The Deepwater Horizon explosion and subsequent sinking produced the largest oil spill in U.S. history. One of
the most prominent portions of the response is mapping the extent to which oil has reached thousands of miles
of shoreline. The most common method of detecting oil remains visual spotting from airframes, supplemented
by panchromatic / multispectral aerial photography and satellite imagery. While this imagery provides a
synoptic view, it is often ambiguous in its ability to discriminate water from hydrocarbon materials.
By employing spectral libraries for material identification and discrimination, imaging spectroscopy
supplements traditional imaging techniques by providing specific criteria for more accurate petroleum detection
and discrimination from water on terrestrial backgrounds. This paper applies a new hydrocarbon-substrate
spectral library to SpecTIR HST-3 airborne imaging spectroscopy data from the Hurricane Katrina disaster in
2005. Using common material identification algorithms, this preliminary analysis demonstrates the
applicability and limitations of hyperspectral data to petroleum/water discrimination in certain conditions. The
current work is also the first application of the petroleum-substrate library to imaging spectroscopy data and
shows potential for monitoring long term impacts of Deepwater Horizon.
A variety of crude oils and refined petroleum products were applied to ten common terrestrial substrates with the
goal of developing a set of representative reflectance spectra for hydrocarbon-substrate combinations. Similar to
previous studies, each hydrocarbon darkened the substrates and produced hydrocarbon absorption features near
1200, 1690-1770, and 2270-2400 nm, along with a host of other minor features in the VIS/NIR/SWIR portion of the
spectrum. Some substrate absorption features interfered with hydrocarbon absorptions, complicating spectral
The reflectance spectra varied directly with the amount of liquid on the substrate. Liquid-saturated samples were
left to age and regularly re-measured, establishing a relationship between evaporative loss for volatile and semivolatile
products and sample reflectance. The results outline temporal windows of opportunity and minimum
detection thresholds for volatiles. They also provide a means for remotely distinguishing 1) water from petroleum
products on some substrates and 2) some similar hydrocarbons from one another based on their volatility.
Water is a common, transient soil material that can be distributed as lattice water bound in crystalline particles, as water of adhesion on the soil particles, and as interstitial or capillary water. It can have important effects on soil reflectance spectra over the visible-near infrared-short wave infrared electromagnetic spectrum, 0.4-2.5 μm. This study's objective was to determine the changes in soil reflectance spectra relative to differences in soil water content. An initial small water application greatly reduced the soil reflectance, masked the spectral features of the air-dry soils, and enhanced water absorption features. As wavelength values increased, water absorptance increased and transmittance decreased, which created non-uniform change in the soil reflectance spectrum. These changes occurred as water filled the interstitial spaces within the soil's optical depth. Water filling the pore space below the sample's optical depth increased the substrate's moisture content but had no effect on substrate reflectance. These water absorption features were amplified over the 0.4-2.5 μm region and spectral sensitivities to water increased directly with wavelength. Soil reflectance maxima in five spectral bands, centered at 0.800, 1.080, 1.265, 1.695, and 2.220 μm, varied inversely with sample water content. The 0.800 and 1.080 μm bands varied more slowly with water content than did the 1.265, 1.695, and 2.220 μm bands. Multiple normalized difference indices (NDI) using these bands correlated strongly with sample water content.
Tree canopy closure is often a desired metric in ecological applications of spectral remote sensing. There are numerous models and field protocols for estimating this variable, many of which are specialized or may have poor accuracies. Specialized instruments are also available but they may be cost prohibitive for small programs. An expedient alternative is the use of in-situ handheld digital photography to estimate canopy closure. This approach is cost effective while maintaining accuracy. The objective of this study was to develop and test an efficient field protocol for determining tree canopy closure from zenith-looking and oblique digital photographs.
Investigators created a custom software package that uses Euclidean distance to cluster pixels into sky and non-sky categories. The percentages of sky and tree canopy are calculated from the clusters. Acquisition protocols were tested using JPEG photographs taken at multiple upward viewing angles and along transects within an open stand of loblolly pine trees and a grove of broadleaf-deciduous trees. JPEG lossy compression introduced minimal error but provided an appropriate trade-off given limited camera storage capacity and the large number of photographs required to meet the field protocol. This is in contrast to relatively larger error introduced by other commonly employed measurement techniques such as using gridded template methods and canopy approximations calculated by tree diameter measurements.
Experiment results demonstrated the viability of combining image classification software with ground-level digital photographs to produce fast and economical tree canopy closure approximations.
Three liquid hydrocarbons of different volatilities were incrementally applied to a quartz sand substrate. These liquids were gasoline, diesel fuel, and motor oil. The reflectance spectra of the hydrocarbon-sand samples varied directly with the amount (weight) of liquid on the sand. Liquid-saturated sand samples were then left to age in ambient, outdoor, environmental conditions. At regular intervals, the samples were re-measured for the residual liquid and the associated change in sample reflectance. The results outlined temporal windows of opportunity for detecting these products on the sand substrate. The windows ranged from less than 24-hours to more than a week, depending on liquid volatility.
Each hydrocarbon darkened the sand and produced hydrocarbon absorption features near 1.70 and 2.31 μm and a hydrocarbon plateau at 2.28-2.45 μm. These features were used to differentiate the liquid-sand samples. A normalized difference index metric based on one of these features and a spectral continuum band described the reflectance-weight loss and reflectance-time relations. The normalized difference hydrocarbon index (NDHI) using the 1.60 and 2.31 μm bands best characterized the samples.
Soil surface materials often originate from different sources and are spectrally variable. Their presence will alter soil spectral features and mask the nature of the underlying soil surface horizon. The upper-most, thin, granular layer determines a soil sample's spectra. This study's objective was to characterize the optical depth of some sandy soils and their relationship to spectral reflectance from 0.35-2.50mm. The reflectance-optical depth relationships were determined for four, air-dried, granular, sieved samples, with particle sizes of 1.0-2.0, 0.5-1.0, 0.25-0.5, 0.125-0.25, 0.075-0.125, or <0.075mm. Each particle size separate has convergent reflectance spectra associated with an optical depth that ranged from 0.2 to 8.1mm. The optical depth was greater for larger sized particles than for smaller sized particles. Normalizing the sample depth by the mean particle diameter of each sieve fraction found the optical depth-spectral feature relationships were determined by a layer of granular materials that was 5-8 particles thick. Three non-sieved, well-graded composite soils were also evaluated and their optical depths ranged from 1.4 to 3.9mm. These non-sieved composite soils include a medium fused-silica sand, a medium calcareous sand, and a medium gypsum sand.
Large size calibration panels are frequently required as reference points for in-scene calibration of remotely sensed spectral data. However, most commercially manufactured calibration panels are costly and sometimes present spectral crossover problems. The panels described in this report are made from readily available fabrics and can provide a lower cost alternative. Four 5.5 x 6.7 m fabric panels that have nominal reflectance of 85%, 38%, 18% or 3% were tested. These fabric panels cost approximately $700 to construct and the materials are available at most hardware stores, which facilitated field panel construction. When properly deployed on a uniform dark-toned surface such as asphalt, gravel, or soil, these alternative panels provide calibration for the entire 0.4 - 2.5 μm spectrum and do not exhibit spectral crossover problems. Remote sensing programs that do not have access to or resources to acquire commercial panels may find these fabric panels a suitable alternative for in-scene calibration.