Channeled spectropolarimetry can measure the complete polarization state of light as a function of wavelength. Typically, a channeled spectropolarimeter uses high order retarders made of uniaxial crystal to amplitude modulate the measured spectrum with the spectrally-dependent Stokes polarization information. A primary limitation of conventional channeled spectropolarimeters is related to the thermal variability of the retarders. Thermal variation often forces frequent system recalibration, particularly for field deployed systems. However, implementing thermally stable retarders results in an athermal channeled spectropolarimeter that relieves the need for frequent recalibration. Past work has addressed this issue by developing athermalized retarders using two or more uniaxial crystals. Recently, a retarder made of biaxial KTP and cut at a thermally insensitive angle was used to produce an athermal channeled spectropolarimeter. This paper presents the results of the biaxial crystal system and compares the two thermal stabilization techniques in the context of producing an imaging thermally stable channeled spectropolarimeter. A preliminary design for a snapshot imaging channeled spectropolarimeter is also presented.
Gas correlation imagers are important instruments for remotely detecting effluent emissions. However, making a
functional design for field testing is non-trivial given the range of environmental conditions the system may be operated under and the required matched imaging performance for both channels. We present a dual channel 7 degree full field of view f/2.5 athermal optical design athermalized from 0 to 50 degrees C that operates in the wavelength range of 2.0 to 2.5 microns suitable for methane imaging. We present the optical design, tolerance budget, and alignment plan used for the system. Predicted and as-built performance data including interferometric and ensquared energy measurements for both imaging channels are also shown.
Proposed is a new technique for simulating nighttime scenes with realistically-modelled urban radiance. While
nightlight imagery is commonly used to measure urban sprawl,1 it is uncommon to use urbanization as metric
to develop synthetic nighttime scenes. In the developed methodology, the open-source Open Street Map (OSM)
Geographic Information System (GIS) database is used. The database is comprised of many nodes, which are
used to dene the position of dierent types of streets, buildings, and other features. These nodes are the driver
used to model urban nightlights, given several assumptions.
The rst assumption is that the spatial distribution of nodes is closely related to the spatial distribution of
nightlights. Work by Roychowdhury et al has demonstrated the relationship between urban lights and development.
2 So, the real assumption being made is that the density of nodes corresponds to development, which is
reasonable. Secondly, the local density of nodes must relate directly to the upwelled radiance within the given
locality. Testing these assumptions using Albuquerque and Indianapolis as example cities revealed that dierent
types of nodes produce more realistic results than others. Residential street nodes oered the best performance
for any single node type, among the types tested in this investigation. Other node types, however, still provide
useful supplementary data.
Using streets and buildings dened in the OSM database allowed automated generation of simulated nighttime
scenes of Albuquerque and Indianapolis in the Digital Imaging and Remote Sensing Image Generation (DIRSIG)
model. The simulation was compared to real data from the recently deployed National Polar-orbiting Operational
Environmental Satellite System(NPOESS) Visible Infrared Imager Radiometer Suite (VIIRS) platform. As a
result of the comparison, correction functions were used to correct for discrepancies between simulated and
observed radiance. Future work will include investigating more advanced approaches for mapping the spatial
extent of nightlights, based on the distribution of dierent node types in local neighbourhoods. This will allow
the spectral prole of each region to be dynamically adjusted, in addition to simply modifying the magnitude of
a single source type.
The Digital Elevation Model (DEM) extraction process traditionally uses a stereo pair of aerial photographs that are sequentially captured using an airborne metric camera. Standard DEM extraction techniques have been naturally extended to utilize satellite imagery. However, the particular characteristics of satellite imaging can cause difficulties in the DEM extraction process. The ephemeris of the spacecraft during the collects, with respect to the ground test site, is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy. A large angle of separation can cause an excessive number of erroneous points in the output DEM. There is also a possibility of having occluded areas in the images when drastic topographic variation is present, making it impossible to calculate elevation in the blind spots. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of the Multispectral Thermal Imager (MTI) allows for multiple collects of the same area to be taken from different perspectives. This functionality of MTI makes it a good candidate for the implementation of DEM extraction using multiple images for improved accuracy. This paper describes a project to evaluate this capability and the algorithms used to extract DEMs from multi-look MTI imagery.