Peer-Reviewed Articles (Important Note: abstracts are displayed here in the order they were intended to appear in the printed journal. The ordering error was discovered post printing)
1171 Landsat: Yesterday, Today, and Tomorrow
Darrel L. Williams, Samuel Goward, and Terry Arvidson
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Landsat, first placed in orbit in 1972, established the U.S. as
the world leader in land remote sensing. The Landsat system
has contributed significantly to the understanding of the
Earth’s environment, spawned revolutionary uses of spacebased
data by the commercial value-added industry, and
encouraged a new generation of commercial satellites that
provide regional, high-resolution spatial images. This PE&RS
Special Issue provides an update to the 1997 25th Landsat
anniversary issue, particularly focused on the contribution
of Landsat-7 to the 34+ year history of the Landsat mission.
In this overview paper, we place the Landsat-7 system in
context and show how mission operations have changed
over time, increasingly exploiting the global monitoring
capabilities of the Landsat observatory. Although considerable
progress was made during the Landsat-7 era, there is
much yet to learn about the historical record of Landsat
global coverage: a truly valuable national treasure. The time
to do so is now, as the memories of the early days of this
historic program are fading as we speak.
1155 Historical Record of Landsat Global Coverage: Mission
Operations, NSLRSDA, and International Cooperator
Stations
Samuel Goward, Terry Arvidson, Darrel Williams,
John Faundeen, James Irons, and Shannon Franks
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The long-term, 34+ year record of global Landsat remote
sensing data is a critical resource to study the Earth system
and human impacts on this system. The National Satellite
Land Remote Sensing Data Archive (NSLRSDA) is charged
by public law to: “maintain a permanent, comprehensive
Government archive of global Landsat and other land
remote sensing data for long-term monitoring and study of
the changing global environment” (U.S. Congress, 1992).
The advisory committee for NSLRSDA requested a detailed
analysis of observation coverage within the U.S. Landsat
holdings, as well as that acquired and held by International
Cooperator (IC) stations. Our analyses, to date, have found
gaps of varying magnitude in U.S. holdings of Landsat
global coverage data, which appear to reflect technical or
administrative variations in mission operations. In many
cases it may be possible to partially fill these gaps in U.S.
holdings through observations that were acquired and are
now being held at International Cooperator stations.
1137 Landsat-7 Long-Term Acquisition Plan: Development
and Validation
Terry Arvidson, Samuel Goward, John Gasch, and
Darrel Williams
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The long-term acquisition plan (LTAP) was developed to
fulfill the Landsat-7 (L7) mission of building and seasonally
refreshing an archive of global, essentially cloud-free, sunlit,
land scenes. The LTAP is considered one of the primary
successes of the mission. By incorporating seasonality and
cloud avoidance into the decision making used to schedule
image acquisitions, the L7 data in the U.S. Landsat archive
is more complete and of higher quality than has ever been
previously achieved in the Landsat program.
Development of the LTAP system evolved over more than a decade, starting in 1995. From 2002 to 2004 most attention has been given to validation of LTAP elements. We find that the original expectations and goals for the LTAP were surpassed for Landsat 7. When the L7 scan line corrector mirror failed, we adjusted the LTAP operations, effectively demonstrating the flexibility of the LTAP concept to address unanticipated needs. During validation, we also identified some seasonal and geographic acquisition shortcomings of the implementation: including how the spectral vegetation index measurements were used and regional/seasonal cloud climatology concerns. Some of these issues have already been at least partially addressed in the L7 LTAP, while others will wait further attention in the development of the LTAP for the Landsat Data Continuity Mission (LDCM). The lessons learned from a decade of work on the L7 LTAP provide a solid foundation
1129 Landsat-7 Long-Term Acquisition Plan Radiometry – Evolution over Time
Brian Markham, Samuel Goward, Terry Arvidson, Julia Barsi,
and Pat Scaramuzza
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The Landsat-7 Enhanced Thematic Mapper Plus instrument
has two selectable gains for each spectral band. In the
acquisition plan, the gains were initially set to maximize the
entropy in each scene. One unintended consequence of this
strategy was that, at times, dense vegetation saturated band
4 and deserts saturated all bands. A revised strategy, based
on a land-cover classification and sun angle thresholds,
reduced saturation, but resulted in gain changes occurring
within the same scene on multiple overpasses. As the gain
changes cause some loss of data and difficulties for some
ground processing systems, a procedure was devised to shift
the gain changes to the nearest predicted cloudy scenes. The
results are still not totally satisfactory as gain changes still
impact some scenes and saturation still occurs, particularly
in ephemerally snow-covered regions. A primary conclusion
of our experience with variable gain on Landsat-7 is that
such an approach should not be employed on future global
monitoring missions.
1179 Characterization of the Landsat-7 ETM+ Automated
Cloud-Cover Assessment (ACCA) Algorithm
Richard R. Irish, John L. Barker, Samual N. Goward, and
Terry Arvidson
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A scene-average automated cloud-cover assessment (ACCA)
algorithm has been used for the Landsat-7 Enhanced Thematic
Mapper Plus (ETM+) mission since its launch by NASA
in 1999. ACCA assists in scheduling and confirming the acquisition
of global “cloud-free” imagery for the U.S. archive. This
paper documents the operational ACCA algorithm and validates
its performance to a standard error of +5 percent.
Visual assessment of clouds in three-band browse imagery
were used for comparison to the five-band ACCA scores from a
stratified sample of 212 ETM 2001 scenes. This comparison
of independent cloud-cover estimators produced a 1:1 correlation
with no offset. The largest commission errors were at high
altitudes or at low solar illumination where snow was misclassified
as clouds. The largest omission errors were associated
with undetected optically thin cirrus clouds over water. There
were no statistically significant systematic errors in ACCA
scores analyzed by latitude, seasonality, or solar elevation
angle. Enhancements for additional spectral bands, per-pixel
masks, land/water boundaries, topography, shadows, multidate
and multi-sensor imagery were identified for possible use
in future ACCA algorithms.
1147 Landsat in Context: The Land Remote Sensing Business
Model
Kass Green
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Earth remote sensing has long been considered essential
to human endeavors. Beginning with military reconnaissance
and evolving to weather, agriculture, environmental,
and disaster monitoring, remote sensing broadens our view
and provides context for our actions. While the provision
of airborne remote sensing data is overwhelmingly a function
of the commercial sector, space remote sensing remains
predominately the purview of the public sector. Most attempts
to commercialize space remote sensing have failed because
there has not been a consumer base large enough to finance
the enormous fixed costs of designing, building, launching,
and operating space remote sensing systems. This paper
reviews the business models for remote sensing with a
particular emphasis on the Landsat program including its
history and its political economy.