Application of Soil and Vegetation Reflectance Spectra to Color and Color Infrared Photography

Abstract

Characterizing arid region soil and vegetation conditions from remotely sensed imagery can be limited by the small image tonal contrast between soil vegetation surfaces. Ground-level reflectance spectra of different soil surfaces can be highly variable over the visible near infrared (NIR region. Spectral differences between cheatgrass, sagebrush, shade scale, greasewood, saltgrass, and alfalfa samples resulted from pigmentation, plant structure, and phenological differences. Some soil surfaces and plant species have similar reflectance in some spectral responses and the likelihood that these surfaces would be separable on Kodak Aerochrome color or color infrared films. Reflectance emulsion factors (REF) were calculated for each surface using the spectral sensitivity of each emulsion dye layer of the color or color infrared film and the surface's reflectance spectra. These values indicate theffect of reflected light from the sample on the film emulsion layer. Shaded soil and shaded vegetation have very similar REF values for both films, while values for dark toned gravels and medium toned soils are similar to many plant surfaces. Medium to light toned soils have REF values larger than any vegetative surface. Discriminating the surfaces with low to medium REF values depends on the film layer (s) affected, the density of the emulsion layer, and the color formed. Reprints

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 1986
Accession Number
ADA196087

Entities

People

  • J. P. Henley
  • Melvin B. Satterwhite

Organizations

  • Geospatial Research Laboratory

Tags

DTIC Thesaurus Topics

  • Aerial Photography
  • Availability
  • Classification
  • Contrast
  • Emulsions
  • Ground Level
  • Infrared Film
  • Infrared Photography
  • Photographic Materials
  • Photography
  • Plant Structures
  • Plants
  • Plastic Explosives
  • Reflectance
  • Security
  • Spectra
  • Vegetation

Fields of Study

  • Agricultural and Food sciences

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Thin Film Deposition Science.