UNIVERSITI PUTRA MALAYSIA CHANGE DETECTION IN MANGROVE...
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UNIVERSITI PUTRA MALAYSIA
CHANGE DETECTION IN MANGROVE FOREST AREA USING LOCAL MUTUAL INFORMATION
MAHIRAH BINTI JAHARI
ITMA 2010 5
CHANGE DETECTION IN MANGROVE FOREST AREA USING LOCAL MUTUAL INFORMATION
MAHIRAH BINTI JAHARI
MASTER OF SCIENCE UNIVERSITI PUTRA MALAYSIA
2010
CHANGE DETECTION IN MAGROVE FOREST AREA USING LOCAL MUTUAL INFORMATION
By
MAHIRAH BINTI JAHARI
Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirements for the Degree of Master of Science
November 2010
Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the degree of Master of Science
CHANGE DETECTION IN MANGROVE FOREST AREA USING LOCAL
MUTUAL INFORMATION
By
MAHIRAH JAHARI
November 2010
Chairman: Siti Khairunniza bt Bejo, PhD Faculty: Institute of Advance Technology
This thesis unveils the potential and utilization of similarity measure for forest change
detection. A new simple similarity approach based on local mutual information is used
to detect any significant changes in the image of forest areas. Point similarity measure is
defined as a measure which is used to calculate the similarity of individual pixels. The
basic idea of the proposed method is that any change pixel will be maximally dissimilar,
i.e. the value of similarity of these pixels will be low. The method has been tested to
detect and identify changes caused by plant growth and plant loss in four sub-areas of
Matang Mangrove Forest, Perak. Image of SPOT 5 satellite taken from band 1, band 2,
band 3, and band 4 with the resolution of 10meter dated on 5 August 2005 and 13 June
2007 has been used to test the method. It is then compared with the results of Principal
Component Analysis 1 (PCA 1). The plant loss areas has been successfully identified as
any pixel with the value of local mutual information less than and equals to zero. The
method has been refined to accurately detect changes caused by the growth areas by
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thresholding the histogram of the average percentage of difference between joint
probability and marginal probability. Results from the experiment showed that a
threshold value of zero is the best threshold value to identify between changed and
unchanged areas in all cases of the images. In overall, band 3 gives the best results of
forest change detection compared to the other bands in all cases. Compared to the image
differencing and normalized differenced vegetation index (NDVI), the proposed method
not only can solve the problem on selecting the threshold value but also provides the
highest percentage of successful classification at the fourth, second and first study area
with the value of 95.07%, 89.47% and 87.66% respectively. From the results, it has
been concluded that local mutual information is not only can be effectively used for
change detection technique but also can be used to classify the plant growth and plant
loss areas.
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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains
MENGESAN PERUBAHAN DI KAWASAN HUTAN PAYA BAKAU
MENGGUNAKAN PENENTUAN KESERUPAAN SETEMPAT
Oleh
MAHIRAH JAHARI
November 2010
Pengerusi: Siti Khairunniza bt Bejo, PhD Fakulti: Institut Teknologi Maju
Tesis ini menyingkap potensi penggunaan penentuan keserupaan setempat dalam
kaedah pengesanan perubahan bagi kawasan hutan. Satu pendekatan keserupaan yang
baharu dan mudah berdasarkan maklumat salingan tempatan digunakan bagi mengesan
apa sahaja perubahan penting dalam imej kawasan hutan. Titik keserupaan setempat
ditakrifkan sebagai satu langkah yang digunakan bagi mengira persamaan pada piksel
individu. Konsep asas bagi kaedah yang dicadangkan adalah piksel yang mempunyai
perubahan akan menghasilkan perbezaan yang maksimum, i.e. nilai persamaan piksel
ini akan menjadi rendah. Kaedah ini telah diuji bagi mengesan kawasan perubahan dan
mengenal pasti sama ada perubahan itu disebabkan oleh pertumbuhan pokok atau
kehilangan pokok dalam empat kawasan di Hutan Bakau Matang, Perak. Imej daripada
satelite SPOT 5 dengan jalur 1, jalur 2, jalur 3 dan jalur 4 yang mempuyai resolusi
10meter bertarikh 5 Ogos 2005 dan 13 Jun 2007 telah digunakan untuk menguji kaedah
ini. Ianya kemudian akan dibandingkan dengan keputusan daripada Analisis Komponen
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Utama 1 (PCA1). Kawasan yang mengalami kehilangan pokok telah dikenalpasti
dengan jayanya di mana nilai setempat maklumat salingan piksel di kawasan tersebut
adalah kurang dan sama dengan sifar. Kaedah ini diperhalusi lagi untuk mengesan
secara tepat kawasan-kawasan yang berubah akibat daripada pertumbuhan pokok
dengan menggunakan kaedah pengembangan titik ambang pada histogram peratusan
purata perbezaan antara kebarangkalian bercantum dan kebarangkalian sut. Keputusan
menunjukkan bahawa nilai ambang yang terbaik untuk menentukan kawasan yang
berubah dengan kawasan yang tidak berubah adalah nilai sifar. Secara keseluruhannya,
dalam penentuan perubahan di kawasan hutan, band 3 memberikan nilai yang terbaik
berbanding jalur-jalur lain dalam semua kes. Berbanding dengan kaedah pembezaan
imej dan kaedah perbezaan normalisasi indeks tumbuhan (NDVI), kaedah ini bukan
sahaja dapat menyelesaikan masalah pemilihan nilai ambang dalam kaedah penentuan
perubahan tetapi juga memberikan peratusan kejayaan yang tertinggi di kawasan
keempat, kawasan kedua dan kawasan pertama dengan nilai masing-masing adalah
95.07%, 89.47% dan 87.66%. Kesimpulan hasil daripada keputusan kajian
menunjukkan maklumat salingan tempatan bukan saja berkesan digunakan sebagai
teknik pengesanan perubahan tetapi juga boleh digunakan untuk mengenalpasti
kawasan-kawasan pertumbuhan pokok dan kehilangan pokok.
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ACKNOWLEDGEMENTS
I am thankful to Allah for making things possible, Alhamdulillah. I would like to
express my sincere gratitude and thanks to my supervisor Dr. Siti Khairunniza Bejo for
her untiring guidance, assistance, encouragement and supervision during the conduct of
the study. I would also like to express my deep appreciation and gratitude to Dr. Helmi
Zulhaidi b. Mohd Shafri and Assoc. Prof. Dr. Abdul Rashid Mohamed Shariff for their
co-supervision, guidance and suggestions.
I am thankful to Mr. Mohd Suhaimi b Mohd Noor (PPHD (Laut)) from Pejabat Hutan
Daerah Larut & Matang, Perak for guidance, assistance providing the data and field trip
to the study area. Special thanks to all members and technicians at Faculty of
Engineering, Universiti Putra Malaysia and Institute of Advance (ITMA) for allowing
and providing the facilities to be used to complete my research and graduate study. I
would also like to record my gratitude to my lecturers and friends who always give
motivation and support to accomplish my study.
Utmost appreciation and heartfelt gratitude goes to my beloved parents and all family
members for their patience, understanding, support and sacrifices throughout my study.
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I certify that an Examination Committee met on XXXX to conduct the final examination of Mahirah binti Jahari on her Master of Science thesis entitled “Change Detection In Forest Area using Local Similarity Measure” in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The committee recommends that the candidate be awarded the relevant degree. Members of the Examination Committee were as follows: Ishak Aris, Ph.D. Associate Professor Faculty of Engineering Universiti Putra Malaysia (Chairman) Abdul Rahman Ramli, PhD Associate Professor Faculty of Engineering Universiti Putra Malaysia (Internal Examiner) Syamsiah Mashohor, PhD Faculty of Engineering Universiti Putra Malaysia (Internal Examiner) Mohd Zubir Mat Jafri, PhD School of Physic Universiti Sains Malaysia (External Examiner) _______________________ BUJANG KIM HUAT, PhD Professor/Deputy Dean School of Graduate Studies Universiti Putra Malaysia Date:
Deleted: ¶
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This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master of Science. The members of the Supervisory Committee were as follows: Siti Khairunniza Bejo, PhD Senior Lecturer Faculty of Engineering Universiti Putra Malaysia (Chairman) Abdul Rashid Mohamed Shariff, PhD Associate Professor Faculty of Engineering Universiti Putra Malaysia (Member) Helmi Zulhaidi Mohd Shafri, PhD Senior Lecturer Faculty of Engineering Universiti Putra Malaysia (Member) ________________________________ HASANAH MOHD GHAZALI, PhD
Professor and Dean School of Graduate Studies Universiti Putra Malaysia
Date: 10 March 2011
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DECLARATION
I declare that the thesis is my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously, and is not concurrently submitted for any degree at Universiti Putra Malaysia or other institutions.
_________________________
MAHIRAH BINTI JAHARI
Date: 3 November 2010
TABLE OF CONTENTS
Page
ABSTRACT ii ABSTRAK iv ACKNOWLEDGEMENTS vi APPROVAL vii DECLARATION ix LIST OF TABLES xii LIST OF FIGURES xiii LIST OF ABBREVIATIONS xiv CHAPTER 1 INTRODUCTION 1
1.1 Problem Statement and Motivation 3 1.2 Objectives 5 1.3 Scope and Limitation of the Study 5 1.4 Thesis Outline 6
2 LITERATURE REVIEW 7 2.1 Mangrove Forest Area 7 2.2 Remote Sensing 9 2.2.1 SPOT 5 Satellite 12
2.2.2 Application of Remote Sensing 13 2.3 Change Detection 15
2.4 Similarity Measure 26 2.5 Summary 29
3 METHODOLOGY 31 3.1 Research Design 31
3.2 Study Area 32 3.2.1 Area 1 35 3.2.2 Area 2 37 3.2.3 Area 3 38 3.2.4 Area 4 39 3.2.5 Reference Image 41 3.3 Preprocessing 42 3.3.1 Geometric Correction 43 3.3.2 Principal Component Analysis 45 3.4 Local Mutual Information 46 3.5 Comparison with the Other Change Detection Method 51
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3.5.1 Normalized Difference Vegetation Image (NDVI) 51 3.5.2 Image Differencing 52 3.6 Accuracy Assessment 52
4 RESULTS AND DISCUSSION 54
4.1 Background 54 4.2 Principal Component Analysis 54 4.3 Experimental Results 56 4.3.1 Threshold Value Selection 56 4.3.2 Band and PCA 1 Images Comparison 62 4.3.3 Band Images Analysis 66 4.4 Type of Changes: Changes Caused by the Plant Growth and Caused by the Plant Loss
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4.5 Band Combination 84 4.6 Other Change Detection Method 89
4.6.1 Image Differencing 89 4.6.2 Normalized Difference Vegetation Index (NDVI) 97 4.7 Accuracy Assessment 102 5 CONCLUSION AND RECOMMENDATIONS 112
5.1 Conclusions 112 5.2 Recommendations for Further Studies 115
REFERENCES 117 APPENDICES 124 BIODATA OF STUDENT 158 LIST OF PUBLICATION 159