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Spectral Analysis

Spectral analysis extracts useful information you might have otherwise missed from the raw pixels of your imagery, adding value, precision and efficiency to your geospatial projects. This analysis is highly customized to the specific needs of a project as well as to the imagery itself.

Apollo Mapping can assist you with all aspects of spectral analysis – from the intermediate stages, whereby you can use the processed imagery in your own geospatial investigation; to a final solution that is tailored to address your specific project needs.

What Does Spectral Analysis Look Like?

Common Spectral Analysis Techniques

Red-Edge NDVI Calculation ExampleSpectral Pre-ProcessingFinal Solutions

In the animation above, a red-edge Normalized Difference Vegetation Index (NDVI) has been calculated using pansharpened WorldView-2 8-band satellite imagery. Red-edge NDVI has been shown to be more consistent and accurate in its assessment of plant health. You will see in the animation that areas of less healthy vegetation have been revealed even though these plants appear to be as ‘green’ as their neighbors. A red-edge NDVI is an invaluable contribution to any high precision agriculture project.

If your goal is to complete your own spectral analysis but need some help along the way, then our pre-processed products are the correct choice for you.

  • Radiance Conversion – convert unit-less digital numbers to a known unit (i.e. radiance, or watts per steradian per square meter)
  • Atmospheric Correction (ATOC) – calculate surface reflectance by removing atmospheric effects
  • Principal Components (PCA) – compute the meaningful bands for this analysis of variance and correlation

An Apollo Mapping representative can work with you to determine the final solution that fits the needs of your project. In the meantime, here is a list of the common solutions we can assist you with:

  • Change Detection – identify features and locations that have changed over time and across broad landscapes
  • Vegetation Indices – assess a wide variety of factors that are related to plant growth and stress to determine locations of healthy and unhealthy plants in your fields, forests and/or study sites
  • Fire Fuel – map potential fire risk by determining the water content of green vegetation and the amount of dried plant matter
  • Imagery Classifications – determine land cover information in an automated fashion with supervised, unsupervised and object-oriented techniques
  • Custom Solutions – ask us how we can help you solve your most challenging land-related problems using advanced spectral analysis customized to your needs

Useful information on spectral analysis

Radiance Conversion
Radiance conversion is a step in an ATOC.
By removing atmospheric effects with an ATOC, it is easier to compare imagery from various dates and sensors in many analytic techniques.
Unknown Relationships
A PCA discovers unknown trends and relationships in imagery, for instance it can help to reveal the footprint of human-made structures in urban environments.
Wildfire Planning
Fire fuel maps can be an important contribution to community wildfire planning and risk management.
Vegetation Indices
Vegetation indices extracted from high resolution satellite imagery are crucial inputs for any high precision agriculture project.

Do you need the JPL ASTER Spectral Library Version 2.0 for an image classification?

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