For our last look at remote sensing, let's turn to some unusual kinds of imagery that might be useful for remote sensing and GIS. These fall into two categories: environmental satellites, such as weather satellites, and radar imagery. Neither have been used extensively in mapping or GIS, though radar continues to show some promise for new applications.
Landsat and the most of the other satellites mentioned in the previous page were specifically designed to gather data about local Earth resources, and to integrate those with other data as we can in a GIS. Another class of satellites, which we can call environmental satellites, aim less at detecting local conditions and more at characterizing regional environmental conditions.
Weather satellites
are among these satellites, and were some of the earliest
satellites in orbit. These satellites are generally in a geostationary
orbit, which means they orbit the Earth at such a speed that
they remain over the same location (Landsat and other
Earth-resources satellites usually use a sun-synchronous
orbit, where they orbit pole-to-pole and can sweep past
successively different areas of Earth in each pass). The
two US geostationary satellites are called Geostationary
Operational Environmental Satellites (GOES). Both GOES
satellites remain 36,000 km (22,000 miles) above the equator, one
at 75° West (views the eastern US), the other at 135° West
(views western US). The European Space Agency operates a
similar satellite called Meteosat over the Prime Meridian.
The images from these weather satellites cover a huge area, basically the full circular disk of Earth. The pixel resolutions are coarse, at several kilometers per pixel. These images are intended for regional monitoring of clouds and other weather conditions, and have rarely been used in detailed studies or GIS. But they are great for tracking storm systems and for the nightly TV weather report.
A number of other environmental satellites gather specialized data. The AVHRR sensor mentioned in the previous page is actually among these satellite sensors. Others include satellites from the US Defense Department, Russia and India.
Microwaves are one type of electromagentic energy, as we saw earlier. Since World War II, radar has used microwave energy for various remote detection purposes, including aircraft tracking, precipitation detection, and bird migration studies. Radar is unlike other remote sensing in that it does not rely on the Sun for the energy it detects. Instead, radar instruments generate a beam of microwaves, which strike objects and reflect back to the radar unit. The echo is then recorded and displayed as an image. Radar is therefore active remote sensing, as opposed to passive systems that rely on other energy sources.
Radar instruments have been carried in aircraft, on satellites and even on the Space Shuttle. Radar instruments normally survey the area off to one side of the craft. One type of radar imaging is called side-looking airborne radar (SLAR) for this reason. More recent radars use a technique called synthetic aperture radar (SAR) that allows very accurate topographic feature detection. For example, an experimental satellite called Seasat used SAR to detect the height of ocean waves from space!
One of the great advantages in radar is that its signals penetrate clouds. In locations with near-permanent cloud cover, such as tropical rainforests and some polar regions, radar can provide images that would be impossible with any other approach. The Amazon Basin was mapped in the 1970s using radar technology. The cloud-shrouded planet Venus has also been extensively mapped with radar.
Radar images
look quite different than images based on visible or even
near-infrared light. This difference is partly because the
image is side-looking rather than directly below the
instrument. But mostly the images look different because
many objects react differently to microwaves than to visible
light. Much of the reflectivity is based on the angle of
the object to the microwave source. A hill facing directly
toward (perpendicular to) the radar instrument shows up brightly
on a radar image. A hill facing mostly away is very dark
because little gets reflected back. Water and pavement tend
to be dark because the microwaves bounce away in the opposite
direction from the detector. Objects with lots of corners,
such as buildings and bridges, are bright because the microwaves
reflect several times around and back to the radar
instrument. Also, some materials are more reflective, such
as metal.
Radar images are also distorted from a true planimetric (map) perspective, so they cannot be used directly with other map data. But computer software is becoming available that allows correction of radar images for use with GIS.
The Space Shuttle has carried experimental radar systems in
missions over several years. Many of the Shuttle Imaging
Radar (SIR) images are availabe on-line at a
NASA Web site.
These images have been used, for example, to detect old channels
covered by surface sand in desert areas. The example shown
here is an SIR-C image of the San Francisco Bay Area.
Other countries have also launched satellites with radar
sensors, including Japan, Russia and the European Space
Agency. Canada launched
Radarsat in 1995,
which was especially intended to map ice conditions in the
arctic, but provides imagery for any location on Earth in a
customized format with spatial resolution down to 10 meters.
Remote sensing is a complex, rapidly-developing field. We've covered many of the basic ideas here, which should enable you to be aware of the kinds of imagery that are available. Most important, you hopefully have some ideas about where air photos or satellite imagery might be useful in work you might do later on. You might not understand the details yet, but the important point is to be familiar with the topic and know where to find more information. I will try to keep these exercises available at our Geography Department web site. Feel free to come back and review any of the exercises any time you want a refresher on a topic!
As usual, submit the answers to the questions in these pages to me (see address below) in an e-mail message. You can delete any data you may have generated during the exercises once you've gotten your assignment scores back. Thanks for paying attention and good luck with your future courses and career!
I'll assume you've read and understood the material here and don't need another question. However, keep in mind that the material will be covered on the final quiz. If you are confused about any material in this page or earlier pages, you can see me or e-mail a question to me or the class list.
Bryan Baker, Sonoma State
University, bryan.baker@sonoma.edu
Updated 17 February 1999