A Simplified Empirical Line Method of Radiometric Calibration for Small Unmanned Aircraft Systems-Based Remote Sensing

Chuyuan Wang, Soe Myint

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

The use of small unmanned aircraft systems (sUAS) to acquire very high-resolution multispectral imagery has attracted growing attention recently; however, no systematic, feasible, and convenient radiometric calibration method has been specifically developed for sUAS remote sensing. In this research, we used a modified color infrared (CIR) digital single-lens reflex (DSLR) camera as the sensor and the DJI S800 hexacopter sUAS as the platform to collect imagery. Results show that the relationship between the natural logarithm of measured surface reflectance and image raw, unprocessed digital numbers (DNs) is linear and the y-intercept of the linear equation can be theoretically interpreted as the minimal possible surface reflectance that can be detected by each sensor waveband. The empirical line calibration equation for every single band image can be built using the y-intercept as one data point, and the natural log-transformed measured reflectance and image DNs of a gray calibration target as another point in the coordinate system. Image raw DNs are therefore converted to reflectance using the calibration equation. The Mann-Whitney U test results suggest that the difference between the measured and the predicted reflectance values of 13 tallgrass sampling quadrats is not statistically significant. The method theory developed in this study can be employed for other sUAS-based remote sensing applications.

Original languageEnglish (US)
Article number7098353
Pages (from-to)1876-1885
Number of pages10
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume8
Issue number5
DOIs
StatePublished - May 1 2015

Keywords

  • Empirical line
  • radiometric calibration
  • small unmanned aircraft systems (sUAS)
  • very high resolution

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

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