The Earth is constantly under observation from dozens of
satellites orbiting the planet and collecting data. They are
engaged in something called "remote sensing: the
act of obtaining information about something without being
in direct contact with it.
Weather reports are one familiar application of
this information-gathering technique. The satellite images,
as well as the actual predictions, are obtained through remote
sensing of the Earth. The satellites don't gather the information
themselves; they simply orbit the Earth and provide platforms
from which the sensors can observe
large areas of the surface. Airplanes also
provide platforms for remote sensing, and some sensors operate
Remote sensing satellites are launched
by government agencies such as NASA (National Aeronautics and
Space Administration), and are usually equipped with sensors
that serve a particular purpose. For example, the National Oceanic
and Atmospheric Administration (NOAA) maintains the Geostationary Operational Environmental
Satellite (GOES), which is a platform for monitoring weather
with sensors that collect images of clouds.
Many types of sensors collect electromagnetic information. Microwave
radiometers, laser meters, magnetic sensors and cameras all gather
different types of data that can be interpreted to derive accurate,
large-scale information about the Earth's surface and atmosphere.1
Because these data and images are digital, they can easily be
quantified and manipulated using computers. This makes remote
sensing a uniquely versatile tool, since the same data can be
analyzed in different ways for different applications. Some of
the fields that use remote sensing are agriculture, geology, archaeology,
oceanography, and even architecture.
In this Discovery Guide we will discuss remote sensing through
the field of forestry. Forests are an important global resource
that human populations depend on for wood, air quality, recreation
and many other uses. They also serve as habitats for millions
of plant and animal species. Both commercial and non-commercial
forestry utilize a particularly diverse range of remote sensing
applications. Traditionally, obtaining information about forests
was achieved by sending a team of scientists into forest to physically
sample small areas of that forest.
The scientists then had to extrapolate
the data and apply the findings to the entire forest.Using remote
sensing, foresters can get more accurate and cost-effective
information, and can directly observe as large an area as necessary.
Due to the versatility and scale of remote sensing, it is invaluable
in all stages of forest management. The forester's task begins with growing healthy forests.
Remote sensing is a useful tool for assessment of environmental
conditions, either in an existing forest or prior to planting
a new one.
Data for climate analysis can be obtained through
microwave or radar sensing, which is ideal for gathering information
about the atmosphere, because, unlike photographic
or video methods, it allows continuous observation regardless
of light or weather conditions. This provides an uninterrupted
flow of accurate data for interpretation, and long-term observations
can be compiled to monitor climate changes.
These data can be used to track rainfall and winds, as well as measure
water and ozone content in the air. Analysis of the data can
help determine the compatibility of the climate with forest
growth, and predict potential problems.
Hydrology is another factor that is critical to forest growth.
Landsat Thematic Mapper (TM) surface hydrology Scanning Multichannel
Microwave Radiometer (SMMR)2
data provide information about soil moisture, the central
component of forest hydrology. Analysis of these data
allows for tracking of other factors such as evaporation
and runoff. Quantitative analysis
of terrain, shown by aerial photography images, is another source
of data for hydrological modeling. These analyses enable foresters to
determine water availability and to predict droughts and flooding.
The composition and viability of a forest may be determined using
a combination of remote sensing and Geographic Information Systems
GIS is a decision-making tool based on geographically referenced
information. GIS uses different levels of geographical information,
such as elevation, hydrology, or location of roads and infrastructure,
to create a multi-layered representation of a site. Some remote
sensing methods that are used in combination with GIS are aerial
videography and Thematic Mapper sensing. These data are available
for large areas and can be interpreted to provide information on
forest age, tree species distribution, and even estimated timber
Forests are often at risk of being destroyed by
forest fires. Remote sensing can be used in efforts to reduce
the risk and minimize damage if a fire occurs. Weather information,
such as measurements of precipitation and temperature, allows
foresters to calculate risk assessments and isolate the areas
most susceptible to fire. Those areas can be closely monitored by satellites, such as
high resolution Advanced Very High Resolution Radiometer (AVHRR)3 and Satellite Pour l'Observation
de la Terra (SPOT).4 Images
from these satellites are readily available and small fires
show up on them almost immediately.
Remote sensing contributes to fire-fighting efforts, as well.
Data on wind direction and speed, and the dryness of surrounding
areas can help predict the directions and speed at which a
fire spreads. With this information, firefighters can be dispatched
with maximum effectiveness and safety, and fires can be put
out before they cause much damage.
Radar and thermal sensing allow for constant observation
of fires, unaffected by clouds, smoke, or other conditions
that hinder aerial observation.
After a fire, damage can be quickly and inexpensively assessed by using AVHRR or
Landsat Thematic Mapper data. With accurate information on the
area of the burn scar, amount of biomass
destroyed and the amount of smoke and air pollution, forest
managers can efficiently proceed with recovery and planning.
During every stage of forest management, foresters can use
remote sensing data to estimate future urban spread and
population growth. Then, forest management can be planned taking
into account the future needs of settlements. Urban planning
data can also be applied to the management of urban forestry,
to create inventories of trees in parks and on streets.
The logical extension of commercial forestry is logging,
and the nature of the industry requires long-term planning
for cutting and regrowth. The accurate data from aerial photography
and satellite images are used for planning and monitoring
of these activities.
Before logging can take place, GIS assessments of forest ecosystems are performed to assess the
impact on local wildlife species. This is another application
of GIS, which usually uses SPOT or AVHRR satellite data to map
regions where animal habitats are located. A remotely sensed
tree species inventory can be used to identify rare or endangered
plant species, as well as the habitats of animal species, based
on the type of surrounding land cover.
Once the distribution of species is known, it can be incorporated
into detailed and extensive maps, which are used to plan logging
and regrowth. By using remote sensing data, foresters can
make optimally informed decisions. They can be aware of the
species distribution in a forest, the projected yields from
logging, which areas contain habitats that cannot be disturbed,
and how much land is needed for growth of settlements. After
sections of forest are cut down, GIS and aerial photography
techniques can be used to assess the speed and success of
For ship route planning, Synthetic Aperture Radar (SAR) data
is transmitted to ships in real-time. SAR systems provide
long-range, high resolution images using extensive electronic
processing of data, and can monitor the ocean surface and
detect wave height and movement. Scatterometers, high frequency microwave radar sensors designed to sense ocean surface condition, are used to measure wind speed and direction at the surface.
Combined data from these sensors provide reliable information on ocean activity and facilitate efficient route
Ships also rely on radar weather
predictions and sea ice detection for safe navigation.
Storms are exhaustively mapped using remotely sensed wave and wind
information in combination with buoy data, and sea ice tracking
is done using microwave sensors in combination with high-resolution
satellite imagery such as AVHRR.
Ships themselves are tracked with radar to pinpoint their
location and proximity to other ships. Using up-to-date remote
sensing information, ships can travel via the most efficient
routes, and can avoid hazardous conditions and collisions
to transport timber without losses.
Finally, if an accident does take
place during shipping, remote sensing can be used to minimize
Rescue personnel use radar and aerial sensing to quickly
locate a damaged ship. In the case of an oil spill, remote sensing
information can be used to map the extent of the spill and track
its spread by monitoring wave movement and wind speed.
By making shipping more effective, remote sensing
aids the forestry industry at the end as well as the beginning
of the timber cycle. From growing and monitoring healthy forests
to transporting the resulting timber to its destination, remote
sensing is a valuable tool for forestry. However, forestry is
only one example of the vast number of uses of remote sensing.
With the use of multiple sensors and varied data collection
and interpretation techniques, remote sensing is a versatile
tool that can provide data about the surface of the earth to
suit to any need.
- See NASA's Remote
Sensing Tutorial for details on sensor technology.
- More information regarding SMMR and the Nimbus
satellite can be found at The
Nimbus 7 Spacecraft System site.
- Carried by NOAA's Polar Orbiting Satellites
(POES), the AVHRR is a scanner that senses in the visible, near-infrared
and thermal infrared portions of the electromagnetic spectrum.
- The SPOT satellites, operated by the French
Space Agency, Centre National d'Etudes Spatials, carry HRV (High
Resolution Visible) sensors that are capable of producing images
at a higher resolution than the AVHRR.