The NEON Imaging Spectrometer: Airborne

The NEON Imaging Spectrometer: Airborne Measurements of Vegetation Cover
and Biochemistry for the Continental-scale NEON Observatory
Thomas U. Kampe, Brian R. Johnson, Michele Kuester, Joel McCorkel
National Ecological Observatory Network, Inc.
Abstract
The National Ecological Observatory Network (NEON) will fly an imaging spectrometer as part of the
instrument payload aboard the Airborne Observation Platform (AOP) to obtain spectroscopic
information on terrestrial ecology at sub-meter to meter scale ground resolution. The NEON imaging
spectrometer will measure surface reflectance over the continuous wavelength range from 380 to 2500
nm sampled at 5 nm with high spatial and spectral uniformity. The NEON imaging spectrometer
represents a significant advancement in ecological research by providing high-resolution remote sensing
data of land cover and lands use, plant biochemistry and biophysical properties, and detection of
invasive plant species. NEON, funded by the National Science Foundation, is a continental-scale
ecological observatory for discovering, understanding, and forecasting the impacts of climate change,
land-use change, and invasive species on ecology. NEON will observe both the human drivers of
climate change and the biological consequences of environmental change. Local flux tower and field
measurements at sites within the 20 NEON ecoclimatic domains distributed across the contiguous
United States, Alaska, Hawaii, and Puerto Rico will be coordinated with high resolution, regional
airborne remote sensing observations. In addition to the NEON imaging spectrometer, AOP remote
sensing instrumentation consists of a scanning, small footprint waveform LiDAR for 3-D canopy
structure measurements and a high-resolution airborne digital camera which, in combination, provide a
unique data set for bridging scales from organisms and stand scales to the scale of satellite based remote
sensing. The AOP science objectives, key mission requirements, and development status are presented
including an overview of near-term activities associated with the development of NEON Imaging
Spectrometer Design Verification Unit.
Introduction
The National Ecological Observatory Network (NEON) is a planned facility of the National Science
Foundation for discovering and understanding the impacts of climate change, land‐use change, and
invasive species on continental‐scale ecology (Keller et al., 2008). A wide range of biotic and physical
processes link the biosphere, geosphere, hydrosphere, and the atmosphere. However, our understanding
of the biosphere does not match our increasingly sophisticated understanding of Earth’s physical and
chemical systems at regional, continental, and global scales. Because many responses and feedbacks
within the biosphere are large-scale, they cannot be investigated effectively with disconnected studies
on individual sites or over short periods of observation. The NEON science focuses on questions that are
relevant to large regions, and that cannot be addressed solely with traditional ecological approaches
(Field et al., 2006). NEON is based on a multi-scaled sampling strategy, employing systematically
deployed ground-based sensors, high-resolution airborne sensors and integration with national
geospatial information.
The objective of the NEON observatory is two-fold: infrastructure will be developed to provide
systematic, long-term, large-scale data sets to scientists, students, educators and decision-makers.
NEON will also serve as a research and educational platform for investigator-initiated sensors,
observations, and experiments. NEON’s educational and outreach program will include numerous
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physical and virtual capabilities to enable educational and public use of the facility, including a central
web portal to provide on-line learning experiences, tools for decision makers, professional
developmental opportunities to prepare educators to use NEON data and educational tools, and research
and internships opportunities. NEON will support workshops, seminars, and courses to provide training
and learning experiences for individuals to more effectively use and contribute to NEON data, tools, and
learning experiences.
In this paper, we discuss the role of airborne remote sensing in the NEON design. The airborne
instrumentation currently under development for NEON will provide the capability for obtaining
detailed, regional measurements of ecosystem structure and function. NEON partitions the United States
into 20 ecoclimate domains (Fig. 1) based on a statistical analysis of ecoclimate state variables. Each
domain contains one fully instrumented core site located in a wildland area and two relocatable sites
which have been selected to address ecological gradients. By bringing together observations from field
observations, core and relocatable sites, airborne sensors, and mobile ground-based observing systems,
as well as assimilating information from satellite and national data sets, the observatory aims to capture
the ecological and climate variability at the continental scale over a 30-year period.
Fig. 1. The NEON Domains distributed across the continental United States, Alaska, Hawaii,
and Puerto Rico.
AOP’s Role in NEON
The NEON Airborne Observation Platform (AOP) will, for the first time, enable routine meter-scale
remote sensing measurements of vegetation structure and biochemistry, and land-use over more than 2
million hectares surrounding the 60 NEON sites on a yearly basis (Johnson et al., 2009). The major
functional elements of the AOP are three aircraft platforms, 3 identical remote sensing instrument
payloads, a sensor calibration facility, a data processing and distribution facility, and flight operations.
Each remote sensing instrument payload consists of an imaging spectrometer, a small footprint
waveform-LiDAR, a high-resolution digital camera, a dedicated Global Positioning System (GPS) and
Inertial Measurement Unit (IMU) subsystem, and an instrument controller and data capture subsystem.
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The requirements for the AOP aircraft are largely driven by the characteristics of the sensors to be
flown and the need to provide observations over the 60 NEON ground sites. In particular, the maximum
flight altitude is set by the required signal-to-noise ratio necessary for retrieving vertical structure from
the waveform LiDAR. The low flight altitude limit and range of ground speeds are set by a desire to
achieve 1 to 3-meter ground resolution, and a need to maximize signal integration time for the
spectrometer, respectively. Together, the waveform LiDAR and spectrometer requirements drive the
desired aircraft platform capability towards a low and slow performance range with survey speeds of
160 to 200 km/hr and survey altitudes between 1,000 and 3,000 m.
Instrumentation
The NEON imaging spectrometer is a pushbroom imaging spectrometer that measures the
upwelling radiance of the Earth in 426 narrow spectral bands from 380 to 2510 nm at a spectral
sampling of 5 nm. The hyperspectral data provided by the imaging spectrometer provides the capability
to assess vegetative species diversity and classify vegetation to plant functional types or species levels
(Ustin et al., 2004). Shortwave infrared bands provide the capability for discriminating tropical and
temperate tree species and discrimination of senesced plant materials, wood, or bark from background
soils (Roberts et al., 2004; Clark et al., 2005). Visible to near-infrared bands provide the capability for
characterizing canopy chemistry, physiology, and type.
The NEON imaging spectrometer uses a single spectrometer module and focal plane array to
achieve the required spatial and spectral uniformity. The entire imaging spectrometer, including
telescope, spectrometer and focal plane array will be housed in a vacuum chamber cryogenically cooled
to 150 K to minimize background and dark noise. This is required to meet the high signal-to-noise ratio
needed to support the science measurements, in addition to providing a controlled thermal environment
for the spectrometer during flight operations. An on-board calibration subsystem integral to each
imaging spectrometer provides the capability for flat fielding every imaging spectrometer data set,
traceability to laboratory calibration standards, and monitoring of imaging spectrometer performance
over time. The on-board calibrator, in conjunction with the NEON laboratory calibration facility also
allows for cross calibration between replacement sensors over the 30-year lifetime of the NEON
observatory and between sensors flying on separate airborne platforms.
The choice of a small footprint waveform LiDAR was driven by the desire to record the entire timevarying intensity of the returned energy from each laser pulse and obtain a record of entire height
distribution of the objects illuminated by the laser pulse (Lefsky et al., 2002) as well as the desire to
resolve individual plant canopies and vegetation clusters. The waveform LiDAR requires a high pulse
repetition frequency; high scan frequency; and measurements over a wide scan angle of 35 degrees with
a ground resolution of 1 to 3 meters to match the observing characteristics of the imaging spectrometer.
High-resolution imagery from the digital camera is useful for determining land use and allows for full
visualization of the morphology of site locations. Panchromatic imagery from the camera will be
provided at a resolution at least three times finer than the spectrometer resolution over a field of view
matching the swath of the other AOP sensors.
Remote sensing measurements from all instruments on the payload must be accurately registered in
a common geographic coordinate system during ground data processing. This requires the relative
alignment of the optical sensors be accurately known and remain stable during flight. The integrated
GPS/IMU provides precision measurements of instrument payload position and attitude during remote
sensing data collection. This information will be combined with knowledge of the relative orientation of
the spectrometer, LiDAR, and camera in the GPS/IMU reference frame to compute the line-of-sight
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trajectory of each laser shot and spectrometer detector element at a specific time. Data collected over
each site will be stored on removable hard drives and sent to the NEON Headquarters for processing at
the NEON Cyber Infrastructure facility.
Operations
The AOP flight plan for each year will include the standard observations of the core and relocatable
sites of all 20 NEON domains, as well as directed flights to planned targets or unplanned flights in
response to unanticipated events (e.g. response to wildfire). The flight season will extend from April to
September for the sites located in the contiguous 48 states. Flights over the Alaskan sites will occur in a
relatively narrow time window in July and August. Data collections over sites in Hawaii and Puerto
Rico have relatively wide time windows of opportunity. Puerto Rico will be flown early in the year to
avoid the hurricane season. Hawaii will be the last domain flown as not to significantly impact the
campaign year since equipment must be shipped over the Pacific Ocean.
The baseline mission flight plan is optimized so that sites are over-flown during peak productivity
and at a time with the best chances for cloud-free weather or minimal cloud cover. These considerations
are balanced with consideration for distances between domains in order to efficiently cover all the sites
with the least amount of transit time. The notional baseline mission-plan for the year will be established
in February and March for the upcoming season and initial flight plans will be released for all sites to be
flown in that year. Payload 3 will be used for directed flights and as a "hot spare" for the first two
payloads. These directed flights could include additional flights over NEON domain sites for phenology,
transects over scientifically important regions, areas impacted by wildfire or other natural disasters,
rapid deployment for significant natural or unnatural disasters, or as part of joint campaigns with other
agencies. The mission plan for each year will be posted on the NEON website (www.neoninc.org).
Near-Term Development Activity
Early development of the remote sensing payload provides an opportunity to reduce the design and
fabrication risk prior to actual spectrometer builds during NEON construction. By building and testing
an imaging spectrometer design verification unit and demonstrating that key performance and
operational goals have been met, the majority of technical risk can be retired prior to science operations.
In September 2009, NEON Inc. was awarded a 2-year grant by the National Science Foundation for the
development of the NEON Imaging Spectrometer Design Verification Unit. In addition to hardware
development, this program includes scientific software design and prototype science algorithm
development associated with Level-1 science data processing. As part of this development effort, a
series of test flights are also planned. These include vicarious calibration flights to verify procedures and
validate radiometric laboratory calibration and instrument boresight co-registration, and a flight
campaign targeted at advancing LiDAR-imaging spectrometer data fusion.
AOP’s Role in NEON Science
By taking advantage of the powerful synergy between imaging spectrometer and waveform LiDAR
measurements (Asner et al., 2007), the AOP provides the capability to quantitatively measure
biochemical and biophysical properties of vegetation at regional scales. It will therefore play a key role
in bridging scales from organism and stand scales, as captured by field and tower observations, to the
scale of satellite-based remote sensing. Unlike traditional field measurements which provide dozens to
perhaps hundreds of samples over a region, the AOP will provide thousands of high resolution (1-3
meters) observations over hundreds of square kilometers at each of the NEON sites distributed across
the contiguous United States, Alaska, Hawaii, and Puerto Rico. While multi-spectral remote sensing
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instruments operating from space can provide global coverage at daily or multi-day intervals, the spatial
resolution obtainable from these instruments (e.g., Landsat; 30 m, MODIS; 250 m) is barely sufficient to
resolve even the largest tree crowns, and insufficient to detect small scale features or disturbances which
are critical for monitoring land use change. As an example, Asner et al. (2005) showed that selective
logging in the Amazon was not detectable in Landsat images but was captured from an airborne
platform. This study showed that selective logging roughly doubled previous estimates of the total
amount of forest degraded by human activities while increasing estimated greenhouse gas emissions by
25%. Similarly, imaging spectrometer/LiDAR measurements from low-flying aircraft have
demonstrated the capability to quantify biomass (Wulder et al., 2004; Tollefson, 2009) and invasive
species (Asner et al., 2008).
The high spectral resolution and broad spectral coverage of the NEON imaging spectrometer
provides flexibility in selection of spectral features used to map plant functional types based on their
unique spectral reflectance signatures, as well as supporting a broader range of measurements including
pigment, water, nitrogen, and carbon chemistry of plants (Ustin et al., 2004). The biochemical and
physiological properties measured by the imaging spectrometer are greatly affected by vegetation
structure and shadows that occur within and between vegetation canopies (Asner et al., 2007). The
fusion of waveform LiDAR data (canopy height, crown shape, biomass estimates) with spectroscopic
data allows for a broad range of products to be produced ranging from estimates of photosynthetic and
non-photosynthetic fractional coverage, vegetation indices, pigment concentrations, light-use efficiency,
and canopy water content to higher-level products such as ecosystem productivity and estimates of
biomass at regional to continental scales that will require the assimilation of data from multiple scales
into ecological models.
AOP’s detailed mapping of sites distributed across the contiguous United States as well as Alaska,
Hawaii, and Puerto Rico, in conjunction with other NEON data sources, will provide researchers,
educators and decision makers with an unprecedented view of ecological change at regional scales over
the next several decades. All data products generated by the observatory, Level-1 data (calibrated
spectral reflectances and LiDAR waveforms), and tools for analyzing data will be freely available from
the NEON web portal.
Acknowledgements
The National Ecological Observatory Network is a large facility project sponsored by the National
Science Foundation and managed under a cooperative agreement by NEON, Inc.
References
Asner, G. P., D. E. Knapp, E. N. Broadbent, P. J. C. Oliveira, M. Keller, J. N. Silva (2005). Selective
logging in the Brazilian Amazon. Science 310, 480-482.
Asner, G. P, D. E. Knapp, T. Kennedy-Bowdoin, M. O. Jones, R. E. Martin, J. Boardman, and C. B.
Fields (2007). Carnegie Airborne Observatory: in-flight fusion of hyperspectral and waveform light
detection and ranging (wLiDAR) for three-dimensional studies of ecosystems. J. Appl. Remote
Sens. 1, 013536 [doi: 19.1117/1.2794018].
Asner, G. P., R. F. Hughes, P. M. Vitousek, D. E. Knapp, T. Kennedy-Bowdoin, J. Boardman, R. E.
Martin, M. Eastwood, R. O. Green (2008). Invasive plants transform the three-dimensional
structure of rain forests. Proc. Natl. Acad. Sci. USA 105(11), 4519-4523 [doi
10.1073/pnas.0710811105].
5
Clark, M., D. A. Roberts, and D. B. Clark (2005). Hyperspectral discrimination of tropical rain forest
tree species at leaf to crown scales. Remote Sens. Environ. 96(3-4), 375-398.
Field, C., R. DeFries, D. Foster, M. Grove, R. Jackson, B. Law, D. Lodge, D. Peters, and D. Schimel
(2008). Integrated science and education plan for the National Ecological Observatory Network,
(23 Oct 2006) <http://www.neoninc.org/documents/ISEP>.
Johnson, B. R., Kampe, T. U., M. Kuester, and M. Keller (2009). NEON: The First Continental-Scale
Ecological Observatory with Airborne Remote Sensing of Vegetation Canopy Biochemistry and
Structure. Proc. SPIE 7454, 745402 [doi: 10.1117/12.825697].
Keller, M., D. S. Schimel, W. W. Hargrove, and F. M. Hoffman (2008). A continental strategy for the
National Ecological Observatory Network. Front. Ecol. Environ. 6(5), 282-284 [doi: 10.1890/15409295(2008)6[282:ACSFTN]2.0.CO;2].
Lefsky, M., W. B. Cohen, G. G. Parker, and D. J. Harding (2002). Lidar remote sensing for ecosystem
studies. BioScience 52, 19-30 [doi: 10.1016/0034-4257(95)0039-4].
Roberts, D. A., S. L. Ustin, S. Ogunjemiyo, J. Greenberg, S. Z. Dobrowski, J. Q. Chen, and T. M.
Hinckley (2004). Spectral and structural measurements of northwest forest vegetation at leaf to
landscape scales. Ecosystems 7, 545-562 [doi: 10.1007/s10021-004-01455].
Tollefson, J. (2009). Counting carbon in the Amazon. Nature 461(22), 1048-1052.
Ustin, S. L., D. A. Roberts, J. A. Gamon, G. A. Asner, and R. O. Green (2004). Using imaging
spectroscopy to study ecosystem processes and properties. Bioscience 54(6), 523-534.
Wulder, M. A., R. J. Hall, N. C. Coops, S. E. Franklin (2004). High Spatial Resolution Remotely Sensed
Data for Ecosystem Characterization. Bioscience 54(6), 511-518.
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