SPECTRAL ANALYSISIN ENVI®
The Basics of Spectral Data
Every object or material – whether solid, liquid, or gas – reflects or emits
electromagnetic energy in a distinctive way. Our eyes can only perceive
electromagnetic energy in shades of red, green and blue (RGB) – thisis called the visible spectrum. Spectral image analysis utilizes morebands from the electromagnetic spectrum to extract distinct spectral
characteristics and derive valuable information.
Spectral data is broken out into two
categories, multispectral (MSI) andhyperspectral (HSI). Multispectral imagery
generally has fewer, broader bands,
while Hyperspectral imagery consists ofmore, narrower bands. Spectra from MSI
imagery, like a Landsat or Sentinel-2 image,contains information that you can use to
identify a material class like vegetation,soil and impervious surfaces. HSI canoftentimes give the exact material types
such as weathered asphalt
versus concrete.

Spectral data has been around for many
years but until recently, compute powerand storage capacity have struggled withthe large size of the data. Having spectral
data at your disposal is only the first step.
In order to answer questions with the data,
you need to be able to quickly preprocess
it and easily and accurately extract
information from it.

ENVI SPECTR AL TOOLS ARE
THE INDUSTRY STANDARD> Advanced data preprocessing,critical for producing accurate
results> Tested, proven and reliable toefficiently handle large datasets> Beneficial to non-experts andexperts alike

ENVI Spectral Analysis
ENVI was initially developed by imaging experts to process and analyze HSI data andit continues to be the definitive leader in spectral analysis. ENVI includes hundreds ofspectral image processing tools to analyze MSI and HSI data and extensibility options toautomate your workflows. These tools are based on established, scientific methods forspectral analysis – using pixel responses at different wavelengths to obtain information
about the materials within each pixel. While initially developed with hyperspectral datain mind, most of the analysis tools in ENVI can be applied to multispectral data as well.
Typical Spectral Workflow
TargetDetection
Prepare Datafor Analysis

Spectral
Libraries

Visualization
MappingUnique
Materials

Indices

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SPECTRAL ANALYSIS IN ENVI ®
PREPARING DATA FOR ANALYSIS
A fair amount of preprocessing is needed to effectively use spectral data and extract
meaningful information from it. This includes radiometric calibration and correction,
atmospheric correction and geometric correction.
> Radiometric Calibration and Correction
ENVI provides tools to calibrate imagery from digital numbers to units of radiance.
This is a precursor to being able to retrieve surface reflectance, which is vital whencomparing data from different dates, times and sensors. Some imagery is delivered as“analysis-ready data,” however, if you wish to control your image processing workflow,
having the ability to work with Level 1 data is key. Radiometric correction can also
remove certain kinds of noise that can be introduced in the imagery collection process.
> Atmospheric Correction
Atmospheric correction is necessary to clean up the diffusion and scattering of lightpresent in a spectral image. ENVI corrects for atmospheric distortion to deliver atrue, reliable representation of a specific image scene. ENVI offers either advanced,
physics-based techniques or more of an on-the-fly method for real-time dataprocessing and works with both multispectral and hyperspectral data. Analysis ready datafrom multiple sensors may have been processed using different atmospheric correction
methods, which can introduce error. ENVI processes data from multiple sensors with aconsistent methodology to ensure that what you see in an image was
not artificially introduced.
> Geometric Correction
ENVI can register one image to another or an image to a map projection to help
maximize the data you can extract. Geometric correction is done by removing
variations in sensor characteristics and orbital/airborne geometry. The result is therepositioning and resampling of pixels into a specified reference grid. This results inthe ability to co-register and compare one image to another (i.e. change detection)or integrate multiple images together (i.e. analysis of multitemporal data for land
use classification).

INDICES
Spectral indices are combinations ofspectral reflectance from two or more
wavelengths that indicate the relative
abundance of features of interest.
ENVI includes more than 50 indices tosave users valuable time. Vegetation
indices are the most popular type, butother indices are available for burned
areas, man-made (built-up) features,water and geologic features. You
can also write a script to compute
spectral indices and write your own
mathematical expressions forcustom indices.
BELOW:
Spectral image processed in ENVI
displaying material classes for minerals.
Base from U.S. Geological Survey HyMap
data of Afghanistan. Image courtesy ofKokaly, R.F. & Bahr, T. (2014).

SPECTR AL LIBR ARIESTARGE T DE TECTIONIn ENVI, spectral libraries are used in many different spectrum identification, feature
extraction, anomaly detection, target finding and material mapping workflows. ENVI
includes a number of existing spectral libraries (i.e. from United States GeologicalSurvey, Johns Hopkins University Applied Physics Laboratory, NASA Jet Propulsion
Laboratory, etc.). Users can also build their own spectral libraries from a variety of spectra
sources, including ASCII files, spectral files produced by spectrometers, other spectral
libraries, user defined regions of interest, and spectral profiles and plots. Libraries can beresampled to other sensor wavelengths to make an exact reflectance comparison.

ENVI utilizes many different spectralfeature matching techniques tocompare unknown spectral signatures
to known reference spectra to findtargets of interest. Targets may be amaterial or mineral of interest or they
may be man-made objects such asvehicles. The tools in ENVI can also belinked to detect gaseous materials.

MAPPING UNIQUE MATERIALS
Spectral data users often want to map where materials are present in an image. For
example, using ENVI you can map soil types to determine the trafficability of an area orif the location has been disturbed. Some classification routines in ENVI use a “fitting”
approach, in which a measured spectrum is used to look for a combination of reference
spectral data that resemble it.

VISUALIZ ATIONENVI can be used to visualize complex
spectral data so that you can interpret
it and make informed decisions. The
human eye can only see a limited
number of spectral bands. Using ENVI, allspectral bands can be viewed in different
combinations to highlight features ofinterest and create mapping products.
ENVI supports hundreds of data sources,
data types, file formats and file sizes.
Visualizing spectral data can be complex
and time-consuming because it often
requires you to re-order displayed bands,
apply color tables, create layers, pan, zoom
blend, integrate geographical data andmore. ENVI has components for every
step of this process from initially viewing
imagery to map creation.
Olive trees in the Lecce Province, Apulia, Italy. Each circle represents an absolute NDVI value.
The healthiest trees are colored green. The source image is from WorldView-2, processed using
ENVI software.

HYPERSPECTRAL IMAGING.
SEEING IS BELIEVING.
The ability to get highly detailed information from spectral data is essential for many applications. This is especially true whencomplex chemical and physical interactions of things like vegetation, soil and mineral types, and even chemical analysis of items needto be understood. Here are several example applications of spectral data and ENVI spectral analysis.
OIL AND GASGEOLOGYMINING

Visualize and understand the chemical
seepage of oil even in areas of mixed land.

Measure the distribution and quantity of thecontent of drill cores and othergeological samples.

Identify and map mineral occurrences at
the topographic surface, estimate mixturesand calculate abundances.

DEFENSE AND INTELLIGENCE

PRECISION FARMING

FORESTRY

Detect camouflaged objects based on thespectral information related to the chemical
makeup of materials.

Map vegetation and crop diseases, detect
stress, identify components in plants anddetect impurities.

Classify individual tree species, discern
foliar chemistry and detect pest andblight conditions.

CULTUR AL HERITAGE

MEDICINE

MICROSCOPY

Use HSI as a noninvasive technique tomonitor and preserve historical documents
or canvas paintings.

Quantify the diagnostic information
available from reflected, fluorescent andtransmitted light in tissue.

Characterize the spectral properties ofnanoscale samples for chemical-freemonitoring of food products.

Spectral Analysis in ENVI®
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