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

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.

Using Remote Sensing to Estimate Scales of Spatial Heterogeneity to Analyze Evapotranspiration Modeling in a Natural Ecosystem

“…To evaluate the difference in daily ET for each vegetation type on the different dates ( [27], which showed daily ET ranging between 2 mm/day and 3.3 mm/day. The large ET rate estimated for grass/shrubs corresponds to the vegetation along the river corridor (see Figure 14).…”

“…In natural environments that are characterized by a heterogeneous natural ecosystem and low precipitation, such as the San Rafael River corridor in Utah, the major component of the water balance is vegetation transpiration (T) and soil evaporation (E) or the combined evapotranspiration (ET). This location also exhibits significant high spatial variability in ET information due to several factors that include soil moisture availability, groundwater depth, leaf area, topography, land surface temperature and vegetation species [27]. Moreover, the San Rafael River corridor is dominated by treated tamarisk, which increases the complexity of the ecosystem's water use and poses additional difficulties beyond the previously mentioned challenges due to the high variability of this vegetation in space and time.…”

“…According to a 2011 study by Neale et al [27] conducted over the Mojave River, California, to estimate ET using high-resolution airborne multispectral imagery, tamarisk and cottonwood plants had the highest ET rate compared with other vegetation species. Furthermore, although a vast amount of information is available on water use by different types of riparian species, plant physiological processes and sources of available water that control water use are still disputed and poorly understood [27]. Hence, further insights into the amount of available water used in such heterogeneous systems would benefit natural and water resource managers and decision-makers.…”

Using High Resolution LiDAR Data and a Flux Footprint Parameterization to Scale Evapotranspiration Estimates to Lower Pixel Resolutions

“…To the authors' knowledge, few studies have used canopy structural information obtained from LiDAR data within land surface or ecosystem models to estimate ET fluxes (Neale et al, 2011;Mitchell et al, 2012), and fewer studies have integrated LiDAR data with a footprint model for the direct purpose of assessing how modelled ET differs using vegetation structure inputs of varying pixel sizes over heterogeneous land surface areas. Chasmer et al (2011a) introduced this topic by integrating LiDAR derivatives of canopy structure with the footprint parameterization of Kljun et al (2004) to better understand uncertainties in gross primary production (GPP) within 1 km resolution MODIS pixels.…”

A Review of Advances in the Identification and Characterization of Groundwater Dependent Ecosystems Using Geospatial Technologies

“…Remote sensing techniques to identify GDEs also include the use of the thermal infrared band to map locations associated with high levels of evapotranspiration and/or saturation [87]. High resolution airborne multispectral and thermal infrared imagery was acquired over the Mojave River, California to estimate evapotranspiration and water use by riparian vegetation [96], thermal infrared remote sensing of vegetation temperature was integrated with a surface energy balance model to efficiently calculate spatially distributed evapotranspiration [97], and LANDSAT Thematic Mapper (TM) thermal infrared band was used for the classification of successional stages of forest growth [98]. Low altitude aerial infrared surveys making use of thermal infrared cameras have also been found to be extremely useful to investigate the interactions between groundwater and surface water [99].…”