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Investigation:

LC-18 (Asner / Natalino da Silva)

LBA Dataset ID:

LC18HYPERION

Originator(s):

1. ASNER, G.P.
2. CARLSON, K.M.
      3. KNAPP, D.E.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Dataset Abstract:

The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines) (http://eo1.usgs.gov/sensors.php). Through this large number of spectral bands, complex land ecosystems can be imaged and accurately classified. Data from the EO-1 Hyperion imaging spectrometer may greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin using four biogeophysical indicators not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. This image was collected by the Hyperion sensor on 10-July-2004 at 13:16:16 GMT and calibrated to apparent surface reflectance using the ACORN atmospheric model.

Beginning Date:

2004-07-10

Ending Date:

2004-07-10

Metadata Last Updated on:

2008-11-13

Data Status:

Archived

Access Constraints:

PUBLIC

Data Center URL:

http://daac.ornl.gov/

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (ornldaac@ornl.gov)

Access Instructions:

PUBLIC

Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.
Datafile(s):

LBA-ECO LC-18 Hyperion 30-m Surface Reflectance, Mato Grosso, Brazil: July 2004 :  http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=889

Documentation/Other Supporting Documents:

LBA-ECO LC-18 Hyperion 30-m Surface Reflectance, Mato Grosso, Brazil: July 2004 :  http://daac.ornl.gov/LBA/guides/LC18_Hyperion.html

Citation Information - Other Details:

Asner, G.P., K.M. Carlson, and D.E. Knapp. 2008. LBA-ECO LC-18 Hyperion 30-m Surface Reflectance, Mato Grosso, Brazil: July 2004. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. doi:10.3334/ORNLDAAC/889

Keywords - Theme:

Parameter Topic Term Source Sensor
REFLECTANCE LAND SURFACE LAND USE/LAND COVER EO-1 (EARTH OBSERVING 1) HYPERION

Uncontrolled Theme Keyword(s):  REFLECTANCE

Keywords - Place (with associated coordinates):

Region
(click to view profile)
Site
(click to view profile)
North South East West
  MATO GROSSO -12.66490 -13.16780 -52.28000 -52.46420

Related Publication(s):

Asner, G.P. 2008. Hyperspectral remote sensing of canopy chemistry, physiology and diversity in tropical rainforests. Chapter 12 in Hyperspectral remote sensing of tropical and subtropical forests. M. Kalacska and G.A. Sanchez-Azofeifa (eds.) Taylor and Francis Group.

Asner, G.P., D.E. Knapp, E.N. Broadbent, P.J.C. Oliveira, M. Keller, and J.N. Silva. 2005. Selective logging in the Brazilian Amazon. Science 310:480-482.

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

The data are in ENVI format, which includes an image file without headers and a separate ASCII header file (*.hdr) which contains the data characteristics. Reflectances for 200 bands are reported at 30-m resolution. The center wavelength for each band can be found in header file (bands listed ordinally 1-200) and as the spectral center wavelength in the binary ENVI file.



Image file: tanguro_hyp_071004_bil_sub_acorn_refl_destrspline_geo



Header file: tanguro_hyp_071004_bil_sub_acorn_refl_destrspline_geo.hdr







Raster dataset information:



o SDTS raster type: Pixel

o Number of raster bands: 200 (See Mato_Grasso_July_2004_image_bands.xls in companion files for specific Hyperion bands. The ENVI header file lists the bands ordinally 1-200.)



Raster properties:



o Origin location: Upper Left

o Data compression type: None

o Display type: pixel codes



Cell information:



o Number of cells on x-axis:668

o Number of cells on y-axis:1852

o Number of cells on z-axis:1

o Number of bits per cell:16



Cell Size:



o X distance: 30.000000

o Y distance: 30.000000



Spatial Reference:



o Projected coordinate system name: WGS_1984_UTM_Zone_22S



Companion Files:



Two companion files are included that provide more information on the HYPERION multispectral bands.



o Mato_Grasso_July_2004_image_bands.pdf file lists the 200 specific Hyperion bands reported in this data set.

o Hyperion_Spectral_Coverage.pdf lists the full set of bands collected by Hyperion. (http://eo1.usgs.gov/sensors.php)

Data Application and Derivation:

This image can be used to detect changes in land cover based on the reflectance in the 200 reported spectral bands.



The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines). The Hyperion capabilities provide resolution of surface properties into hundreds of spectral bands versus the six optical multispectral bands flown on traditional Landsat imaging missions. Through this large number of spectral bands, complex land ecosystems can be imaged and accurately classified.



Potential applications include improved multiresolution characterization of the surface (scaling), improved optical-geometric characterization of vegetation canopies, improved assessments of surface phenology and ecosystem seasonal dynamics, and improved maintenance of long-term, inter-annual, time series data records.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

This image was visually and quantitatively assessed for reasonable and accurate values in various spectral regions.

Process Description:

Data Acquisition Materials and Methods:

The original Hyperion data were acquired from NASA Goddard Space Flight Center. Data were calibrated to apparent surface reflectance using the Atmospheric CORrection Now (ACORN) atmospheric model.

References:

Miller, C. J., 2002, Performance assessment of ACORN atmospheric correction algorithm, Proceedings SPIE Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII ,v. 4725, pp. (http://eo1.usgs.gov/hyperion.php). Source: TRENDS IN ECOLOGY & EVOLUTION (Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests), Chambers JQ, Asner GP, Morton DC, et al., Volume: 22 Issue: 8 Pages: 414-423 Published: AUG 2007.

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