PART 8. CONTINUOUS IMPROVEMENT PROGRAM

**1. Introduction**

On March 7, 2003, Dr. Bryant Cramer gave a presentation on the EO-1
Continuous Improvement Program (CIP) at the 17^th^ annual NASA
Continuous Improvement and Reinvention Conference. This presentation
represented GSFC's contribution to this awards program. His presentation
was very well received and as a result the EO-1 Mission received a NASA
Continuous Improvement Award. The following is a photograph of Dr.
Cramer receiving the award.

![](media/image1.wmf){width="4.021527777777778in"
height="3.0145833333333334in"}

**2. Overview**

Let it first be emphasized that the CIP is International Standards
Organization (ISO) based and it is a process focused on continually
increasing the effectiveness of the management organization. The
motivation for doing this is to enhance the dissemination of EO-1
imagery to enable more infusion opportunities for its technologies into
future missions. In other words, the objective is to get EO-1 imagery
into the hands of as many people as possible, so as to maximize infusion
opportunities.

To reach this objective, the CIP was divided into four phases as shown
in Figure 1. Phase 1, known as "Accelerated Mission", started at launch
and proceeded through the first six months of the mission. The goal of
Phase 1 was to accelerate the rate at which the validation objectives
were met. It was successful and enabled Phase 2, known as "Public
Access".

Phase 2, Public Access, had two goals: The first goal was to
substantially enlarge the user community and the second goal was to
substantially reduce the cost of a data collection event (DCE). A DCE is
a set of three images simultaneously taken by the three instruments
(ALI, Hyperion, & LEISA Atmospheric Corrector) on the EO-1 spacecraft.

Phase 3, known as "SensorWeb/Test-Bed Technology Development", is
devoted to new applications and takes advantage of the enlarged user
community produced by Phase 2 to explore new opportunities for the
infusion of EO-1 technologies.

Phase 4, known as "Virtual Observatory", has the objectives to reduce
the cost of EO-1 operations by increasing the use of automation and to
reduce the overall price of delivered data.

![](media/image2.wmf)Given this short overview, specific information
follows on how the continuous improvement program was accomplished.

# Figure 1. Continuous Improvement Program Time Line

**3. Mission Description**

The EO-1 Advanced Land Imager (ALI) remote sensing instrument was
designed with five to ten times better signal to noise ratio than its
predecessor on Landsat 7. Yet EO-1's ALI uses one quarter the power,
takes up one fourth the space, and has no moving optical parts that
makes it more reliable. And all of this is accomplished for half the
cost.

EO-1 also possesses the first hyperspectral imager ever flown in space.
The Hyperion imager was designed with 220 spectral bands compared to 10
bands on the ALI. These additional bands provide finer detail of many
scientifically significant land features. For example, features on the
Earth's surface have distinctive spectral signatures, whether they are
trees in the forest, crops in the field, or minerals lying on the
surface. Traditionally, these features have been imaged through
multispectral imaging such as the Landsat capability. However, with
hyperspectral imaging, due to its many more channels and finer spectral
resolution, finer detail can now be see. And this is akin to the
difference between the earlier black and white TVs and modern color
television. With this capability, both the quantity and quality of these
features, such as crop production, can now be estimated. With this
capability, management of natural resources throughout the world can be
enhanced.

The EO-1 has also demonstrated technical improvements in formation
flying, on-board recording, and attitude control. EO-1 has also tested
an Atmospheric Corrector instrument for measuring atmospheric
disturbances inherent in space imaging data.

**4. Phase 1 -- Accelerated Mission**

To maximize the use of these new capabilities, the first key decision
was to compress the high priority objectives into the first three months
of the baseline 12 months mission. Hence, this effort was named the
Accelerated Mission phase. Successful completion meant that ample time
would be available for more risky technology assessments. The GSFC team
not only achieved these high priority objectives on schedule, but also
completed 90% of all baseline objectives in less than six months.

Figure 2 explains how this was done. The Accelerated Mission process was
initiated by addressing the original problem. That is, the calculated
reliability of the EO-1 spacecraft, taken from a probabilistic risk
assessment completed some months prior to launch, was considered. It
shows that the likelihood of completing all of our validation objectives
is approximately 0.75. This was judged to be marginal. The problem was
then, how could the probability of completing the higher priority
objectives be improved.

![](media/image3.wmf)

**Figure 2. Accelerated Mission Concept**

Such an improvement in probability was done in the following way. All of
the validation objectives were prioritized into high priority, a medium
priority, and a lower priority. Then the high priority objectives were
segregated into the first four months of the mission so that they would
enjoy the higher reliability associated with that period. The
intermediate priority objectives were then segregated into the next five
months, and the lowest priority objectives segregated into the last
three.

In order to accomplish the high priority objectives, staffing was
started at a level of 24 hrs a day and 7 days a week from the outset.
For insurance, additional ground stations were added, and an activity
was begun immediately to automate the operational procedures. In fact,
when this approach was implemented, practically all of the high priority
objectives were completed well ahead of the four months target. By the
end of six months, there was completed 90% of all that was planned to
do; and by the end of 12 months, there were produced over 2,500 Data
Collection Events which is two and a half times the sum originally
expected.

**5. Phase 2 -- Public Access**

In November 2001, EO-1 reached the 1-year mark of its mission. Armed
with its early improvements, the GSFC EO-1 team then devised new goals
for the Public Access phase of the extended mission.

The key problem to be solved was to figure out how to make the mission
self-sustaining. The budget was projected to go to zero at the end of
the baseline mission. So to solve the problem, four areas were attacked.
One, it had to be determined how to reduce the overall costs of the
mission. Two, the number of scenes acquired per day had to be increased.
Three, the turnaround time had to be decreased because some clients
needed fast delivery for their products. Four, the total user base had
to be increased.

To decrease the cost of the mission, a collaborative partnership was
established with the U.S. Geological Survey (USGS). They have a site in
Sioux Falls, South Dakota called the EROS Data Center (EDC) where they
have an antenna and processing equipment. Therefore, EDC has the
capability to downlink, process, and deliver EO-1 data much faster to
clients. EDC is good at servicing remote sensing clients and GSFC is
good at operating the satellite. Marriage of these two efficiencies has
added up to reduced costs to the mission. Further details of this
partnership are presented in Part 6.

To increase the number of images acquired per day, the image sequences
had to be streamlined to take advantage of the spacecraft maneuver
capability, where the spacecraft can be made to point and shoot
off-path. By utilizing this capability, two images can be acquired in
the same sunlight period. As a result, the number of images acquired per
day increased dramatically from approximately 6 to 20.

Holding workshops and promoting the publishing of science journal
articles by the Science Validation Team have increased the user base.
For example, there is an IEEE Transactions publication special issue
devoted entirely to the EO-1 mission science validation subject. In
addition, there are a lot of remote sensing trade journals that are
publishing results of the EO-1 mission.

With all of the above improvements incorporated, the overall mission
cost has been reduced, numbers of acquired images have increased
dramatically, people that need fast delivery are being satisfied, and
the EO-1 user base has increased to the point where the mission is
almost self sustaining. A single sensor image of just about anywhere on
the earth can be delivered by EDC for [\$500]{.underline}.

Numerous government and industry partners are now taking part in this
Public Access phase. The compacted schedule afforded by the Accelerated
Mission phase provided opportunities to pursue on-orbit engineering
tests that would likely never have been approved in a conventional
science mission. With the advanced imaging techniques developed during
the baseline phase, continued operations of the EO-1 created even more
useful images and permitted new applications to further evolve at
increasingly rapid rates and at very low cost.

Two examples of new applications that evolved from increased "public
access" relate to the fields of forest inventory and disaster
assessment. Typically, forest field workers cover 10-12 miles on the
ground per day in a costly and time consuming process. By contrast the
EO-1's Hyperion imager can cover 7.5 km per second with huge potential
for more accurate estimates of biomass, consistent forestry measurement
from year to year, and significant savings of time and money. As a
second example, the EO-1 team was called into La Plata, Maryland to
supply images for supporting the area's tornado disaster assessment
activity. This example demonstrates the EO-1's potential in performing
natural hazards analysis. Future possibilities exist in agricultural
development, coral reef and coastline protection, and mineral
evaluation.

How was it possible to substantially increase the EO-1 product output
rate while simultaneously decrease the cost of each output unit by a
significant amount? How did the EO-1 team develop what could be the
benchmark of mission efficiency through continuous improvement? The EO-1
Mission Management team took EO-1's continuous improvements from the
drawing board to orbit through an innovative application of a widely
respected business tool known as The Balanced Scorecard model of Dr.
Robert Kaplan and Dr. David Norton as published in the Harvard Business
Review of February 1996. A diagram of the methodology is shown in Figure
3.

# Figure 3. Balanced Scorecard Methodology

The key feature about EO-1 was change. Things changed rapidly and as an
example, a major instrument (Hyperion) was changed out 18 months before
launch. When dealing with a team as large as 200 people at its maximum
and 480 over the life of the mission, it is not easy to get them to make
a major change in direction on a very short notice. So this Balanced
Scorecard approach allowed communications to be streamlined and
connected management strategies to day-to day activities at all levels
in the organization via metrics.

Early in the mission, the management team sought to adopt a more formal
approach to continuous improvement. The team liked the Balanced
Scorecard technique because they maintained that managing an
organization solely through financial spreadsheets is an inadequate
approach. It was found that change is the prime mover that drives an
organization toward its objectives in a competitive environment.

Consider the above shown four boxes as maturational milestones of an
incremental improvement. Initially, the objective must be fully
understood and communicated to others so they know their part. Next,
finish the planning and proceed with the implementation. Then, what has
been done must be periodically reviewed for feedback and the vision
modified if that proves necessary.

The Balanced Scorecard tool allows one to manage all of the components
of change in a coordinated way. This management tool was liked because
it is simple, it is easily understandable, and it kept the mission
office focused on what had to be done.

Application of the Balanced Scorecard tool started with a vision. During
the first year, the GSFC team sought to accomplish the baseline mission
objectives while the EO-1 systems had the greatest reliability. This
early-on strategy was critical to the overall plan of creating the
opportunity to perform additional technology assessments in the Phase 3
SensorWeb/Test-Bed Technology Development phase.

By the time of launch, an operations plan was established that maximized
the likelihood of completing the mission. This was accomplished by time
compressing the whole mission and as a result, things, that would
normally be done at the end during months 11 and 12, were moved into the
first three months. As a result, 90% of the mission was completed in the
first 6 months.

This approach produced excess capacity that could be reinvested to
develop the follow-on Test-Bed phase of the mission. The reason this was
done was to maximize the investment and benefit to the public. As a
result, communications were successfully streamlined to match the
overall strategy with day-to-day operations and activities.

The GSFC team coordinated communication between hundreds of specialists
working for numerous organizations around the world. Through electronic
mail, and other informal interactions, they effectively defined the
metrics that would measure EO-1's success.

In terms of planning, the team developed action plans to optimize the
key metrics and defined the necessary tasks, such as finding ways to
automate the operation procedures and staff the first three months at 24
hours a day and 7 days a week.

Finally, the feedback came by measuring and evaluating the results.
First year results included the fact that 90% of the baseline mission
was completed by the end of the sixth month. Instead of collecting only
the required 800 images, over 2000 images were successfully collected in
the first 11 months.

EO-1's continuous improvement process has been reaping benefits. As
metrics clearly show in Figure 4, EO-1's continuous improvements include
a drastically reduced cost per data collection event (DCE) from [\$7500
to \$1100]{.underline} and most likely it will drop below the goal of
[\$1000]{.underline}.

## Phase 2 -- Public Access

![](media/image4.wmf)

# Figure 4. DCE Cost Reduction Process

Since the fourth month, successive iterations of continuous improvements
show similar success in reducing mission workload through automation as
shown in Figure 5 below.

## Phase 2 -- Public Access

![](media/image5.wmf)

# Figure 5. Results of Automating Procedures

A metric shown in Figure 6 illustrates that the GSFC team also reduced
image turnaround time by more than 60 % during CY 2002 alone. During the
last 7 months of CY 2001 plus all of CY 2002, multiple iterations of
data collection demonstrate continuous improvement in the number of
images produced by EO-1 as demonstrated in Figure 7. Another metric in
Figure 8 shows that the number of users accessing these images nearly
doubled during CY 2002.

***Phase 2 -- Public Access***

![](media/image6.wmf)

# Figure 6. Turnaround Time

### Phase 2 -- Public Access

![](media/image7.wmf)

# Figure 7. Data Collection Rate (DCE per Day)

### Phase 2 -- Public Access

![](media/image8.wmf)

# Figure 8. User Growth

**6. Phase 3 -- SensorWeb/Test-Bed Technology Development**

Phase 3 seeks to capitalize on the expanded user community developed
under the preceding Phase 2 -- Public Access phase to explore new
applications for EO-1 technologies. Specifically, the purpose of Phase
3, which started 19 months after launch, is to use EO-1 as a test-bed to
validate some key concepts necessary to implement sensorwebs in the
future. Figure 9 shows the concept validation activities thus far
initiated with color-coding to show which activities are funded and
which are proposed. The motivation for pursuing this phase is based on
the belief that some of these new applications will develop into
infusion opportunities for EO-1 technologies. For example, as shown, the
EO-1 team has developed an on-board cloud detection algorithm that
operates in real time that can both greatly decrease the number of
cloudy images which would be subjected to unnecessary costly full
processing and also increase the number of cloud free images taken by
utilizing autonomous rescheduling. See Part 16 -- Appendices, Item 13
for a paper that documents the successful flight validation of the cloud
detection algorithm.

#### ![](media/image9.wmf)Phase 3 -- SensorWeb Test-Bed Technology Development

# Figure 9. EO-1 Test-Bed Activities

The key capability necessary to enable the performance of the
Preliminary EO-1 Autonomous Experiment is to create a mission wide,
end-to-end information bus that performs like the internet. A user
should be able to send a message to any software task used on the
mission (whether space or ground) by naming it and the sensor web system
should take care of the details. Once this end-to-end information bus is
available, then progressive mission autonomy is easily created by
writing scripts and using various autonomy applications on top of this
messaging system. To optimize this messaging system mission-wide, the
space to ground interface must be seamless and also the
spacecraft-to-spacecraft interface must be seamless. An important
concept is that the messaging system sits on top of any protocol whether
it is TCP/IP or any other protocol For example, if you make a phone
call, all that you care about is that the phone call gets to the
targeted party. The phone call may be routed through the internet and
two other phone systems. Finally, these capabilities can be used to
group a set of unrelated satellites and for some arbitrary time declare
them a functional constellation such as is the case for the "Morning
Constellation" with the key difference being that they act functionally
uniform as is the case with many disparate functions on the internet.

For the purposes of these activities, the messaging system is being
called a "Dynamic Software Bus". It is built on top of the existing EO-1
software bus that is a static software bus. The key added feature being
added is the "Dynamic" ability to plug new applications in, whether on
the satellite or on the ground and have the system recognize the
application by name. Applications added to this system, such as the
CASPER onboard planning system, enable the larger concept of Dynamic
Resource Management whereby this distributed constellation system takes
care of many of the details of allocating and managing resources. In an
initial demonstration, a part of the EO-1 tasking process will be
handled onboard by CASPER that will plug into the dynamic software bus
that was implemented on EO-1. Figure 10 shows the conceptual layout of a
mission-wide dynamic software bus. Color coding cross correlates
activities related to Figure 9.

![](media/image10.wmf){width="5.0in" height="3.75in"}

# Figure 10. Mission-wide messaging system to enable progressive autonomy

Figure 11 shows how software can be added to convert the EO-1 software
bus, being performed by Spacecraft Control language (SCL), into a
dynamic software bus. The key capability is the ability to easily plug
in new applications while EO-1 is on-orbit and having the EO-1 flight
software recognize the software. Figure 12 shows the top level
architecture of how CASPER, the onboard planner, is "plugged-into" the
dynamic software bus.

##### ![](media/image11.wmf){width="5.0in" height="3.75in"}Figure 11. Depicts the adding of software to create a dynamic software bus on EO-1

![](media/image13.wmf){width="5.0in" height="3.75in"}

**Figure 12. Depicts planning architecture being developed on top of
dynamic software bus**

Figure 13 is a representative set of types of experiments that will be
conducted once the CASPER system is installed on EO-1. Furthermore, once
CASPER is onboard, some rudimentary sensor web experiments will be run
whereby observations on EO-1 are triggered by some key MODIS instrument
observation such as forest fires and volcanoes. EO-1 would be triggered
to semi-autonomously take a closer look. JPL is also participating to
have an EO-1 observation triggered by a ground sensor web
![](media/image14.wmf){width="5.0in" height="3.7506944444444446in"}if
certain flood conditions occur.

##### Figure 13. Some of the planned types of experiments once CASPER is installed on EO-1

Another concept was studied to overcome a problem hindering the
implementation of sensor webs due to the limited contacts that exist for
low earth orbiting satellites. If a user wants to message a low earth
orbiting satellite at present, there is a limitation of 4 --8 ea. 10
minute passes for satellites such as EO-1. This does not lend itself
well to the concept of having a messaging system that can access a
satellite from anywhere in the mission at any time. Therefore, there is
an effort to develop a concept of inexpensive, ground-based hybrid
phased array antennas that would be placed around the country and
perhaps the world to provide as close to total coverage as possible,
thus making the dynamic software bus for a mission more of a reality.
This is especially essential if true progressive autonomy is desired
whereby functionality is inserted into an ad hoc constellation mission
while on-orbit. This concept is illustrated in Figure 14.

The Preliminary EO-1 Autonomy Experiment activity was conducted wherein
an on-board planning system, CASPER, was installed that allowed EO-1 to
perform on-board replanning to perform such things as event driven
onboard planning. With successful completion of this activity as a
prerequisite, a SensorWeb Demonstration activity was performed. The
general concept for this technology activity is to demonstrate the
ability to autonomously trigger the EO-1 into an onboard DCE replanning
mode based on a scene observation made by another spacecraft instrument.
As a preliminary demonstration, the TERRA MODIS instrument observation
of a forest fire was used to trigger an EO-1 observation. Initially all
planning was done on the ground but with all the planning steps
automated as much as possible in incremental steps. Figure 15
illustrates SensorWeb Demonstration -- Scenario 1 and Figure 16
illustrates SensorWeb Demonstration -- Scenario 2.

### ![](media/image15.wmf)

# Figure 14. Hybrid Ground Phased Array Antenna Concept

### 

# ![](media/image16.wmf)Figure 15. SensorWeb Demonstration -- Scenario 1

# 

![](media/image17.wmf)

# Figure 16. SensorWeb Demonstration -- Scenario 2

Not only would all of this improvement technology be infused into future
NASA missions, but also it will be widely disseminated to the public
through the Internet, scientific publications, and through lectures and
public forums.

**7. Phase 4 -- Virtual Observatory**

Phase 4 has two objectives. One objective is to reduce the cost of EO-1
operations by increasing automation both on-board and on the ground.
Examples of how to do this are to steadily reduce labor over time by
incremental improvements and to run a "lights out" Flight Operations
Team with minimal engineering support after June 2004. The other
objective is to reduce the price of conducting new sciences studies
commensurate with the operations cost reductions. The goal is to reduce
the customer price for image acquisition plus delivered data from
[\$2000]{.underline} to between [\$500 and \$700]{.underline}. The price
breakdown goal is \$300 to \$500 for acquisition and \$200 for data. The
potential price for archived data is [\$100]{.underline}.

To streamline EO-1 operations, the following approach was adopted:

-   USGS/EDC to convert to a web-based automated scheme for fulfilling
    user requests and to track orders and delivery.

-   NASA/GSFC to implement automation for real-time operations, scene
    ingest, scheduling, and command load generation.

-   Bullet-proof on-board autonomy.

-   Fully implement Science Goal Monitor and other web-based interfaces
    for SensorWeb activities.

In concert with an incremental approach, EO-1 is pursuing increased
mission operations autonomy by going into a more fully automated mode
using both Automated Scheduling and Planning ENvironment (ASPEN) on the
ground and Continuous Activity Scheduling, Planning Execution and
Replanning (CASPER) flight software on EO-1. The purpose of this
increased automation is to further extend the automation of operations
to include the activities of the scheduling and prioritization group
which consisted of the USGS National Center for Earth Resources
Observations and Science (EROS); EO-1 Mission Science Office; JPL
Autonomous Sciencecraft Experiment (ASE) group, which is the group
conducting the Volcano Sensor Web experiments on EO-1; and the EO-1
flight operations team (FOT). Normally, this group holds a meeting once
a week to plan out the following weeks' activities by selecting them
from a master list of available targets and other engineering and
technology activities. In the new more fully automated mode, ASPEN will
generate the weekly selected targets at JPL automatically using an
internal prioritization scheme developed by the team, thus removing the
scheduling group as the middleman between the customers and the actual
imaging operations. ASPEN will then uplink the plan to CASPER on the
spacecraft via the EO-1 Mission Operations Center (MOC) as the baseline
default schedule. Possible daily changes to the schedule can originate
from 3 sources -- volcano sensor web replacements, Earth Phenomena
Observation System (EPOS) which optimizes selections for least cloudy
scenes, and last minute priority inserts from the USGS EROS or GSFC. The
EPOS system is a system created by MIT Draper Labs through a NASA Earth
Science Technology Office NASA Research Announcement award.

Checkout of each interface will be conducted in parallel with each of
the two target selection methods, over a period of 4-5 weeks, until the
automated system is proven to work.

Here are some individual items that will help clarify the needed
procedure changes.

-   EROS will send a subset of the Long Term Plan (LTP) records, with
    appropriate priorities, to JPL (and GSFC) by COB each Monday. The
    LTP is a list of all desired future targets for the life of the
    mission. These scenes will not include JPL or GSFC
    records/selections as those will be ingested directly by the ASPEN
    system at JPL.

-   JPL will generate a weekly selected targets list by COB each
    Wednesday and send the list to everyone.

-   CASPER Goal file(s), containing each day of the week\'s selected
    targets, will be uplinked to EO-1 daily as the baseline default
    observation schedule. These files, generated for CASPER , are
    abstractions of the full list of commands used to command EO-1 to
    take scenes. The Goals are ingested by CASPER onboard and as a
    result, CASPER knows how to control EO-1 to take the desired targets
    and make decisions on its own based on the observations. The
    possible daily changes, sent to ASPEN for uplink, can come from the
    sensor web software (for volcanoes/etc.); EROS or GSFC (priority
    replacements); and EPOS replacement requests based on evaluated
    choices for least cloudiness between conflicting scenes of equal
    priority.

-   After each day's activities are accomplished, the JPL ASPEN software
    will generate a report telling what activities have been executed
    on-board that includes all replacements inserted since the baseline
    schedule was uplinked, and will deliver this report to EROS and
    GSFC. EROS will update their systems to pick up the new records so
    they can be processed to Level 0 and deliver, via FTP, any sensor
    web scenes to JPL in addition to delivering all Level 0 scenes to
    GSFC for off-site archive backup.

Some required constraints during this initial phase of attaining a more
fully automated mode are:

-   No Dual scenes

-   No Hobart or EDC downlinks

-   Last minute replacements are required to have their priority set
    higher than their

-   corresponding default baseline record before being uplinked.

**8. Conclusions**

EO-1 has experienced four phases of continuous improvement. In Phase 1,
GSFC conducted 90% of the validation objectives in only half of the time
allowed and went on to gather two and a half times the number of images
originally expected.

In Phase 2, the cost of a data collection event (DCE) was reduced from
\$7500 in the first month to only [\$843]{.underline} at the end of the
17^th^ month. The data collection rate was increased from four to 20
DCEs per day, which is essentially the design limit of the spacecraft.
And finally, a partnership was forged with the USGS that makes all of
the archived EO-1 data publicly available through the Internet for the
cost of reproduction and that provides the public the opportunity to
order unique images of their choosing.

In Phase 3, new applications for these technologies were explored. The
EO-1 Continuous Improvement Program proved to be a powerful and
practical tool for enhancing the effectiveness of the EO-1 mission.

In Phase 4, a high degree of mission autonomy was implemented both at
NASA/GSFC and at USGS/EDC for on-board and ground operations. This high
degree of autonomy resulted in a substantial reduction in mission
operations cost and a corresponding reduction in the price structure for
image data.