Spatial Pattern of Soil Organic Carbon Acquired from Hyperspectral Imagery at Reynolds Creek Critical Zone Observatory (RC-CZO)

Aihua Li, Ryan Will, Nancy F. Glenn, Shawn Benner, Lucas P. Spaete

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Soil Organic Carbon (SOC) is a key soil property and is important for understanding carbon storage and soil-vegetation dynamics. Hyperspectral imagery (imaging spectroscopy) providing detailed spectral signatures of vegetation and soil make it possible to continuously map SOC content over a watershed scale. In this paper, the Next Generation Airborne Visible / Infrared Imaging Spectrometer (AVTPJSng) was used with an unmixing algorithm, the Multiple Endmember Spectral Mixture Analysis, to differentiate fractional cover of healthy vegetation, stressed vegetation and soil at the Reynolds Creek Critical Zone Observatory (PC-CZO). The fractional cover information was used to remove noisy spectra and the resulting residual spectra were used to predict SOC by Partial Least Squares Regression (PLSP). The results showed that the root mean standard error and mean bias of the predicted SOC (%) are 0.75 and 2.4, respectively. We found the best relationship between SOC and spectra after filtering out the influence of green vegetation from mixed spectra. The resulting residual, spectra comprised of stressed vegetation and soil, contained enough information for mapping SOC distribution within the shrub dominated regions of the watershed. This may provide a method to better understand the interaction of soil and vegetation in semiarid ecosystems.

Original languageEnglish
Title of host publication2016 8th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781509006083
DOIs
StatePublished - 28 Jun 2016
Event8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016 - Los Angeles, United States
Duration: 21 Aug 201624 Aug 2016

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume0
ISSN (Print)2158-6276

Conference

Conference8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016
Country/TerritoryUnited States
CityLos Angeles
Period21/08/1624/08/16

Keywords

  • Carbon
  • Imaging spectroscopy
  • MESMA
  • PLSP
  • Sagebrush
  • Soil
  • Vegetation

EGS Disciplines

  • Earth Sciences
  • Geophysics and Seismology

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