Estimating evapotranspiration of riparian vegetation using high resolution multispectral, thermal infrared and Lidar data

Christopher M.U. Neale, Hatim Geli, Saleh Taghvaeian, Ashish Masih, Robert T. Pack, Ronald D. Simms, Michael Baker, Jeff A. Milliken, Scott O'meara, Amy J. Witherall

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

High resolution airborne multispectral and thermal infrared imagery was acquired over the Mojave River, California with the Utah State University airborne remote sensing system integrated with the LASSI imaging Lidar also built and operated at USU. The data were acquired in pre-established mapping blocks over a 2 day period covering approximately 144 Km of the Mojave River floodplain and riparian zone, approximately 1500 meters in width. The multispectral imagery (green, red and near-infrared bands) was ortho-rectified using the Lidar point cloud data through a direct geo-referencing technique. Thermal Infrared imagery was rectified to the multispectral ortho-mosaics. The lidar point cloud data was classified to separate ground surface returns from vegetation returns as well as structures such as buildings, bridges etc. One-meter DEM's were produced from the surface returns along with vegetation canopy height also at 1-meter grids. Two surface energy balance models that use remote sensing inputs were applied to the high resolution imagery, namely the SEBAL and the Two Source Model. The model parameterizations were slightly modified to accept high resolution imagery (1-meter) as well as the lidar-based vegetation height product, which was used to estimate the aerodynamic roughness length. Both models produced very similar results in terms of latent heat fluxes (LE). Instantaneous LE values were extrapolated to daily evapotranspiration rates (ET) using the reference ET fraction, with data obtained from a local weather station. Seasonal rates were obtained by extrapolating the reference ET fraction according to the seasonal growth habits of the different species. Vegetation species distribution and area were obtained from classification of the multispectral imagery. Results indicate that cottonwood and salt cedar (tamarisk) had the highest evapotranspiration rates followed by mesophytes, arundo, mesquite and desert shrubs. This research showed that high-resolution airborne multispectral and thermal infrared imagery integrated with precise full-waveform lidar data can be used to estimate evapotranspiration and water use by riparian vegetation.

Original languageEnglish (US)
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XIII
DOIs
StatePublished - 2011
Externally publishedYes
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology XIII - Prague, Czech Republic
Duration: Sep 19 2011Sep 21 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8174
ISSN (Print)0277-786X

Conference

ConferenceRemote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Country/TerritoryCzech Republic
CityPrague
Period9/19/119/21/11

Keywords

  • Airborne remote sensing
  • Energy balance
  • Lidar
  • Tamarisk evapotranspiration
  • Thermal infrared

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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