Airborne Hyperspectral Image Analysis for Grain Sorghum Yield Variability Mapping

Abstract

In this paper we will investigate airborne hyperspectral imagery for mapping grain sorghum yield variability as compared with yield monitor data. All the spectral bands are used for yield variability mapping in order to fully use the plenty spectral information in hyperspectral imagery. Yield variability mapping is achieved by estimating the fractional abundance image corresponding to the yield, where a pixel with high gray-scale value represents high yield in the area it covers. To accommodate in-field spectral variation, an unsupervised method is used. Preliminary study demonstrates the feasibility of this technique, although more thorough investigation is needed.

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 2005
Accession Number
ADA452408

Entities

People

  • Chenghai Yang
  • James H. Everitt
  • Qian Du

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Airborne
  • Algorithms
  • Cell Size
  • Coordinate Systems
  • Correlation Analysis
  • Data Science
  • Earth Sciences
  • Engineering
  • Factor Analysis
  • Gray Scale
  • Hyperspectral Imagery
  • Image Processing
  • Materials
  • Multispectral
  • Regression Analysis
  • Remote Sensing

Readers

  • Atmospheric Remote Sensing.
  • Image Processing and Computer Vision.
  • Systems Analysis and Design