This paper describes a collaborative collection campaign to
spectrally image and measure a well characterized scene for hyperspectral algorithm development and validation/verification
of scene simulation models (DIRSIG). The RIT Megascene, located in the northeast corner of Monroe County near Rochester, New York, has been modeled and characterized under the DIRSIG environment and has been simulated for various hyperspectral and multispectral systems (e.g., HYDICE, LANDSAT, etc.). Until recently, most of the
electro-optical imagery of this area has been limited to very
high altitude airborne or orbital platforms with low spatial
resolutions. Megacollect 2004 addresses this shortcoming by
bringing together, in June of 2004, a suite of airborne sensors
to image this area in the VNIR, SWIR, MWIR, and LWIR regions.
These include the COMPASS (hyperspectral VNIR,SWIR), SEBASS
(hyperspectral LWIR), WASP (broadband VIS, SWIR, MWIR, LWIR)
and MISI (hyperspectral VNIR, broadband SWIR, MWIR, LWIR). In conjunction with the airborne collections, an extensive ground truth measurement campaign was conducted to characterize atmospheric parameters, select targets, and backgrounds in the field. Laboratory measurements were also made on samples to confirm the field measurements. These spectral measurements spanned the visible and thermal region from 0.4 to 20 microns. These measurements will help identify imaging factors that affect algorithm robustness and areas
of improvement in the physical modeling of scene/sensor phenomena. Reflectance panels have also been deployed as control targets to both quantify sensor characteristics and atmospheric effects. A subset of these targets have also been deployed as an independent test suite for target detection algorithms. Details of the planning, coordination, protocols, and execution of the campaign will be discussed with particular emphasis on the ground measurements. The system used to collect the metadata of ground truth measurements and disseminate this data will be described. Lastly, lessons learned in the field will be underscored to highlight additional measurements and changes in protocol to improve future collections of this area.
[1]
David W. Warren,et al.
LWIR/MWIR imaging hyperspectral sensor for airborne and ground-based remote sensing
,
1996,
Optics & Photonics.
[2]
Harry N. Gross,et al.
An Advanced Synthetic Image Generation Model and its Application to Multi/Hyperspectral Algorithm Development
,
1999
.
[3]
Edwin M. Winter,et al.
Compact Airborne Spectral Sensor (COMPASS)
,
2001,
SPIE Defense + Commercial Sensing.
[4]
J. Schott,et al.
Remote optical detection of biomass burning using a potassium emission signature
,
2002
.
[5]
Scott D. Brown,et al.
Advances in wide-area hyperspectral image simulation
,
2003,
SPIE Defense + Commercial Sensing.
[6]
John R. Schott,et al.
Remote Sensing: The Image Chain Approach
,
1996
.
[7]
John R. Schott,et al.
Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment
,
2005
.
[8]
James A. Smith,et al.
A multi-wavelength thermal infrared and reflectance scene simulation model
,
2002,
IEEE International Geoscience and Remote Sensing Symposium.