To: Brenda
Brown and Sherry Farwell
From: Xuexia Chen and Lee Vierling
Re: Report for travel to the High
Spatial Resolution Commercial Workshop held in Reston, VA, March 25-27, 2002.
Xuexia Chen, a Ph.D. student in the lab of Dr. Lee Vierling,
participated in the above conference with her travel partially funded by
NASA-EPSCoR. Ms. Chen was one of
approximately 12 presenters who were invited by the USGS to present at this
meeting, which was convened for scientists and administrators from NASA, USGS,
and NIMA to learn about how the commercial satellite imagery purchase program
(specifically, for purchasing IKONOS imagery) has been utilized to conduct
various scientific research. Ms.
Chen’s presentation was co-authored by participants from SDSM&T,
Horizon’s Incorporated of Rapid City, and the EROS Data Center (see abstract
and authors listed below). The
presentation was well received and has led to the request and approval for 2
additional IKONOS images to be delivered to the research team for research sites
in the Black Hills of South Dakota. As
a result, new and continued opportunities for collaboration among NASA,
SDSM&T, Horizon’s, and EROS Data Center have arisen from this conference.
The following paper was submitted and presented at the conference:
Relationships Among IKONOS Imagery, Airborne Scanning
LIDAR, and Ground-Based Tree Inventory Data in a Ponderosa Pine Forest:
A Multiple Endmember Approach
X. Chen1,
L. Vierling1*, E. Rowell2, D. Dykstra1, W.
Capehart1, and T. DeFelice3
1South
Dakota School of Mines and Technology, Institute of Atmospheric Sciences
2Horizon’s
Incorporated, Rapid City, SD
3USGS EROS
Data Center, Sioux Falls, SD
* Corresponding Author: Lee.Vierling@sdsmt.edu
Estimating forest structure and stand density using
remotely sensed data is important for a wide range of scientific and management
goals, including assessing biogeochemical budgets (e.g. aboveground carbon
storage) and determining the susceptibility of an area to catastrophic fires.
The objective of this study is to determine relationships among
ground-collected forest inventory data, high resolution IKONOS imagery, and
airborne scanning LIDAR collected at an Ameriflux tower site in the Black Hills
of South Dakota. The site is
located in the Black Hills Experimental forest, which is largely dominated by
Ponderosa Pine.
Ground data were collected in the summer of 2001 along
eight 10x150 meter belt transects radiating from the tower. These data included tree species identification, diameter at
breast height, tree height, percent and type of ground cover, and effective leaf
area index (LAIe) as determined using two LAI-2000 instruments (Li-COR,
Lincoln, NE). IKONOS imagery was
obtained over the site on July 28, 2000, and airborne scanning LIDAR was
acquired at a 2 meter post spacing (±3m beam footprint) in October 2001.
No thinning or fire activity occurred at the site between data collection
dates. Transect data were
subdivided into 10x10 meter plots and co-registered with the IKONOS and LIDAR
data for analyses. A combination of
IKONOS multispectral and panchromatic data was used to select image endmembers
(i.e. spectrally “pure” components) of bare soil, open grass, and
tree/shade.
Effective tree canopy LAI (m2 leaf/m2 ground) ranged from 0 to 2.5 among the 100 m2 plots, and was used as an indicator of forest canopy coverage. A significant positive correlation existed between LAIe and the IKONOS-derived tree/shade endmember fraction for pixels falling within the transect plots (Pearson’s correlation coefficient [PCC] = 0.76), while LAIe and the open grass endmember fraction was significantly negatively correlated (PCC = -0.67). The Enhanced Vegetation Index (EVI) was negatively correlated with all measures of tree density, including the canopy LIDAR return fraction (PCC = -0.65) and tree/shade endmember fraction (PCC = -0.94). Conversely, EVI exhibited a very strong positive correlation with the open grass endmember fraction (PCC = 0.99). These results indicate that IKONOS data can serve to make the important distinction between tree canopy coverage and exposed understory grasses near peak summertime greenness.
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