International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
Acronym | Genus Species Common name
POHE Populus | heterophylla | swamp cottonwood
PRSE Prunus serotina black cherry
QUAL Quercus alba white oak
QUBI Quercus | bicolor swamp white oak
QUCO Quercus coccinea scarlet oak
QUEA Quercus falcata southern red oak
QUIM Quercus imbricaria shingle oak
QUL Y Quercus lyrata overcup oak
QUMA Quercus | marilandica blackjack oak
QUMC Quercus macrocarpa bur Oak
QUMI Quercus | michauxii swamp chestnut
oak
QUMU Quercus | muehlenbergii |, chinquapin oak
QUNI Quercus nigra water oak
QUPA Quercus | pagoda cherrybark oak
QUPH Quercus | phellos willow oak
QUPL Quercus | palustris pin oak
QUPR Quercus prinus chestnut oak
QURU Quercus rubra northern red oak
QUSH Quercus shumardii shumard oak
QUST Quercus | stellata post oak
QUVE Quercus velutina black oak
RHCA Rhamnus | caroliniana carolina buckthorn
ROPS Robinia psuedoacacia | black locust
SAAL Sassafras | albidum sassafras
SANI Salix nigra black willow
TADI Taxodium| distichum bald cypress
ULAL Ulmus alata winged elm
ULAM Ulmus americana american elm
ULRU Ulmus rubra
slippery elm
Table 1. Summary of tree species found in LBL.
High spectral resolution (ultraspectral) leaf, soil, and water
reflectance data were collected on a regular basis with an ASD
Field Spec FR?, a full-range field spectroradiometer, in the
field to create a spectral library to aid the classification of the
surface material During the satellite and aerial data collection
events, ground spectra were also collected for selected
spectral targets.
3. IMAGERY
Several hyperspectral remotely sensed datasets collected by
the Hyperion satellite (Figure 2) on April 29, 2001, and the
airborne RDACS-3 (Figure 3) on on September 7, 1999 were
utilized in this research. AVIRIS data were also used but
because of some system problems with the sensor, only small
parts of the data were utilized. AVIRIS was flown on the
Twin Otter turboprop at approximately 4000m above the
ground with 4m spatial resolution on November 11, 1999 and
September 10, 2001. The Hyperion provided 242 spectral
bands (from 0.4 to 2.5 pm) with a 30 meter spatial resolution
and covered 7.5km by 200km area. An RDACS-3 imagery
1308
with 120 spectral bands and 2x4m spatial resolution was
collected at 2350m above the ground by the ITD Spectral
Visions. Hyperion was NASA's first hyperspectral imager
aboard NASA's Earth Observing-1 (EO-1) spacecraft,which
had three land imaging instruments; Advanced Land Imager,
Hyperion, and Atmospheric Corrector.
4. METHOD
Hyperspectral imagery can be considered as a single image
dataset with a continuous spectrum of radiance (or
reflectance) values associated with each image pixel (Bateson
and Curtiss, 1996). Hyperspectral imagery can distinguish
between slope and brightness variations and ' resolve
absorption bands n the spectrum, which can allow one to
identify surface material such as specific minerals or any
material with absorption features (Clark et al, 1992).
AVIRIS was the first airborne hyperspectral sensor to
measure reflected solar radiation from 400nm to 2500 nm
(Green et al., 1998).
Individual bands of the RDACS hyperspectral datasets were
calibrated to percent reflectance using the known reflectances
of two gray scale placards placed on the ground during the
overflight (Figure 4). The calibration and radiance to
reflectance conversions for the Hyperion dataset were done
using several ground targets (dark, medium and light arcas),
for which ground spectra were collected using the field
spectrometer. A simple linear regression model was used in
the calibration and conversion process.
PE Lake Barkley
— LL
Hi icinl 56 6103.7 nm
Blige: Band-21 (56,77 rns
Figure 2. The Hyperion dataset, April 29, 2001
A spectral library of surface material (endmembers) and
vegetation species (Table 1 and Figure 5) was created for
hyperspectral analysis of the datasets. Several techniques
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