS

Remote sensing and GIS technologies were initially developed for different purposes. However, both of these resources can provide information about the earth's resources. Advancements in computer hardware and software technology now make it possible for data from these sources to be easily integrated.

Most GIS software packages allow remotely sensed data to be imported, or at least viewed, within the software application. This ability allows the analyst to overlay remote sensing data layers with other spatial data layers. Analysts use remotely sensed imagery with GIS data sets for a variety of reasons, including providing a continuous regional view of the areas and extracting GIS data layers, such as contours or building footprints.

A Digital Ortho Quarter Quads (DOQQ) Data Overlaid with a Road Coverage.