1. Hyperspectral remote sensing
The topic of my research is Georferencing of images by exploiting geometric distortions in stereo images of UK DMC. And this is my preliminary defense presentation.
Contact:
Mirza Muhammad Waqar

2. Contents Data Cube – A way to visualize the data The Ultimate Benefit
Introduction
What is Hyperspectral Sensing
Hyperspectral vs Multispectral
Data Cube – A way to visualize the data
The Ultimate Benefit
Imaging Spectrometry Concept
Spectrometry
Imaging Spectrometry
n-Dimensional Data
These are the contents of my presentation.

3. Overview
In previous lessons, you were introduced to extraction of thematic information from the spectral content of digital multiband imagery.
You learned to manipulate various
Band combinations for display and analysis
Performed simple classification and change detection using classified and unclassified imagery.
Performed advance classification techniques

4. Cont… The same concepts can be applied to hyperspectral imagery, but
Hyperspectral image analysis is much more complex than multispectral

5. Objectives
Explain the fundamental principles of hyperspectral remote sensing
Explain the georeferencing and radiometric calibration of hyperspectral data
Identify standard hyperspectral mapping products and applications
Explain the basic principles of hyperspectral image analysis

6. Introduction
Remote sensing involves examination of features observed in several regions of electromagnetic spectrum.
Multispectral remote sensing is based upon use of several broadly defined spectral regions
Hyperspectral remote sensing is based upon examination of many narrowly defined spectral channels.

7. Cont… Hyperspectral remote sensing combines imaging and spectroscopy
Generally 100 to 200 or more narrow spectral bands (5 – 10 nanometers wide)
Compared to multispectral sensors with typically 4 to 12 spectral bands (70 – 100 nm wide)
Generates large data sets
Requires new / different analysis methods

8. What is Hyperspectral Sensing?

10. Multispectral vs Hyperspectral

12. Data Cube – A way to visualize the data

13. Diagnostic / identifying characteristics are lost in wide bands
The Ultimate Benefit…
Diagnostic / identifying characteristics are lost in wide bands

14. Imaging Spectrometry Concept

15. Analysis Approach
Direct identification using diagnostic absorption and reflection features
Comparison to laboratory and field measured spectra

16. Spectroscopy
Spectroscopy pertains to the dispersion of an object's light into its component colors (i.e. energies)
Spectroscopy can be used to detect individual absorption features due to specific chemical bonds in a solid, liquid, or gas
By performing this dissection and analysis of an object's light, one can infer the physical properties of that object (such as temperature, mass, luminosity and composition, etc.)
Continuous spectra
Discrete spectra
Emission line spectra
Absorption line spectra

17. Continuous vs Discrete Spectra

18. Image Spectroscopy
Imaging spectroscopy is a new tool that can be used to map specific materials by detecting specific chemical bonds
It is an excellent tool for environmental assessments, mineral mapping and exploration, vegetation species and health studies, general land management studies, and others

19. Cont…
Hyperspectral imaging is the simultaneous acquisition of images in many narrow, contiguous, spectral bands
Each pixel in the remotely acquired scene has an associated spectrum similar to the spectra of the material / mineral obtained in the laboratory

21. Properties of a Spectrometer
Parameters that describe the capability of a spectrometer
Spectral range
Spectral bandwidth
Spectral sampling
Signal-to noise ratio
FWHM = Full Width at Half Max

22. Spectral resolution – Sampling Interval
Spectral resolution = narrowest spectral feature
that can be resolved by a spectrometer (full width at half maximum FWHM)
Spectral sampling interval = interval, in wavelength units,
between data points in the measured spectrum.
Spectral bandwidth
used for spectral sampling interval)

24. Properties of a Spectrometer
Parameters that describe the capability of a spectrometer
Spectral range
Spectral bandwidth
Spectral sampling
Signal-to noise ratio

25. Goniometer

26. ASD Fieldspec Pro

27. ASD Fieldspec Pro

28. ASD Fieldspec Pro

29. GER 3700

30. PIMA II PIMA (Portable Infrared Mineral Analyser)
Spectral range 1300 – 2500 nm
Spectral resolution 7nm, interval 2-4 nm
Measurement is made in contact mode
Measurement time seconds
Produces reflectance spectra
Spectra measured on a sample area of about 10 mm by 2 mm
Internal illumination (does not need solar illumination)
Internal reflectance standard, wavelength calibration uses internal target

31. PIMA II (cont’d)

32. Spectral Libraries
SLI’s are collections of spectra different surface materials.
Often grouped by surface type (vegetation vs. soils vs. man-made materials etc.) and sometimes by grain size fraction (influence on spectra).

33. Spectral Libraries (cont’d)
Usually measured under laboratory conditions with excellent spectrometers.
Availability
Publicly available SLI’s are included in ENVI
ASTER speclib on the internet
Create own from field/lab measurements
Create own from image (point measurements or average of ROI)

34. n-Dimensional Data
Hyperspectral data (or spectra) can be thought of as points in an n-dimensional scatterplot.
The data for a given pixel corresponds to a spectral reflectance for that given pixel.
The distribution of the hyperspectral data in n- space can be used to estimate
the number of spectral endmembers and their pure spectral signatures and to help understand
the spectral characteristics of the materials which make up that signature.

35. Vegetation Spectral Reflectance extracted from AVIRIS data

36. Questions & Discussion