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WHIS&T 2010

On November 19th, 2010 the AMETHYST Program hosted a workshop on Hyperspectral Imaging Science and Technology. This was the first occurrence of our annual workshop, and was a great success. The workshop included four internationally renowned speakers in hyperspectral imaging; presenting on a broad range of topics and were very well received. Their presentations have been recorded and made available for you below. Also, a brief introduction to the NSERC CREATE AMETHYST Program was presented by Dr. Phil Teillet, AMETHYST Principle Investigator.

 

For a complete agenda of the workshop, please see our AMETHYST WHIS&T 2010 Agenda.

 

Dr. Phil Teillet 

University of Lethbridge

“Introduction to the NSERC CREATE AMETHYST Program”

 


Dr. Vern Singhroy 

Canada Centre for Remote Sensing

“Geological Applications of Hyperspectral Images”

 

Abstract:

Hyperspectral imagery acquired using airborne systems have been used in the geologic community since the early 1980’s and represents a mature technology. The spectral range 0.4–2.5 μm provides abundant information about many important earth-surface minerals. In particular, the 2.0–2.5 μm shortwave infrared (SWIR) spectral range covers spectral features of hydroxyl-bearing minerals, sulphates, and carbonates common to many geologic units and hydrothermal alteration assemblages. Spectrally distinct minerals such as kaolinite, alunite, muscovite, and pyrophyllite all are important in natural resource exploration and characterization.


Dr. Richard Frayne 

University of Calgary

“Quantitative Techniques in Neuroimaging”

 

Abstract: 

Medical imaging provides for novel assessments of both normal and abnormal function in the human brain. Magnetic resonance (MR) imaging, in particular, is a wide spread technology that allows for unprecedented imaging of the human brain without needing ionizing radiation. Today, MR imaging is used in a variety of clinical and research applications. An MR image consists of a matrix of image intensity values. In principle these values are quantitative. However in a typical MR image they are generally utilized in a relative manner, as each image pixel often has a complex dependence on scanner-specific properties. Indeed, underlying each image are the intrinsic (and quantitative!) contrast mechanisms of the nuclear magnetic resonance phenomenon, such as T1 and T2 relaxation. Relative MR data provide valuable information about the anatomical structure of the brain, allowing an experienced radiologist to be able to identify abnormal structures or morphological changes related to pathological processes or abnormalities. Nonetheless, relative signal changes on T1-weighted, T2-weighted, or a number of other types of MR images potentially can also be used in a quantitative fashion to potentially better identify abnormal tissue. The potential exists to see earlier or subtler disease changes with quantitative MR images and assessment tools. Applications in cerebrovascular disease and epilepsy will be used to illustrate this potential.

 


Dr. Olaf Niemann 

University of Victoria

“Hyperspectral Remote Sensing of Forested Environments: The case for multisensor data for feature extraction from a radiometrically porous surface

 

Abstract:

Forested environments (and wild lands in general) provide us with a series of unique challenges when applying remotely sensed data. These surfaces are 3-dimensional at the same time as being “radiometrically porous” so that our prediction or understanding of the relationships between material and radiometric properties is inconsistent at best. The porosity of the reflective surface of a forested environment affects our data in two ways. First, there is considerable leakage of radiometric information from different reflectors within a canopy that limits as to how well we can extract “pure reflectors”. Second, this leakage increases with increases in pixel size. Typical remote sensing using optical or microwave data is of low spatial dimensionality leading to relatively low quality feature extraction. While hyperspectral data have increased our ability to discriminate some of the nuances of the reflecting object, these data still limit our ability to extract many of the attributes of interest. We need to integrate multidimensional data so that we can get insights on both form and functioning of the reflecting surface as well as accounting for the porosity of the forest surface.

 


Dr. Ann-Lise Norman

University of Calgary

 “Determining Trace Gas & Aerosol Origins: How Can Spectral Analysis Help?”

 

Abstract:

Isotope ratio techniques are currently used to identify and quantify the origins and transformations of compounds in the atmosphere. The oxidation of a sulphur gas, dimethyl sulphide, to sulphur dioxide and sulphate, which in turn may nucleate to form cloud condensation nuclei, is an example where isotope apportionment is used to distinguish the source of atmospheric sulphate, a key component of the global radiation budget. Other applications of isotope techniques to trace gas and particle analysis include determining the source of volatile organic compounds, a class of organic pollutants that oxidize and condense forming fine aerosols that are inhalable deep into the lungs, affecting the health of individuals downwind. Field sampling for such studies typically consists of sampling hundreds if not thousands of litres of air which are filtered and/or processed in a laboratory in order to obtain a single analysis. Satellite and ground-based spectral techniques have been developed that can be used to detect the concentration of a number of atmospheric compounds. However, in situ measurement of isotope ratios for atmospheric components remains a challenge. This talk will present an overview of atmospheric apportionment studies with a view to identify where new developments in spectral analysis could be used to greatly diminish the labour involved in atmospheric isotope measurements.