introduction to hyperspectral data

Introduction to hyperspectral data

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Unformatted text preview: I N T R O T O H Y P E R S P Introduction to Introduction to Hyperspectral Imaging Hyperspectral Imaging with TNTmips® page 1 Introduction to Hyperspectral Imaging Before Getting Started For much of the past decade, hyperspectral imaging has been an area of active research and development, and hyperspectral images have been available only to researchers. With the recent appearance of commercial airborne hyperspectral imaging systems, hyperspectral imaging is poised to enter the mainstream of remote sensing. Hyperspectral images will find many applications in resource management, agriculture, mineral exploration, and environmental monitoring. But effective use of hyperspectral images requires an understanding of the nature and limitations of the data and of various strategies for processing and interpreting it. This booklet aims to provide an introduction to the fundamental concepts in the field of hyperspectral imaging. Sample Data Some illustrations in this booklet show analysis results for a hyper- spectral scene of Cuprite, Nevada. This scene was acquired using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which is operated by the NASA Jet Propulsion Laboratory. The same scene is used in the exercises in the companion tutorial booklet Analyzing Hyperspectral Images. You can download this scene in the TNTmips Project File format (along with associated sample data) from the MicroImages web site or contact MicroImages to obtain the data on a free CD-R. More Documentation This booklet is intended only as a general introduction to hyperspectral imaging. In TNTmips, hyperspectral images can be processed and analyzed using the Hyperspectral Analysis process (choose Raster / Hyperspectral Analysis from the TNTmips menu). For an introduction to this process, consult the tutorial booklet entitled Analyzing Hyperspectral Images. Additional background information can be found in the booklet Introduction to Remote Sensing of Environment (RSE). TNTmips® and TNTlite® TNTmips comes in two versions: the professional ver- sion and the free TNTlite version. This booklet refers to both versions as “TNTmips.” If you did not purchase the professional version (which requires a hardware key), TNTmips operates in TNTlite mode, which limits object size and does not allow preparation of linked atlases. Randall B. Smith, Ph.D., 14 July 2006 ©MicroImages, Inc., 1999-2006 It may be difficult to identify the important points in some illustrations without a color copy of this booklet. You can print or read this booklet in color from MicroImages’ web site. The web site is also your source for the newest Getting Started booklets on other topics. You can download an installation guide, sample data, and the latest version of TNTlite. page 2 Introduction to Hyperspectral Imaging Welcome to Hyperspectral Imaging Multispectral remote sensors such as the Landsat Thematic Mapper and SPOT XS produce images with a few relatively broad wavelength bands. Hyperspectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow, adjacent spectral bands. These measurements make it possible to derive a continuous spectrum for each image cell, as shown in the illustration below. After adjustments for sensor, atmospheric, and terrain effects are applied, these image spectra can be compared with field or laboratory reflectance spectra in order to recognize and map surface materials such as particular types of vegetation or diagnostic minerals associated with ore deposits. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of ground materials we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. Images acquired simultaneously in many narrow, adjacent wavelength bands. The technological background of hyperspectral sensors is discussed on page 4. Pages 5-10 introduce the concepts of spectral reflectance of natural materials, spectra as vectors in n-dimensional spectral space, and spectral mixing. Factors contributing to the measured radiance values in an image are detailed on pages 11-13, followed by methods for converting from radiance to reflectance on pages 14-15. Strategies for analyzing hyperspectral images are discussed on pages 16 21, and a list of literature references is provided on pages 22-23. Set of brightness values for a single raster cell position in the hyperspectral image. A plot of the brightness values versus wavelength shows the continuous spectrum for the image cell, which can be used to identify surface materials. Relative Brightness 0.6 0.4 0.2 0.0 Spectral Plot 0.7 1.2 1.7 2.2 Wavelength (micrometers) page 3 Introduction to Hyperspectral Imaging The Imaging Spectrometer Hyperspectral images are produced by instruments called imaging spectrometers. The development of these complex sensors has involved the convergence of two related but distinct technologies: spectroscopy and the remote imaging of Earth and planetary surfaces. Spect...
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This note was uploaded on 12/16/2010 for the course ENV 148 taught by Professor Chang during the Spring '10 term at APU Japan.

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