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Ideation Method for Satellite Image Applications
with Three Axes Data Representation andCause-Effect Chains
Yuki Ojiro*
PASCO Corporation
Seiko Shirasaka
Graduate School of System Design and Management, Keio University

ABSTRACTThis study aims at proposing a method to support generating satellite image utilization
ideas. Recently, expectations for potential values of satellite image utilization have been
increasing. However, the use of satellite images is still limited to specific fields. One of
the reasons is the difficulty in generating utilization ideas, but none of the ideation
methods previously developed addresses the difficulties involved in creating satellite
images application ideas. Therefore, the authors developed a method consisting of four
sub methods; supporting clarification of what can be seen from satellite images,
supporting extraction of what can be understood from satellite images, supporting
identification of potential users and supporting consideration of potential users’ issues tobe solved. To evaluate the method, the author conducted experiments of idea generation
with the method. The result indicates that the method is effective to generate novel ideas
with unobvious connection between satellite images and addressed issue.
Keywords: Satellite images, Idea generation, Ideation method.
Received 1 February 2019 | Revised 5 May 2019 | Accepted 1 June 2019.

1. INTRODUCTION
Recently, expectations for potential values of satellite image utilization have been
increasing. For example, the World Bank (European Space Agency, and the World Bank,2013) and the United Nations Statistical Commission (Australian Bureau of Statistics,
2016) have been trying to utilize satellite images to facilitate the achievement of
Sustainable Development Goals (SDGs). Cabinet Office of Japan (CAO) also states theimportance of promoting satellite image utilization as space industry including services
utilizing satellite images is strong driving force to increase productivities of other sectors(Space Policy Commission, 2017).
However, the use of satellite images is still limited to specific fields. According to thestudy by National Space Policy Secretariat, CAO, the size of a global market for services
using satellite images is only 4% of that for services using positioning satellites (locationand time data) and moreover only 2% of that for services using communication satellites(National Space Policy Secretariat, 2016).
There are several reasons for the limited use of satellite images. They are inadequacy ofcontinuously observed satellite images, difficulty in accessing satellite images, skills
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required to analyze satellite images and difficulty in creating satellite utilization ideas(Space Policy Commission, 2017).
Among those factors mentioned above, difficulty in creating utilization ideas needs to beaddressed. This is because it is expected that other factors will be improved. For instance,with respect to the insufficient data, development of small satellites is currently active
globally, and it is believed that the data volume will rapidly increase. Also, with regard to
expertise and cost required for analysis, artificial intelligence has been utilized to analyze
satellite images recently, which will make the analysis of satellite images easier in the
future. In this situation, it is necessary to support creation of satellite image utilization
ideas to promote satellite image utilization.
One of the reasons for the difficulty in creating ideas is that information extracted directlyfrom satellite images is not directly related to the issues to be solved. The authors
analyzed cases where satellite images are utilized to solve social or business issues andfound out that there is no direct connection between what can be seen directly fromsatellite images and addressed issues and that issues are rather solved by what can beunderstood from the things directly seen from satellite images and further, what can beunderstood from that. Accordingly, it is difficult to search for potential issues which canbe solved by satellite images, and this makes it difficult to create ideas of satellite image
utilization.
There have been many researches about ideation methods. Takahashi (2001) categorizes
ideation methods into four types; divergent method, convergent method, combined
method and attitudinal method. For the purpose of creating satellite image utilization
ideas, firstly, one needs to generate ideas, and thus divergent method or combined method(combination of divergent and convergent methods) are suitable. However, none ofdivergent and combined method developed before addresses difficulties in creating
satellite images utilization ideas mentioned previously. Brainstorming (Osborn, 1953),
one of divergent method is useful to expand solution areas for one theme. This method
would be suitable when one tries to come up with many ideas of what can be known froma certain thing seen from satellite images, but it is difficult to think from satellite images
to issues to be solved. Input-output method (Takahashi, 2001), one of combined methods
can support considering solutions to certain issues step by step, but as issues need to be
set for ideation, this method is not suitable for generating ideas of satellite image
utilization. Ideation methods utilizing analogy thinking such as TRIZ (Altshuller, 1984)and WordTree (Linsey and Wood, 2012) are also difficult to be applied as there is not somuch practices of satellite image utilization. Therefore, the authors decided to develop an
ideation method which can address the difficulties in creating satellite image utilization
ideas needs to be developed.
This paper consists of four chapters. The first chapter explained background and the
purpose of this research. The second chapter will explain the method developed in thisresearch. The third chapter will explain evaluation of the developed method. Lastly,
chapter 4 will explain conclusion of this paper.
2. PROPOSED METHOD
2.1. Development of method
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2.1.1. Extraction of functions
To extract functions necessary to facilitate generating satellite image utilization ideas, theauthors analyzed cases where satellite images are utilized to solve social or businessissues. Cases were collected from good practices introduced on Eurisy and Japan
Aerospace Exploration Agency (JAXA) and applications awarded from Copernicus
Masters held by European Space Agency (ESA). We extracted constituent elements ofcollected cases and analyzed how they are connected each other to extract required
functions.
As a result of the analysis, four elements that make up satellite image applications wereextracted; what can be seen from satellite images, what can be understood from that, users
utilize the information and addressed issues (Figure 1). For example, in the case of
improving the efficiency of poverty mitigation measures, the height of houses and thematerial of roofs which can be viewed from satellite images are used to detect areas to beprioritized for poverty mitigation measures. The height of houses and the material ofroofs change depending on the economic situation of families living there (poorhouseholds tend to have straw roofs, while families with certain income have metal roofs),so from the height of houses and the material of roofs one can understand economic
situations of households. Accordingly, economic situations of households tell the
mitigation measures implementers where households in need are located and where theyshould put priority (Figure 2).

Issue
Solve

Satellite image

What can be seen
See

Have

user

Understanding

Use

UnderstandFigure 1 Elements in satellite image application

Solve

House height
Roof material

Householdeconomic situation

UnderstandIssue: do not know
where to place priority
on poverty prevention
Have

Location of householdin need of assistance

UnderstandPoverty alleviation
organization
Use

Figure 2 Analysis result of improving the efficiency of poverty mitigation measures

In malaria risk monitoring case, vegetation distribution extracted from satellite images isused to address the need by governments or organizations taking malaria preventing
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measures to know places to distribute mosquito net for malaria control with priority.
From vegetation coverage, one can know places with good condition for mosquitoes tobreed. As mosquitoes transmit malaria, mosquito breeding sites can be malaria prone
areas. Then, by providing information on places where malaria is likely to occur, theissues the governments or organizations have will be solved (Figure 3).

Solve

Vegetation
distribution

places with goodcondition formosquitoes

Understand

Places wheremalaria is likely
to occurIssue: do not know
where to prioritize to takemeasures against malaria
Have

Organization to takemeasures against malaria

UnderstandFigure 3 Analysis result of malaria risk monitoring

Based on the result of case studies, the authors decided to develop a method with thefollowing four functions. In order to extract what can be understood from what can beseen from satellite images, it is necessary to clarify what can be seen from satellite images
beforehand. However, it is difficult to understand what can be seen from satellite images
for non-experts on satellite image analysis. Therefore, making it easier to clarify what isvisible from satellite images is added as a function.
 Function 1: supporting clarification of what can be seen from satellite images
 Function 2: supporting extraction of what can be understood from what can be seenfrom satellite images
 Function 3: supporting identification of users who use extracted information
 Function 4: supporting consideration of issues held by the users and to be solved by
the extracted information
Figure 4 shows the overall picture of the functions of the proposed method.
2.1.2. Construction of methods
To construct methods to realize the four functions extracted in the previous section, theauthors further analyzed examples used for function extraction. The result of analysis
shows that what can be seen from satellite images can be expressed in three axes; objects,
states of objects and changes in states (Figure 5) and that there is cause-effectrelationships between what can be seen from satellite images, what can be understoodfrom that and users of the information. Therefore, expressing what can be seen fromsatellite images in three axes is adopted as a method for function 1, and listing up causes
and effects of what can be seen from satellite images and what can be understood fromthat are adopted as methods for function 2 and 3. Regarding function 4, no common
relationship between users and addressed issues was found from the result of case studies.
Thus, the authors decided to adopt associating issues from combination of extracted
information and users as a method for function 4. Table 1 summarizes the functions andmethods of the proposed method. As the developed method utilizes three axes torepresent what can be seen from satellite images and cause-effect to extract what can beunderstood from satellite images and potential users, the authors named the method
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155“ideation method for satellite image applications with three axes data representation andcause-effect chains (hereinafter, the method).

Satellite image
What can be seen fromsatellite image
What can be understoodfrom satellite image

Function 1
Support clarification of what can be seen fromsatellite image
Function 2
Support extraction of what you can understandfrom what you saw
Function 3
Support identification of users

Users of the information
Function 4
Support extraction of users’ issues
Users’ issues
Figure 4 Four functions of the proposed method[Object]
Natural objects : plants,
water, surface, sea, sea
ice, clouds, rain, snow,
fire, atmosphere, etc.
Artifact : house, building,factory, road, bridge, car,ship, farmland, park, fish
farm etc.

[State]Height / depth,
temperature, humidity,
size (area), shape,quantity (number), color,
position, texture,material, shadow,brightness[change]
Increase, decrease,change (such as color),
movement

Figure 5 Method to represent what can be seen from satellite images

2.2. How to create ideas with the method
In this section, how to use the proposed method to generate satellite image utilization
ideas will be described. First, one selects an object seen from satellite images and writeout the selected object, the states of the object and the changes in the states (step 1). Next,
one lists up causes and effects of states of the object and changes in states as indicated in
Figure 6 (step 2). Causes of states are things or events that affect the state of the object,and effects of states are things or events affected by states of the object. Causes ofchanges in states are factors causing changes, and effects of changes are things or events

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brought about by changes. By writing out these items, it becomes possible to extract what
is known from satellite images.
Table 1 Summary of the proposed method

No.
1
2
3
4

ObjectFunction
Support clarification of what canbe seen from satellite images
Support extraction of what can beunderstood from satellite images
Support identification of users

Methods to realize functions
Represent in object + state + change

Identify the causes and effects of what
can be seen from satellite images
Identify people and organizations
affected by what you can see
Support extraction of users’ issues Associate with the combination of users
and what can be understood fromsatellite images

Effect : Things orevents which the stateof the object affects

Effect: Things or events
caused by changes

State of object

Change in state of theobjectCause: Things orevents which affectthe state of the object

Cause: Things orevents which causechangesFigure 6 How to extract what can be understood from satellite images

Thirdly, as shown in Figure 7, one lists up persons and organizations that affect or are
affected by the things or events listed up in step 2 (step 3). By writing out persons andorganizations from these two points of view, it becomes possible to extract possible users
of information extracted in step 2. An example of the description of steps 1 to 3 is shownin Figure 8.

Affectingperson / organization

What can belearned from thesatellite image
Figure 7 How to extract users

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Affectedpeople / organization

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Farmers
Suitable to theland or not
Lack ofnutrition

Farmers

Change inplant color

Plant
color

YieldsGrowthlevel

Investors

Shadedarea

Asset valueof the land

Plant

Cleanlinessof airTax amountof the land

Change inplant location

Change inplant heightPlantheightPlant type

Municipalities

Deforestation

Plant
location

Plant
area

Change inplant area

Insect breeding
Infection
spreadPrice ofcrops

Planting

Government

Figure 8 Example of the description of steps 1 to 3

Lastly, one picks up combination of 1) what can be seen from satellite images, 2) what
can be understood from 1) and, 3) potential users of 2) and associate issues from the threeelements. An example is described in Figure 9. This example is an idea to solve theproblem of a municipality that wants to know whether tax is appropriately collected or
not by estimating tax amount on land from colors of trees as types of trees planted in lands
may affect the value of lands.
1. What can be seenfrom satellite image

2. What can beunderstood from 1

3. User that is likely
to use 2

4. Issues of users (3)which is likely to besolved by 2

Plant color

Tax on land

municipalities

want to check if thetax is appropriately
collected

Plant color

Plant
type

Tax
amount of
the land

Asset valueof the land

1. What can be seenfrom satellite image

2. What can beunderstood from 1

Figure 9 Example of step 4
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municipalities
3.Users

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3. EVALUATION
3.1. Evaluation method
To evaluate the proposed method, the authors conducted experiments of idea generation
with individual and group works. In individual work, subjects generated ideas with andwithout the proposed method, and in group work, subjects generated ideas only with theproposed method. evaluation criteria are understandability, usability and effectiveness ofthe method (Nakada and Ioki 2019). The authors evaluated those three criteria based on
the result of questionnaire answered by subjects after experiments and the third party’s
evaluation of ideas generated in individual work. The evaluation method is summarizedin Table 2.
Table 2 Evaluation method

Evaluation criteria
Evaluation method
Understandability
Questionnaires by participants
Usability(individual and group works)
Effectiveness of fourfunctions
Effectiveness of thewhole method
Ideas evaluation by the third party(individual work)

In individual work experiment, 12 subjects generated satellite image utilization ideas
both with and without the proposed method. Subjects were divided into two groups; A
and B. Subjects in group A generated ideas with the method first and then generated ideas
again without the method. Subjects in group B generated ideas without the method andthen with the method. The theme of ideas was the same for group A and B but changed
after the first work; houses for the first work and cars for the second work. Individual
work experiment is summarized in Table 3.
Table 3 Experiment method of individual work

Item
With or without themethod (group A)
With or without themethod (group B)
ThemeWork timeFirst work
With the method
Without themethodHouse
50 mins

Second work
Without themethodWith the methodCar
50 mins

22 subjects participated in group work experiment. Subjects were divided into groups
with 3 to 4 members, and each group generated satellite image utilization ideas. The
theme of ideas was houses for all groups.
3.2. Result
3.2.1. Understandability

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After experiments with individual and group works, participants answered questions ofwhether it was easy to understand four functions and the whole method. There were six
options to answer the questions; 1. Strongly disagree, 2. Disagree, 3. Rather disagree, 4.
Rather agree, 5. Agree, 6. Strongly agree. Table 4 shows questions about
understandability.
Table 4 Questions about understandability

No.
1
2
3
4
5

Questions
Did you easily understand function 1 of the proposed method?
Did you easily understand function 2 of the proposed method?
Did you easily understand function 3 of the proposed method?
Did you easily understand function 4 of the proposed method?
Did you easily understand the whole method of the proposed method?

The result of questionnaire is shown in Table 5. Although there was a slight difference
between individual and group works, more than 90% of answers were positive. In otherwords, almost all participants evaluated that the proposed method was easy to understand.
Table 5 Result of questions about understandability

Evaluation
objectWork type

Function1
Function2
Function3
Function4
Whole

Percentage of answers
1

2

3

4

5

6

Individual

0%

0%

0%

17%

25%

58%

Group

0%

0%

0%

0%

47%

53%

Individual

0%

0%

8%

8%

42%

42%

Group

0%

0%

0%

18%

55%

27%

Individual

0%

0%

0%

8%

50%

42%

Group

0%

0%

0%

27%

36%

37%

Individual

0%

0%

0%

25%

33%

42%

Group

0%

0%

9%

14%

45%

32%

Individual

0%

0%

0%

17%

58%

25%

Group

0%

0%

0%

14%

53%

33%

3.2.2. Usability
After experiments with individual and group works, participants answered questions ofwhether it was easy to use four functions and the whole method. There were six options toanswer the questions; 1. Strongly disagree, 2. Disagree, 3. Rather disagree, 4. Rather
agree, 5. Agree, 6. Strongly agree. Table 6 shows questions about usability.

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Table 6 Questions about usability

No.

Questions

1

Was the function 1 of the proposed method easy to use?

2

Was the function 2 of the proposed method easy to use?

3

Was the function 3 of the proposed method easy to use?

4

Was the function 4 of the proposed method easy to use?

5

Was the entire method of the proposed method easy to use?

The result of questionnaire is shown in Table 7. Although there was a slight difference
between individual and group works, more than 85% of answers were positive. In otherwords, almost all participants evaluated that the proposed method was easy to use.
Table 7 Result of questions about usability

Evaluation
objectWork type

Function1
Function2
Function3
Function4
Whole

Percentage of answers
1

2

3

4

5

6

Individual

0%

0%

0%

25%

33%

42%

Group

0%

0%

0%

0%

44%

56%

Individual

0%

0%

0%

25%

50%

25%

Group

0%

0%

0%

14%

41%

45%

Individual

0%

0%

0%

25%

42%

33%

Group

0%

0%

5%

9%

50%

36%

Individual

0%

0%

0%

25%

33%

42%

Group

0%

5%

9%

14%

45%

27%

Individual

0%

0%

0%

8%

58%

34%

Group

0%

4%

0%

14%

41%

41%

3.2.3. Effectiveness of four functions
After experiments with individual and group works, participants answered questions ofwhether four functions of the proposed method have the intended effects. There were six
options to answer the questions; 1. Strongly disagree, 2. Disagree, 3. Rather disagree, 4.
Rather agree, 5. Agree, 6. Strongly agree. Table 3-3 shows questions about effectivenessof four functions.
Table 8 Questions about effectiveness of four functions

No.

Questions1

Do you think function 1 of the proposed method has the intended effect?

2

Do you think function 2 of the proposed method has the intended effect?

3

Do you think function 3 of the proposed method has the intended effect?

4

Do you think function 4 of the proposed method has the intended effect?

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The result of questionnaire is shown in Table 9. Although there was a slight difference
between individual and group works, more than 85% of answers were positive. In otherwords, almost all participants evaluated that the proposed method has the intended
effects.
Table 9 Result of questions about effectiveness of four functions

Evaluation
objectWork type

Function1
Function2
Function3
Function4

Percentage of answers
1

2

3

4

5

6

Individual

0%

0%

0%

8%

33%

59%

Group

0%

0%

11%

10%

26%

53%

Individual

0%

0%

0%

17%

33%

50%

Group

0%

0%

5%

19%

33%

43%

Individual

0%

0%

0%

25%

33%

42%

Group

0%

5%

9%

14%

48%

24%

Individual

0%

0%

0%

33%

25%

42%

Group

0%

0%

14%

29%

38%

19%

3.2.4. Effectiveness of the method as a whole
The object of the method is to support searching potential users or issues connected towhat can be seen from satellite images (easiness to find connections) and to support
generating ideas of satellite image utilization (easiness to generate ideas). To evaluate theeffectiveness of the whole method, participants were asked to evaluate the two points. To
compare with easiness without the method, the same questions were asked after workwith and without the method in individual work. In group work which generated ideas
only with the method, the participants with the experience to generate satellite image
utilization ideas were asked to evaluate the easiness by comparing their own experience.
There were six options to answer the questions; 1. Strongly disagree, 2. Disagree, 3.
Rather disagree, 4. Rather agree, 5. Agree, 6. Strongly agree. Table 10 shows questions
about effectiveness of the whole method.
Table 10 Questions about effectiveness of the whole method

No.

Questions1

Using the method, was it easy to find potential users and issues to be solved whichhave connections with what can be seen from satellite images?

2

Using the method, was it easy to generate ideas of satellite image utilization?

3

Without the method, was it easy to find potential users and issues to be solved whichhave connections with what can be seen from satellite images?

4

Without the method, was it easy to generate ideas of satellite image utilization?

Firstly, the result of individual work will be explained. Table 11 shows the result ofquestionnaire of participants of individual work. Regarding easiness to find connections,
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the average point of work with the method was 5.08 and work without the method was
2.42. Regarding easiness to generate ideas, the average point of work with the method
was 4.92 and work without the method was 2.42.
In order to verify whether there is a significant difference between the evaluation result ofwith and without the method, the authors conducted two tailed t-test with significant levelof 5 %. Regarding the easiness to find connections, significance value of Levene’s test
was 0.140 (not significant), and thus the variances can be treated as equal. Sincesignificance level of equal variance is 0.000 (1% significant), there is a significant
difference in the evaluation of easiness to find connections between with and without themethod. In addition, since the average point is 5.08 for the former and 2.42 for the latter,
the authors conclude that the connections are easier to find with the method than without
the method.
Regarding the easiness to generate ideas, significance value of Levene’s test was 0.221(not significant), and thus the variances can be treated as equal. Since significance levelof equal variance is 0.000 (1% significant), there is a significant difference in theevaluation of easiness to generate ideas between with and without the method. In addition,
since the average point is 4.92 for the former and 2.42 for the latter, the authors conclude
that ideas are easier to generate with the method than without the method. The results oft-test are summarized in Table 12.
Table 11 Result questions about effectiveness of the whole method (individual work)

Percentage of answers

Evaluation object Work type

1

2

3

4

5

6

Easiness to findconnections

With the method

0%

0%

0%

25%

42%

33%

Without the method

25%

25%

33%

17%

0%

0%

Easiness togenerate ideas

With the method

0%

0%

8%

17%

50%

25%

Without the method

25%

25%

33%

17%

0%

0%

Table 12 Result of t-test

Evaluation object

Average

Average(with method)(without method)

Easiness to findconnections

5.08

2.42

Easiness to generate
ideas

4.92

Significance value
0.000(1% significant)

2.42

0.000
(% significant)

The questionnaire results of group work are shown in Table 13. For both easiness to findconnections and easiness to generate ideas, more than 90% of answers was positive.
Almost all participants evaluated that the method makes it easy to find connections andgenerate ideas compared to their own experience.

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Table 13 Result questions about effectiveness of the whole method (group work)

Evaluation

Percentage of answers

objectEasiness to findconnections
Easiness togenerate ideas

1

2

3

4

5

6

0%

0%

0%

25%

38%

37%

0%

0%

6%

18%

53%

23%

From the results of questionnaires of individual and group works, the authors conclude
that the method makes it easier to find connections between satellite images and issues tobe solved and to generate ideas of satellite image utilization.
3.2.5. Quality of ideas
Ideas generated in individual work experiment were evaluated in three terms; novelty,
technical feasibility and distance between what can be seen from satellite images andaddressed issues (whether the connections between them can be directly associated).
Three experts engaged in satellite image business evaluated ideas without knowing
whether ideas were generated with or without the method. Table 14 shows the options ofevaluation.
In order to verify whether there is a significant difference between the evaluation result ofideas generated with and without the method, the authors conducted two tailed t-test withsignificant level of 5%. Regarding the distance between satellite image and addressedissue, the average points of ideas with the method was 3.56, and that without the method
was 2.88. Significance value of Levene’s test was 0.372 (not significant), and thus thevariances can be treated as equal. Since significance level of equal variance is 0.000 (1%significant), there is a significant difference in the evaluation of distance of relationships
between ideas with and without the method. In addition, since the average point is 3.56
for the former and 2.88 for the latter, the authors conclude that the ideas created using themethod have indirect connections between satellite images and addressed issues.
Regarding novelty, the average points of ideas with the method was 2.53, and thatwithout the method was 2.10. Significance value of Levene’s test was 0.000 (1%significant), and thus the variances cannot be treated as equal. Since significance level ofunequal variance is 0.016 (5% significant), there is a significant difference in theevaluation of novelty between ideas with and without the method. In addition, since theaverage point is 2.53 for the former and 2.10 for the latter, the authors conclude that theideas created using the method are more novel than the others.
Regarding technical feasibility, the average points of ideas with the method was 2.55, andthat without the method was 3.30. Significance value of Levene’s test was 0.818 (notsignificant), and thus the variances can be treated as equal. Since significance level of
equal variance is 0.000 (1% significant), there is a significant difference in the evaluationof technical feasibility between ideas with and without the method. In addition, since theaverage point is 2.55 for the former and 3.30 for the latter, the authors conclude that theideas created without the method are more technically feasible than the others. The test
results are summarized in Table 15.
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Table 14 Evaluation criteria of generated ideas

Evaluation object
Distance between
what can be seen fromsatellite images andaddressed issues

Questions
The addressed issue is easy to
associate from what can be seenfrom satellite images.

Options
1. Agree
2. Rather agree
3. Neither agree or disagree
4. Rather disagree
5. Disagree

Novelty

The idea is novel.

1. Disagree
2. Rather disagree
3. Neither agree or disagree
4. Rather agree
5. AgreeTechnical feasibility

The ideas is technical feasible.

1. Disagree
2. Rather disagree
3. Neither agree or disagree
4. Rather agree
5. AgreeTable 15 Result of t-test of idea quality evaluation
Evaluation object
Average
Average
Significance(with the method)(without the method)
value
Distance
3.56
2.88
0.000
(1% significant)Novelty
2.53
2.10
0.016
(5% significant)Technical feasibility 2.55
3.30
0.000
(1% significant)3.3. Consideration
In this section, consideration on the evaluation result explained in the previous section
will be discussed. Firstly, in order for the method to fully demonstrate its intended effects,
the method must be easy to be understood and used. Analysis of the questionnaire result
indicated that the proposed method is easy to understand and use. Therefore, it can be said
that the proposed method has no particular problem in understandability and usability todemonstrate the intended effects. Next, the effectiveness of four functions will be
discussed. More than 85% of responses were positive, and thus, it can be concluded thatthe methods designed for four functions work well to realize the four functions.
Regarding the effectiveness of the method as a whole, the questionnaire result indicatedthat it was easier to find connections between satellite images and issues to be solved andto generate satellite image utilization ideas when using the method than when not using

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Review of Integrative Business and Economics Research, Vol. 9, Issue 2

165

the method. Therefore, the authors conclude that the proposed method achieves its
purpose.
The result of evaluation of generated ideas also led to the same conclusion. As theevaluation of generated ideas, three perspectives were evaluated; distance of satellite
image and addressed issue, novelty and technical feasibility. For distance between
satellite image and addressed issues and novelty, ideas generated with the method were
evaluated higher. Therefore, it is considered that the method makes it easier to findunobvious connections. Furthermore, with such connections, it becomes easier togenerate novel ideas.
On the other hand, the technical feasibility was lower for the ideas created using themethod. In the proposed method, one considers causes and effects of what can be seenfrom satellite images when he or she extracts what can be understood from that. By listingup causes and effects not directly extracting what can be understood, one can remove
restrictions on his or her thinking as he or she does not need to consider if things or events
can be really known from satellite images or not. It is considered that this led to lower
technical feasibility of ideas generated with the method.
However, considering that removing the limitation of thinking makes it possible to findunobvious connections and moreover to generate more novel ideas, there is trade-off
between novelty and technical feasibility. Therefore, the authors consider that it ispreferable to generate many novel ideas and to select ideas with high technical feasibility
rather than modifying the method to generate ideas higher technical feasibility.
4. CONCLUSION AND FUTURE WORKIn this research, the authors developed the method to support finding connections
between satellite images and issues to be solved and generating satellite image utilization
ideas. To develop the method, the authors analyzed satellite image applications andextracted four functions necessary to realize the objectives. Furthermore, the authors
constructed the methods for four functions; supporting clarification of what can be seenfrom satellite images, supporting extraction of what can be understood from what can beseen from satellite images, supporting identification of users who use extracted
information and supporting consideration of issues held by the users and to be solved by
the extracted information. The authors then constructed the methods to realize the fourfunctions by analyzing the applications again; representing what can be seen fromsatellite in three axes and connecting from that to addressed issues using cause-effectrelationships.
In addition, the author evaluated if the method can realize four functions and theobjectives of this research. Evaluation was done by individual and group work
experiments in which participants generated satellite image utilization ideas.
Understandability, usability and effectiveness of the method were evaluated based on the
result questionnaires and the third party evaluation of generated ideas. The result showsthat the proposed method is effective for the purpose of facilitating finding the potential
connection between satellite images and issues, and for supporting the idea creation
utilizing satellite images.

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Review of Integrative Business and Economics Research, Vol. 9, Issue 2

166

While the result of evaluation indicates that the developed method is effective, there isroom for improvement on this method. Firstly, some of issues addressed in ideas
generated with the method can be solved by other means, and utilization of satellite image
does not have advantages. Secondly, the method does not support creating ideas with the
combination of multiple kinds of information derived from satellite images. Future works
should improve the method in these regards.
ACKNOWLEDGEMENTS
We would like to express sincere appreciation to Mr. Tuyoshi Hirose, Mr. Fumihito Oura,
Ms. Kii Iizawa, and Mr Ryoya Inomata.
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