Development of gis-based decision support system for small island (a case study in ndana island, nusa tenggara timur)

DEVELOPMENT OF GIS-BASED DECISION

SUPPORT SYSTEM FOR SMALL ISLAND

(A Case Study in Ndana Island, Nusa Tenggara Timur)

ATI RAHADIATI

GRADUATE SCHOOL

DEVELOPMENT OF GIS-BASED DECISION

SUPPORT SYSTEM FOR SMALL ISLAND

(A Case Study in Ndana Island, Nusa Tenggara Timur)

ATI RAHADIATI

A thesis submitted for the degree of Master of Science of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY FOR NATURAL RESOURCES MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY August 2006

STATEMENT

I, Ati Rahadiati, here by stated that this thesis entitled:

Development of GIS-based Decision Support System for Small Island (A Case Study in Ndana Island, Nusa Tenggara Timur)

are results of my own work during the period of February until July 2006 and that

it has not been published before. The content of the thesis has been examined by

the advising committee and the external examiner.

Bogor, August 2006

ACKNOWLEDGEMENT

Alhamdulillah. Thanks to The Almighty Allah who always give His endless Grace and Blessing on me. The success of this study would not have been possible without various contribution and support from many individuals that I would like to express my deep gratitude to all of them.

First, I would like to express my thanks and gratitude to BAKOSURTANAL especially for Chief of Center for Marine Resources Survey for gave me the opportunity to join this program and also for facilities and financial support during my study.

Many thanks go to my supervisors Dr. Tania June, M.Sc. and Dr. Dewayany Sutrisno, M.App.Sc. for their valuable suggestions, guidance and word of encouragement and scientific support. Without their contribution and guidance, this thesis would be of less quality.

My sincere thank to external examiner Dr. Gatot H. Pramono for suggestions and comments that improve this thesis. High appreciation goes to the lectures of MIT who taught me with important knowledge. Thanks also to The MIT management and staffs as well as IPB post graduate for supported our administration, technical aspects and the facilities.

I wish also to thanks to my friends and colleagues at Center for Marine Resources Survey for their support, for gave positive ideas and great discussion and supported data needs for this thesis.

Special thanks to all of MIT students especially my class mates, with whom I share laughs and pressures during my study, for our togetherness, helpful, and solidarities.

Finally, my special heartfelt gratitude goes to my family for their prayer, support, encouragement, and everything.

CURRICULUM VITAE

Ati Rahadiati was born in Bogor, West Java, at July 18,

1969. She received her undergraduate diploma from

Bogor Agricultural University in 1993 in the field of

Agrometeorology. Since 1995 to present, she works for

National Coordinating Agency for Survey and Mapping (BAKOSURTANAL).

In the year of 2004, she received a financial support from Center for

Marine Resources Survey – BAKOSURTANAL to pursue her graduate study.

She received her Master of Science in Information Technology for Natural

Resources Management from Bogor Agricultural University in 2006. Her thesis

entitles “Development of GIS based Decision Support System for Small Island (A

ABSTRACT

ATI RAHADIATI (2006). Development of GIS-based Decision Support System for Small Island (A Case study in Ndana Island, Nusa Tenggara Timur). Under the supervision of TANIA JUNE and DEWAYANY SUTRISNO.

Ndana Island in East Nusa Tenggara province is selected as the study area, because the island was classified as small island, located in the Australian border, and need a special management for achieving sustainable natural resources especially at marine area. The development of GIS-based DSS will be has some advantages for Ndana Island such as increasing and protecting the carrying capacity of border territory; using natural resources potencies with sustainable management; increasing income of local people; and developing an isolated island.

The objectives of this research are to identify and analyze potencies of Ndana Island, to develop prototype of GIS-based Decision Support System as a tool for analysis of decision making and to propose potential solutions based on sustainable management of Ndana Island.

There are four main activities to comply this research are data collection and preparation, database design and implementation, data analysis, and graphical user interface. The suitable area for coral reef conservation area in Ndana Island will be analyzed based on ecology, economic and social factors using GIS analysis. Results from this analysis are three zones in conservation area: core zone, buffer zone and use zone which core zone should be a closed area for development, accessible only for research activity. Buffer zone and use zone areas can be analyzed further for diving suitability.

Result of this research is the suitable area for coral reef conservation in Ndana island are S1 (highly suitable) for core zone, S2 (moderately suitable) for buffer zone, S3 (marginally suitable) for use zone and N (not suitable) for non-conservation area. Percentage of S1 is 0.29%, S2 is 3.01%, S3 is 75.58% and N is 21.12%. In buffer and use zone of conservation area, there are 31.33 hectares is moderately suitable (S2) and 146.27 hectares is marginally suitable (S3) for diving suitability.

Based on spatial suitability and economic valuation, scenario IV is the best management to apply in coral reef area of Ndana Island, which has the biggest value of NPV, Rp. 86,767,185,416. In scenario IV there are zonation area for tourism, fisheries and protected area with ecology, economic and social consideration. Hopefully this scenario can increase income of local people with sustainable management of natural resources. With this method can help improve coral reef conservation and management, but the level of detailed analysis required depend on the use of data and the value estimation.

This research has been developed graphical user interface using Microsoft Visual Basic and MapObject that makes the system easy to understand, handle and use by the user means it can be helpful for the user.

Research Title : Development of GIS-based Decision Support System for Small Island (A Case study in Ndana Island, Nusa Tenggara Timur)

Name : Ati Rahadiati

Student ID : G 051040121

Study Program : Master of Science in Information Technology for Natural Resource Management

Approved by,

Advisory Board

Dr. Ir. Tania June, M.Sc. Supervisor

Dr. Ir. Dewayany Sutrisno, MApp.Sc. Co-supervisor

Endorsed by,

Program Coordinator

Dr. Ir. Tania June, M.Sc.

Dean of the Graduate School

TABLE OF CONTENTS

STATEMENT ... ii

ACKNOWLEDGEMENT ... iii

CURRICULUM VITAE ... iv

ABSTRACT... v

TABLE OF CONTENTS... vii

LIST OF TABLE ... ix

LIST OF FIGURE... x

LIST OF APPENDIX ... xii

I. INTRODUCTION ... 1

1.1. Background ... 1

1.2. Problem Identification... 3

1.3. Location ... 5

1.4. Objectives... 6

1.5. Advantages... 6

II. LITERATURE REVIEW ... 7

2.1. Small Island... 7

2.1.1. Definition and Characteristic ... 7

2.1.2. Potencies of Small Island ... 8

2.1.3. Island Directory... 10

2.2. Tools for Analysis of Small Island... 12

2.2.1. Decision Support System ... 12

2.2.2. Geographic Information System ... 15

2.3. Research Dealing with GIS–based DSS ... 18

2.4. Sustainable Development of Natural Resources ... 20

III. METHODOLOGY... 23

3.1. Method ... 23

3.1.2. Need Assessment ... 25

3.1.3. Database ... 26

3.1.4. Data Analysis ... 27

3.1.5. Graphical User interface ... 35

3.2. Data Source ... 35

3.3. Tools Used ... 36

IV. DATABASE DESIGN AND CONSTRUCTION ... 37

4.1. Data Preparation... 37

4.2. Database Building ... 39

4.2.1. Conceptual Design ... 39

4.2.2. Logical Design ... 41

4.2.3. Physical Design... 42

V. RESULTS AND DISCUSSION ... 43

5.1. Data Analysis ... 43

5.1.1. Spatial Analysis... 43

5.1.2. Economic Analysis ... 50

5.1.3. Development Alternatives... 52

5.2. Graphical User Interface (GUI) ... 63

VI. CONCLUSION AND RECOMMENDATION... 68

6.1. Conclusion ... 68

6.2. Recommendation ... 69

REFERENCES... 70

LIST OF TABLE

No. Caption Page

Table 1. Computerized support for decision making (adapted from Turban,

1995) ... 17

Table 2. Question from need assessment ... 26

Table 3. Criteria for coral reef conservation area ... 29

Table 4. Criteria for diving activity... 30

Table 5. Criteria for seaweed cultivation ... 30

Table 6. Economic value of alternatives in coral reef area ... 34

Table 7. List of software ... 36

Table 8. Classification and standardization data for non spatial data ... 38

Table 9. Classification and standardization data for spatial data ... 38

Table 10. Master data list ... 40

Table 11. Area and percentage of coral reef conservation... 44

Table 12. Area of diving and seaweed cultivation suitability... 46

Table 13. Number of boat in Rote Barat Daya District ... 51

Table 14. Economic valuation of coral reef ecosystem in Ndana Island ... 52

Table 15. Revenue and cost components ... 56

DEVELOPMENT OF GIS-BASED DECISION

SUPPORT SYSTEM FOR SMALL ISLAND

(A Case Study in Ndana Island, Nusa Tenggara Timur)

ATI RAHADIATI

GRADUATE SCHOOL

DEVELOPMENT OF GIS-BASED DECISION

SUPPORT SYSTEM FOR SMALL ISLAND

(A Case Study in Ndana Island, Nusa Tenggara Timur)

ATI RAHADIATI

A thesis submitted for the degree of Master of Science of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY FOR NATURAL RESOURCES MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY August 2006

STATEMENT

I, Ati Rahadiati, here by stated that this thesis entitled:

Development of GIS-based Decision Support System for Small Island (A Case Study in Ndana Island, Nusa Tenggara Timur)

are results of my own work during the period of February until July 2006 and that

it has not been published before. The content of the thesis has been examined by

the advising committee and the external examiner.

Bogor, August 2006

ACKNOWLEDGEMENT

Alhamdulillah. Thanks to The Almighty Allah who always give His endless Grace and Blessing on me. The success of this study would not have been possible without various contribution and support from many individuals that I would like to express my deep gratitude to all of them.

First, I would like to express my thanks and gratitude to BAKOSURTANAL especially for Chief of Center for Marine Resources Survey for gave me the opportunity to join this program and also for facilities and financial support during my study.

Many thanks go to my supervisors Dr. Tania June, M.Sc. and Dr. Dewayany Sutrisno, M.App.Sc. for their valuable suggestions, guidance and word of encouragement and scientific support. Without their contribution and guidance, this thesis would be of less quality.

My sincere thank to external examiner Dr. Gatot H. Pramono for suggestions and comments that improve this thesis. High appreciation goes to the lectures of MIT who taught me with important knowledge. Thanks also to The MIT management and staffs as well as IPB post graduate for supported our administration, technical aspects and the facilities.

I wish also to thanks to my friends and colleagues at Center for Marine Resources Survey for their support, for gave positive ideas and great discussion and supported data needs for this thesis.

Special thanks to all of MIT students especially my class mates, with whom I share laughs and pressures during my study, for our togetherness, helpful, and solidarities.

Finally, my special heartfelt gratitude goes to my family for their prayer, support, encouragement, and everything.

CURRICULUM VITAE

Ati Rahadiati was born in Bogor, West Java, at July 18,

1969. She received her undergraduate diploma from

Bogor Agricultural University in 1993 in the field of

Agrometeorology. Since 1995 to present, she works for

National Coordinating Agency for Survey and Mapping (BAKOSURTANAL).

In the year of 2004, she received a financial support from Center for

Marine Resources Survey – BAKOSURTANAL to pursue her graduate study.

She received her Master of Science in Information Technology for Natural

Resources Management from Bogor Agricultural University in 2006. Her thesis

entitles “Development of GIS based Decision Support System for Small Island (A

ABSTRACT

ATI RAHADIATI (2006). Development of GIS-based Decision Support System for Small Island (A Case study in Ndana Island, Nusa Tenggara Timur). Under the supervision of TANIA JUNE and DEWAYANY SUTRISNO.

Ndana Island in East Nusa Tenggara province is selected as the study area, because the island was classified as small island, located in the Australian border, and need a special management for achieving sustainable natural resources especially at marine area. The development of GIS-based DSS will be has some advantages for Ndana Island such as increasing and protecting the carrying capacity of border territory; using natural resources potencies with sustainable management; increasing income of local people; and developing an isolated island.

The objectives of this research are to identify and analyze potencies of Ndana Island, to develop prototype of GIS-based Decision Support System as a tool for analysis of decision making and to propose potential solutions based on sustainable management of Ndana Island.

There are four main activities to comply this research are data collection and preparation, database design and implementation, data analysis, and graphical user interface. The suitable area for coral reef conservation area in Ndana Island will be analyzed based on ecology, economic and social factors using GIS analysis. Results from this analysis are three zones in conservation area: core zone, buffer zone and use zone which core zone should be a closed area for development, accessible only for research activity. Buffer zone and use zone areas can be analyzed further for diving suitability.

Result of this research is the suitable area for coral reef conservation in Ndana island are S1 (highly suitable) for core zone, S2 (moderately suitable) for buffer zone, S3 (marginally suitable) for use zone and N (not suitable) for non-conservation area. Percentage of S1 is 0.29%, S2 is 3.01%, S3 is 75.58% and N is 21.12%. In buffer and use zone of conservation area, there are 31.33 hectares is moderately suitable (S2) and 146.27 hectares is marginally suitable (S3) for diving suitability.

Based on spatial suitability and economic valuation, scenario IV is the best management to apply in coral reef area of Ndana Island, which has the biggest value of NPV, Rp. 86,767,185,416. In scenario IV there are zonation area for tourism, fisheries and protected area with ecology, economic and social consideration. Hopefully this scenario can increase income of local people with sustainable management of natural resources. With this method can help improve coral reef conservation and management, but the level of detailed analysis required depend on the use of data and the value estimation.

This research has been developed graphical user interface using Microsoft Visual Basic and MapObject that makes the system easy to understand, handle and use by the user means it can be helpful for the user.

Research Title : Development of GIS-based Decision Support System for Small Island (A Case study in Ndana Island, Nusa Tenggara Timur)

Name : Ati Rahadiati

Student ID : G 051040121

Study Program : Master of Science in Information Technology for Natural Resource Management

Approved by,

Advisory Board

Dr. Ir. Tania June, M.Sc. Supervisor

Dr. Ir. Dewayany Sutrisno, MApp.Sc. Co-supervisor

Endorsed by,

Program Coordinator

Dr. Ir. Tania June, M.Sc.

Dean of the Graduate School

TABLE OF CONTENTS

STATEMENT ... ii

ACKNOWLEDGEMENT ... iii

CURRICULUM VITAE ... iv

ABSTRACT... v

TABLE OF CONTENTS... vii

LIST OF TABLE ... ix

LIST OF FIGURE... x

LIST OF APPENDIX ... xii

I. INTRODUCTION ... 1

1.1. Background ... 1

1.2. Problem Identification... 3

1.3. Location ... 5

1.4. Objectives... 6

1.5. Advantages... 6

II. LITERATURE REVIEW ... 7

2.1. Small Island... 7

2.1.1. Definition and Characteristic ... 7

2.1.2. Potencies of Small Island ... 8

2.1.3. Island Directory... 10

2.2. Tools for Analysis of Small Island... 12

2.2.1. Decision Support System ... 12

2.2.2. Geographic Information System ... 15

2.3. Research Dealing with GIS–based DSS ... 18

2.4. Sustainable Development of Natural Resources ... 20

III. METHODOLOGY... 23

3.1. Method ... 23

3.1.2. Need Assessment ... 25

3.1.3. Database ... 26

3.1.4. Data Analysis ... 27

3.1.5. Graphical User interface ... 35

3.2. Data Source ... 35

3.3. Tools Used ... 36

IV. DATABASE DESIGN AND CONSTRUCTION ... 37

4.1. Data Preparation... 37

4.2. Database Building ... 39

4.2.1. Conceptual Design ... 39

4.2.2. Logical Design ... 41

4.2.3. Physical Design... 42

V. RESULTS AND DISCUSSION ... 43

5.1. Data Analysis ... 43

5.1.1. Spatial Analysis... 43

5.1.2. Economic Analysis ... 50

5.1.3. Development Alternatives... 52

5.2. Graphical User Interface (GUI) ... 63

VI. CONCLUSION AND RECOMMENDATION... 68

6.1. Conclusion ... 68

6.2. Recommendation ... 69

REFERENCES... 70

LIST OF TABLE

No. Caption Page

Table 1. Computerized support for decision making (adapted from Turban,

1995) ... 17

Table 2. Question from need assessment ... 26

Table 3. Criteria for coral reef conservation area ... 29

Table 4. Criteria for diving activity... 30

Table 5. Criteria for seaweed cultivation ... 30

Table 6. Economic value of alternatives in coral reef area ... 34

Table 7. List of software ... 36

Table 8. Classification and standardization data for non spatial data ... 38

Table 9. Classification and standardization data for spatial data ... 38

Table 10. Master data list ... 40

Table 11. Area and percentage of coral reef conservation... 44

Table 12. Area of diving and seaweed cultivation suitability... 46

Table 13. Number of boat in Rote Barat Daya District ... 51

Table 14. Economic valuation of coral reef ecosystem in Ndana Island ... 52

Table 15. Revenue and cost components ... 56

LIST OF FIGURE

No. Caption Page

Figure 1. General scheme for management of Ndana Island ... 4

Figure 2. Location index and Quickbird image of Ndana Island (Acquisition February 26, 2005) ... 5

Figure 3. Conceptual model of DSS (Turban, 1995) ... 13

Figure 4. General research scheme ... 23

Figure 5. Framework of research ... 24

Figure 6. Hybrid system design ... 27

Figure 7. Flowchart of decision support process ... 28

Figure 8. Context diagram ... 39

Figure 9. Entity Relationship Diagram ... 41

Figure 10. Sample of table design using Microsoft Access ... 42

Figure 11. Relationship of non-spatial data in Microsoft Access ... 42

Figure 12. Map of suitable area for coral reef conservation ... 47

Figure 13. Map of suitable area for diving... 48

Figure 14. Map of suitable area for seaweed cultivation ... 49

Figure 15. Spatial scenario 1 and 2 ... 54

Figure 16. Spatial scenario 3 and 4 ... 55

Figure 17. NPV of four scenarios ... 57

Figure 18. NPV of four scenarios at the 1st of five years... 59

Figure 19. Map of Scenario I ... 61

Figure 20. Map of Scenario II ... 62

Figure 21. Map of Scenario III... 62

Figure 22. Map of Scenario IV ... 63

Figure 23. Flowchart of application system... 64

Figure 27. Spatial analysis form... 66 Figure 28. Form of buffer and query functions... 66 Figure 29. Flow process form ... 66 Figure 30. Result of conservation suitability ... 66 Figure 31. Input economic data of four scenarios... 67 Figure 32. Table and graph from NPV analysis... 67 Figure 33. TEV of Ndana Island ... 67

LIST OF APPENDIX

No. Title of Appendix Page

Appendix 1. Comparison of characteristics of study area with references ... 73

Appendix 2. Map of administrative boundary ... 74

Appendix 3. Thematic maps ... 75

Appendix 4. Logical design of database ... 78

Appendix 5. Economic Valuation of Scenario I ... 81

Appendix 6. Economic Valuation of Scenario II ... 83

Appendix 7. Economic Valuation of Scenario III... 85

Appendix 8. Economic Valuation of Scenario IV ... 87

I.

INTRODUCTION

1.1. Background

Indonesia is the world’s largest archipelago state consists of 17,508 islands

and 81,000 km coastline. More than 10,000 islands are classified as small islands

characterized by many resources. Small islands have limited terrestrial natural

resources, but rich in marine resources (Dahuri, 1998). These make small islands

have lots of potencies to develop such as for fisheries and tourism.

Characteristics of islands have long been noted for their unique fauna and

flora, but particularly vulnerable to the disturbance and destruction by human

activities. The islands also face some problems to be well managed, such as

adaptations to the societies, difficulties in economic development, and the

challenge of achieving sustainable development within limited resources. Besides

that, the increasing rate of global change makes the islands represent some of the

most fragile and vulnerable resources on the planet (UNEP, 2004). Indeed, the sea

and land adjacent to it are recognized by the government as critical to the present

and future well being of the country’s expanding population, and must therefore

be protected and developed in an environmentally sustainable and sustainable

manner.

Dealing with the change in the national policies, management of small

islands now becomes a national agenda. The island’s development policy has also

been changed to the more sustainable management planning.

Several small islands have important political value because it’s referring

to the Indonesia territory where 92 from 183 boundary points are small islands

in border area was not a complete study for island development, only

identification of the island characteristics (Suryansyah, 2005). Main aims of

bordered small islands development are to make self-development and to

strengthen position of small islands as territory guard.

Due to the complexity of small island management in border area, decision

making for small islands management may well benefit from the development of a

flexible computer system capable of running several analyses at one time. This

system is termed Decision Support Systems (DSS). A comprehensive decision

support will require the effective integration with Geographic Information System

(GIS). GIS-based DSS provided effective decision support that can handle spatial

and spatial databases. This allows for the spatial database organization,

non-spatial datasets organization (attributes), analysis and transformation for obtaining

the required information, obtaining information in specific format (map or report)

and organization of a user-friendly query system.

The system that will be developed assembles information on the

importance of islands in the world. It is intended to the use of the system for

management policy of the small island in border area. The advantages of GIS-

based DSS that can be access, use, and update easily. Also it can help those living

on islands or involved in island development and conservation to understand the

environmental problems of islands, to identify islands with special problems or

under particular threat, and to compare and classify islands globally to show

which islands may share common problems and be able to cooperate in solving

1.2. Problem Identification

Main issues for development of small islands in border area are:

1. Most of the small islands are undeveloped; limited in infrastructure,

non-educated local people, and poor economic;

2. There are some infiltration in economic, social and culture from neighbour

country;

3. Poor attention may change in national sovereignty for the island in border

area (case: Sipadan and Ligitan Island)

Therefore, the small islands located in the border area need to be managed

properly by both the local and central government. Indeed the local people and

non-government organization (NGO) can joint in monitoring and evaluating of the

policy.

Ndana Island in Nusa Tenggara Timur Province is selected as the study

area, because:

a. The island was classified as small island;

b. Located in the Australian border;

c. The island has many flora and fauna, such as many kinds of coral reef,

fish, and sea grass.

d. The island has been develop as the conservation area for game hunting

park (Taman Burubased on Ministry of Forestry No. 83/Kpts-II/1993);

e. Need a special management for achieving sustainable natural resources.

Due the complexities of the use as can be seen in Figure 1.

It seems the use of GIS-based DSS for developing the sustainable

management of the island become crucial. The development of GIS-based DSS

will be has some advantages for Ndana Island such as increase and protect the

carrying capacity of border territory; to use natural resources potencies with

sustainable management; to increase income of local people; and to develop an

isolated island.

Ndana Island

Ministry of Forestry No. 83/Kpts-II/1993)

Government Regulation No. 38/2002

- Coordinate of boundary points

Potencies of Ndana Island

Ecology Social Economic Politics

Management of Ndana Island

Sustainable development for Ndana Island

Tools: GIS-based DSS

Zonation at marine area Regional planning

of Ndana Island Land area Marine area

Conservation area as Hunting Park

Government Regulation No. 78/2005 -Management of small islands in boundary area

1.3.Location

The location of Ndana (Dana) Island, Nusa Tenggara Timur as the study

area can be seen in Figure 2. Ndana Island bounded by Rote Island in the north,

Hindia Ocean in the south, Sabu Sea in the west and Timor Sea in the east. Area

covers 1,562 hectares.

Figure 2. Location index and Quickbird image of Ndana Island (Acquisition February 26, 2005)

1.4.Objectives

The objectives of this research are:

1. To identify and analyze potencies of Ndana Island

2. To develop prototype of GIS-based Decision Support System as a tool

for analysis of decision making

3. To propose potential solutions based on sustainable management of

Ndana Island

1.5.Advantages

The advantages of this research are:

1. Data and information of Ndana Island can be structured and accessible.

2. GIS-based decision support system may help decision maker in

managing a small island in a sustainable manner.

3. This research may become a reference and scientific contribution for

II.

LITERATURE REVIEW

2.1.Small Island

2.1.1. Definition and Characteristic

Definition of an island is a naturally area of land, surrounded by water

which is above water at high tide. Small island is island that has small size,

ecologically separated from main island and has fixed border. Small islands are

unique and intensively individual and often requiring special management skills.

According to Ministry of Marine and Fisheries Affair (Doc. No. 41/2000),

definition and characteristic of a small island are:

a. Island that has area equal or less than 10,000 km2 and total citizen less than or equal 200,000 people.

b. Ecologically separated from mainland and has a clear physical border. c. Has specific flora and fauna

d. Little catchments area where almost all of water’s surface and sediment directly go to the sea.

e. Local community has specific social, culture and economic value and activities.

Small islands have all the environmental problems and challenges of the

coastal zone concentrated in a limited land area. They are considered extremely

vulnerable to global warming and sea level rise, with certain small low-lying

islands facing the increasing threat of the loss of their entire national territories.

Most tropical islands are also now experiencing the more immediate impacts of

increasing frequency of cyclones, storms and hurricanes associated with climate

Because small island development options are limited, there are special challenges

to planning for and implementing sustainable development. Information on the

geographic, environmental, cultural and socio-economic characteristics of islands

should be compiled and assessed to assist in the planning process. Existing island

databases should be expanded and geographic information systems developed and

adapted to suit the special characteristics of islands (UNEP, 2004).

Several characteristics of small islands that can be obstacles to develop

small islands are (Dahuri, 1998):

a. Size of area is small and isolate from other island, expensive in infrastructures and seldom in educated human resources.

b. Difficult to reach an optimal economic in part of production, transportation and administration.

c. Sometimes specific local culture in conflict with the development activity of small islands

Government Regulation No. 78/2005 is a new order for management of 92

bordered small islands in Indonesia and Ndana Island is one of them. It is written

in the regulation that bordered small island is island with area equal or less than

2,000 km2 which has boundary point of Indonesia territory based on National and International Laws. The aims of bordered small island management are as

national security, to use natural resources with sustainable development and to

increase income of local people.

2.1.2. Potencies of Small Island

There are several natural ecosystems in coastal area of small islands, i.e:

formation, estuary, lagoon and delta. Besides that there are manmade ecosystem,

such as tourism area, marine culture and settlement (Dahuri et al., 2001).

The main potencies of ecosystem of small islands in tropical area are

(UNEP, 1998):

a. Coral reefs. Coral reefs are a very productive type of ecosystem with many kinds of plants and animals crowded together and usually occur in

shallow tropical waters. Many different kinds of fishing and food

collecting are possible in reef areas, producing very high catches. Coral

reef ecosystems also provide opportunities for recreation and tourism,

scientific research, education, and shoreline protection.

b. Fisheries. Fish and other animals from the sea provide an important source of protein for people living on islands. Fishing activity in the

shallow coastal waters around the islands is an important occupation

today as it has been for hundreds of years. Fish are a renewable resource

because they can continue to be used over and over again if they are

taken care of. If too many fish are caught at once, it is call over fishing,

and it may not be possible for the few that are left to replace all those that

were taken. Today it is happening in many places especially in the

tropical islands. Fishery activity must be managed in accordance with

certain ecological principles to avoid over fishing and other damage to

fish resources.

c. Lagoon. Lagoons are common in the coastal environments of many islands. They are areas of water with some link to the sea, but sufficiently

cut off or protected so that there are special environmental conditions

inside them.

d. Tourism. Tourism in the small islands context involves people who come from other region or countries for the pleasure of visiting the island

environment. Tourism can be an important source of income for islands

with few other possible sources of revenue because tourists may spend

money on travel, hotels, food, entertainment and recreation. The most

important tourism resources are the natural beauty of the island, their

recreation possibilities, and the cultural interest of the people. The basic

problem with tourism development is that tourism facilities and the

tourists themselves have impacts on the environment. And the tourism

development should be managed with ecological principal as ecotourism

activity. The problem can be particularly serious on tropical small islands

where the environment is fragile and easily degraded, and even moderate

tourism development may have a proportionately large impact.

2.1.3. Island Directory

According to Island Directory from United Nations Environment

Programme (UNEP, 2004) there are several kinds of information that should be

collected for each island when available, as described below:

a. The present name in English, the official name if in another language, and

significant former names if widely used in the literature;

b. Basic descriptive information on each island, such as its geographic

d. Climate data;

e. The major natural and human catastrophic threats which could endanger

an already vulnerable population or feature, such as volcanic eruptions,

earthquakes, tsunamis, and other effects;

f. Demographic data;

g. Indicators of human impact;

h. The major ecosystem types or biomes around the island;

i. Features of special interest for conservation

j. The size and diversity of the flora and fauna;

k. The numbers of endemic;

l. The scientific and common names of endemic species and other species of

special conservation interest;

m. Information on introduced biota;

n. The names and area of terrestrial and marine protected areas;

o. References;

p. Indicators used to evaluate certain island characteristics. These include:

ecosystem richness, species richness, natural vulnerability, human threat,

economic pressure, and three aggregate indicators for the potential for

human impact on the island, and for the terrestrial conservation importance

and marine conservation importance of the island. The details of island

directory and the basis for and calculation of all of indicators can be seen

in UNEP (2004).

2.2.Tools for Analysis of Small Island 2.2.1. Decision Support System

Turban (1995) stated that decision support system is an interactive,

flexible and adaptable computer based information system, especially developed

for supporting the solutions of a non-structured management problem for

improved decision making.

A Decision Support System allows decision-makers to combine personal

judgment with computer output, in a user-machine interface, to produce

meaningful information for support in a decision-making process. Such systems

are capable of assisting in solution of all problems (structured, semi-structured

and unstructured) using all information available on request. They use quantitative

models and database elements for problem solving and an integral part of the

decision-maker’s approach to problem identification and solution (Simonovic,

1998).

According to Sol in Terfai and Schrimpf (2004), decision support is the

development of approaches for applying information systems technology to

increase the effectiveness of decision makers in situations where the computer can

support and enhance human judgment in the performance of tasks that have

elements, which cannot be specified in advance.

Actually, there are many definitions of a DSS there is general agreement

that these systems focus on decisions and on supporting rather than replacing the

user's decision-making process. There is also a general consensus in the

than on supporting the modeling process, but the main goal of a DSS should be to

provide decision makers with tools for interactively exploring, designing and

analyzing decision situations. Users should be able to perform the following

functions: they can analyze decision situations according to their personal styles

and knowledge; they can build and compare various quantitative models; they can

adapt these models to changing conditions; and they can evaluate different aspects

of their activities using a variety of different means (Terfai and Schrimpf, 2004).

Other computer-based systems

Data management

Model management

Knowledge manager

Dialog management

Manager (user) Data, external

and internal

Figure 3. Conceptual model of DSS (Turban, 1995)

DSS is composed of the following subsystem (Turban, 1995):

a. Data management. The data management includes the database which

contains relevant data for the situation and is managed by software called

database management system (DBMS)

b. Model management. A software package that includes financial, statistical,

management science or other quantitative models that provide the system’s

analytical capabilities and an appropriate software management

c. Communication (dialog system). It provides the user interface.

d. Knowledge management. This optional subsystem can support any of the

other subsystem or act as an independent component.

Within the framework of management information systems (Mittra in

Simonovic, 1998) the DSS has four primary characteristics:

• It helps decision-makers at the upper levels;

• It is flexible and responds quickly to questions;

• It provides “what if” scenarios; and

• It considers the specific requirements of the decision-makers.

In the period since DSS came to prominence there has been considerable

growth in the importance of geographic information systems (GIS). This growth

in GIS reflects the decreased cost of the required technology and the increasing

availability of appropriate spatial data. Recent improvements in mainstream

computer technologies facilitate this spread of the use of spatial data. These

include inexpensive gigabyte sized hard disks, large high-resolution color

monitors, graphics accelerators and CD-ROM storage. This explosion in the use

of computer technology can also be seen in other areas, where a virtuous circle of

declining hardware costs leads to larger software sales and therefore reduced

2.2.2. Geographic Information System

A Geographic Information System (GIS) is a specific information system

applied to geographic data and mainly referred to as a system of hardware,

software and procedures designed to support the capture, management,

manipulation, analysis, modeling and display of spatially-referenced data for

solving complex planning and management problems (Burrough, 1986).

Since GIS has been introduced in 1960 and due to the user demand for

mapped data focused attention on data availability, accuracy, and standards, as

well as data structure issues, GIS has served an important role as an integrating

technology. The capability in providing data spatial and non-spatial that are

cannot be fulfilled by another application, considering GIS, as an application for a

user needs. The ultimate need, GIS has been linked to models, decision support

systems and expert systems in order to make these tools applicable in spatially

explicit planning and decision-making.

GIS applications have been developed for wider application of digital data;

encourage more sectors to invest in GIS technology that can be run on their

existing computer. The growth of GIS application has been paralleled by the

extraordinary gains of computer performance. Furthermore, the range of

commercially available products of information technology that candidate for the

implementation of a GIS has widened, including CAD (computer assisted

drafting), DBMS (database management system), geo-processing, remote sensing,

GPS (global positioning system), Multimedia, network communication and EDI

(electronic data interchange).

There are three important stages of working with geographic data (de By,

2000):

1. Data entry. The early stage in which data about the study phenomenon is

collected and prepared to be entered into the system.

2. Data analysis. The middle stage in which collected data is carefully

reviewed, and for instance, attempts are made to discover patterns.

3. Data presentation. The final stage in which the results of earlier analysis are

presented in an appropriate way.

Data GIS demonstrated the advantage of organizing, managing, and

distributing geographic information culled from various databases while

maintaining data integrity and focusing on project direction.

In the framework of decision making perception, GIS evolves around its

decision support capabilities including query functions, statistical analysis

capabilities, spreadsheet analysis, graphics and mapping function for evaluating

decision options and assessing the optimal and most suitable alternative (United

Nations, 1996).

GIS is gaining importance and widespread acceptance as a tools for

decision support in land, infrastructure, resources, environmental management and

spatial analysis, and in urban and regional development planning. With the

development of GIS, environmental and natural resource managers increasingly

have at their disposal information systems in which data are more readily

accessible, more easily combined and more flexibly modified to meet the needs of

despite the proliferation of GIS software systems and the surge of public interest

in the application of the system to resolve the real world problems, the technology

has commonly seen as complex, inaccessible, and alienating to the decision

makers (Sharifi, 2002).

Table 1. Computerized support for decision making (adapted from Turban, 1995)

Phase Description Traditional Tools Spatial tools

Early compute, "crunch numbers", summarize, organize early computer programs, management science models computerized cartography Intermediate

find, organize and display decision relevant information database management systems, MIS workstation GIS Current perform decision relevant computations on decision relevant information; organize and display the results. Query based and user friendly approach. "What if" analysis

financial models, spreadsheets, trend exploration, operations research models, decision support systems. spatial decision support systems

Spatial Decision Support System (SDSS) can therefore be seen as an

important subset of DSS, whose potential for rapid growth has been facilitated by

technical developments (Table 1). The availability of appropriate inexpensive

technology for manipulating spatial data enables SDSS applications to be created.

The benefits of using GIS based systems for decision making are increasingly

recognized. There is evidence that GIS software is becoming increasingly

suitable for use as a generator for a SDSS. As GIS designers gain a greater

awareness of decision-making possibilities, their systems will be designed to

facilitate interaction with models. GIS software provides a sophisticated interface

for spatial information. Even limited functionality GIS software will provide the

ability to zoom and to display or highlight different features. GIS provides

database support that is designed to allow for the effective storage of spatial data.

Furthermore GIS software provides a link between the interface and database to

allow the user to easily query spatial data.

2.3.Research Dealing with GIS–based DSS

There are several studies using GIS-based DSS for natural resources

management but not specific in small island case. O’Donnell et al. (2003)

reported on use GIS tools for decision support in coastal habitat which this project

was designed to house and manage a broad ranging spatial database and as a

development tool in the production of a GIS based sensitivity analysis model.

They used ArcInfo and Microsoft Visual Basic for this application.

In the other location Terfai and Schrimpf (2004) used GIS and remote

sensing data for development of decision support system for coastal management

in Morocco. They used three kinds of software that are Omnimage as graphical

software, IDRISI for raster geographic analysis system and GRASS as raster or

vector geographic system. They suggest that DSS for environmental management

is a useful method and could be used at regional or national level. According to

Agrawal et al (2003) the GIS based DSS provides an advanced modeling and

analysis system for environmental parameters which they studied about GIS as

modeling and decision support tool for air quality management.

From several case studies, Hall (1996) stated there are five kinds of

- Education and training. The current practice of decision making in

developing countries has not advanced much in comparison to the tools

available to help and may not yet be aware of the benefits of technology.

Little effort has been spent on transforming data into information for

making decisions. Training programs are needed for five major groups of

users - policy makers, decision makers, programmers, technicians, and

educators.

- Leadership and organization. The function of the leadership is to set clear

goals and objectives, to win acceptance among information system users

for such goals and objectives, and to provide commitment to achieve

project goals and tasks. Another critical function of leadership is

coordination of different departments sharing the information system.

- Software development. Most of the programs and manuals are written in

English, but most of the users, have limited understanding of English.

User-friendly application programs which hide the technology form the

users, with instructions or pull-down menu written in local languages need

to be developed in order to enable local planners and decision-makers to

use decision support systems.

- Maintenance. The development of DSS should be considered as a

continuous process.

Spatial DSS is a continued development of GIS and DSS integration.

AVSWAT (ArcView-Soil Water Analysis Tool) is one of Spatial DSS

application. It has been developed at Black Land Research Center, Texas for the

district level decision makers. This system as a dynamic tool could be help in

generating alternate management scenarios for land and water management

(Dutta, 2000).

Other study of spatial DSS reported by Ostendorf and Carrick (2004)

about South Australia’s Prawn Fisheries. This report described the process of

spatial decision-making and the utility of spatial information techniques using

historic spatial data in conjunction with near real-time survey data and statistical

risk assessment. The system is implemented linking an Oracle database to

ArcGIS, Genstat and Splus and mobile phone technologies.

2.4.Sustainable Development of Natural Resources

The concept of sustainability was first launched in the World Conservation

Strategy at 1980. It took quite a long time before the concept became more widely

known, a process stimulated by the report 'Our Common Future' of the World

Commission on Environment and Development (WCED, 1987 in Rothmans et al.,

1994). In general, sustainable development is to meets the needs of the present

without compromising the ability of future generations to meet their own needs or

in other word, sustainable development is a process of change in which the

exploitation of resources, the direction of investments, the orientation of

technology development and institutional change are made consistent with future

as well as present need (Cicin-Sain and Knecht, 1998).

Due to the difference in human perspectives and values among cultures,

societal sectors and interest groups the concept of sustainable development lacks a

a holistic view of developments in different societal domains (social, ecological

and economic) and at different levels: macro, meso, micro (Rotmans et al., 2001

in LOICZ, 2004). Sustainable development and management of global and

regional resources is not an ecological problem, nor an economic one, nor a social

one. It is a combination of all three.

There are three conditions to achieve sustainable development in

ecological aspect, i.e.: spatial harmonization, assimilation capacity and sustainable

use (Dahuri et al., 2001). Spatial harmonization means in developing area should

be not all for use zone but there are also locations for preservation and

conservation zone.

One of the most important challenges facing society today is maintaining

the natural values and resource potential that provide continuity of benefits for

society from the goods and services of the small island areas. Therefore,

sustainable natural resource use needs information on actual and predicted options

and their ecological and monetary evaluation. Development involves making

decisions, making choices amongst alternative possible development paths,

selecting one line of action which returns benefit to the developing country. It is

important that these decisions are made well, using the best information, methods

and tools available. For sustainable development it need to make decisions that do

not have long term negative effects, and assess the long term effects and impacts

as well as the short term benefits.

Cicin-Sain and Knecht (1998) concluded that sustainable development

involves three major emphases:

- Economic development to improve the quality of human life;

- Environmentally appropriate development – development that is

environmental sensitive and makes appropriate use of natural resources,

development that protects essential ecological processes, life support

system and biological diversity;

- Equitable development - equity in the distribution of benefits from

development” intra societal equity, intergenerational equity and

III.

METHODOLOGY

This study was conducted from February to July 2006 at Research Lab.

Master of Science in Information Technology for Natural Resources Management

– Bogor Agricultural University.

3.1.Method

GIS-based Decision Support System was developed to solve the Ndana

Island – the small island in border area problems. When the system approach is

applied to solve the problem in the framework of information system, it is called

information system development. Using the system approach to develop

information system solutions involve a multi step process called the information

system development cycle, also known as the System Development Life Cycle

(SDLC). The steps of SDLC are: (1) investigation, (2) analysis, (3) design, (4)

implementation and (5) maintenance (O’Brien, 1999).

This research was based on the SDLC steps: analysis, design and

implementation (Figure 4). Figure 5 show all research activities, which is set of

three main steps starting with problem identification and ending on going use of

the system.

Analysis - Problem identification - User identification

- Need assessment

Design - Database design - User interface design

- Data analysis

Implementation - Building GUI (Coding)

- Testing

Literature Study

Problem identification

User and needs assessment

Data collection & identification

Non-spatial data

design Digital spatial

data design Island Directory

criteria (UNEP, 2004)

Data entry Base &

thematic Non-spatial data Image data Spatial data GUI design Data analysis Building GUI Testing

Recommendation for small island in border area:

Sustainable management of Ndana Island A na lys is s ta g e D es ign sta g e Imple menta tio n s ta g e Pre-analysis stage

3.1.1. User Identification

User identification analysis is needed for defining the specific target and

appropriate information. This should be done for designing the system. The

considered users of the GIS-based DSS for small islands in border area can be

classified into two categories, i.e.:

1) Government (Local/Central) as a decision maker, ex: Governor, DPRD,

DPR etc.

2) Researchers or Non Government Sectors. They will take benefit from the system by increasing their knowledge of small islands in the border area.

3.1.2. Need Assessment

In the beginning of the analysis and general design phase, intending to

elicit an understanding of the scope of a study, a needs assessment was performed

to understand the project process, to know what they want to accomplish with the

automation, and to involve them at an early stage of the implementation. The

information needed for the study have been elaborated by two approaches:

¾ Definition of the information for major issues, i.e., environmentally

sustainable small islands management, problems identifications, and the

development of small islands utilization;

¾ Definition of the types of information important to the expected

beneficiaries. The completion of this needed information was checked by

relating of the data sets.

There are some questions arise during the need assessment of GIS-based

decision support system for Ndana Island. The questions are shown in Table 2.

Table 2. Question from need assessment

User as decision maker Researcher

What are the natural resources potencies of that island?

What are the physical characteristic of that island?

What is the best management for that island?

What are the demographic and socioeconomic characteristic of the local people?

How much the cost and benefit to develop that island?

How about the data of that island? It’s complete or not? Can we display, share or access those data? Can we make an analysis with those data?

From literature review, it was found that Ndana Island needs a system to be

implemented to enhance the information of this small island in the border area.

To achieve the goals GIS-based Decision Support System will be developed and

used.

3.1.3. Database

There are three main activities of the database system design where

conceptual design is the first step (Rao, 1993), with the following activities:

a. _{Conceptual data modeling: identify data content, describe data, define} features and entities, list attributes and characteristics of each entity.

b. _{Logical design of the information system: converting the conceptual} design to the logical design of the GIS database, include logical

process modeling and logical data modeling.

c. _{Physical design of the information system: design of the application} programs and design of the database. It describes the actual software

and hardware application, including how data is processed and

Database development is focused on two categories, spatial and

non-spatial data that refers to the database design and developed by using hybrid

system approach (Figure 6). A hybrid architecture manages geospatial data

independently and in different software module from the non-spatial data

(Worboys and Duckham, 2004). Spatial and non-spatial data in the designed

small island database has to be linked up for better analysis and visualization of

desired output. The link is provided by interface with connectivity function to

other related database. Non-spatial database will be designed in MS Access and

link up with the spatial data through ActiveX Data Object (ADO). ADO is

familiar to database programmers using Microsoft Visual Basic.

GIS-based DSS for Small Island

Visual Basic

Map Object Microsoft Access

Spatial data Non-spatial _data

Figure 6. Hybrid system design

3.1.4. Data Analysis 3.1.4.1.Spatial Analysis

The suitable area for coral reef conservation area in Ndana Island was

analyzed based on ecology, economic and social factors. Results from this

analysis are three zones in conservation area: core zone, buffer zone and use zone

(Figure 7). Bengen (2001) in Angkotasan (2003) stated conservation area can be

divided to three zones:

a. Core zone. This area has high value of conservation. It should be a closed

area for development and accessible only for research activity.

b. Buffer zone is transition area but still need a strict control. Function of

buffer zone is to protect core zone from disturbance of external factor.

Several activities can permit, i.e.: research, traditional fisheries and limited of

tourism activity.

c. Use zone. This area still has value of conservation but can be used by people

such as for fisheries, tourism and limited marine cultivation activities.

Marine database of Ndana Island

Conservation area

Suitability criteria for conservation

Sea tourism (diving)

Seaweed cultivation

Best alternative for management of Ndana Island

Core zone

Buffer zone Use zone

Criteria for diving

Non-conservation area

Criteria for Seaweed cultivation

Benefit transfer analysis

Existing condition: Fishery activity

Based on the above explanation buffer and use zones can be analyzed

further for marine activities suitability. This study will be focused on marine

suitability analysis especially for sea tourism (diving).

Non-conservation area can be analysis for site selection of seaweed

cultivation. Diving and seaweed cultivation suitability analysis used the physical

factor. Criteria’s for coral reef conservation area, diving and seaweed cultivation

can be seen in Table 3, 4 and 5. These criteria were based on literature and the

availability of data. Scoring and weighting system was applied for assessing the

suitability aspects. Decision of weighting value based on the importance of factor

for a suitability analysis (Haris, 2003). The suitable area was determined based on

the total of all scores. There are four classes in every criteria, i.e.: S1 = highly

suitable, S2 = moderately suitable, S3 = marginally suitable and N = not suitable.

Table 3. Criteria for coral reef conservation area

Category and scoring No Variable Unit Weig

hting _{S1 Score S2 Score S3 Score N Score} Ecology aspect

1. _{Coral reef}

% 5 Live coral, >75% 4 Live coral, 25-75% 3 Live coral, <25% 2 Died coral, sand 1 2. _{Distance from beach}

M 3 < 100 4 100-150 3

150-200 2 >200 1 3. _{Slope % 3 0-15 4 15-25 3 25-40 2 >40 1} 4. _Salinity

ppt 3 30-32 4 32-34 3 28-30 2 <28 >34 1 5. _{Sea Surface}

Temperature

0 _{C 3 29-31 4 31-33 3 27-29 2} <27

>33 1

Economy aspect

6. _{Number of economy} activities (fisheries, marine culture)

2 Non 4 1 3 2 2 > 3 1

Social aspect

7. _{Distance from}

settlement Km 2 > 4 4 3 - 4 3 2 - 3 2 < 2 1 8. _{Number of tourism}

area 2 Non 4 1 3 2 2 >3 1 9. _{Number of special}

species 2 > 3 4 2 3 1 2 Non 1

Source: Haris (2003) and Angkotasan (2003) with modification.

The suitability classes were calculated based on the total maximal scores

minus total of minimum scores divided by four classes. The ranges of suitable

value for coral reef conservation area are:

S1 (highly suitable) : 81.25 – 100

S2 (moderately suitable) : 62.50 – 81.25 S3 (marginally suitable) : 43.75 – 62.50

N ( not suitable) : 25 – 43.75

Table 4. Criteria for diving activity

Category and scoring No Variable Unit Weig

hting _{S1 Score S2 Score S3 Score N Score}

1. Water clarity M 10 >15-20 10 10-15 8 5-10 6 < 5 4 2. Percentage of life

coral

% 8 >75 9 >50-75 7 25-50 5 < 25 3 3. Variation of coral 8 >27 9 > 18-27 7 9-18 5 < 9 3 4. Variation of fish 8 > 70 9 > 50-70 7 > 20-50 5 ≤20 3 5. Current velocity M/se

c

6 0-0.1 8 0.11-0.4 6 0.41-0.5

4 > 0.5 2 6. Depth M 4 >10-20 7 >5-10 5 2-5 3 < 2 1

Source: BAKOSURTANAL (1996) and Yudasmara (2004)

Range of suitable index:

S1 (highly suitable) : 326 – 392

S2 (moderately suitable) : 260 – 326 S3 (marginally suitable) : 194 – 260

N ( not suitable) : 128 – 194

Table 5. Criteria for seaweed cultivation

Category and scoring No Variable Unit Weight_ing

S1 Score S2 Score S3 Score N Score

1. Salinity ppt 4 32 - 34 4 30 - 32 3 28-30 2 <28 & > 34 1 2. SST 0 _{C 4 26 - 29 4 29-30 3 30-31 2} < 26 & >

31 1 3. Current

velocity

Cm/s

ec 4 20-30 4 30-40 3 - 2 <20 & >

40 1 4. Substrate on _{bottom sea} 3

Sand, coral, and seagrass 4 Sand, coral and seagrass

3 Coral _sand 2 Coral _sand 1 5. pH 3 7.5 - < 8 4 7-7.5 &

8-8.5 3 - 2 < 7 & >

Range of suitable index:

S1 (highly suitable) _{: 68.25 – 84}

S2 (moderately suitable) _{: 52.50 – 68.25} S3 (marginally suitable) _{: 36.75 – 52.50}

N ( not suitable) _{: 21 – 36.75}

3.1.4.2. Economic Valuation

Economic valuation is conducted to choose the best alternative for coral

reef management of Ndana Island after site selection using GIS. The ultimate aim

of applying valuation technique to the ecosystem is to highlight the ways in which

economic issues can be addressed, economic tools used and management

strengthens.

Spurgeon (2003) said that Total Economic Valuation (TEV) is a useful

framework to help understand the full range of economic welfare benefits of coral

reefs, which it measure the value of ecosystem services to people by estimating

the amount people are willing to pay to preserve or enhance the services. TEV is

based on the theory that environmental assets give rise to a range of economic

values that include direct use values, indirect use values and non-use values. As

based on World Bank definitions (Munasinghe, 1993 in Spurgeon, 2003):

TEV = DUV + IUV +OV + EV + BV

where: TEV = Total economic value; DUV = Direct use value; IUV = Indirect use value; OV = Option value; EV = Existence value; BV = Bequest value.

Direct use value is determined by the contribution an environmental asset makes

to current production or consumption. Such values may comprise net economic

returns (i.e. market revenues less “opportunity costs”, the cost of inputs in their

next best alternative use) and “consumer surplus” (i.e. the amount of satisfaction

gained over and above the amount paid for). E.g. fuel wood or recreation and

tourism.

Indirect use valueincludes the benefits derived from functional services that the

environment provides to support current production and consumption (e.g. coral

reefs providing biological support to near-shore fisheries and a coast protection

function to shoreline assets).

Option value is the premium that consumers are willing to pay for an unutilized

asset, simply to avoid the risk of not having it available in the future (e.g. marine

resources may be underutilized today but may have a high future value in terms of

scientific, educational, commercial and other economic uses).

Non-use (passive) value: Existence value arises from the satisfaction of merely knowing that the asset exists; although the value has no intention of using it (e.g.

People donate money to save endangered species even though they may only see

it in books or on television). Part of the motive can be for future generations, in

which case that element of value is known as “bequest value”. These values capture some of the social value afforded by corals.

There are various valuation techniques for estimated monetary values of

natural resources, i.e.: Travel Cost Method, Contingent Valuation Method (CVM)

that the value of a natural resource or impact calculated in one location can be

used to estimate the value of a similar resource or impact elsewhere. Considerable

care is needed in its application, for example to adjust the values appropriately,

because most “site” and “impact” specific details are likely to vary considerably.

Unfortunately, at present few thorough valuation studies exist for coral reefs that

can be effectively transferred (Spurgeon, 2003).

This study estimated economic valuation of coral reef area based on

research of Husni (2001) in Lombok Timur and Agus (2005) in Lombok Barat.

Husni (2001) calculated value of Total Economic Valuation of coral reef area for

fishery and tourism activities while Agus (2005) only estimated value of fishery

activity in coral reef area. Characteristics of the area study can be seen in

(Appendix 1).

Indicators that used to evaluate decision rule of economic aspect are NPV

(Net Present Value), and BCR (Benefit Cost Ratio). NPV is the present value of

all benefits, discounted at appropriate discount rate minus the present value of all

costs discounted at the same rate. BCR is the ratio between discounted total

benefits and cost.

n

NPV = ∑ (Bt – Ct ) / (1 + i)t t=1

n n

BCR = [∑ (Bt/(1 + i)t ] / [ ∑ (Ct/(1 + i)t ] t=1 t=1

where: NPV = Net present value

BCR = Benefit cost ratio

Bt = Benefits

Ct = Cost

t = Year

i = discount rate

In most cases the NPV and BCR will give the same results and will

produce the same alternatives ranking. But in general, where the government is

using some sort of target (minimum or cut off) rate of return on capital,

maximizing NPV should be the criterion with the BCR as a supplementary check

(Anonim, 2000). The alternative can be develop if NPV > 0 or BCR > 1 and the

best choice is maximize of NPV.

3.1.4.3.Development Alternatives

Four alternatives was made for sustainable management of Ndana Island,

using economic valuation especially NPV. This because NPV is a tool that can be

used to determine if an alternative is viable or not and make comparison between

alternatives and rank alternatives. Ranking alternatives or choosing between

mutually exclusive alternatives which all have a positive NPV, should be made on

the basis of the highest NPV.

Table 6. Economic value of alternatives in coral reef area

Scenario Alternatives Economic value

I Existing condition (There is fishery activity)

NPV1

II All for conservation area, not for other activities

NPV2

III Based on suitability analysis for conservation and diving

NPV3

IV Core zone + diving + fishery (zonation based on literature and own judgment)

3.1.5. Graphical User interface

GIS-based DSS Application Development - preparing applications

identified in the Needs Assessment, which require additional programming using

the macro language or other supporting programming languages. Several models

have been introduced for system development. In this research used prototyping

model.

Prototyping is the rapid development and testing of working model or

prototypes of new application in an interactive, iterative process that can be used

by both systems analyst and end user. Prototyping makes the development process

faster and easier for system analyst, especially for project where end user

requirements are hard to define (O’Brien, 1999).

Graphical user interface is an application that can be used by users and it

has specific functions. The system development can be integrated and operated in

a personal computer. The interface has been developed using Microsoft Visual

Basic and supported by database reference (ADO) and several ActiveX

components, i.e. ESRI MapObject.

3.2.Data Source

Mainly the spatial data used for this research acquired from Center for

Marine Natural Resources Survey, BAKOSURTANAL. There are two kinds of

data, i.e:

a. Non-spatial data (based on criteria of Island Directory (UNEP, 2004): - Demographic (population, density, number of fisherman etc.) derived

from district statistical agency (BPS, 2002).

- Geography, geology and ecology data (latitude, longitude, ecosystem etc.) derived from report of survey by BAKOSURTANAL and LPPM - IPB (Anonim, 2005).

b. Spatial data:

- Vector: administration boundary, coastline, bathymetry, land use, geology, landform, slope, SST, salinity, current velocity, water clarity, depth and pH.

- Raster: image of Ndana island (Quickbird satellite image, acquisition February 26, 2005).

3.3. Tools Used

The hardware used for this study is one unit of personal computer with

Pentium III processor, 256 MB RAM and 40 GB hardisk. Several software

employed to accomplish this research are shown in Table 7.

Table 7. List of software

Software Type Function

ArcView Ver. 3.x GIS application Spatial data analysis

MapObject Ver. 2.1 Active X Developing user interface

Visual Basic Ver. 6.0 Programming software Developing user interface and database programming Microsoft Access Database application Developing attribute data Microsoft Excel Spreadsheet application Non spatial data entry and

IV.

DATABASE DESIGN AND CONSTRUCTION

4.1.Data Preparation

The data that used for the study were collected from several sources such

as BAPPEDA, BAKOSURTANAL, BPS, and DISHIDROS. Prior to the

analysis, these should be prepared for this system development, including data

identification and classification, standardization, and conversion.

Data identification defines the data on spatial and non spatial types.

Identified spatial data can be classified into feature (coverage or theme), scale

(large, medium or small) and geometric type (point, line or polygon). Non spatial

data can be classified into feature (topic or theme) and scale (province, regency,

district or island).

Data standardization of spatial data refers to Map Accuracy for Spatial

Planning Act No. 10, 2000 (Peraturan Pemerintah Nomor 10 tahun 2000 tentang

Tingkat Ketelitian Peta untuk Penataan Ruang Wilayah) and Technical

Specification for Database Development of Coastal and Marine Natural Resources

(Spesifikasi Teknis Penyusunan Basisdata Sumberdaya Alam Pesisir and Laut).

For example: administrative boundary used A code and settlement used S code.

List of classification and standardization data can be shown in Table 8 and 9.

Last activity in data preparation is data conversion which data should be

conversion to the same coordinate (UTM) and clip in the same area. All spatial

data were prepared in ArcView shape formats and maps of spatial data can be

seen in Appendix 2 and 3.

Appendix 2 show administrative boundary of Rote Ndao Regency divided

Daya, and Rote Barat Laut district while Ndana Island is located in Rote Barat

Daya District. There are seven spatial data in marine area of Ndana Island that are

salinity, sea surface temperature (SST), coral reef, depth of water, water clarity,

current and pH (Appendix 3). Vegetation covers are palm and coconut in the

central of island and grass field around the beach (see Landuse map in Appendix

3). White sand beach and some steep beach can be found with the island (see

Quickbird image in Figure 2).

Table 8. Classification and standardization data for non spatial data

No. Theme Scale Name

1. Administrative code and name Regency Kab_indo

2. Geography data Island Tb_geogpul

3. Geology data Island Tb_geolpul

4. Ecology data Island Tb_ekolpul

5. Demographic District Tb_demopul

6. Indicator Island Tb_indikator

7. Graphic data Island Tb_grafis

Table 9. Classification and standardization data for spatial data

No. Theme Geometric type Scale Name

1. Administrative boundary Polygon 25.000 A00NDANA

2. Settlement Polygon 25.000 S00NDANA

3. Coast line Line 25.000 L00NDANA

4. Land use Polygon 25.000 QA0NDANA

5. Landform Polygon 250.000 FA0NDANA

6. Geology Polygon 250.000 GA0NDANA

7. Slope Polygon 25.000 RC0NDANA

8. SST Polygon 25.000 OB0NDANA

9. Coral Polygon 25.000 OC0NDANA

10. Depth Polygon 25.000 OE0NDANA

11. Salinity Polygon 25.000 OH0NDANA

4.2.Database Building 4.2.1. Conceptual Design

The conceptual design of database is the result of the first understanding of

the application and illustrates the application at its simplest. To answer the

question those arise during the need assessment, conceptual design will defines

the objective of the database and the data need which required in the system.

Context Diagram

The context diagram is the highest level and represents the overall system,

means context diagram shows all the external entities that interact with the system

through data or information flow over the system. The Context Diagram for this

study shows three main entities and what they currently share in the way of

information; administrator, data source and user (Figure 8).

Figure ext

aster Data

Maste ovided ion that listed in the

Table 10. Th vided in type abular data. The

spatial data a again i ypes n and line.

8. Cont diagram

M List

r data list pr informat based on the data

e data are di to two s, i.e. spatial and t

re subdivided nto two t , i.e. polygo

Table 10. Master data list

Data Type Entity Feature type Attribute

A00NDANA Polygon id_kab, nm_kab, Kecamatan, Area, Perimeter

L00NDANA Line id_shoreln, keterangan S00NDANA Polygon id_settle, keterangan QA0NDANA Polygon id_lu, klas_lu RC0NDANA Polygon id_slope, klas_slope FA0NDANA Polygon id_lf, klas_lf OH0NDANA Polygon id_sali, klas_sali OB0NDANA Polygon id_SST, klas_SST OI0NDANA Polygon id_current, klas_cv OE0NDANA Polygon id_depth, klas_depth

OJ0NDANA Polygon id_wcl, klas_wcl

OK0NDANA Polygon id_ph, klas_ph

GA0NDANA Polygon id_geol, geologi, formasi Spatial

OC0NDANA Polygon id_coral, klas_coral

Kab_indo Table KodeBPS, Id_prop, NM_prop, id_kab, NM_kab

Tb_pulau Table id_pul, id_kab, nm_pul, nm_lain, gugusan, laut, desa, kecamatan, luas Tb_geogpul Table

d, id_pul, lat, long, luas, altitude, reef, lagoon, shoreln, scale, coastal, low_lan nearsl, jarak, depth

Tb_geolpul Table u, iklim,

ncam, ik_protek, change, ps_bdaya, ps_kritis, ps_reef, ps_mrove, ek_darat, ek_laut, ks_spes

id_pul, jenis, geologi, hujan, suh sd_air, ancaman, ik_a

ekosis, ps_hutan, ps_

Tb_ekolpul Table id_pul, sup_ksv, kws_ldg, jml_ldg, ldg_drt, ldg_laut, rel_data, referen, da_nil Tb_demopul Table id_pul, inhabit, human, popup, tahun,

densitas, grade, mjr_act, mnr_act, hm_imp, urb_pop, hab_type, port, airport, pop_agr, eco_prs, pop_tamb, pop_fish Tb_indikator Table id_pul, kls_TH, kd_np, kls_er, kls_sr,

kls_ep, kls_pa_kls_da, nilai_sk kls_ie_drt, kls_ie_laut, kls_inv, kls_ur,

2

Tabular

Entity Relationship Diagram

On Conceptual design, the master data list table would be follow by the

design of Entity Relationship Diagram (ERD) of the database. ERD model

contains components of entity set including their relationship set with their

attributes that represent all facts from part of the real world. This diagram also

describes cardinality, the number of possible relationship of each entity. There are

three type of cardinality, namely one to one (1:1), one to many (1:M) and many to

many (M:N). Figure 9 show ERD of this system.

Figure 9. Entity Relationship Diagram

4.2.2. Logical Design

The logical design of the database pertains to logical definition of the

database and is a more detailed organization activity in a GIS. Logical design also

describe the logic of the database which is the process of construction a model of

information based on specific data model but independent of a particular DBMS

and other physical consideration. Logical design table can be seen in Appendix 4.

4.2.3. Physical Design

Physical model is database software specific, meaning that the objects

efined during physical model can vary depending on the relational database

oftware being used. In this study, Microsoft Access software is used for the

lational database. During physical design, object such as tables and columns are

created bas al design.

onstraints are also defined including primary keys and foreign keys. Figure 10

sample of table design in Microsoft Access.

Figure 10. Sample of table design using Microsoft Access d

s

re

ed on entities and attributes that were defined in logic

C

V.

RESULTS AND DISCUSSION

5.1.Data Analysis 5.1.1. Spatial Analysis

Coral Reef Conservation Area

Conservation means protecting something from changer or destruction

while permitting its wise use. It thus involves managing the use of natural

resources so that can benefit from them now without damaging the possible

benefits they can provide in the future (UNEP, 1998).

There is a lot of coral reef in marine area of Ndana Island. Condition of

coral is variety and particularly soft corals. Type of fish is variety too which

sharks and rays relatively common. According to Anonym (2005) the best

condition of coral reef in north part of Ndana Island and percentage of coral reef

25% - 50%. This condition is fair class of coral reef. Based on Yap and Gomez

(1988) in Angkotasan (2003), there four classes in coral reef classification i.e.: <

24.9% is poor, 25 – 49.9% is fair, 50 – 74.5% is good and 75 – 100% is well

class.

Parameters that had been used for suitability analysis of coral reef

conservation area are ecological aspect, such as condition of coral reef, distance

from beach, slope, salinity and sea surface temperature; economy aspect: number

of economy activity; and social aspect: number of tourism area, number of special

species (aesthetic value) and distance from settlement. The requirement criteria

were in attribute of shape file that has been obtained by overlaying shape files of

nine parameters (union function in Geoprocessing wizard and query analysis

Based on spatial analysis in marine area of Ndana island, there are four

classes for conservation zone that are S1, S2, S3, and N. According to

Angkotasan (2003), highly suitable class (S1) for core zone, moderately suitable

(S2) for buffer zone, marginally suitable (S3) for use zone and not suitable (N) for

non-conservation area. Area and percentage of every class can be seen in Table

11 and the result of mapping suitability area for coral reef conservation is

presented in Figure 12.

Table 11. Area and percentage of coral reef conservation

No. Class Area (hectares) Percentage (%)

1. Core zone 17.95 0.29

2. Buffer zone 187.42 3.01

3. Use zone 4700.61 75.58

4. Non-conservation 1313.23 21.12

Total of marine area 6,219.21 100

Result of analysis show that only 0.29% is highly suitable and this area

should be for coral reef conservation area, not used for other applications. Highly

suitable is located in east part of Ndana Island.

78.59% of Ndana Island is suitable area for buffer and use zones. It means

that condition for conservation is at marginal level. This area can be analyzed for

sea tourism (diving) suitability. Non suitable area for conservation is location at

north part of Ndana Island and near Rote Island. It can be used for seaweed

cultivation.

Diving Suitability

There is scale bar at below the map which it’s change if scale of the map change.

Figure A.2. Main display with c

Figure A.3. Displa

There are two sub-me nus at View menu,

four sub-menus at Layers menu, three s nu, three sub-menus at Analysis menu and two sub-menus at Help menus (Figure A.4).

oordinate location of the arrow

y identify result nus at File menus, five sub-me

n

itor sub-menus at Layer menu is to change legend of active layer using single, unique, classes or label based on attributes (Figure A.5). In this form also can change fill color, s fill and outline width.

Figure A. 4. Display all of sub-menus

Function sub-me us at File and View menus same as function of print, full extent, zoom in, zoom out, and identify buttons. Function of Legend ed

Figure A. 6. Result of identity button ( )

There three sub-menus in Data menu that are Tabular, Indikator and Grafis sub-menus (Figure A.7). Functions of these sub-menus are to show tabular and indicator data same as button, but in this form need to choose name of island first. Function of Grafis sub-menus is show photo or image of the island.

Figure A.7. Display of tabular and graphic data by using sub-menus There are TEV and NPV sub menus in Economic valuation sub-menus.

Figure A.8. Total Economic Valuation (TEV) and Net Present Value (NPV)

Figure A.9. Table and graphic of NPV

Data of NPV can save by using Save command and then choose Run to show table and graph.

Process in scenario sub-menus is first input of four file and save the output, then to see the result of NPV click Run command button. Output table

Figure A. 10. Process of Scenario

There are three main functions on the spatial analysis form that are buffer, query and suitability process. Choose the layer that want to buffer and type the distance of buffer in Buffer process (Figure A.11).

Figure A.12. Result of query process

Figure A.13. Result of conservation suitability

To know information of this program, choose About sub-menu at Help menu. Close the GIS-based DSS program by using tool or choose Exit sub-menus at File menu.