In a typical waveform light detection and ranging (lidar) system, the received pulse can be represented by the convolution of the system impulse response, the outgoing pulse, and the underlying signal representing actual target interactions. Deconvolution is the process of removing the contribution of the system impulse response and outgoing pulse from the received signal, so that the true interactions may be seen. In many examples, deconvolution has been shown to expose fine structure within the waveform, which may be used to improve accuracy when estimating the vertical location of certain features. For instance, the exact location of the ground may be more accurately determined by separating the response of the ground from that of understory vegetation or vegetative ground cover. However, in order for the deconvolution to be successful, the impulse response and outgoing pulse must be known, and many deconvolution methods are sensitive to small errors in the estimation of these inputs. In this study, we propose a deconvolution method that uses a flat target response in place of the impulse response and outgoing pulse.
The National Ecological Observatory Network (NEON) is a planned facility of the National Science Foundation with the
mission to enable understanding and forecasting of the impacts of climate change, land use change and invasive species
on continental-scale ecology. Airborne remote sensing plays a critical role by providing measurements at the scale of
individual shrubs and larger plants over hundreds of square kilometers. The NEON Airborne Observation Platform is
designed to bridge scales from organism and stand scales, as captured by plot and tower observations, to the scale of
satellite based remote sensing. Fused airborne spectroscopy and waveform LiDAR is used to quantify vegetation
composition and structure. Panchromatic photography at better than 30 cm resolution will retrieve fine-scale information
on land use, roads, impervious surfaces, and built structures. NEON will build three airborne systems to allow for
regular coverage of NEON sites and the capacity to respond to investigator requests for specific projects. The system
design achieves a balance between performance and development cost and risk, taking full advantage of existing
commercial airborne LiDAR and camera components. To reduce risk during NEON construction, an imaging
spectrometer design verification unit is being developed at the Jet Propulsion Laboratory to demonstrate that operational
and performance requirements can be met. As part of this effort, NEON is also focusing on science algorithm
development, computing hardware prototyping and early airborne test flights with similar technologies. This paper
presents an overview of the development status of the NEON airborne instrumentation in the context of the NEON
mission.
The National Ecological Observatory Network (NEON) will be the first observatory network of its kind designed to
detect and enable forecasting of ecological change at continental scales over multiple decades. NEON will collect data at
sites distributed at 20 ecoclimatic domains across the United States on the impacts of climate change, land use change,
and invasive species on natural resources and biodiversity. The NEON Airborne Observation Platform (AOP) is an
aircraft platform carrying remote sensing instrumentation designed to achieve sub-meter to meter scale ground
resolution, bridging the scales from organisms and individual stands to satellite-based remote sensing. AOP
instrumentation consists of a VIS/SWIR imaging spectrometer, a scanning small-footprint waveform LiDAR, and a high
resolution airborne digital camera. AOP data will provide quantitative information on land use change and changes in
ecological structure and chemistry including the presence and effects of invasive species. A Pathfinder Flight Campaign
was conducted over a two week period during late August to early September 2010 in order to collect representative
AOP data over one NEON domain site. NASA JPL flew the AVIRIS imaging spectrometer and NCALM flew an Optech
Gemini waveform LiDAR over the University of Florida Ordway-Swisher Biological Station and Donaldson tree
plantation near Gainesville Florida. The pathfinder data are discussed in detail along with how the data are being used
for early algorithm and product development prototyping activities. The data collected during the campaign and
prototype products are openly available to scientists to become more familiar with representative NEON AOP data.
The WorldView-1 high spatial resolution commercial imaging satellite was launched on September 18, 2007.
WorldVew-1 contains a single panchromatic band with a spectral range of 400-900 nm capable of collecting half-meter
pixels on the ground with a swath width of 17.6 km. The instrument is a pushbroom scanner with a focal plane of 36400
detectors, six time-delayed integration (TDI) exposure rates, and bi-directional scanning. All of the detectors must be
calibrated for each of the twelve TDI/scan direction combinations. A pre-launch radiometric calibration was performed
on the instrument using a full-aperture integrating sphere and NIST-traceable transfer radiometers. The test data are used
to determine the absolute radiometric calibration of the instrument in units of radiance per count and also generate the
relative pixel-to-pixel gain and offset values for the non-uniformity correction. The relative gain and offset values are
updated on orbit using uniform desert targets. Image quality metrics for banding and streaking are applied to the uniform
scenes comparing calibration factors derived pre- and post-launch showing reduced values when using the updated
calibration factors. Relative radiometric performance assessment of imagery collected in the first nine months on orbit
shows that WorldView-1 has excellent radiometric image quality with banding better than 0.55% and streaking better
than 0.23%. Long term trends show that banding and streaking are not changing significantly with time.
One of the top radiometric priorities of the high-spatial resolution, commercial remote sensing industry is to achieve a superior level of image quality in all imagery products. Errors in detector gain and offset correction during product generation create noticeable image artifacts such as banding and streaking that degrade the overall image quality. Banding and streaking can be minimized by relative radiometric calibration, however, this calibration is only a temporary solution as the gain and offset of each detector will drift over time. The work presented here examines the relative radiometric performance of the QuickBird panchromatic and multispectral bands and tracks the performance from January 2005 until the present. During radiometric operations, uniform scenes of desert, ocean, forest, and snow areas are identified in the DigitalGlobe ImageLibrary. Products for these uniform scenes are generated and detector statistics are calculated for each scene. The QuickBird focal plane contains detectors that are masked so that no light reaches them. The statistics for the masked detectors are analyzed to study image-to-image variability and determine changes in detector offsets over time. Next, the detector averages for all active detectors are radiometrically corrected, and banding and streaking metrics are applied. Banding and streaking are trended to monitor changes over time. Quality metrics are also established based on the banding and streaking results to determine when the detector's gains and offsets have drifted sufficiently to require recalibration. Relative radiometric performance of the uniform scenes is compared with and without recalibration.
The QuickBird commercial imaging satellite is a pushbroom system with four multispectral bands covering the visible through near-infrared region of the spectrum and a panchromatic band. The focal plane contains 6972 detectors in each MS band and 27888 detectors in the pan band that must be calibrated. A relative radiometric correction is performed on all image data to account for detector-to-detector non-uniformities and to reduce banding and streaking that would otherwise be seen in the imagery. The goal of the relative radiometric correction, other than to minimize image artifacts, is to scale all image pixel brightness digital numbers (DNs) to top-of-atmosphere spectral radiances so that one set of absolute calibration factors can be applied to all pixels in a given band. A series of uniform imagery collected between February and June of 2004 was radiometrically corrected and analyzed for banding and streaking performance. Banding in QuickBird imagery is less than four DNs in normal desert, ocean, and forest scenes. Desert scenes alone have a percent banding of less than 0.5% in the MS bands and less than 0.7% in the pan band. Banding is less than 2% for typical scenes. Streaking is less than 0.6% for all MS and pan detectors.
The QuickBird commercial imaging satellite is a pushbroom system with four multispectral bands covering the visible through near-infrared region of the spectrum and a panchromatic band. 6972 detectors in each MS band and 27888 detectors in the pan band must be calibrated. In an ideal sensor, a uniform radiance target will produce a uniform image. Unfortunately, raw imagery generated from a pushbroom sensor contains vertical streaks caused by variability in detector response, variability in electronic gain and offset, lens falloff, and particulate contamination on the focal plane. Relative radiometric correction is necessary to account for the detector-to-detector non-uniformity seen in raw imagery. A relative gain is calculated for each detector while looking at a uniform target such as an integrating sphere during ground calibrations, diffuser panel, or large desert target on-orbit. A special maneuver developed for QuickBird called the "Side-Slither" technique is discussed. This technique improves the statistics of a desert target and achieves superior non-uniformity correction in imagery. The "Side-Slither" technique is compared to standard techniques for calculation of relative gain and shows a reduction in the streaking seen in imagery.
Radiometric calibration of spacecraft sensors using an on-board diffuser has become an accepted method in recent years for sensors operating in the solar-reflective portion of the spectrum. In many of these approaches, the radiance from a sunlit diffuser is used to illuminate the full aperture and full optical path of the sensor. If both the bi-directional reflectance distribution function (BRDF) of the diffuser and the incident solar irradiance are known, the absolute radiance from the diffuser can be used to determine the absolute radiometric calibration of the sensor. In this work, a method for the absolute radiometric calibration using a diffuser made of S13G/LO paint for a silicon-based detector sensor with spectral bands similar to Landsat-7 ETM+ is discussed. The spectral BRDF of a witness sample of the diffuser was measured with the goniometric facility at the Remote Sensing Group of the Optical Sciences Center at the University of Arizona. A measured solar spectral irradiance spectra is used to model the radiance at the sensor entrance pupil. Also presented is a sensitivity analysis of the diffuser-leaving radiance as a function of sensor view and incident solar angle. This sensitivity analysis is used to provide an error estimate for the calibration of the sensor using a diffuser based on the S13G/LO paint.
Airborne radiometric instruments are often used to collect radiance data, whether for producing remote sensing imagery, for use in vicarious calibration, or for atmospheric correction. Reflected radiance from a test site is detected by an Exotech model 100BX radiometer that contains four different spectral filters which coincide with the first four bands of Landsat Thematic Mapper (TM). These filters can be interchanged with filters that correspond to the first three multispectral bands of SPOT. Typically these radiometers are calibrated in a laboratory environment with incandescent radiance sources whose spectral outputs are known by some established standard. In the field, the radiometers are used with a different source than that used for the laboratory calibration, namely the sun. The solar radiation based calibration (SRBC) has been demonstrated to be an accurate calibration method for these instruments. The major advantage of this method is that the source for the calibration is the same source used in acquiring field measurements. In this work, solar radiation based calibration is compared to laboratory radiometric calibration done with a spherical integrating source (SIS) and a lamp source in the Remote Sensing Group (RSG) blacklab for airborne radiometers. Results of measurements taken over Ivanpah Playa on 6 July 2000 and 4 June 2000 by an Exotech model 100BX calibrated with these methods are presented and biases in the three different calibration methods are discussed.
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