The Application of GIS and Remote Sensing for Determining Sensitive Area Based On Geological Hazard Perspectives

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T

HE

A

PPLICATION OF

GIS

AND

R

EMOTE

S

ENSING

FOR

D

ETERMINING

S

ENSITIVE

A

REA

B

ASED

O

N

G

EOLOGICAL

H

AZARD

P

ERSPECTIVES

EFO HADI

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2006

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STATEMENT

I, Efo Hadi, here by stated that this thesis entitled:

The Application of GIS and Remote Sensing

for Determining Sensitive Area

Based on Geological Hazard Perspectives

Are result of my own work during the period of January to August 2006 and that it has not been published before. The content of the thesis has been examined by the advising committee and external examiner.

Bogor, August 2006

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ABSTRACT

EFO HADI (2006). The Application of GIS and Remote Sensing for Determining Sensitive Area Based On Geological Hazard Perspectives. Under the supervision of KUDANG BORO SEMINAR and IWAN SETIAWAN

Geological hazards is hazard which is usually classified as geological: earthquakes, faulting, tsunamis, volcanoes, avalanches, landslides, and floods. It is a well known fact that geological hazard disaster strikes countries, causes enormous destruction and creates human sufferings and produces negative impacts on national economies. Due to diverse geo-climatic conditions prevalent in different parts of the globe, different types of geological hazard disaster strikes according to vulnerability of the area. Worldwide growth of population and particularly concentration of man and his works into urban areas, has heightened such treats to level where large-scale, and often costly, planning to reduce the hazard has become essential in many country.

By using GIS and Remote sensing technology to determine sensitive area based on geological hazard persepectives, constitute the new point of view in performing hte research. Remote sensing can enable geomorphic study of areas that are inacessible to field-investigation and GIS can performing spatial analysis by an unique way. Such conducting unsupervised to determine settlement area, generating slope from satellite imagery and with GIS all result can be map and analysis by using spatial analysis. To develop knowledge base which will use as an input for decision support system.

The core and simultaneously benefit of this research is the capabilities of GIS and Remote Sensing technology that can help geoscientist especially geologist to capture, manipulate and analyze of information about an object without physical contact as preliminary survey (reconnaissance), mainly for geomorphic study of areas that are inaccesible to field-base investigation. Moreover, by utilizing the available sources of data (data provider) GIS and Remote Sensing can be used more effective and efficient compared to the current or traditional methods for interpreting extremely large cover research area.

The sensitive area in research area, occupied by volcanic and sedimentary breccias, conglomerate, sandstone, limestone, claystone and alluvium, with slope controlled bigger than 15%. In some places, its also occupied by igneous rock with slope controlled bigger dan 50%, particularly the area with dominantly contrlolled by geologic structure. Determination concerning unstable zone in term of ‘sensitive area’ in research area immensely supported by principal component analysis in determining iron-oxide and clay-hydroxyl (alteration zone) combined with geomorphological interpretation (geology structure & drainage pattern), slope and rock characteristics weighting. There are 215 villages in Banten and West Java province which occupied sensitive area, thus detail field-investigation can be focused concerning those areas.

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THE APPLICATION OF GIS AND REMOTE SENSING

FOR DETERMINING SENSITIVE AREA

BASED ON GEOLOGICAL HAZARD PERSPECTIVES

EFO HADI

A Thesis for the degree of Master of Science Of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCE MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

August 2006

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Master of Science in Information Technology for Natural Resources Management

: Study Program

G.051034011 :

Student ID.

Efo Hadi :

Name

The Application of GIS and Remote Sensing for Determining Sensitive Area Based On Geological Hazard Perspectives

: Research Title

Approved by, Advisory Board

Ir. Iwan Setiawan, PM Co-Supervisor DR. Ir. Kudang Boro Seminar, M.Sc.

Supervisor

Endorsed by,

Dean of Graduate School

DR. Ir. Khairil A. Notodiputro, MS Program Coordinator

DR. Ir. Tania June

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CURRICULUM VITAE

Efo Hadi was born in Jakarta, Capital City of Indonesia at September 24, 1963. He spent of his childhood and school from elementary to SMU at Jakarta. He achieved his undergraduate degree from Department of Geological Engineering, Universitas Pakuan, Bogor in 1995. Since 1987, during undergraduate study, he worked as geologist assistant in several mining companies in Indonesia, particularly for geological data processing by means of computer technology.

In the year 2003, Efo Hadi pursued his master degree at MIT (Master of Science in Information Technology) for Natural Resource Management Program at Bogor Agricultural University. He proposed a method for Determining Sensitive Area based on Geological Hazard Prespectives by using GIS and Remote sensing Application.

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ACKNOWLEDGEMENT

Intiallly, I would like to express my gratefulness to ALLAH SWT for the favors and mercies to me during the time. I wish to thank to my supervisor DR. Ir. Kudang Boro Seminar, M.Sc and my co-supervisor Ir. Iwan Setiawan, PM for the guidance, advices, comments, encouragement and also constructive criticism during the supervision of my research through all months until the research was finished.

I wish also to thank and give most appreciation to MIT student’s batch 2003 for the togetherness, assistances, and the enlightment we shared for all this time, how we support each other during study until the last semester of our study. It is really a big gift and honor to me for knowing great people with different background and expertise like you guys. I would like to thank also to the staff of the Master of Science in Information Technology for Natural Resources Management (MIT) Program for the good cooperation and facilitation, special thank also to MIT lectures for sharing and imparting their knowledge and experiences during the time.

Finally, I deeply wish to express my most gratefulness to my beloved wife, Vietnami Ardya Gharini Kusumawardhani, for her support, patient, caring, devotion, and everything during my study, especially to watch over our doughters (Maulidina Inayah and Nabila Lam’anah) and son (Ahmad Sya’roni). Thank also to my mother and father (alm.), sister, uncles, aunts, parent in law for your support and caring. Last but not least, I wish to dedicate this thesis to my dear uncle, Prof. DR. Harsono Suwardi, MA for spirit you inspired me in finishing this research.

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45 Geological Hazard Sensitive Area

4.6. . . . 44 Geomorphological Interpretation

4.5. . . . 43 Rock Type Risk Zone

4.4. . . . 42 Slope Stability Risk Zone

4.3. . . . 40 Land Stability Risk Zone

4.2. . . . 39 Settlement Area

4.1. . . .

RESULT AND DISCUSSION IV.

38 Geological Hazard Mitigation Map

3.7. . . . 35 Geomorphological Interpretation

3.6. . . . 34 3.5.2. Vector Data Preparation, Classification and Analysis . . . .

33 3.5.1. Images Data Preparation, Classification and Analysis . . . .

32 Methodology

3.5. . . . 31 Required Tools

3.4. . . . 28 Data Sources

3.3. . . . 28 Research Area

3.2. . . . 28 Time and Location

3.1. . . .

RESEARCH METHODOLOGY III.

22 Geology of Research Area

2.5. . . . 20 2.4.3. Geological Risk Map . . . .

19 2.4.2. Sensitive Area . . . .

18 2.4.1. Plate Tectonics At A Glance . . . .

14 2.4. Geological Hazards . . . .

12 2.3. Decision Support System . . . .

11 2.2.1. Classification of Remotely Sensed Imagery . . . .

9 2.2. Remote Sensing And Interpretation . . . .

5 2.1. Geographic Information System (GIS) . . . .

LITERATURE REVIEW II.

4 1.5. Thesis Structure . . . .

3 1.4. Benefit of Research . . . .

3 1.3. Objectives . . . .

2 1.2. Scope of The Research . . . .

1 1.1. Background . . . .

INTRODUCTION I.

vi List of Appendices . . . .

v List of Tables . . . .

iii List of Figures . . . .

i Table of Contents . . . .

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REFERENCES . . . . 52 Recommendations

5.2. . . . 52 Conclusions

5.1. . . .

CONCLUSIONS AND RECOMMENDATION V.

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LIST OF FIGURES

Figure 4.6. . . . 44 Structural Geology interpretation by fault pattern of back-hill, valley

and main stream of research area Figure 4.5.

. . . . 44 Risk Zone by Rock Type

Figure 4.4. . . . 43 Slope Stability Risk Zone Map

Figure 4.3. . . . 41 Mineralization Zone indicating Land Stability Risk Zone

Figure 4.2. . . .

39 Result of unsupervised settlement area

Figure 4.1. . . . 37 Types of drainage patterns (Thornbury, 1989)

Figure 3.7. . . .

36 Dendritic pattern (Thornbury, 1989)

Figure 3.6. . . . 32 Methodology of Research

Figure 3.5. . . . 30 Landsat 7ETM+ of research area

Figure 3.4. . . . 30 Geologic Map of Study Area

Figure 3.3. . . . 29 SRTM of Study Area

Figure 3.2. . . . 29 Administration Map from BAKOSURTANAL

Figure 3.1. . . .

26 Southeast Asia Seismic Zonation Map Planned by USGS (USGS in

Irsyam, 2006) Figure 2.11.

. . . . 25 Active Tectonic of Indonesia: Crustal motion from GPS study. (Bock

et all. 2004 in Natawijaya & Latif, 2006) Figure 2.10.

. . . . 23 Physiographic Distribution Map of West Java (Asikin, 1986)

Figure 2.9. . . .

22 Research area (Landsat TM Path/Row: 122/65)

Figure 2.8. . . .

19 The rock cycle, interpreted in plate-tectonic terms. (Source:

Montgomery, 1991, p. 140) Figure 2.7.

. . . . 18 Lithosphere plate movements (Source: Asikin, 2003)

Figure 2.6. . . .

17 Volcanism and Plate Tectonic (Source: After Montgomery, 1991, p.

180) Figure 2.5.

. . . . 16 Location of modern volcanoes and earthquake around the world

(Source: After Montgomery, 1991, p. 126) Figure 2.4.

. . . . 14 General Tectonic Pattern of Indonesia (Source: USGS)

Figure 2.3. . . .

11 A. Geology structure interpretation on satellite image showing the

direction of earth surface movement (strike-slip fault). B. (Top) The occurrence processes of fault and slip; (Middle) Elastic energy will assembled within the earth; (Below) Earthquake damage settlement along the fault line.

Figure 2.2.

. . . . 5 Component of GIS (Eastman, J.R, 2003)

Figure 2.1. . . . 3 Research Scope that will be Applicated By Using Remote Sensing

and GIS (Asikin, 2003) Figure 1.1.

. . . . Page Caption

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T

HE

A

PPLICATION OF

GIS

AND

R

EMOTE

S

ENSING

FOR

D

ETERMINING

S

ENSITIVE

A

REA

B

ASED

O

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G

EOLOGICAL

H

AZARD

P

ERSPECTIVES

EFO HADI

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2006

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STATEMENT

I, Efo Hadi, here by stated that this thesis entitled:

The Application of GIS and Remote Sensing

for Determining Sensitive Area

Based on Geological Hazard Perspectives

Bogor, August 2006

(13)

ABSTRACT

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THE APPLICATION OF GIS AND REMOTE SENSING

FOR DETERMINING SENSITIVE AREA

BASED ON GEOLOGICAL HAZARD PERSPECTIVES

EFO HADI

A Thesis for the degree of Master of Science Of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCE MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

August 2006

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Master of Science in Information Technology for Natural Resources Management

: Study Program

G.051034011 :

Student ID.

Efo Hadi :

Name

The Application of GIS and Remote Sensing for Determining Sensitive Area Based On Geological Hazard Perspectives

: Research Title

Approved by, Advisory Board

Ir. Iwan Setiawan, PM Co-Supervisor DR. Ir. Kudang Boro Seminar, M.Sc.

Supervisor

Endorsed by,

Dean of Graduate School

DR. Ir. Khairil A. Notodiputro, MS Program Coordinator

DR. Ir. Tania June

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CURRICULUM VITAE

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ACKNOWLEDGEMENT

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45 Geological Hazard Sensitive Area

4.6. . . . 44 Geomorphological Interpretation

4.5. . . . 43 Rock Type Risk Zone

4.4. . . . 42 Slope Stability Risk Zone

4.3. . . . 40 Land Stability Risk Zone

4.2. . . . 39 Settlement Area

4.1. . . .

RESULT AND DISCUSSION IV.

38 Geological Hazard Mitigation Map

3.7. . . . 35 Geomorphological Interpretation

3.6. . . . 34 3.5.2. Vector Data Preparation, Classification and Analysis . . . .

33 3.5.1. Images Data Preparation, Classification and Analysis . . . .

32 Methodology

3.5. . . . 31 Required Tools

3.4. . . . 28 Data Sources

3.3. . . . 28 Research Area

3.2. . . . 28 Time and Location

3.1. . . .

RESEARCH METHODOLOGY III.

22 Geology of Research Area

2.5. . . . 20 2.4.3. Geological Risk Map . . . .

19 2.4.2. Sensitive Area . . . .

18 2.4.1. Plate Tectonics At A Glance . . . .

14 2.4. Geological Hazards . . . .

12 2.3. Decision Support System . . . .

11 2.2.1. Classification of Remotely Sensed Imagery . . . .

9 2.2. Remote Sensing And Interpretation . . . .

5 2.1. Geographic Information System (GIS) . . . .

LITERATURE REVIEW II.

4 1.5. Thesis Structure . . . .

3 1.4. Benefit of Research . . . .

3 1.3. Objectives . . . .

2 1.2. Scope of The Research . . . .

1 1.1. Background . . . .

INTRODUCTION I.

vi List of Appendices . . . .

v List of Tables . . . .

iii List of Figures . . . .

i Table of Contents . . . .

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REFERENCES . . . . 52 Recommendations

5.2. . . . 52 Conclusions

5.1. . . .

CONCLUSIONS AND RECOMMENDATION V.

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LIST OF FIGURES

Figure 4.6. . . . 44 Structural Geology interpretation by fault pattern of back-hill, valley

and main stream of research area Figure 4.5.

. . . . 44 Risk Zone by Rock Type

Figure 4.4. . . . 43 Slope Stability Risk Zone Map

Figure 4.3. . . . 41 Mineralization Zone indicating Land Stability Risk Zone

Figure 4.2. . . .

39 Result of unsupervised settlement area

Figure 4.1. . . . 37 Types of drainage patterns (Thornbury, 1989)

Figure 3.7. . . .

36 Dendritic pattern (Thornbury, 1989)

Figure 3.6. . . . 32 Methodology of Research

Figure 3.5. . . . 30 Landsat 7ETM+ of research area

Figure 3.4. . . . 30 Geologic Map of Study Area

Figure 3.3. . . . 29 SRTM of Study Area

Figure 3.2. . . . 29 Administration Map from BAKOSURTANAL

Figure 3.1. . . .

26 Southeast Asia Seismic Zonation Map Planned by USGS (USGS in

Irsyam, 2006) Figure 2.11.

. . . . 25 Active Tectonic of Indonesia: Crustal motion from GPS study. (Bock

et all. 2004 in Natawijaya & Latif, 2006) Figure 2.10.

. . . . 23 Physiographic Distribution Map of West Java (Asikin, 1986)

Figure 2.9. . . .

22 Research area (Landsat TM Path/Row: 122/65)

Figure 2.8. . . .

19 The rock cycle, interpreted in plate-tectonic terms. (Source:

Montgomery, 1991, p. 140) Figure 2.7.

. . . . 18 Lithosphere plate movements (Source: Asikin, 2003)

Figure 2.6. . . .

17 Volcanism and Plate Tectonic (Source: After Montgomery, 1991, p.

180) Figure 2.5.

. . . . 16 Location of modern volcanoes and earthquake around the world

(Source: After Montgomery, 1991, p. 126) Figure 2.4.

. . . . 14 General Tectonic Pattern of Indonesia (Source: USGS)

Figure 2.3. . . .

11 A. Geology structure interpretation on satellite image showing the

Figure 2.2.

. . . . 5 Component of GIS (Eastman, J.R, 2003)

Figure 2.1. . . . 3 Research Scope that will be Applicated By Using Remote Sensing

and GIS (Asikin, 2003) Figure 1.1.

. . . . Page Caption

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48 Geological Hazard Risky Settlement

Figure 4.10. . . . 48 Geological Hazard Settlement Sensitive Area

Figure 4.9. . . .

47 Sensitive Area over Rock Type

Figure 4.8. . . . 45 Drainage pattern interpretation of research area

Figure 4.7. . . .

45 Rose-diagram of 150 lineaments of research area, show the

Southwest-Northeast direction of fault system of research area

(N10o_-20o_E) _{. . . .}

Page Caption

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LIST OF TABLES

49 Risky Settlement Area in West Java and Banten

Table 4.4. . . .

43 Rock Type Distribution Weighting

Table 4.3. . . . 42 Slope Distribution Weighting

Table 4.2. . . . 42 Mineral Distribution Weighting

Table 4.1. . . . 35 Rock type and physical characteristics in research area (Sampurno,

1975) Table 3.2.

. . . . 34 Characteristics of the slope categories for land development (Howard

& Remson, 1978) Table 3.1.

. . . . 23 Study Area of Research

Table 2.1. . . . Page Caption

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LIST OF APPENDICES

Appendix 5. Geologic Time Scale

Appendix 4. Slope Generating from SRTM by means of Global Mapper & ArcGIS

Appendix 3. Creating Alteration Zone by means of ER Mapper

Appendix 2. Settlement Extraction from Landsat Imagery by means of ER Mapper and ArcView/ArGIS

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I. INTRODUCTION

1.1. Background

Overall assessment of actions needed is complicated in many ways. In fact, the source of major geological hazard may be, at the same time, a great asset to community. A mountain range providing water, irrigation, and recreation may lead to killer flood; rich volcanic soil for agriculture may surround a still lethal volcano; by products of great active fault or rift are often minerals, natural resources, beneficial climatic effects and magnificent scenery. Volcanic and geothermal areas may provide geothermal steam for power generation.

The area under study it self is located in the West Java province that represent a part of Java Island in Indonesia which has a complex geologic structure pattern that controled the development of existing land forms.

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According to Sampurno (1975) this area has many experiences of suffering hazard from landslides compared to other areas. Those hazard are progressively felt nowadays due to mass movements or landslide is endangering human life and their properties, such as houses, roads and rail roads, rice fields and farms, ranch, irrigation channel and others.

Although landslide is influenced by steepness of slope factor, rain falls, water stream, vegetation, and the result of man activities such as digging and others that can enlarger particular slope angle, however the major dominant control factor of those hazard is beginning from geologic structure which includes stratigraphic implications and tectonic activities to constructs the land forms from within the earth’s.

In the framework of this research, GIS and remote sensing technology will be used to determine geological hazard sensitive area. Remote sensing is used for geological interpretation such geomorphology, drainage and structure patterns which indicate the general tectonic patterns. While GIS is used for spatial analysis to determine geological hazard sensitive area by overlying the geological interpretation result with geologic map and other maps that required in analysis.

1.2 Scope of The Research

Geological hazard is disaster generated by effect of direct or indirect corresponding natural phenomenon with geologic processes including man.

The scope of this research is how GIS and Remote Sensing technology simultaneously can be used to determining geological hazard sensitive area based on geomorphological interpretation from satellite imagery, distribution of rocks and minerals characteristics and degree of slope steepness.

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Figure 1.2. Research scope that will be applicated by using Remote Sensing & GIS. (Asikin, 2003)

1.3 Objectives

The main purpose of the research is using GIS and Remote Sensing technology to determine sensitive area based on geological hazard perspectives. It will have a function to support a decision support system in order to take decision for placement of settlement location in West Java area. The result will contribute as a knowledge base which can be utilized by public, city planners, city officials and also policy makers to make future decision concerning the places of suitable settlement in order to obtain the sustainable development.

1.4 Benefit of Research

The core and simultaneously benefit of this research is how GIS and Remote Sensing technology will helps geoscientist especially geologist to capture, manipulate and analyze of information about an object without physical contact as preliminary survey (reconnaissance), mainly for geomorphic study of areas that are inaccesible to field-base investigation. Moreover, by utilizing the available

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sources of data (data provider) GIS and Remote Sensing can be used more effective and efficient compared to the current or traditional methods particularly for interpreting extremely large cover research area.

Finally, the result of the research will be mapped in digital and paper forms that come with additional data showing further information, created with GIS software and intentionally published in digital map which entitled as Geological Hazard Sensitive Area Map.

1.5 Thesis Structure

The thesis is structured into five chapters, each of which is described as follows:

Chapter 1 describes research background, scope and objectives;

Chapter 2 describes literature review related to the theory of Geological Hazard, remote sensing and spatial analysis in GIS and decision support system weighting methods;

Chapter 3 describes research methodology includes data source, tools used in the research, location and also weighting procedures;

Chapter 4 represent results and discussions of the research, and Chapter 5 consists of conclusions and recommendations.

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II. LITERATURE REVIEW

To determine geological hazard sensitive area by using GIS and remote sensing approach needs fundamental building theory to stretch the system thinking of building thesis structure.

2.1 Geographic Information System (GIS)

Geographic Information System (GIS) is a computer-assisted system for the acquisition, storage, analysis and display of geographic data. GIS is typically made up of variety of different components. Figure 2.1 gives a broad overview of the software components typically found in a GIS.

Figure 2.1. Components of GIS (Eastman, J.R, 2003)

Central to the systems is the database - a collection of maps and associated information in digital form. Since the database is concerned with earth surface

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futures, it can be seen to be compromised of two elements: (i) a spatial database describing the geography (shape and position) of earth surface features, and (ii) an attribute database describing the characteristics or qualities of these features. Thus for example, a property parcel defined in the spatial database and qualities such as its land use, owner, property valuation, and so on, in the attribute database.

In some systems, the spatial and attribute database are rigidly distinguished from one another, while in others they are closely integrated into a single entity, hence the line extending only half-way through the middle circle of Figure 2.1. However, it also offers the option of keeping some elements of the attribute database quite separate.

Surrounding the central database, there are a series of software components. The most basic of these is the Cartographic Display System. Cartographic Display System allows one to take selected elements of the database and produce map output on the screen or some hardcopy device such as a printer or plotter. Software systems that are only capable of accessing and displaying elements of the database are often referred to as Viewers or Electronic Atlases.

After cartographic display, the next most essential element is a Map Digitizing System. With a Map Digitizing System, one can take existing paper maps and convert them into digital form, thus further developing the database. In the most common method of digitizing, one attaches the paper map to a digitizing tablet or board, then traces the feature of interest with stylus or puck according to the procedures required by the digitizing software. Many Map Digitizing Software also allow for editing of the digitized data. Scanners may also be used to digitized data such as aerial photographs. The result is a graphic image, rather than the

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outlines of features that are created with a digitizing tablet. Scanning software typically provides users with a variety of standard graphics file formats for export. These files are then imported into the GIS. Digitizing packages, Computer Assisted Design (CAD), and Coordinate Geometry (COGO) are examples of software system that provide the ability to add digitized map information to the database, in addition to providing cartographic display capabilities.

The next logical component in a GIS is a Database Management System (DBMS) such as those which have been discuss in the previous. Traditionally, this term refers to a type of software that used to input, manage and analyze attribute data. It is also used in that sense here, although we need to recognize that spatial database management is also required. Thus, a GIS typically incorporates not only a traditional DBMS, but also a variety of utilities to manage the spatial and attribute components of the geographic data stored.

With a DBMS, it is possible to enter attribute data, such as tabular information and statistics, and subsequently extract specialized tabulations and statistical summaries to provide new tabular reports. However, most importantly, a Database Management System provides us with the ability to analyze attribute data. Many map analyses have no true spatial component, and for these, a DBMS will often function quite well. The final product (a map) is certainly spatial, but the analysis itself has no spatial qualities whatsoever. Thus, the double arrows between the DBMS and the attribute database in Figure 2.1 signify this distinctly non-spatial form of data analysis. Software that provides cartographic display, map digitizing, and database query capabilities are sometimes referred to as Automated Mapping and Facilities Management (AM/FM) systems.

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Beside a very powerful set of capabilities of the ability to digitize spatial data and attach attributes to the features stored, to analyze these data based on those attributes, and to map out the result, one most important in GIS is Geographic Analysis System.

With a Geographic Analysis System, the capabilities of traditional database query can be extend to include the ability to analyze data based on their location. Perhaps the simplest example of this is to consider what happens when users are concerned with the joint occurrence of features with different geographies. For example, suppose the user want to find all areas of residential land on bedrock types with high level of radon gas. This is a problem that a traditional DBMS simply cannot solve because bedrock types and landuse divisions do not share the same geography. Traditional database query is fine as longs we are talking about attributes belonging to the same features. But when the features are different, it cannot cope. For this we need GIS. In fact, it is this ability to compare different features based on their common geographic occurrence that is the hallmark of GIS. This analysis is accomplished through a process called overlay, thus named because it is identical in character to overlaying transparent maps of the two entity groups on top of one another.

Like the DBMS, the Geographic Analysis System is seen in Figure 2.1 to have a two way interaction with database. The process is distinctly analytical in character. Thus, while it may access data from the database, it may equally contribute the results of that analysis as a new addition to the database. For example, we might look for the joint occurrence of lands on steep slopes with erodable soils under agriculture and call the result map of soil erosion risk. This

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risk map was not in the original database, but was derived based on existing data and set of specified relationships. Thus the analytical capabilities of the Geographic Analysis System and the DBMS play vital role in extending the database through the addition of knowledge of relationships between features.

In addition to these essential element of a GIS, a Cartographic Display System, a Map Digitizing System, a Database Management System and a Geographic Analysis System, some software system also include the ability to analyze remotely sensed images and provide specialized statistical analyses. Image processing software allows one to take raw remotely sensed imagery (such as Landsat or SPOT satellite imagery) and convert it into interpreted map data according to various classification procedures.

For statistical analysis, some GIS software system offers both traditional statistical procedures as well as some specialized routines for the statistical analysis of spatial data. Geographers has developed a series of specialized routines for the statistical description of spatial data, partly because of the special character of spatial data, but also because spatial data pose special problems for inferences drawn from statistical procedures.

2.2 Remote Sensing and Interpretation

Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand and Kiefer, 1994). Satellite-based systems can measure phenomenon that change continuously over time and cover large, often inaccessible areas

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(Aronoff, 1989). By convention “from distance” generally considered being large relative to what a person can reach out and touching, hundreds of feet, hundred of miles or more. Remote sensing techniques are used extensively to gather measurement.

Geologists, geomorphologist, and other scientists routinely use the synoptic view associated with remotely sensed data to identify and interpret geomorphic features on the Earth’s surface. In fact, identifying, understanding, and appreciating the nature of landforms present on remotely sensed imagery is one of the great benefits of remote sensing science. One should take time to appreciate the tremendous beauty and variety of landform on the Earth and how ecosystems associated with the various landforms interact with one another. For example, satellite-based system can measure that change continuously over time and large cover, even inaccessible areas. The science of remote sensing provides instrument and theory to understand how objects and phenomena can be detected. The art of remote sensing is in the development and use of analysis techniques to generate useful information.

Though remote sensing will not replace the traditional geological field study, the value of remote sensing to provide a synoptic overview of a landscape cannot be overlooked. Historically, the use of remote sensing in geomorphology has been mainly interpretive, enabling geomorphologist to develop ‘picture’ of landscape and as a map-making aid. However, the use of remote sensing for quantitative geomorphic study is growing rapidly.

Remote sensing provides unique global views at different spatial scales and in different regions of electromagnetic spectrum. These global view are extremely

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useful for the sub disciplines of megageomorphology, which emphasizes the study of planetary surfaces at large scales (Baker, 1986). Remote sensing can also enable geomorphic study of areas that are inaccessible to field-based investigation.

In the framework to this research, since geomorphology constitute a primarily geology (Thornbury, 1969) we will use remote sensing as the tools for monitoring geomorphological aspects that produced by geological processes.

Figure 2.2. A. Geology structure interpretation on satellite image (SRTM) of research area, showing the direction of earth surface movement (strike-slip fault). B. (Top) The occurrence processes of fault and slip; (Middle) Elastic energy will assembled within the earth; (Below) Earthquake damage settlement along the fault line.

2.2.1 Classification of Remotely Sensed Imagery

Classification is the process of developing interpreted maps from remotely sensed images. As a consequence, classification is perhaps the most important aspect of image processing to GIS. Traditionally, classification was achieved by visual interpretation of features and the manual delineation of their boundaries.

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However, with the advent of computers and digital imagery, attention has focused on the use of computer-assisted interpretation. Although the human eye still brings a superior set of capabilities to the classification process, the speed and consistency of digital procedures make them very attractive. As a consequence, the majority of classification projects today make use of digital classification procedures, guides by human interpretation.

There are two basic approaches to the classification process: supervised and unsupervised classification. With supervised classification, one provides a statistical description of the manner in which expected land cover classes should appear in the imagery, and then a procedure (known as a classifier) is used to evaluate the likehood that each pixel belongs to one of these classes. With unsupervised classification, a very different approach is used. Here another type of classifier is used to uncover commonly occuring and distinctive reflectance patterns in the imagery, on the assumption that these represent major land cover classes. The analyst then determinees the identity of each class by combination of experience and ground truth (i.e., visiting the study area and observing the actual cover types).

2.3 Decision Support System

While decision support is one of the most important function of a GIS, tools designed especially for this are relatively few in most GIS software. However, a complete GIS software should include several modules specifically developed to aid in the resources allocation decision making process. These include modules that incorporate error into the process, help in the construction of multi-criteria

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suitability maps under varying levels of trade off, and address allocation decision when there are multiple objectives involved. Used in conjunction with the other components of the system, these modules provide a powerful tool for resource allocation decision makers.

The concept of decision support system (DSS) was first enunciated in 1970s by Scott Morton under term management decision systems. He defined such systems as “interactive computer-based system, which help decision makers utilize data and models to solve unstructured problems”. Another definition was also introduced by Keen and Scott Morton in 1978s that declare the “decision support system couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computer-based support system for management decision makers who deal with semi-structured problems.”

Furthermore, Moore and Chang (1980) define DSS as (i) extendable systems, (ii) capable of supporting ad hoc data analysis and decision modeling, (iii) oriented toward future planning, and (iv) used at irregular, unplanned intervals. Thereby, from several definition above and much more, we can simplify that DSS constitute an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improving decision making. It utilizes data, it provides easy user interface, and it allows for the decision maker’s own insight.

Aiding the deficiencies of human judgment and decision making has been a major focus of science through its history, because in many situations the quality

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of decisions is important, as particularly in complex systems, as management of organizational operations, industrial processes, or bidding processes.

2.4. Geological Hazards

The majority of geological hazard that happening in Indonesia, especially take place along volcanic belt mostly in Indonesian islands. This indicates that Indonesian Islands located and controlled by a set of major tectonic activities. Most of Indonesia's volcanoes are part of the Sunda arc, a 3,000-km-long line of volcanoes extending from northern Sumatra to the Banda Sea. Most of these volcanoes are the result of subduction of the Australian Plate beneath the Eurasian Plate. Volcanoes in the Banda Sea are the result from subduction of the Pacific Plate under the Eurasia Plate. On the Figure 2.3 shows the black "teeth" are on the overriding plate and the arrows showing the direction of movement along major transform faults.

Figure 2.3. General Tectonic Pattern of Indonesia (Source: USGS)

In congeniality of geomorphic processes, the landscape changes is a response to geologic and climatic stimuli. Its appearance at any one time

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represents a fleeting stage in a continuing conflict between internal processes

which tend to elevate the lands and external processes which tend to wear them down. Although the results of such changes is generally imperceptible and becomes visible in the landscape only after centuries or millennia, however, individual local events such earthquakes, tsunamis, volcanoes, avalanches, landslides and floods may take place very rapidly and constitute serious environmental hazards.

Those geological hazards, are mostly, unpredictable. On the other hand, human often induce change or accelerate the process of changes with their needs for existence. Their problems is not to bring environmental change to a halt, a generally impossible task, but to adapt to the environmental and to occupy it with the least physical and aesthetic damage. Thereby, as a consequence, one of them, as does a victim of geologic disaster that occurred in our country is primarily caused by poorly planned placement of settlement locations. To do so, people must be familiar with earth processes so that they may avoid or minimize damage to the terrain as well as to life and property, equally, to reduce its detrimental effects, however, we should understand the condition of our environment geologically, mainly the major of geological aspect that operates in selected areas.

Refering to the scope of the research on the previous chapter, geological hazards is disaster generated by effect of direct or indirect corresponding natural phenomenon with geologic processes including man. There are two types of geological hazards generated by the direct effect, first earthquake and the second is vulcanism.

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Figure 2.4. Location of modern volcanoes and earthquakes around the world (Source: After Montgomery, 1991, page: 126)

Earthquakes result from sudden slippage or failure of rocks along fault zones in response to stress. Most earthquakes occur at plate boundaries and are related to plate-tectonic processes. The pent-up energy is released through seismic waves, which include both compressional and shear body waves, plus surface waves, which cause the most structural damage. Earthquake hazards include damage from ground rupture and shaking, fire, liquefaction, landslide, and tsunamis (Montgomery, 1991).

We cannot hope to stop earthquakes, but we can try to limit their destructive effects. Physical damage could be limited by the following: seeking ways to cause locked faults to slip gradually and harmlessly, perhaps by using fluid injection to reduce frictional resistance to shear; designing structures in active fault zones to be more resistant to earthquake damage; identifying and, wherever possible, avoiding developments in areas at particular risk from earthquake-related hazards. Casualties could be reduced by increasing public awareness of and by improving our understanding of earthquake precursor phenomena so that accurate and timely predictions of earthquake occurrence can be made.

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Furthermore, most volcanic activity is concentrated near plate boundaries. Volcanoes differ widely in eruptive style and thus in the kinds of dangers they represent. Spreading ridges and hot spots are characterized by the more fluid, basaltic lava's. Subduction-zone volcanoes typically produce much more viscous, silica-rich, gas-charged andesitic magma, so in addition to lava they may emit large quantities of pyroclastics and other deadly products like nuées ardentes. Lava is perhaps the least serious hazard associated with volcanoes: it moves slowly, it can sometimes be diverted, and its path can be predicted.

Figure 2.5. Volcanism and Plate Tectonic (Source: Montgomery, 1991, page: 180)

The result of explosive eruption are less predictable, and the eruptions themselves more sudden. According to Montgomery (1991) an early sign of potential volcanic activity includes bulging and warming of the ground surface and increased seismic activity. Volcanologists cannot yet predict precisely the definite time or type of eruption, except insofar as they can anticipate eruptive style on the basis of historic records, the nature of the products of previous eruptions, and tectonic settings.

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2.4.1 Plate Tectonics At A Glance

The outermost solid layer of the earth is the 50- to 100-kilometer-thick lithosphere, which is broken up into a series of rigid plates. The lithosphere is underlain by a plastic, partly molten layer of the mantle, asthenosphere, over which the plates can move.

Figure 2.6. Lithosphere plates movements (Source: Asikin, 2003)

This plate motion give rise to earthquakes and volcanic activity at the plate boundaries. At seafloor spreading ridge, which are divergent boundaries, new sea floor is created from magma rising from asthenosphere. The sea floor moves in conveyor-belt fashion, ultimately to be destroyed in subduction zones, a type of convergent plate boundary, where it is carried down into the asthenosphere and eventually remelted. Convergence of continents from high mountain ranges.

According to Montgomery (1991), the evidence for seafloor spreading includes the distribution of ages of seafloor rocks, and magnetic stripes on the ocean floor. Continental drift can be demonstrated by such means as polar-wander curves and evidence of ancient climates as revealed in the rock record. Past

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margins and matching up similar geologic features and fossil deposits from continent to continent.

Present rates of plate movement average a few centimeters a year. A mechanism for moving the plates has not been proven definitively. The most likely driving force is slow convection in the asthenosphere (and perhaps in the deeper mantle). Although plate motions are less readily determined in ancient rocks, plate- tectonic processes have probably been more or less active for much of the earth’s history. They play an integral part in the rock cycle as shown in Figure 2.7.

Figure 2.7. The rock cycle, interpreted in plate-tectonic terms. (Source: Montgomery, 1991, page: 140)

2.4.2 Sensitive Area

The term of sensitive area in this research is areas which are geologically can generate hazard when on those respected areas used as settlement areas or human other activities. Its includes areas which are dominant controlled by structure geology such mountain range, plateau and plain, arid lands particularly

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areas which are formed above clay and limestone, volcanic and geothermal area and of course an opened coastal areas surrounds by bay, which entirely, in agreement with on going geomorphic processes which shape the Earth’s surface.

2.4.3 Geological Risk Map

The first step in the study of collective geological hazards is the plotting of specific information on maps at the same scale. A geological map, for example, present the areal distribution of rock structure and type. The scale chosen and the emphasis on particularr features may be selected to optimize the use of information for a particular need.

In California, a new 1:750,000 scale geological map was produced in 1972 to give an over-view of the geological properties of the State with sufficient detail to be useful for preliminary land-use planning. Published in color, it emphasizes recent volcanic rocks and volcanoes, earthquake fault and the major folds in the layered rocks. Maps with much more detail than feasible on the usual 1:250,000 to 1:1,000,000 scale maps are needed for specific hazard evaluations. For urban areas, specializied mapping for land-use planning and engineering design must show considerable detail and even include geophysical and boreholes studies of local subsurface structure. The required scale may be of the order of 1:20,000. Recent examples are slope maps produced by the U.S. Geological Survey with scale of 1:24,000. These maps indicaete the per cent of slope of hills and mountains by means of color code so that assessment of hillside erosion and stability conditions can be made. Likewise, U.S.G.S and Corps of Engineers flood hazard maps at about this scale show the elevations attained by major historical floods and floods of a specific frequency of occurences (Bolt et al 1975: 288).

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There are several unsatisfactory features of the usual geological map published in most countries. First, these maps often emphasize the formations (igneous, basin deposits, etc.) rather than the rock types involved. Alluvium consists of fine- and coarse-grained material may have depth and horizontal facies changes that lead to major seismic response consequences. Again, it is not sufficient to say that a given formation consists largely of sandstone and shale without mapping bed boundaries. The Geological Survey of New South Wales in Australia has tried to solve the problem by indicating overburden and underlying rock units by appropriate symbols. In this way, the map color defines the underlying rock, while the map symbol tags the type of overburden. In New Zealand, the Soil Bureau of the Department of Scientific and Industrial Researche produces maps of soil type that may be read in conjunction with standard geological maps. In the New England States, USA, one series of maps delineates bedrock and another the superficial glacial deposits (Bolt et al 1975: 288).

Another weakness is lack of detail when mapping the weathered conditions

of the rock types. The depth of weathering may be of considerable importance in estimating the response of the ground to strong earthquake motion. In the same way, locations of unobscured bedrock exposures deserve plotting on the basic geological maps so that when detailed investigations are needed these outcrops can be revisited quickly Alluvial deposits often require sub-division, appropriate to the scale used (e.g. 1:250,000) showing flood plains, lake deposits, colluvial, residual soils, and so on. In this way, parts of a particular surficial deposit, consisting of fine-grained material with braided stream channels of coarser material, could be identified from the map.

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In many country and also in Indonesia, a recent imaginative development is the use of computers to calculate and draw predictive hazard maps. Once the controling parameters of the hazard are known these can be combined into mathematical form and programmed once and for all.

The differences between this research compared with another that mentioned above, principally in geological and geomorphological interpretation point of view. This research thoroughly used GIS and Remote Sensing Technology for determining geological hazard sensitive area through integrating remote sensing capability especially principal component analysis (PCA) procedures to obtain common picture of present rocks and minerals distribution which indicating past as well as endogenetic and exogenetic processes.

2.5. Geology of Research Area

Research area located in West Java, precisely one scene of Landsat 7 ETM, path: 122 row: 65. (Figure 2.8)

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In general, geologically, there are three physiographic zone that represent sensitive areas in Southern West Java, that are Bogor Zone, Southern Mountain Range Zone (‘Zona Pegunungan Selatan’) and range of hill in Bandung Zone.

Ra n ge of h ill in Ba n du n g Zon e

Pa da la r a n g

Sou t h e r n M ou n t a in s Zon e Ga r u t Se la t a n , Cia n j u r ,

Su k a bu m i, Pe la bu h a n Ra t u

Bogor Zon e Su ba n g, Cia m is, Su m e da n g

Physiographic Zone Training Area

Table 2.1. Study area of Research

Figure 2.9. Physiographic Distribution Map of West Java (Asikin, 1986)

According to Sampurno (1975), Bogor Zone is characterized by series of Tertiary marine deposite which mostly consist of clay, napal, tuff claystone, sandstone and volcanic sediment. Most of those sedimentary beds folded moderately with steepness more than 25 degree. Dimensional of this area more or less 10 percent of West Java. Covered unconformability by young volcanic sediment which characterized incoherent to crumbel, porous and permeable.

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Fault structures frequently founded with intensive joint. Field frequently constitute elongated hilliest that unidirectional with strike of bed that shows West-East direction with steepness of slope about 10 - 30 percent in general including steepy escarpment. Loose rock particles deposit can be founded at base of escarpments as there are in North Ciamis area.

Furthermore, the Southern Mountain Range Zone, geologically characterized by Tertiary marine sedimentary rocks in term of clay, sandstone, limestone and turbidity volcanic sediment. Additionally, igneous rock intrusion also exist in this zone. According to Sampurno (1975), in general, this zone has a horizontal or aslant beds direct to South. Dimesional of this area more or less 20 percent of West Java and in general constitute form of plateau with steepy valley incised. Loose rock particles deposit founded at broad valley basement which represent accumulated from valleys wall surrounding as there are in South Garut and South Cianjur.

Endmost, the Range of Hill in Bandung Zone, According to Sampurno (1975), this area deputized by Rajamandala Mountains which geologically characterized by Tertiary marine sedimentary rocks in term of clay, sandstone, limestone, with small intrusion on some place. Steepness of slope is about 25 - 45 degree which controlled by fault and intensive joint. The area, in general approximately steepy in term of elongated hilliest with steepy escarpments.

Tectonically, physiographically Banten area very resemble with characteristic of Sumatra Island, if compared with its East side. Except some similarity of its morphological forms, its also with existence of volcanism product

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which many acid tuff (Banten Tuff) as does Acid Lampung Tuff, at least it can be used as a base of an opinion.

Figure 2.10. Active Tectronic of Indonesia: Crustal motion from GPS study. (Natawijaya & Latif 2006)

According to Asikin (1986) based on gravity, seismic, landsat image interpretation and field observation, there are four fault pattern systems in West Java, i.e.:

1. Sumatra direction (Northwest - Southeast), 2. Java direction (East - West), and

3. North - South direction which very dominant at North side of Java Island and Java Sea area.

4. Southwest - Northeast direction that very prominent at corner of Northeast of Java Island (Cimandiri / Sukabumi) which assumed still active in connection with distribution of intermediate and shallow earthquake epicentre. (Figure 2.11.)

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Figure 2.11. Southeast Asia Seismic Zonation Map Planned by USGS ( USGS in Irsyam, 2006)

The oldest rock unit that exsposed in West Java is Early Eocene rocks at Ciletuh area (Southern Pelabuhan Ratu). Its tectonically connected with brecciated and serpentinized ophiolites rock at contact belt. Those ophiolites interpreted as part of melangé which also constitute of Early Eocene olistostrome. Thus, the oldest rock unit in West Java is Pre-Eocene subduction belt.

Another Pre-Tertiary rocks in West Java only founded from oil drilling at North in the form of granitic igneous rock, andesitic volcanic rock association

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such volcanic breccia, lava and tuff (Jatibarang Formation), and also metamorphic rocks such slate, phyllite and marble. Those rocks association mentioned can be related with Cretaceous subduction belt that in this case constitute its magmatic belt.

Another tectonic setting of West Java according to Asikin (1986) is Tertiary Magmatic Belt which located along Southern Java Island coast line namely Old Andesite Formation at the age of Early Oligo Miocene. In West Java, part of this formation called as Jampang Formation.

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III. METHODOLOGY

3.1 Time and Location

This research has been conducted from January 2006 to May 2006 at MIT (Master of Science in Information Technology) research laboratory, SEAMEO BIOTROP, Bogor Agricultural University, Bogor and GTC@UNPAK (UNPAK GIS Center), Faculty of Engineering, Universitas Pakuan, Bogor. The location of this research is in Southern West Java (Figure 2.8. Page: 22) where active tectonic produces many geological phenomena which generated hazard sensitive areas.

3.2 Research Area

The research is focus on the determination toward sensitive area based on geological hazard perspectives by means of remotely sensed data and GIS spatial analysis methods, and also it will extend the mitigation recommendation for secure settlement location by means weighting procedures for decision making.

3.3 Data Sources

Mainly the data has been used for this research acquired from previous geologic research report, Administration Map from BAKOSURTANAL (Figure 3.1), free downloaded SRTM-Shuttle Radar Topographic Mission (Figure 3.2) from internet, Geologic digital map from PT. Aneka Tambang, Tbk - Geomineral Unit, Jakarta (Figure 3.3) and Landsat TM image of West Java 2001 with path/row = 122/65 (Figure 3.4.)

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Figure 3.1. Administration Map from BAKOSURTANAL

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Figure 3.3. Geologic Map of Study Area

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3.4 Required Tools

Some supporting hardware’s and software’s that used for accomplishing this research among others are:

y Microsoft Windows XP Professional SP1 operating system run on Dell Latitude D400, Pentium class 1398 MHz and 512 MB RAM. y ER Mapper 6.4. This software is used for image data collecting,

capturing, processing and analysis.

y Global Mapper 7.01. This software is used for converting SRTM (shuttle radar topographic mission) to Digital Elevation Model format. y ArcGIS 8.3. This software is used for spatial data collecting, capturing,

processing and analysis.

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3.5 Methodology

There are five main steps to perform the research as seen in figure 3.5.

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3.5.1 Images Data Preparation, Classification and Analysis

The first step to this research is preparation of Landsat 7ETM+ (path/row: 122/65, 2001) using ER Mapper 6.4 software to obtain Settlement Area, surely

after correcting spatial distortion in an image (geometric correction) and removing noise and image intensity variations due to antenna radiation pattern dan ground scattering elements before. In this research topographic map from BAKOSURTANAL data used in geometric correction as the GCP (ground control point) information to rectify the errors. After all images corrected, the next procedures is classifying image by unsupervised classification to obtain the classified imageries. Furthermore, from the classified imageries, querying performs to obtain settlement and openland area that have dimensional bigger than 10 hectares. Finally, the desirable Settlement Area obtained after

performing overlay analysis (union) base on the image by means ArcGIS software.

Meanwhile, by means of Landsat 7ETM+ path/row 122/65, year 2001, another procedures to obtain Mineralization Zone can generated by extracting

iron-oxide and clay mineral in an image by performing PCA (principal component analysis), filtering and convertion in ER Mapper software.

Another images data preparation is to generate Slope Stability Risk Zone

from SRTM data. As does Landsat imagery, SRTM also use topographic map to make its corrected by geometric correction procedures in ER Mapper. Afterwards, DEM obtained by generating contour in ArcGIS, where Slope Stability Risk

Zone obtained from weighting the slope generation based on characteristics of the

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Generally too steep for real real estate development. Best resticted to wildlife, forestry, and limited grazing. Over 50 percent

(over 270₎

High-rise apartment clusters and large-lot residences appropriate. Low density required. Suitable for low-intensity recreation and summer resorts. Forest and grazing lands.

30 to 50 percent (17 to 270

)

Too steep for most cultivation. Erosion problems. Slopes up to 20 percent suitable for crops such as artichoke and brussel sprouts. Also suitable for limited light industry, detached houses, high-rise apartments, institutional complexes and intensive recreational facilities.

15 to 30 percent (9 to 170

)

Moderately sloping. Too steep for airports or most heavy industry. I rrigation restricted but suitable for dry farming. Good drainage. Good setting for residential development.

5 to 15 percent (3 to 90

)

Almost level. Suitable for urban and agricultural development. Part susceptible to flooding and part with poor drainage.

0 - 5 percent (0 to 30

)

Characteristics and Suitability Slope Category

Table 3.1. Characteristics of the slope categories for land development

(Howard & Remson 1978)

3.5.2 Vector Data Preparation, Classification and Analysis

The only one vector data is Geological/Lithologic Map that will proceeses to obtained Rock Type Risk Zone, where all procedures for this purpose has

been done by means of ArcGIS software. Lithologic/rock weighting obtained base on the nature of the rock physical characteristics in West Java. (Table 3.2).

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Loose soil, plastics Hard

Poor Volcanic breccia,

igneous rock, lava or andesite intrusion, dasite Composing decomposed soil; unfertile; exessively landslides for claystone/ shale Hard for limestone,

greywacke and soft/ intermediate for claystone Good for limestone;

poor for another rock. Limestone, sandstone, claystone/ shale, greywacke, volcanic breccia Composing loose soil - plastics; fertile soil:

escarpment slide / landslide potential I ntermediate, sometimes loose cause low cemented, permeable good: (10-1_-10-2₎

cm/ det. Volcanoc tuff, tuffaceous sandstone, lapili (lava fragment), volcanic breccia Loose weathered soil - plastics; partly can function as good aquifer, flood potential. Elastic, brittle,

permeable, loose poor: some may

good (10-1

-10-7

) cm/ det.

Clay, Tuffaceous claystone, organic clay, sand, gravel (breccia).

Another Condition Hardness

Permeability Rock type/ Bed

structure

Table 3.2. Rock type and physical characteristics in research area.

(Sampurno 1975)

3.6 Geomorphological Interpretation

Geomorphology is the branch of geology that examines the formation and structure of the features of the surface of the Earth or another planet’s surface.

For geologists, geomorphological interpretation regularly conducted for preliminary study before field-investigation performed.

In this research, geomorphic interpretation and description conducted concerning fault (Figure 3.6.) and drainage (Figure 3.7.) pattern based on Landsat 7ETM+ (band 457 for structure lineaments and band 542 for drainage pattern) supported with digital elevation model from SRTM imageries.

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Endogenic processes would give constructional forms which continuingly slowly or catastrophically and causing lifting, folding and faulting. This phenomenon produced Earth’s surface architecture known as structural geology.

In performing interpretation, structural geology represented by drawing lineaments of back-hill, valley and main stream over a combined satellite images such Landsat 7 ETM+ band 457 and SRTM of research area. Whereas in performing drainage pattern interpretation conducted by using Landsat 7 ETM ban 542 based on types of drainage pattern from Thornbury (1969).

The most commonly encountered drainage patterns are the dendritic, trellis, barbed, rectangular, complex and deranged. Among these patterns, dendritic pattern are by far the most common. They are characterized by irregular branching of tributary streams in many directions and at almost any angle, although usually at considerable less than a right angle. They develop upon rocks of uniform resistance and imply a noteable lack of structural control. Dendritic pattern are most likely to be found upon nearly horizontal sedimentary rocks or in areas of massive igneous rocks but may be seen on folded or complexly metamorphosed rocks, particularly when imposed upon them by superposision.

Figure 3.6. Dendritic pattern (Thornbury, 1969. )

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Another, parallel patterns are usually found where there are pronounced slope or structural control which lead to regular spacing of parallel or near-parallel streams. In rectangular drainage patterns, both main stream and its tributaries display right-angle bends. They reflect control exerted by joint or fault systems. Furthermore, trellis pattern display system of subparallel streams which constitute characteristics of folded and strong steepnes area. Whereas radial pattern have streams diverging from a central elevated tract. They developes on domes, volcanic cones, and various other types os isolated conical or subconical hills.

Figure 3.7. Types of drainage patterns (Thornbury, 1969)

Radial pattern Parallel pattern

Rectangular pattern Trellis pattern

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3.7 Geological Hazard Sensitive Area Map

The Geological Hazard Sensitive Area Map will be produced by intersections between Land Stability Risk Zone, Rock Type Risk Zone and

Slope Stability Risk Zone Maps named Risk Zone Map. Finally Settlement

Area Map is overlaid under the risk zone map. Importantly, the result from

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IV. RESULT AND DISCUSSION

4.1 Settlement Area

Settlement area was extracted from Landsat 7 ETM+ data which is recorded in year 2001.

Classification method being used is ISOCLASS Unsupervised Classification with the result showed on Figure 4.1. Cause of the limitation of spatial resolution in Landsat imagery which is 1 pixel represents area around 30 m2_{, it is quite difficult to distinguish between settlement area and open land. Thus,} the interpretation of settlement area was regarded from the calculation of settlement class and open land class. (Appendix 2).

Figure 4.1. Result of unsupervised settlement area over Landsat 7ETM+ Year 2001

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One of many Landsat 7 ETM+ capabilities is used for alteration zone interpretation which geologically can explains general pictures of structural condition and level of weathering in research area. Those information can be extracted from several satellite channels where placed in bands.

Alteration extraction results from soil and rock data which indicates the content of laterite minerals. Iron oxide interpretation was extracted from iron rich soil gained from band 1 and band 3 which have good capabilities in iron anomaly recognition and band 5 and band 7 which have capabilities in clay rich soil recognition.

By means of principal component analysis (PCA) techniques, the anomaly data of mineral features recorded in band 1, band 3, band 5 and band 7 could be enhanced with the calculation of statistic features data and performed as dominant or majority data in population. Iron oxide and clay hydroxyl data is useful in order to interpret and predict stability zone.

Band ratio of mineral contents used for delineating areas which have contents of metal-oxide (especially iron) although clay-hydroxyl minerals. Concentration of these minerals constitute alteration process of weathering and sedimentation. The area which contains of high iron-oxide shown by reddish color whereas the higher content shown by red color. Additionally, the areas which have high contains of clay-hydroxyl are shown by blue color. While yellow color consitute unification of them.

Band ratio anomaly with circular distribution pattern generally related to concentric volcano forms. Elongated distribution pattern possibility caused by weathered iron-oxide or clay-hydroxyl on structural zone in the term of fault zone,

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where around the fault zone usually represent of weak zone and enable to occurring of alteration or weathering.

Based on alteration analysis for mineralization zone by means of principal component analysis (PCA), West Java area shown some concentrated zones (Figure 4.2.). The mentioned result progressively supported some zones which has been interpreted lithologically and geomorphologicaly.

Figure 4.2. Mineralization Zone indicating Land Stability Risk Zone

Those iron-oxide possibility consitute result of weathered igneous rocks which contains iron element in term of pyrite (FeS2), chalcopyrite (CuFeS2) and

hematite (Fe2O3) minerals. Although those igneous rock weathered or oxidized,

its characteristics still more stable than weathered rocks contains clay-hydroxyl minerals like montmorillonite (Mg2Al10Si24O5 (OH12) + Na,Ca), kaolinite

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(Al2Si2O5(OH)4) and illite ((Al,Fe,Mg)(Si,Al)2O5 (OH) + K)), where those mineral

elements have a plastic or unstable characteristics. Furthermore, the areas with yellow and cyan colors, caused by weathered rocks which contains same percentage of iron-oxide and clay-hydroxyl, but the characteristics it self not more stable than rock contains iron-oxide and more stable than rocks which contains clay-hydroxyl. Caused iron-oxide mineral that compose the rock indicating the resistant rock than clay-hydroxile mineral. Therby, Land Stability Risk Zone can

be obtained by giving weight (Table 4.1.) toward those mineral distribution in an image. Unstable 3 Clay I ntermediate 2 I ron-Clay Stable 1 I ron Description Weight Mineral Distribution

Table 4.1. Mineral Distribution Weighting

4.3 Slope Stability Risk Zone

Slope distribution weighting (Table 4.2.) obtained based on charactersitics of the slope categories for land development (Table 3.1. Page: 34) which used for generate slope map from DEM in ArcGIS. (Appendix 4).

> 50% 3 Unstable

30 - 50%

I ntermediate

15 - 30%

5 - 15% 1 Stable

0 - 5%

Description Weight

Slope

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Figure 4.3. Slope Stability Risk Zone Map

4.4. Rock Type Risk Zone

Rock type distribution weighting (Table 4.3.) obtained based on rock type and physical characteristics (Table 3.2. Page: 35) as shown in Figure 4.4.

Unstable

Claystone/ Shale, Alluvial

I ntermediate

Sandstone, Tuff (Lapilli), Bedded Limestone, greywacke

Conglomerate

Stable

I gneous Rocks, Volcanic Breccia, Crystalline Limestone

Description Weight

Rock Type

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Figure 4.4. Risk Zone by Rock Type

4.5 Geomorphological Interpretation

Based on statistical calculation of 150 lineaments in Figure 4.5., common direction of lineaments will be obtained which is N 10o_{- 20}o_{E (Figure 4.6.)}

Figure 4.5. Structural Geology interpretation by fault pattern of back-hill, valey and main stream of research area

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Figure 4.6. Rosette-diagram of 150 lineaments of research area, show the Southwest-Northeats direction of fault system of research area (N 10o_{- 20}o_E).

The pattern consitute one of the four fault pattern system in West Java and its controled by strike-slip-left fault which influenced by relatively Northwest-Southeast force in Tertiary period.

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Furthermore, based on interpretation from Figure 4.7, generally, there are three drainages pattern which shapes the land form, i.e. parallel-rectangular,

trellis-rectangular and radial patterns.

Thereby, parallel-rectangular (Pr-Rct) pattern in research area explains that

area controlled by structure geology dominantly such normal fault and then forced by strike-slip fault on the next period of tectonic occurrence. Whereas trellis-rectangular (Tr-Rct) also controlled the research area by structure geology

dominantly, but the first tectonic occurrence produced folded area.

4.6 Geological Hazard Sensitive Area

In connection with geological hazards sensitive area, integrating existing settlement area, alteration zone, slope steepness and geomorphological interpretation (fault & drainage pattern), finally, determination of sensitives area can be mapped.

In general, sensitive area occupied by volcanic and sedimentary breccias, conglomerate, sandstone, limestone, claystone and alluvium, with slope controlled bigger than 15%. In some place, it is also occupied by igneous rock with slope controlled bigger than 50%. Whereas, most of clay-hydroxyl which occupied in study area (Figure 4.2. Page: 42) indicated those area rich with mineral which produced caused by tectonic activity. Clay-hydroxyl itself formed by tectonic activity possibilities or geothermal processes that reacted with country rock/host rock that distributed by permeability fracture. (Figure 4.8).

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Figure 4.8. Sensitive Area over Rock Type

Thereby, based on raster and spatial analysis and supported by geomorphological and geological interpretation, it can be clearly seen the risky settlement area occupied around areas which is classified as sensitive area (Figure 4.9.)

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Figure 4.9. Geological Hazard Settlement Sensitive Area.

Finally, after sensitive area and risky settlement overlaid over the administration map (Figure 4.10), it can be clearly seen the distribution of risky settlement in several places in West Java and Banten Province (Table 4.4.).

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Karawang Sukabumi Ciengang Geger Bitung Hegarmulya, Cidadap Sagaranten Cibenda Ciemas Cimaherang Kabandungan Padabeunghar Jampang Tengah

Bantargadung, Hegarmanah, Sirnajaya Warung Kiara

Cibodas, Pelabuhanratu, Citarik Pelabuhan Ratu

Sinaresmi, Caringin, Pasirbaru, Cikahuripan, Gunung Kramat, Gunung Tanjung, Cikelat, Cicadas., Cimaja, Karang Papak, Cisolok, Ridogalih, Margalaksana, CIleungsi Cisolok Cidahu, Hutan Cidahu Cipeteuy Kabandungan Sukabumi West Java

Kopo, Citeko, Cibeureum, Tugu Utara Cisarua

Gadog, Kuta Megamendung

Babakan Raden, Cariu, Cibatu Tiga, Mekarwangi, Cikutamahi, Tanjung Rasa, Bantar Kuning, Buanajaya, Tanjung Sari, Cibadak Cariu Karang Tengah Babakan Madang Hambalang, Tajur Citeureup

Pangradin, Jugala Jaya, Cileuksa Jasinga

Ciaruten Ilir Cibungbulang

Leuwiliang, Wangun Jaya Leuwiliang

Pabuaran Kemang

Karihil Parung

Cipinang, Kampungsawah, Rabak, Leuwibatu

Rumpin

Argapura, Rengasjajar, Mekarjaya, Batujajar

Cigudeg

Sukaresmi, Sukadamai, Sukaharja, Pabuaran

Sukamakmur

Singasari, Bendungan, Balekambang, Sukajaya

Jonggol

Nambo, Kembang Kuning, Lulout, Leuwikaret

Cileungsi

Cikeas Udik, Wanaherang Gunung Putri

Bogor West Java

Cilograng, Cibareno Bayah

Gunung Gede, Cihara, Situregen, Sukajadi, Hegarmanah, Sindangratu, Mekarjaya, Cimancak

Panggarangan

Ciparay, Ciusul, Citorek Cibeber Cirinten Bojongmanik Haurgajrug Cipanas Muncang Muncang Wantisari Leuwidamar

Cimarga, Sangkan Manik Cimarga Sajiramekar Sajira Guradog Maja Lebak Banten Village District Sub-Province Province

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Cupunagara Cisalak Ciater, Cibeusi Jalan Gagak Banggalamulya Cipendeuy

Ponggang, Talagasari, Curugagung Sagalaherang

Subang West Java

Mekarjaya Cempaka

Margaluyu, Mekarjaya, Taringgul Landeuh Wanayasa Kertasari Bojong Citamiang Maniis Parakanlima Purwakiarta Pesawahan Pesawahan Tegalega Ciampel

Sukatani, Cibodas, Cianting Sukatani

Kutamanah, Ciririp, Parungbanteng, Danau, Jatimekar, Kembangkuning, Tajursindang, Sindanglaya Jatiluhur

Medalsari, Mekarbuana, Wargasetra, Cintalaksana, Cintawargi, Kutalanggeng, Kutamaneuh

Pangkalan

Karawang West Java

Sukapura, Cibeureum, Tarumajaya, Cikembang, Cihawuk, Neglawangi Kertasari

Mandalahaji, Nagrak, Cikawao, Pangauban, Cikitu, Girimulya Pacet

Arjasari, Pinggirsari Arjasari

Ciheulang, Gunungleutik Ciparay

Bojongmalaka, Baleendah, Manggahang Baleendah

Pananjung, Bandasari, Nagrak Banjaran Malasari, Sukamaju Cimaung Cibodas Pasirjambu Cintakarya, Sindangkerta Gununghalu Jambu, Cintaasih Cipongkor Sukajaya, Cikahuripan,

Gudangkahuripan, Jayagiri, Suntenjaya Lembang Kertawangi, Jambudipa Cisarua Lagadar Margaasih Leuwigajah Cimahi Selatan Gadobangkong Ngamprah

Cipatat, Citatah, Gunungmasigit, Cirawamekar

Cipatat

Puteran, Rende, Cikalong, Kangasari Cikalong Wetan

Ciroyom, Sirnaalih, Sirnaraja, Nanggeleng, Margaluyu Cipendeuy Bandung West Java Sinarjaya, Cijayana Bungbulang Cimahi Cisewu Selaawi Talegong Garut West Java Ramasari, Cihea Bojong Picung

Mekar Sari, Sukamulya, Mekar Mulya, Cigunungherang, Cirama Euwah Girang, Kamurnag

Cikalong Kulon

Sukaresmi Sukaresmi

Ciloto, Cimacan, Sukatani, Cipendawa, Gadog, Cibodas Pacet Cianjur West Java Village District Sub-Province Province

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Sukahurip Cijambe

Tanggulun Timur, Jambelaer, Cisampih Kalijati

Village District

Sub-Province Province

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V. CONCLUSIONS AND RECOMMENDATION

5.1 CONCLUSIONS

In general, sensitive areas are occupied by volcanic and sedimentary breccias, conglomerate, sandstone, limestone, claystone and alluvium, with slope controlled bigger than 15%. In some places, it is also occupied by igneous rock with slope controlled bigger dan 50%, particularly the areas which are dominantly contrlolled by geologic structure.

Determination concerning unstable zone in term of ‘sensitive area’ in research area is primarily supported by principal component analysis in determining iron-oxide and clay-hydroxyl (alteration zone) combined with geomorphological interpretation (geology structure & drainage pattern), slope and rock characteristics weighting.

Based on Geological Hazard Risky Settlement on Figure 4.10, there are 215 villages in West Java (193) and Banten (22) province which occupied sensitive area (Table 4.4.), thus more detailed field-investigation can be focused concerning those area.

5.2 RECOMMENDATIONS

In order to landscape study which mainly for settlement area, the area which rich contains of clay-hydroxyl and areas which have elongated alteration distribution pattrern constitute unstable areas which not suggested for settlement area.

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Due to the limitation of time and other resources, the research was focused only to determine the Geological Hazard Sensitives Area based on satellite imagery and secondary data. Therefore, more detailed study in geomorphology and field-investigation in structural geology will be given more prefect analysis due to decision support system.

Integrating with other data such geophysics and seismic data will produce more interactive dynamic map including to develop an information system for the purpose of decision making regarding geological hazard mitigation.

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(ISOCLASS unsupervised method) continued...

Convert all classification result (raster) from both images to vector by means of ArcGIS/ArcView software.

Classified Imagery

Query Settlement > 10 Hectare

settlement area

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Appendix - 3

Creating Alteration Zone by means of ER Mapper

Make virtual dataset of landsat imagery, consists of : 1. Band 1345

2. Band 1457

Create PCA for each virtual dataset included PC1,PC2,PC3, and PC4

1. PC1234 from Virtual dataset Band 1345 2. PC1234 from Virtual dataset Band 1457

Iron Oxide is correlated in Band 1 and Band 3 and saved in PC4 and Clay hydroxile saved in Band 5 and Band 7

Make virtual dataset of PC4 from PC4 of Band 1,3 and PC4 from PC4 of Band 5,7

1. PC Iron from PC4 of Band1,3 2. PC Clay from PC4 of Band 5,7

Put PC Iron in Red Layer, PC Clay in Blue Layer and Green Layer is Additional among each PC's with formula : PC4 Iron + PC4 Clay

Enhanced the histogram and filter each layer with Median 3x3

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Appendix - 4

Slope Generating from SRTM

by means of Global Mapper & ArcGIS

Appendix 4 - 1 SRTM image by Global Mapper

Export to TIFF

Reduce minus value from SRTM using formula in ArcGIS

Create contour interval 45 meter from SRTM using formula in ArcGIS

Creating TIN

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Creating TIN using formula in ArcGIS

(Slope generating from SRTM) continued...

Creating DEM from TIN using ArcGIS

Creating slope in percent using formula in ArcGIS

Reclassify slope

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Appendix 4 - 3 Reclassify slope in percent using formula in ArcGIS

(Slope generating from SRTM) continued...

0 - 5 5 - 15 15 - 30 30 - 50 50 - 3171.601563 NoData

1 2 3 4 5 NoData

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Appendix - 5

GEOLOGIC TIME SCALE

0 50 100 150 200 250 300 350 400 450 500 550 4,600 Relative Duration of Major Geologic

Intervals E r a P e r i o d E p o c h

Approximate Duration in Millons of Years Milllions of Years Ago Cenozoic Mesozoic Paleozoic

Precambrian Precambrian 4,030

70 70 570 500 35 50 430 395 20 45 55 35 345 325 280 225 54 190 71 136 11.0 65 16.0 12.0 19.0 4.5 2.5 Approx. the last

54 38 26 7 2.5 10,000 years Paleozoic Mesozoic Cenozoic Cambrian Ordovician Silurian Devonian Permian Triassic Jurassic Cretaceous Pennsylvanian Mississippian C arbonifer rous Tertiary Quarternary Paleocene Eocene Oligocene Miocene Pliocene Pleistocene Holocene

The Application of GIS and Remote Sensing for Determining Sensitive Area Based On Geological Hazard Perspectives

T

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GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2006

STATEMENT

The Application of GIS and Remote Sensing

for Determining Sensitive Area

Based on Geological Hazard Perspectives

THE APPLICATION OF GIS AND REMOTE SENSING

FOR DETERMINING SENSITIVE AREA

BASED ON GEOLOGICAL HAZARD PERSPECTIVES

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCE MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

August 2006

CURRICULUM VITAE

ACKNOWLEDGEMENT

TABLE OF CONTENTS

LIST OF FIGURES

T

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PPLICATION OF

GIS

AND

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EMOTE

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ENSING

FOR

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ETERMINING

S

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G

EOLOGICAL

H

AZARD

P

ERSPECTIVES

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2006

STATEMENT

The Application of GIS and Remote Sensing

for Determining Sensitive Area