Satellite Remote Sensing of Coral Reefs: By Learning about Coral Reefs, Students Gain an Understanding of Ecosystems and How Cutting-Edge Technology Can Be Used to Study Ecological Change

Article excerpt

Coral reefs are one of the most important ecosystems on the planet, providing sustenance to both marine organisms and humans. Yet they are also one of the most endangered ecosystems as coral reef coverage has declined dramatically in the past three decades. Researchers continually seek better ways to map coral reef coverage and monitor changes over time. In recent years, satellite remote sensing has become a popular and effective mapping tool for ecological studies, especially in marine science.


In this article we present a lesson plan for high school science students that demonstrates how marine scientists use satellite remote sensing to gather detailed information about coral reefs worldwide. Before discussing the lesson plan, we provide an in-depth review of both remote sensing and coral reefs.

What is remote sensing?

In the broadest of terms, remote sensing is the study of one location from a different location. Remote sensing involves gathering data using sensors located at some distance from the target of study. Various types of sensors are used in remote sensing, including acoustical (sonar) sensors, optical (visible spectrum and infrared) sensors, and radar. These sensors can be carried on ships, airplanes, satellites, and even balloons.

Certain satellite sensors measure the amount of light emitted and/or reflected from Earth's surface at specific wavelengths in the electromagnetic spectrum (Figure 1). A researcher then interprets the measurements and determines what the data may imply. A simple analogy is human vision: Humans use their eyes as sensors, which gather sight information; the information is then sent to the brain, which interprets what the eyes see.

Satellites provide an extraordinary amount of detailed information about Earth's surface. Scientists use this information for a variety of applications, such as managing renewable and nonrenewable resources. For example, scientists use satellites to measure a suite of environmental factors, including

* ocean color (a proxy for primary productivity),

* temperature (sea-surface and terrestrial),

* land cover and usage (e.g., human-made versus natural),

* benthic cover (underwater habitats),

* winds,

* topography and bathymetry, and

* hurricanes.

In fact, satellites provide the only tool to study processes that affect the entire planet at one time by giving researchers a way to see the whole Earth at one time. Certain satellites (e.g., Landsat) have been designed to look at Earth in small detailed pieces, specifically the terrestrial and coastal zones.

Landsat satellites

The first Landsat, launched in 1972, was primarily used to study agriculture and to determine the size and yield of a farm or field. Landsat 7, launched in 1999 by the National Aeronautic and Space Administration (NASA), is the current satellite and is often used for marine and coastal studies. The United States Geological Survey (USGS) is responsible for the archive of all Landsat data and has at least one cloudfree image of every known shallow-water coral reef in the world (approximately 1,500 images).

Landsat 7 follows a polar orbit (north-south) in conjunction with Earth's rotation (west-east). An orbit cycle is complete when the satellite retraces its path and passes over the same spot on Earth's surface. This takes 16 days and is termed the satellite's temporal resolution. Landsat 7 carries a sensor called the Enhanced Thematic Mapper Plus (ETM+), which has a spatial resolution or footprint, of 30 m. Therefore, any object smaller than 30 m cannot be detected or identified, as it is smaller than the footprint frame that encompasses that object. This means that when an image is displayed at full resolution, each pixel (picture element or smallest unit of an image) represents an area of 30 m X 30 m on the ground (image pixels are typically squares that depict a specific area on an image). …


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