1. Lecture 20: Introduction to Remote Sensing Principles By Weiqi Zhou University of Vermont ------Using GIS-- Introduction to GIS Thanks are due to Austin Troy and Jarlath O’Neil Dunne, upon whose lecture much of this material is based, and whose graphics were used in many slides for this lecture

2. ©2007 Austin Troy What is remote sensing Maximal Definition: “remote sensing is the art and science of obtaining information about an object without being in direct physical contact with the object” (Jensen, 2000) Minimalist definition: “remote sensing is the noncontact recording of information from the ultraviolet, visible, infrared, and microwave regions of the electromagnetic spectrum by means of instruments such as cameras, scanners, lasers, linear arrays, and/or area arrays located on platforms such as aircraft or spacecraft, and the analysis of acquired information by means of visual and digital image processing.” (Jensen, 2000) Introduction to GIS

3. ©2007 Austin Troy What is remote sensing Key components of remote sensing – Data collection The instrument (Sensor): Recording information of electromagnetic energy from an object or area Noncontact: View from space by locating sensors on aircrafts or spacecrafts – Data analysis: Visual and digital image processing Introduction to GIS

4. ©2007 Austin Troy Why remote sensing Remotely sensed imagery is the original source for most of the GIS data we use. Local and global coverage: Global monitoring is possible from nearly any site on earth. Repetitive coverage (time series): Look at changes in the environment. Sensors can measure energy at wavelengths which are beyond the range of human vision (ultra-violet, infrared, microwave). Introduction to GIS

5. ©2007 Austin Troy Some Applications Planning and transportation – Road updates – Infrastructure monitoring – Growth monitoring Introduction to GIS Source: Halcon

6. ©2007 Austin Troy Some Applications Natural resource mapping – Urban Lawns – Lawn conditions – Crop conditions – Yield estimation Introduction to GIS Clubroot disease Source: NGIC

7. ©2007 Austin Troy Some Applications Natural resource mapping Land use change analysis Habitat and natural communities mapping Introduction to GIS Source: TRIC

8. ©2007 Austin Troy Some Applications Environment monitoring: Algae bloom Introduction to GIS

9. ©2007 Austin Troy The Physics of RS Remote sensing data are collected in the electro- magnetic radiation (EMR) spectrum, principally the visible, infra-red and radio regions – Passive RS systems collect data on energy that is reflected or emitted from the earth; most systems are passive – Active RS systems: such as lasers and radars that emit their own EMR Most RS systems record reflectance in multiple wavelengths spectrums Introduction to GIS

10. ©2007 Austin Troy Passive vs. Active Introduction to GIS Source: http://rst.gsfc.nasa.gov/Intro/

11. ©2007 Austin Troy Electromagnetic Radiation (EMR) Energy from the sun travels to Earth through space as electric and magnetic waves, or electromagnetic radiation(EMR) EMR exists across a range of wavelengths, referring to distance between two peaks Introduction to GIS Source: http://rst.gsfc.nasa.gov/Intro/Part2_2.html

12. ©2007 Austin Troy Electromagnetic Spectrum The range of electromagnetic radiation, extending from Gamma ray to radio waves, is known as the electromagnetic spectrum (EMS) Introduction to GIS Source: http://www.sci-ctr.edu.sg/ssc/publication/remotesense/em.htm Only 2% of EMS

13. ©2007 Austin Troy Energy Interactions with Terrain Light can either be reflected, absorbed or transmitted. Most sensors record the reflected light. Introduction to GIS Source: http://landsat.usgs.gov

14. ©2007 Austin Troy Reflectance Reflection is emission of photons caused by excitation of the surface, due to incident radiation Reflected E = incident E - absorbed and transmitted E Spectral reflectance:  = E(r)  E(i) Or the proportion of reflected to incident radiation – Reflectance is a function of wavelength: varying in each wavelength – This is why two features may appear similar in the same wavelength band, but distinguishable in different wavelength band Introduction to GIS

15. ©2007 Austin Troy Reflectance Each class of objects has a different spectral responses across wavelength RS sensors can detect spectral responses from objects in various wavelength ranges. Spectral reflectance curve – Spectral reflectance values of an object can be plotted on a graph as a function of wavelength – Each object feature class on the earth has a spectral reflectance curve that helps us to identify it remotely. Introduction to GIS

16. ©2007 Austin Troy Reflectance Curve The wavelengths in which it is reflected determine the color of the object Introduction to GIS High Low BlueGreenRed Reflectance 0.4  m 0.5  m0.6  m 0.7  m White Light Green Blue Red Source: Jarlath O’Neil-Dunne

17. ©2007 Austin Troy Spectral Reflectance Curve A spectral reflectance curve for several very different classes of object Introduction to GIS Source :Lillesand and Kiefer 2000. Remote Sensing and Image Interpretation Wiley and Sons

18. ©2007 Austin Troy Spectral Reflectance Curve Introduction to GIS Source: Jarlath O’Neil-Dunne

19. ©2007 Austin Troy Spectral Reflectance Curve Introduction to GIS Example: identify appropriate bands to differentiate objects by using spectral reflectance curve. Source :Lillesand and Kiefer 2000

20. ©2007 Austin Troy Reflectance differs by wavelength Introduction to GIS Panchromatic B&W: can’t tell deciduous from conifer Source :Lillesand and Kiefer 2000 Infrared B&W: can clearly see deciduous because higher reflectance in those wavelengths

21. ©2007 Austin Troy Reflectance differs by wavelength Introduction to GIS © Space Imaging Green ReflectanceNIR Reflectance

22. ©2007 Austin Troy The Physics of RS Introduction to GIS RS sensors’ ability to sense in these non-visible wavelengths allow us to visualize things we normally could not perceive with the human eye, like water temperature Source :Lillesand and Kiefer 2000

23. ©2007 Austin Troy The Physics of RS Introduction to GIS Here’s one showing suspended sediment in San Francisco Bay Source :USGS

24. ©2007 Austin Troy Light Interactions with the Atmosphere Introduction to GIS Affecting incoming and outgoing EMR through scattering, refraction, and absorption: modify the direction and penetration of EMR as it passes through the atmosphere Source: http://landsat.usgs.gov

25. ©2007 Austin Troy Light Interactions with the Atmosphere Scattering, refraction, and absorption: modify the direction and penetration of EMR as it passes through the atmosphere – Scattering: degrades the image in shorter wavelengths, particularly the ultraviolet and blue – Refraction: change the direction and speed of light (predictable) – Absorption: radiation energy is absorbed and converted into other forms of energy. Introduction to GIS

26. ©2007 Austin Troy Light Interactions with the Atmosphere Many wavelengths are also absorbed by gases in the atmosphere, including CO 2 and O 3 Introduction to GIS Source :Lillesand and Kiefer 2000

27. ©2007 Austin Troy So, what are RS data? RS imagery is raster data. Introduction to GIS Each pixel has a geographic coordinate and reflectance/intensity value, or digital number (DN).

28. ©2007 Austin Troy Display of RS data Grayscale image: One band, with each pixel represented by a grayscale value Multispectral Display – Combining 3 bands, assigned to the three color channels (red, green, blue). True color composite: Colors in the image roughly correspond with the colors in the real world False color composite: Showing colors that don’t really exist in that location. Key: Showing best contrast between feature classes that may be indistinguishable to the human eye. Introduction to GIS

29. ©2007 Austin Troy Multispectral Display Introduction to GIS BLUE GREEN RED NEAR IR SHORT WAVE IR MID- WAVE IR LONGWAVE IR 1Landsat TM Band 234 5 7 6 Band Combination = 7 4 2 (LANDSAT) Color Guns = Band Composite Output = Source: Jarlath O’Neil-Dunne

30. ©2007 Austin Troy Display of Single Band Three bands, green, red and near infra-red displayed separately as grayscale Introduction to GIS green red Near- infra red

31. ©2007 Austin Troy Display of Multispectral Image True color composite (Natural color composite) Introduction to GIS Bands Applied to color RedGreenBlue Resulting Image

32. ©2007 Austin Troy Display of Multispectral Image False color composite Introduction to GIS BandsApplied to color Resulting Image Near Infrared Red Green

33. ©2007 Austin Troy Multispectral Display Assign bands to channels in the Layer Properties interface Introduction to GIS Grayscale Composite