This document discusses spectral signatures and remote sensing. It begins by defining remote sensing as observing objects from a distance without direct contact using sensors. Spectral signatures are defined as the pattern of electromagnetic radiation that identifies a chemical or compound. Different materials can be distinguished by what portions of the electromagnetic spectrum they reflect and absorb. The most common portions used in remote sensing are ultraviolet, visible, infrared, microwave, and LiDAR. Spectral signatures allow identification of different materials from their unique reflectance and absorbance patterns across wavelengths.

1. This material is based upon work supported by the National
Science Foundation under Grant No. DUE ATE 1205069. Any
opinions, findings, and conclusions or recommendations
expressed in this material are those of the author(s) and do not
necessarily reflect the views of the National Science Foundation.
iGETT Concept Module
Spectral Signatures

2. What is ‘remote sensing’?
Remote sensing refers to the activities of
recording/observing/perceiving (sensing) objects or events at far away
(remote) places. In remote sensing, the sensors are not in direct
contact with the objects or events being observed.

3. What is ‘remote sensing’?

4. ‘Spectral signature’ defined
• The pattern of electromagnetic radiation that identifies a
chemical or compound.

5. ‘Spectral signature’ defined
• The pattern of electromagnetic radiation that identifies a
chemical or compound.

6. ‘Spectral signature’ defined
Objects and materials can be distinguished from one another by
interpreting the portions of the spectrum they reflect and absorb.

7. Electromagnetic Spectrum
The electromagnetic spectrum can be drawn in several ways, but the
information will always be the same. In this example the wavelengths are
from largest to smallest in m to nm.

8. Electromagnetic
Spectrum
 Remote Sensing mainly uses
 Ultraviolet spectrum
 Visible spectrum
 Infrared region
 Microwave spectrum (RADAR)
 LiDAR (visible spectrum)

9. Electromagnetic
Spectrum
This is an interesting diagram to give you an idea about the size of a wavelength
and sources of the various wavelengths.

10. Spectral Signatures of Different Objects
The concept of a
"spectral
signature", another
name for a plot of
the variations of
reflected (or
absorbed) EM
radiation as
function of
wavelengths, gives
rise to the widely
used approach to
identifying and
separating different
materials or objects
using multispectral
data obtained by
remote sensors.

11. Spectral Signatures of Different Objects

12. Spectral Signatures of Different Objects

13. Landsat TM Channels and
Sample Spectral Curves
Landsat TM collects
information in bands, and
as shown here, each band
collects information from a
different range of
wavelengths. This
information, when
analyzed with digital
software, produces
spectral signature curves.

14. Thinking Critically – Questions to Ponder
 1. The approach to identifying and separating material types in remote
sensing images is possible due to what unique property of all materials?
 2. Define a spectral signature using the following terms, reflectance and
absorbance.
 3. Which portions of the electromagnetic spectrum are the most widely
used in remote sensing?
 4. In a spectral curve, what does the x axis represent?
 5. In a spectral curve, what does the y axis represent?

15. Thinking Critically – Questions to Ponder
 6. In the curve shown, at what
wavelength is reflectance fo rclear
water the highest? Where is
reflectance for vegetation the
highest.
 7. Examine the curve and explain
why vegetation would be higher in
reflectance in the visible green
portion of the electromagnetic and
lower in the blue and red portions?

16. Thinking Critically – Questions to Ponder
Answer Key
 1. The approach to identifying and separating material types in remote sensing
images is possible due to what unique property of all materials?
Objects and materials can be distinguished from one another by interpreting the
portions of the spectrum they reflect and absorb.
 2. Define a spectral signature using the following terms, reflectance and
absorbance.
A spectral signature is like a thumbprint, based on the unique reflectance and
absorbance patterns of objects.
 3. Which portions of the electromagnetic spectrum are the most widely used in
remote sensing? Ultraviolet, Visible, Infrared, Microwave, LiDAR
 4. In a spectral curve, what does the x axis represent? Wavelength.
 5. In a spectral curve, what does the y axis represent? Percent Reflectance.

17. Thinking Critically – Questions to Ponder
Answer Key
 6. In the curve shown, at what
wavelength is reflectance for water the
highest? Where is reflectance for
vegetation the highest.
Water is highest at 450 nm
Vegetation is highest at 800 nm
 7. Examine the curve and explain why
vegetation would be higher in reflectance
in the visible green portion of the
electromagnetic and lower in the blue
and red portions?
Vegetation reflects strongest in the visible
green wavelengths and absorbs the
strongest in the visible blue and red
portions of the electromagnetic spectrum
because plants use the read and blue
portions for photosynthesis and reflect
strongest in the green portions. This is why
plants appear green.

18. References
 Shelito, Bradley. 2012. Introduction to Geospatial Technologies.
W. H. Freeman, New York.
 Bhatta, Basudeb. 2011. Remote Sensing and GIS, 2nd ed. Oxford
University Press, India.
 Esri GIS Dictionary
http://support.esri.com/en/knowledgebase/Gisdictionary/brows
e
 The Remote Sensing Tutorial
http://www.fas.org/irp/imint/docs/rst/Homepage/Homepage.html
 http://missionscience.nasa.gov/ems/01_intro.html
 ENVI 5.0 Software, Excelis Corp. 2013.

19. This material is based upon work supported by the National
Science Foundation under Grant No. DUE ATE 1205069. Any
opinions, findings, and conclusions or recommendations
expressed in this material are those of the author(s) and do not
necessarily reflect the views of the National Science Foundation.
iGETT Concept Module
Spectral Signatures
Module Created by Michelle Kinzel,
kinzelm@cox.net