UNIVERSITI PUTRA MALAYSIA

THE USE OF LANDSAT TM IN ASSESSING FOREST AREA CHANGE

IN SELANGOR, MALAYSIA

ZULHAZMAN HAMZAH

FH 1999 11

THE USE OF LANDSAT TM IN ASSESSING ' .

FOREST AREA CHANGE IN SELANGOR, PlALA YSIA

ZULHAZMAN HAMZAH

MASTER OF SCIENCE UNIVERSITI PUTRA MALAYSIA

1999

THE USE Of LANDSAT TM IN ASSESSING FOREST AREA CHANGE IN SELANGOR, MALAYSIA

By

ZULHAZMAN HAMZAH

Thesis Submitted in Fulfilment of the Requirements for the Degree of Master of Science in the Faculty of Forestry

Universiti Putra Malaysia

August 1999

ACKNOWLEDGEMENTS

I would like to express my deepest appreciation to my Supervisor,

Prof. Capt. Dr. Kamaruzaman Jusoff for his invaluable guidance, constructive

criticisms and encouragement throughout the period of the study.

Special appreciation to Prof. Dr. Nik Muhamad Nik Ab. Majid and

Assoc. Prof. Dr. Azizi Muda for their useful comments on the writing of this

project report.

I would like also to thank to the Director of Malaysian Centre for

Remote Sensing (MAC RES), Mr. Nik Nasruddin Mahmood for kindly allowing

the use of necessary facilities and materials during image processing and

also his invaluable comments and ideas on writing this project report. My

gratitude to Mr Shamsuddin Omar for the technical assistance and

cooperation to make this study possible.

Special thanks are also dedicated to my beloved family and to

Haszuliana Mohd. Hassan for her valuable assistance, patience,

encouragement and support.

ii

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , ., .......................... ii LIST OF TABLES . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . v LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . '" ........... , ........................ vii LIST OF PLATES . . . . . . . . , .................. '" ......... '" .. , ., ............ , .... , .............. ix ABBREViATIONS . . . . .. . . ... . . .. . . ... . . . . . . . . . . . . . .... . .. . .. . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . x ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii ABSTRAK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .' ............... , . .................... xiv

CHAPTER

INTRODUCTION . . . . . . . . . . . . . . . . . . . . , . . . . . .... ... . .... . . . . ... '" .. , . . . . . . . . . 1 General .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Statement of Problems . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . 4 Objectives .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . 6

II LITERATURE REVIEW . . . . . . . . . '" . . . . , . . . , . . . . . . . . . . . . . . . . ... , . . . . . . . .... 7 Forest Changes in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Agricultural Development. . . . . . . . . . . . " ... . . . . . . .. . . .. . . . . . . . . . . . . . 8 Timber Exploitation . . . . . . . . . . . . . . . . . . . . . . . . . . . " . . . . . . . . . . . .. . .. . . . 10 Urbanization .. . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . 15

The Tools for Monitoring Forest Changes . . . . . . . . . . . . . . . . , . ... . ... .. 16 The Major Operational Remote Sensing Satellite . . . . . . . . . . 17

Application of Remote Sensing Technology in Assessing and Monitoring Forest Cover Changes . . . . . . . . . . . . . . . . 33

LANDSAT Data Applications . . . . . . . . .. . . . . . . . . . . . . . . . . .. . . . . . . . . 34 SPOT Data Applications . .. . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 NOAA Data Applications . . . '" ........... , ... , .............. , .... 40

III MATERIALS AND METHODS . .. .. . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . .. . . 44 Description of Study Area . . . . . . . . . . . . . .. . . . . . . . .. . . . . . . . . . . . . . . . , . . .. . .. . . 44

Topography and Hydrology . . . . . . . . . . . . . . . . '" . . . . . . . . . . . . . . . . . . . 50 Geology and SoiL . . . . . . . . . . . . . . . . . .. . . . . . . . . .. . . . . . . . . . . . . . . . . . . .. . 5 1 Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 52

Materials . . .. " " .. " .. ...................... . ................................. 53 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Image Processing System . . . '" . . . .. . .... ... '" .. . . .. ....... , . .. 54

Methodology . . . '" '" ............ ............................. , .............. 54 Digital Image Analysis . . . . . . . . . . '" . ...... . . ....... ... . . ... '" . . . .. 58 Pre-processing . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Image Enhancement. . . . . . . ... . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . 59 Normalized Difference Vegetation Index (NDVI) . . . . . . . . . . . 65

iii

Image Classification . . . . .. . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 66 Ground Truthing . . . . . . . . . . . . . . . . . . , . . .. . , .. . . , . . . . . , . . . . . . . . . ... . . . . 70 Classification Accuracy ................. , ......................... 71

IV RESULTS AND DISCUSSION . .... . . . . . . , . . . . . . . .. '" . . . . . . . . . . . . . . . ... 72 I mage Enhancement. . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . .. . .. . . . . . . . . . . . .. 72

Band Combination and Contrast Stretching . . . . . . . . . . . . . . . . . 72 Spatial Filtering . . . . . . . . . . . , . . . . . . . . . . '" . . . . . , . . , . . . . . . . . . . , . . , . . . . . 80

Normalized Difference Vegetation Index (NDVI) .. . . . . . . . . . . . . . . . . . . 87 I mage Classification . . . . . . . . . . . '" . . . . . . . . . . '" '" . . . . . . '" . . . . . . . . . . .. .. . . . 90

Unsupervised Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Maximum Likelihood Classification . . . . . . . . . . '" . . . . . . . . . . . . . . . 96

Post Classification Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . 1 02 Ground Truthing ... . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 08 Accuracy Assessment. .. .. . .. . . . . .. . . . . . . , . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . 1 08 Comparison Between Maximum Likelihood Classification (MlC) and Selangor Forestry Department (SFD) Data . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 1 17 Factors Influencing Forest Changes . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . 1 21

V CONCLUSIONS AND RECOMMENDATIONS . . . . . . '" ., . . . . . . .. 1 24 Conclusions . . . '" . . . . . . .. . . , . . , . . , . . . . . . . . . . '" . . . . .. .. , . . . . . , . . . . . . . , . . . . . 1 24 Recommendations . . . . . , . . . . . . . . . . , . . . . . . . . . . '" . . . . . . . . , . . . . . , . . . . , . . , . . 1 25

BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . '" .. , . . . . . , . . , . . . . , . . . . . , . . . . . . . 127

ViTA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 37

iv

LIST OF TABLES·

Table Page

1 Status of Forest Changes in Malaysia (million ha) . . . '" . ..... . . .. .. . .. . ... . . .. 7

2 Distribution and Extent of Major Forest Types 1994 ..... ... ............. .. ... 8

3 Land Development by FELDA (1956-1990) ... ... ... ......... . .. . .... . . .. ... .... 9

4 Malaysia: Export of Major Timber. Products from 1993-1996 by Volume ('000 cubic meters) and Value (RM'OOO) . . . . . . . . . . . . . . . . . . . . . . . . 12

5 The Main Environment Polar Orbiting Satellite Systems or Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

6 Characteristics of LANDSAT-1 to -6 Missions . . . . . . . . . . . . '" . , .... ....... ... 20

7 Sensors Used of LANDSAT-1 to -6 Missions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

8 Thematic Mapper Spectral Band . . . . . . . . . . . . '" .. . . . . ... . . . . .. . .. .. , . , ... , ....... 22

9 Bands and Applications of the SPOT XS, or MultispectraL . . . . . . . . '" . . , .24

10 Characteristics of NOAA-6 to -12 Missions . . . . . . . . . . . . . . . '" . .. ... ..... . . ... . 26

11 Non-Forested Land in Selangor as of 31.12.1995 .. ....... . '" .......... , .. .46

12 Permanent Forest Estate (PFE) by Forest Type, in Selangor as of 31.12.1995 .... .. .. . ...... .. .. ........ .......... ..... ......... .. ............... . 48

13 Correlation Between Seven TM Bands of 1993 Image . . . . . . .. . . . . . . . . . . . . . 72

14 Correlation Between Seven TM Bands of 1996 Image . . . . . . . . . . . . . . . . . . . . . 73

15 The Various Class Means of NDVI1993 and NDVI1996 . . . . . . . . . . . . . . . . . 87

16 The Statistical Result of Seven Classes by Supervised Classification of Multitemporal NDVl lmages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

17 Unsupervised Classification Statistical Results of Eight Clusters of LANDSAT TM 1993 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . � . . . . . . 92

18 Unsupervised Classification Statistical Results of Nine Clusters of LANDSAT TM 1996 .... . ... .. . .. .... . . .. ... . .... . . .. . ...... . .. . . . ..... 92

v

19 Statistical Result of Eight Classes by MlC of 1993 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

20 Statistical Result of Ten Classes by MlC of 1 996 LANDSAT TM Image ... ..... . ... . ........ . . . .... .. . .... . . . . . ..... .... ..... .. .. .... . .... .... . . . . ... . 97

2 1 Classified Pixels of Forest Type i n 1 993 and 1 996 . .. .. . . . ....... . .. .. .... 1 06

22 The MlC Statistical Result of Forest Chan ges Within 1 993-1 996 Period .. . . .... . .. . . ... .. . . . ... . .. .... ... . . . .. . .... . .. . .. . ... . .... . ... . . . 1 07

23a Confusion Matrix of MlC 1 993 ... .. . ... . .. .. . . ... .. ....... ... . . . .. ..... .. . . . . . . . 1 1 6

23b Confusion Matrix of MlC 1 996 . ... . . .. . .. . . . . . . . . ... . . . . . .. . ... .. . . .. . . .... . . . . . 1 1 6

24a Excision of Forest Reserve in Selangor in 1 993 ..... .. ............. ........ 1 1 8

24b Excision of Forest Reserve in Selangor in 1 994 . . . . .. ..... , '" .... . . ... . . . . 1 1 8

24c Excision of Forest Reserve in Selangor i n 1 995 .. . .... . .. . . . ..... .... ...... 1 1 9

24d Excision of Forest Reserve in Selangor in 1 996 . . . . .. . . . . .. . ... .. ... .. . . . .. 1 1 9

25 Forest Reserve Excision Within 1 993-1 996 .. . .... .. ... .. . .. . . .. . ... .. ... . ... 1 20

26 Areal Extent Differences Between Data Derived from Selangor Forestry Department (SFD) and Maximum Likelihood Classification (MLC) . ... . . . . . . . . .. . . . . , . . , . . .. .. . 1 20

vi

LIST OF FIGURES

Figure Page

1 The Location of Study Area . . . . . . . , . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

2 The Location of Permanent Forest Estate (PFE) in State of Selangor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

3 F low Diagram of Study . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . , . . . . . 57

4 Graphic Representation of LUT . . . . . . . . . . . . . . . . , . . , . . . . . . . . . . . . '" . . . . . . . . . '" . . . 62

5 Grey Level Thresholding . . . . . . . . . . . . . . . , . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

6a Average Filter (3x3) '" ., . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . , . . . . . . . . . . . 64

6b Edge Filter (5x3) . . . . . . '" . . . . . . . . . . . . . '" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

6c Edge Sharpen ing Filter (3X3) . . . . . , . . , . . . . . . . . . . . . . , . . , . . . . . . . . . , . . . . . . . . , . . . . . . . . 65

7a Band 3 of 1 993 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

7b Band 4 of 1 993 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

7c Band 5 of 1 993 LANDSAT TM Image . . . . . . . . . . . . . .. . .. . . .. . . . . .. . . . . . . . . . . . . . . . 76

8a Band 3 of 1 996 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

8b Band 4 of 1 996 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

8c Band 5 of 1 996 LANDSAT TM Image . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

9a Combination of Bands of 4, 5 , and 3 of 1 993 LANDSAT TM Image . . . . . .. . . . . , . . . . . . . . . . . . . . . . . . . . . . , . . , . . , . . . . . . . . . . . .. . .. . . . . . . . 81

9b Combination of Bands of 5,4, and 3 of 1 993 LANDSAT TM Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 82

1 0a Combination of Bands of 4, 5, and 3 of 1 996 LANDSAT TM I mage . . . . . . . . . . . . . . . '" . . . '" . . . . , . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

1 0b Combination of Bands of 5, 4, and 3 of 1 996 LANDSAT TM Image . . . . . . . .. . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . '" . . . 84

1 1 Filtered 1 993 I mage . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

vii

1 2 F iltered 1 996 I mage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. , . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

1 3 Multitemporal NOVI C lassification on 1 993 and 1996 I mage . . . . . . . . . . . . . 88

1 4 Multitemporal N OV I Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

1 5 Eight Clusters of Unsupervised Classification on 1 993 Image . . . . . . . . . . . . 94

1 6 N ine Clusters of Unsupervised Classification on 1 996 Image . . . . . . . . . . . . 95

17 Three Classes of Forest Cover Types of MLC on 1 993 Image . . . . . . . . . . . 98

1 8 Three Classes of Forest Cover Types of MLC on 1 996 I mage . . . . . . . . . . . 99

1 9 SIEVE F iltered on 1 993 Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . 1 00

20 SIEVE F iltered on 1 996 Image . . . . . . . . . .. . . . . .. . . . . ... ... .. . . . . .. . . . . . . . . . . . . . . . 1 01

2 1 a Changes on In land Forest Between 1 993-1 996 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 03

2 1 b Changes on Peat Swamp Forest Between 1 993-1 996 . . . . . . . . . . . . . . . . . . . . 1 04

2 1 c Changes on Mangrove Forest Between 1 993-1 996 . . . . . . . . . . . . . . . . . . . . . . . 1 05

22 Location of Training S ites . . . '" . . . . . . . . . . . . . . . . . . . . . . . . , . . .. . , . . . . . . . . . . . . . . . . . . . . 1 09

viii

UST OF PLATES

Plate Page

1 A Stand of Inland Forest in S9. Lalan9 F.R. ....................... .......... 110

2 A Stand of Matured Peat-Swamp Forest at Raja Musa F.R . . . . , ........................ , ... '" ............. '" .................. 110

3 A Stand of Bakau Minyak (R. apicu/ata) in Mangrove Forest at Pulau Ketam F. R. ...................................................... 111

4 A View of Paddy Field Which Misinterpreted as Peat-swamp Forest. . . . . . . . . . . . . . . . . . '" ......... '" ......... '" .......... " ., ...... 111

5 An Area of Mangrove Forest in Teluk Gong F.R. Which Was Cleared for Fish and Prawn Breeding . . . . . . . . . . . . . . . . . . . . . . . . . 112

6 A View of Marina's Marine Park Which Was Converted from Mangrove Area at Pulau Indah F. R. .................................... 112

7 A Segment of 'Matau' in Peat-swamp Forest at Raja Musa F.R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . '" '" ...... '" '" ...... 113

8 Logging Activity in Peat-swamp Forest at Raja Musa F.R . . . . . . . . . '" .......................................................... 113

9 A Segment of National Sport Complex Construction Which Was Converted from Rubber Estate Near the Boundary of Air Hitam F. R. . . . .. . . . . . . .. . . . . . . . . . .. . . . , ................ .......... 114

10 A Segment of Logged-Over Forest Which Have Been Cleared in 1993 in Sg. Lalang F.R . . . . . . . . . . . . . . . . .. . .. . . . . . . . . . . . . . . . . . . . . . . . . 114

11 A New Highway Constructed Near the Boundary of Kuala Langat F.R ....... , ................ '" .................. '" '" ........ , ...... 115

12 A Part of Ex-Oil Palm Plantation Which Was Opened Up for KLiA Project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

ix

AVHRR

cn

CNES

DOA

DTM

ERTS

FCC

FD

FDHQ

FELDA

FOB

F .R.

FRIM

GAC

GOP

GIS

GNP

HRV

Ino

LAC

LANDSAT

LUT

MAC RES

MLC

MSS

NDVI

NEP

PFE

RBV

RCFM

ABBREVIATIONS

Advanced Very High Resolution Rad iometer

Computer Compatible Tape

French Centre National d'Etudes Spatiales

Department Of Agriculture

D igital Terrain Model

Earth Resources Technology Satellites

False Color CompOSite

Forestry Department

Forestry Department Headquarters

Federal Land Development Agency

Freight On Board

Forest Reserve

Forest Research Institute Of Malaysia

Global Area Coverage

Gross Domestic Product

Geographical Information System

Gross National Product

High Resolution Visible

International Tropical Timber Organ ization

Local Area Coverage

Land Satellite

Look Up Table

Malaysia Centre For Remote Sensing

Maximum likelihood Classification

Multispectral Scanner

Normalized Difference Vegetation Index

New Economy Policy

Permanent Forest Estate

Return Beam Vidicon

Regional Centre For Forest Management

x

SFD Selangor Forestry Department

SFM Sustainable Forest Management

SPOT Systeme Pour I'Observation de Ie Terre

TM Thematic Mapper

VI Vegetation Index

xi

Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirements for the degree of Master of Science.

THE USE OF LANDSAT TM IN ASSESSING FOREST AREA CHANGE IN SELANGOR, MALAYSIA

By

ZULHAZMAN HAMZAH

August 1999

Chairman : Professor. Capt. Kamaruzaman Jusoff, Ph.D

Faculty : Forestry

The rate of development due to industrialization and human

settlement in the state of Selangor has accelerated tremendously in recent

years, with a corresponding escalation in the rate of depletion of the forest

areas. This trend has given rise to fears of impending depletion of forest

areas and considerable concern for environmental stability and quality.

Under these circumstances, the need for conservation and effective

management of the forests in Selangor is imperative and cannot be under

emphasized. One fundamental set of tools crucial in assessing forest cover

changes will be the data provided by remote sensing. This study was

undertaken to assess forest area changes in Selangor using satellite

remote sensing technology. Detection of forest area change was performed

using multitemporal LANDSAT data taken in 1993 and 1996, with the

support of existing land use, topographic, and forest resource maps. The

data were initially analyzed using Normalized Differences Vegetation Index

(NDVI) in order to get a preliminary scenario of the change in forest

xii

cover. The data were then classified using Maximum Likelihood

Classification (MLC) and Qvenaid to generate forest change. A total of 39

ground reference points were selected randomly and visited in ground

truthing work. Results from this ground truthing showed that forest types

can be identified and discriminated easily in LANDSAT TM data.

The study quantified that within 1993 to 1996 the loss of inland forest

was about 2 824.5 ha which implies 941.5 ha per year of inland forest have

been converted to other land use types. Peat-swamp forest and mangrove

forest have also been reduced by 655.2 ha and 4 738.5 ha, which account

for an annual loss of 218.4 ha and 1 579.5 ha, respectively. This means a

total of 8 218.2 ha of forest areas in Selangor have been converted to other

land use types between 1993 to 1996, which implies an annual loss of

about 2 739.4 ha, with an accuracy of 84.2 percent. Factors causing forest

cover changes include industries, human settlement, logging activities,

aboriginal areas, agricultural, recreation and tourism, livestock and illegal

settlement areas.

xiii

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains

PENGGUNAAN LANDSAT TM BAGI MENILAI PERUBAHAN KAWASAN HUTAN 01 SELANGOR, MALAYSIA

Oleh

ZULHAZMAN HAMZAH

Ogos 1999

Pengerusi : Profesor Kapt. Kamaruzaman Jusoff, Ph.D

Fakulti : Perhutanan

Dewasa ini, kadar pembangunan perindustrian dan kawasan

penempatan di Selangor semakin bertambah, mengakibatkan kemerosotan

terhadap kawasan-kawasan hutan. Keadaan ini tetah mencetuskan

kebimbangan terhadap kemerosotan kawasan hutan ini dan pertimbangan

yang sewajamya harus diberikan terhadap kestabilan dan kualiti alam

sekitar. Dalam keadaan ini, keperJuan kepada pemuliharaan dan

keberkesanan pengurusan hutan di Selangor adalah sangat dikehendaki.

Salah satu daripada alat yang penting dalam penilaian perubahan kawasan

hutan adalah data yang dibekalkan oleh alat penderian jauh. Kajian ini

dijalankan untuk menilai perubahan kawasan hutan di Selangor

menggunakan satelit penderiaan jauh. Pengesanan perubahan kawasan

hutan diadakan menggunakan data LANDSAT multitemporal yang diambil

xiv

pada tahun 1 993 dan 1 996, dengan bantuan pete gunatanah, topografi

dan sumber hutan.

Data ini pada mulanya dianalisa menggunakan keadah Normalized

Difference Vegetation Index (NDVI) untuk mendapatkan gambaran awal

mengenai keadaan perubahan kawasan hutan yang berlaku. Data ini

kemudiannya diklasifikasikan menggunakan kaedah Maximum Likelihood

Classification (MLC) dan ditindankan untuk memperoleh perubahan

kawasan hutan. Sebanyak 39 titik sampel di lapangan telah dipilih secara

rawak dan dilawati semasa ke�a-kerja di lapangan. Keputusan daripada

ke�a-kerja lapangan ini menunjukkan bahawa jenis-jenis hutan boleh

dikenalpasti dan dibezakan dengan mudah menggunakan data LANDSAT

TM.

Kajian ini mendapati bahawa di antara tahun 1993 dan 1 996 terdapat

kemerosotan hutan darat sebanyak 2 824.5 ha iaitu 941.5 ha setahun

kawasan hutan darat telah ditukar menjadi lain-lain jenis guna tanah. Hutan

paya gam but dan paya laut juga telah berkurangan sebanyak 655.2 ha dan

4 738.5 ha, di mana jumlah kemerosotan tahunan adalah sebanyak 218.4

ha setahun bagi hutan paya gambut dan 1 578.5 ha setahun bagi hutan

paya laut. Ini menunjukkan bahawa di antara tahun 1993 dan 1996

sebanyak 8 218.2 ha daripada luas hutan di Selangor telah ditukarkan

menjadi lain-lain jenis guna tanah, di mana kemerosotan tahunannya

xv

adalah sebanyak 2 739.4 ha setahun, dengan ketepatan sebanyak 84.2

peratus. Faktor-faktor yang menyebabkan perubahan kawasan hutan ini

adalah termasuk perindustrian, kawasan penempatan, kegiatan

pembalakan, kawasan untuk orang asH , pertanian, kawasan rekreasi dan

pelancongan, temakan dan kawasan setinggan.

xvi

CHAPTER I

INTRODUCTION

General

Tropical rain forest thrives in the warm, wet environment of the humid

tropics. It has high rainfall and moderately high temperatures throughout the

year. The high rainfall, generally averaging 1 800 to 4 000 mm per annum and

at least 1 200 mm results from the ascent of warm moist air due to thermal

convection and the meeting of the two sets of trade winds that flow towards the

equator from subtropical latitudes (30-40° North and South). The fairly even

distribution of solar radiation during the year leads to constant high

temperatures with little variation; mean monthly temperatures are generally 24-

28°C (Grainger, 1 993).

Malaysia is divided into three distinct regions; Peninsular Malaysia (P.

Malaysia), encompassing twelve states, and the states of Sabah and Sarawak

in northern Borneo. Forest endowments vary greatly between these areas, and

state governments are largely autonomous in managing land and forest. The

total area of natural forest in Malaysia as at the end of 1994 was estimated to

be 19.0 million ha or 58.0 percent of the total land area, with the proportion of

forested land being higher in Sabah and Sarawak than in P. Malaysia (Abdul

Rashid and Koh, 1 996)

2

The tropical rain forest of Malaysia is one of the oldest and highly

complex ecosystem which is rich and varied in plant and animal life. The

forest plays a significant role in economic development of the country,

especially in foreign exchange earnings, government revenues, the

development of local wood-based and related industries and employment.

Apart from these, the forest maintains environmental stability of the country

and is a store house of plant and animal species in such a way their richness

and diversity have been considered to be the centre of origin and diversity of

many present day and future crop plants (Chin and Lai , 1 993).

Although the tropical rain forest of Malaysia is generally taken to be

synonymous with the species-rich lowland and hil l dipterocarp forests that

extend over large parts of the country, there are other forest types such as

the montane forest, mangrove and peat-swamp forests. In 1 994, forest cover

of P. Malaysia extended over an area of about 6 .0 million ha. , constituting

45.6 percent of the total land area (Anon, 1 994).

The forest resources in Malaysia have been systematically managed

for the sustained production of timber and other services. The two most

prominent and current management approaches by the Forestry Department

are the Malaysian Uniform System (MUS) and the Selective Management

System (SMS). The MUS is basically a system which converts the virgin

tropical lowland forest which is rich, complex multi-species and multi-aged

forest to a more or less even-aged forest containing a greater proportion of

the commercial species. The MUS is achieved by felling aU trees exceeding

3

45 cm dbh for selected species and abounding the forest to natura\

regeneration through growth of seed\ings. This may be foUowed by

systematic poisoning of "defective relics and non-commercial species" to 1 5

cm dbh (Thang, 1 987). The mangrove forest areas are also being managed

to achieve maximum sustained yield of wood for charcoal, fuel wood and

poles. The mangrove rotation cycle varies from 20 to 30 years.

In order to manage natural resources efficiently, concerned agencies

as well as the Forestry Department (FD), Forest Research Institute of

Malaysia (FRIM), Regional Centre for Forest Management (RCFM) and

Malaysia Centre for Remote Sensing (MACRES) have focused attention on

developing more effective techniques for monitoring and surveying of tropical

forest. One of the present technologies being used in Malaysia is remote

sensing. However, although the government is aware of its potential and

usefulness, remote sensing technology is stil l in its infancy. To date, only few

studies have been carried out on the use of practical remote sensing method

in monitoring forest resources, especially in detecting forest disturbances

and cover types, rates of deforestation, and assessment of logged-over

forest for forest plantation development planning (Abdul Haye, 1 993; Mohd.

Rasol, 1 994; Zulhazman, 1 995).

4

Statement of Problems

Tropical forests are being cleared at the rate of 1 40 000 km2 to 200

000 km2 per year (Houhgton, 1 990) for agriculture, timber exploitation,

pasture and land speculation. The detrimental impacts of extensive forest

conversion on rural communities, plant diversity, soil, wildlife, watershed and

ultimately global climatic patterns are very serious. For the estimated 50.0

million people who live in the forests and who depend on the forests for their

survival, the effects on them are even more immediate and tragic. Every day

they witness their homes being bulldozed and their food and water supplies

destroyed, whether for dam construction, mining activities, highways, or for

timber extraction (Peng, 1 992). The current rates of change may mean

nearly complete loss of the extent of tropical forests for much of the world

over the next few decades. Some countries formerly rich in forests now have

little or no primary forest left.

P. Malaysia has probably the most reliable forest loss figures in Asia

because most of the forest destruction is government controlled (Hurst,

1 992). The total forested area in P. Malaysia is getting smaller each year,

giving way to agriculture, human settlement development and logging

purposes. In 1 983, the total forested area was 6 373 064 ha. However, in

1993, i t was reduced by 5 .5 percent, to 6 024 008 ha (Anon, 1 993) .

The loss of 2 .0 million ha. of forested land or 0. 1 4 million ha. annual ly

over the period 1 979 to 1 992 was due to agricultural development and

to a lesser extent urban and infrastructural development, and in hydro-dam

construction. At the end of 1 992, Malaysia had a total of 4.5 million ha. of

agricultural tree crops. These are mainly rubber, oil palm, coconut and

cocoa. Increasingly these crops can be looked upon as alternative sources

of wood supplies especially that of rubber wood (Thang, 1993).

In Selangor, the rate of industrialisation and human settlement have

accelerated tremendously, with a corresponding escalation in the rate of

depletion of the forest areas. According to statistical data issued by Forestry

Department of P. Malaysia, in 1993, the total Permanent Forest Estate (PFE)

was 247 342 ha. However, in 1997, it was reduced by 1 percent to 246 780

ha (Anon, 1997). Being one of the most developed states in P. Malaysia,

many human settlements and new townships were developed. Forest areas

were also opened up for the construction of new highways. These trends

which will be aggravated by the growing population and increasing

industrialization, have given rise to fears of impending depletion of forest

areas and considerable concern for environmental stability and quality.

Under these circumstances, the need for conservation and effective

management of the forests in Malaysia, with special emphasis to the state of

Selangor is imperative.

One fundamental set of tools crucial in assessing forest cover

changes will be the data provided by remote sensing and the data

management capacity of Geographic Information System (GIS). Current

trends in technology indicate that remote sensing and GIS will play a

5

6

greater role in forest monitoring. Recent advances include an increasing

number of useful earth observing sateUites, the advent of radar sateUites,

and major improvements in our ability to manage the vast quantities of data

will be available to further monitor changes in the forest cover over certain

period of time. Remote sensing will become increasingly indispensable in

Malaysia for the effective conservation, management and development of its

resources (Khali Aziz, 1991).

Objectives

The general objective of this study is to monitor and assess forest

area changes in the state of Selangor using satellite technology. The specific

objectives are to:

1. identify and quantify forest changes,

2. determine the factors influencing forest changes, and

3. produce a current forest map for the state of Selangor.

CHAPTER II

LITERATURE REVIEW

Forest Changes in Malaysia

The New Economy Policy (NEP) had important implications for forests

because, among other things, it sought to increase access of the poor to land

and to modernize rural life. One result was a great proliferation of federal and

state agencies and authorities. This section focuses on the three main

processes of anthropogenic forest change, namely; agricultural development,

timber exploitation and urbanization. Tables 1 and 2 provide some information

of forest changes and total land area in Malaysia.

Table 1: Status of Forest Changes in Malaysia (million. ha.)

Year Total Land Area Forested Area Percentage (%) Annual Forest Change (million ha) 1980 32.9 20.54 62.3 nil 1983 32.9 20.30 61.7 -0.24

1986 32.9 20.40 62.0 +0.10

1987 32.9 20.20 61.4 -0.20

1988 32.9 20.10 61.1 -0.10

1989 32.9 19.47 59.2 -0.63

1990 32.9 19.42 59.0 -0.05

1991 32.9 19.24 58.5 -0.18

1992 32.9 19.21 58.4 -0.03

1993 32.9 19.17 58.3 -0.04

1994 32.9 18.80 57.1 -0.37

1995 32.9 19.01 57.B +0.21

1996 32.9 1B.87 57.4 -0.14

1997 32.9 20.53 62.4 +1.66

Source: Abdul Rashid and Koh (1996); Anon (1998)

7