Change detection and analysis of shoreline in the northeast of taiwan using remotely sensed data

i THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURAL AND FORESTRY NGUYEN VU TUAN ANH CHANGE DETECTION AND ANALYSIS OF SHORELINE IN THE NORTHEAST OF TAIWAN USING REMOTELY SENSED DATA B

i

THAI NGUYEN UNIVERSITY

UNIVERSITY OF AGRICULTURAL AND FORESTRY

NGUYEN VU TUAN ANH

CHANGE DETECTION AND ANALYSIS OF SHORELINE IN THE NORTHEAST OF TAIWAN USING REMOTELY SENSED DATA

BACHELOR THESIS

Study Mode : Full - Time

Major : Environmental Science and Management

Faculty : International Training and Development Center Batch : K44 – AEP

THAI NGUYEN - 2016

i

Thai Nguyen University of Agriculture and Forestry

Taiwan using remotely sensed data

sensing, geographic information system Number of pages

Date of submission

ii

ACKNOWLEDGEMENT

First and foremost, I wish to express my sincere thanks to the boards of Thai Nguyen University of Agriculture and Forestry, Faculty of International Training and Development Center; Advanced Education Program, for giving me this valuable and unforgettable chance studying and working in Taiwan, and more important providing

me all necessary facilities, skills and knowledge to complete this bachelor thesis

Furthermore, I want to deeply thanks to Assoc Prof Tang-Huang Lin (Head

of Environmental Remote Sensing Laboratory (ERSL), National Central University, Taiwan) for given permission to accomplish my Bachelor thesis there, and also his contact motivating supervision during my studies in the research group of ERSL, I

would like to thank to Ms Nicole Wang, who provided me the materials for my

research

This study was also supported and instructed by Professor Nguyen Van Hieu

(Head of Spatial Research Laboratory, Thai Nguyen University of Agriculture and Forestry, Vietnam) In particular, I place on record my gratitude to him for the multivariate analysis, and the knowledge of some significant change of sandy beaches around the world Without him, this work cannot be done

Finally yet importantly, I take this opportunity to record my sense of gratitude

to my families and friends who encourage and backing me unceasingly

Thank you very much!

Student signature

Nguyen Vu Tuan Anh

iii

TABLE OF CONTENTS

LIST OF FIGURES vi

LIST OF TABLES viii

LIST OF ABBREVIATIONS ix

PART I INTRODUCTION 1

1.1 Research rationale 1

1.2 Research objectives 3

1.3 The requirement 3

1.4 Limitattions 4

1.5 The significance 4

PART II LITERATURE REVIEW 5

2.1 Theoretical basis 5

2.1.1 Shoreline erosion and accretion 5

2.1.2 Geographic information system (GIS) 10

2.1.3 MNDWI method 11

2.2 Practical basis 13

PART III METHODOLOGY 19

3.1 Material 19

3.1.1 The objects 19

3.1.2 The scope 19

3.2 Methods 19

3.2.1 Collecting and selecting data 19

3.2.2 Software 20

iv

3.2.3 Flowchart of methodology 20

3.3 Image pre-processing 21

3.3.1 Radiometric correction 21

3.3.2 Geometric correction 22

3.4 Compute Modified Normalize Difference Water Index (MNDWI) 23

3.5 Overlay 24

PART IV RESULTS 25

4.1 Result of shoreline change detection map 25

4.1.1 Radiometric correction 25

4.1.2 Geometric correction 27

4.1.3 Compute Modified Normalize Difference Water Index (MNDWI) 28

4.1.4 Overlay 30

4.2 Shoreline change mapping in research area 31

PART V DISCUSSION AND CONCLUSION 38

5.1 Discussion 38

5.2 Conclusion 38

REFERENCES 39

vi

LIST OF FIGURES

Figure 1.1 Different types of coasts in Taiwan 1

Figure 1.2 Map of study area 1

Figure 2.1 Typhoon routes and No of occurrence (1897 - 1997) 8

Figure 2.2 Relative spectral response (RSR) profiles showing the spectral band difference between Landsat-8 Operational Land Imager (OLI) (solid curve) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) (short dot curve) 12

Figure 3.1 The flowchart of analysis procedure 20

Figure 3.2 Band 7,4,2 21

Figure 3.3 Band 3,2,1 21

Figure 3.4 Band 4,3,2 21

Figure 4.1 Radiometric correction of Landsat 7 25

Figure 4.1a Original 25

Figure 4.1b Radiometric calibration 25

Figure 4.1c Region of interest 25

Figure 4.1d Dark object subtract 25

Figure 4.2 Radiometric correction of Landsat 8 26

Figure 4.2a Original 26

Figure 4.2b Radiometric calibration 26

Figure 4.2c Region of interest 26

Figure 4.2d Dark object subtract 26

Figure 4.3 Landsat image 2000 27

Figure 4.4 Landsat image 2015 27

vii

Figure 4.5 The registration between Landsat image 2000 and 2015 28

Figure 4.6 MNDWI (Landsat 7) 29

Figure 4.7 MNDWI (Landsat 8) 29

Figure 4.8 Overlay 30

Figure 4.9 Shoreline change detection map in Yilan county, 2000 - 2015 31

Figure 4.10 Shoreline change detection map in Waiao beach and Wushi port, 2000 - 2015 33

Figure 4.11 Shoreline change detection map at the south of Toucheng Township, 2000 - 2015 34

Figure 4.12 Shoreline change detection map at the coast of Zhuangwei Township, 2000 - 2015 35

Figure 4.13 Shoreline change detection map at the coast of Wujie Township, 2000 - 2015 36

Figure 4.14 Shoreline change detection map at the north of Su'ao Township, 2000 - 2015 37

viii

LIST OF TABLES

Table 3.1 Satellite and sensor characteristics 19

ix

LIST OF ABBREVIATIONS

the Ministry of the Interior

Research

Difference Water Index

Figure 1.1: Different types of coasts in Taiwan Figure 1.2: Map of study area

2

The 73-km Lanyang River originates from the northern part of the Nanhu Mountain at 3740 m above sea level and winds through the Yilan County from west to east Its upstream is very steep with rapid flow coupled with a great deal of sand grains Torrential rains as well as earthquakes make the river more susceptible to collapse and erosion at the rock base, and thus create an alluvial fan in the midstream region In the downstream region, the flowing speed of the river turns slow gradually and gravels in various sizes are deposited in the river bed The river carries mass eroded materials such as mud, sand and gravels, which is one of the main sources that form sandy beaches Besides, sands drifting with tides result in shoreline changes The estuary sand source is determined by the river sediment transport capacity and sand source supply amount (Sun, 2003) Beach stabilization along the Yilan Coast must rely

on the sand source from the Lanyang River (Lee et al., 2004) Beach erosion makes direct impacts on the tourism economy of the Yilan County because the tourism economy depends highly on beautiful sandy beaches

Monitoring coastal erosion and accretion using remote sensing data is a good solution to overcome the challenges which traditional methods face to in coastal environment In assessment of coastal change, in a given period of time, the integration of remote sensing data with other geodata into Geographical Information Systems (GIS) is a powerful tool for quantitative spatial data analysis (Thao, N V., 2005)

The development of Remote Sensing (RS) and Geographical Information systems (GIS) technology can supports mapping and detecting useful information that always updated periodically Beside some types of satellite imagery with medium

3

resolution, such as Landsat images that downloaded freely from website of USGS

(http://earthexplorer.usgs.gov)appropriate with the research of erosion or deposition in

large area like Yilan county To gain a better understanding of this vulnerable area and make a good plan for the sustainability, it is crucial to observe and provide the erosional and depositional areas, as well as to study the coastline changes from past to present time

1.2 Research objectives

The objective of this study is to detect the coastline change of Yilan county using multiple space-born remote sensing resources The following tasks will be carried out to accomplish the aim of this research:

- Detection the shoreline position and identifying of the coastline change in the sandy beaches since 2000 using different approaches;

- Investigation and analysis of the reasons of coastline change;

- Evaluation of the practically of satellite remotely sensed data in the detection of coastline change, and the assessment of digital image processing and GIS techniques for the quantificative of variation in coastline over study area

1.3 The requirement

- To classify and process spatial data

- To know the rate of erosion and accretion in the research area

- To be familiarized in GIS software in mapping and analyzing data

4

1.4 Limitations

In this study, the tidal level data is not available, therefore, the shorelines determined by visual and manual techniques are appropriately considered for the reference in validating the final results from satellite imagery

1.5 The significance

Shoreline erosion is a worldwide problem that causes a major concern to the socio-economic developments in coastal cities for many countries (Chen and Zong, 1998; Genz et al., 2007) Bird (1985) indicated that about 70% of the world’s sandy beaches retreated at a rate of 0.5-1.0 m per year The increasingly intensive human activities in river basins and/or along coasts enlarge coastal erosion areas and aggravate erosion processes, and thus cause land losses: moreover the global climate change in the past decades results in rising sea levels (IPCC, 2007; Church et al., 2008) and accelerates the sand losses of beaches (Bruun, 1962; Davidson-Arnott, 2005) Such threat is particularly severe in Taiwan, an island bearing intense shoreline changes Recent surveys indicate that more than 80% of the island’s sandy beaches have undergone erosion over the past three decades and coastal erosion has occurred along most of sandy shores at an alarming rate, which becomes an island-wide problem in Taiwan (Hsu et al., 2007) Therefore, the environmental protection against beach loss, disaster warning systems for coastal zones and appropriate land management along the coasts are critical issues that need to be carefully studied and adequately developed

5

PART II LITERATURE REVIEW

2.1.1 Shoreline erosion and accretion

Shorelines are known to be unstable and vary over time Short-term changes occur over decadal time scales, more or less, and are related to daily, monthly and seasonal variations in tides, currents, wave climate, episodic events and anthropogenic factors Shoreline movement is a complex phenomenon (signal) from short-term changes (noise) Analysis of shoreline variability and erosion-accretion trend is elementally important to coastal scientists, engineers and managers (Douglas and Crowell, 2000) Both coastal management and engineering design requires information

of the past, current and future shoreline positions Successful coastal management requires long-term shoreline erosion rates to be determined and forecasts made of future shorelines positions along with the estimates of their uncertainty (Douglas and Crowell, 2000)

Shoreline erosion is the wearing away and breaking up of rock along the coast

Destructive waves erode the coastline in a number of ways: Hydraulic action: air may become trapped in joints and cracks on a cliff face When a wave breaks, the trapped air is compressed which weakens the cliff and causes erosion; Abrasion: bits of rock and sand in waves grind down cliff surfaces like sandpaper; Attrition: waves smash rocks pebbles on the shore in each other, and they break and become smoother; Solution: acids contained in sea water will dissolve some types of rock such as chalk

or limestone

6

Shoreline accretion is the process of coastal sediment returning to the visible

portion of a beach or foreshore following a submersion event A sustainable beach or foreshore often goes through a cycle of submersion during rough weather then accretion during calmer periods If a coastline is not in a healthy sustainable state, then erosion can be more serious and accretion does not fully restore the original volume of the visible beach or foreshore leading to permanent beach loss

Shoreline erosion-accretion is driven by both natural and human factors in response to the complexity of coastal hydrodynamics Natural factors involve sea levels, tidal waves, crust changes, typhoons, and sand particle size as well as sediment transport in nearby rivers while human factors involve land subsidence induced by groundwater over-pumping, illegal sand and gravel mining in river basins, a series of dams on rivers for reducing sediment transport to coastal zones, and flow conditions varied by local terrains rendered from coastal structures, which could significantly alter coastal landforms (Hsu et al., 2007) Although great efforts have been devoted to quantifying the rates of shoreline movement and obtaining the empirical relationships between shoreline changes and the variables affecting the changes process (Hsu, 1999), a definite solution, if impossible, is still far away and has not yet been found

Causes of shoreline erosion and accretion are controlled by the following factors:

Natural causes (Typhoon and storm)

Due to its particular geographic location, the Yilan County suffers from not only northeastern monsoons in winter but frequent typhoon invasions in summer Shoreline recession occurs after each typhoon attacks Taiwan Nevertheless, typhoon-

7

induced torrential rains bring abundant sediments to replenish beach losses and continuous beach nourishment works carries out for several months after typhoon seasons, which consequently lead to a cyclical dynamic equilibrium Yo (1993) compared the topographic maps of the Yilan County in the years of 1919–1987 and divided this area into three regions to discuss the shoreline erosion status Based on the topographic data measured four times during June 1992 and June 1994, Xu (1995) estimated that the shoreline retreat was about 50 m along the coast between the south

of the Wushi Port and the north of the Lanyang River A mixture of shoreline recession and accretion is found in the coast located south of the Lanyang River Nevertheless, the entire shoreline of the Yilan County still retains a stable morphology

In sum, the shoreline change along the Yilan County shows great spatial and temporal variations and it is essential to develop a site-specific model for predicting the shoreline change of the Yilan Coast

There were 350 typhoons and more than one thousand storms occurred in the past 101 years, those were most severe natural disasters in Taiwan According to the last 13 to 16 years' data, it indicates that there were approximately 3,000 buildings damaged by flood annually with a loss around 12.8 billion NT Dollars which is approximately 4.6 times the loss by fire damage

Data from the Construction and Planning Agency under the Ministry of the Interior (CPAMI) show that nearly 56 percent of Taiwan's 1,349-kilometer coastline is occupied by manmade facilities, including more than 200 fishing, commercial and military ports Most ports are protected against sea surges by barriers that project into the ocean, such as jetties and seawalls As these barriers interrupt the flow of suspended sand particles, sand accumulates on the upcurrent side of the seawall but fails to reach the other side, causing severe erosion Toucheng beach in the

9

northeastern county of Yilan which once stretched for 2 km and had a total area equal to 60 football fields is one such casualty It has been vanishing since the construction more than 10 years ago of protective jetties at the Wushih fishing harbor, located just north of the beach

Effect from coastal erosion and accretion in study area

Coastal erosion is a natural process that is generally only of concern when threatening human habitation or development The extensive urbanisation of Yilan, a region with 103 km of coastline, has resulted in exposure to hazardous coastal erosion and accretion processes and both 'soft' and 'hard' shoreline and cliff erosion

'Soft shorelines' refer to sandy beaches and dunes made up of unconsolidated or very weakly consolidated materials Sandy beaches in the Yilan region experience periods of accretion (net sediment accumulation) and erosion (net sediment decrease)

On beaches experiencing a sustained period of erosion, sediment loss results from waves, currents and wind removing sediment from the beach faster than it is replaced

Erosion and instability also happens from natural and human factors such as cliff height and modification Geology is the main factor that affects the extent of coastal erosion in Yilan

Coastal erosion can pose a risk to residential developments, roads, lifeline utilities and coastal structures

Specific impacts of coastal erosion in Yilan include:

- danger to life in the case of sudden onset landslide events

10

- structural damage or destruction of buildings and infrastructure

- damage or destruction of lifeline infrastructure such as water, sewage and gas pipes and roads

- loss of land, resulting in coastal cliffs or shorelines retreating closer to other buildings

- land instability at neighbouring slopes and properties

- loss of beach amenity due to cliff collapse or sea wall construction

2.1.2 Geographic information system

Definition: A geographic information system (GIS) is a computer system for

capturing, storing, checking, and displaying data related to positions on Earth’s surface GIS can show many different kinds of data on one map This enables people

to more easily see, analyze, and understand patterns and relationships

Components of GIS: The key components of GIS consist of computer system,

spatial data, and users, in which: computer system includes hardware and software for capturing, processing, and displaying information Spatial data may be maps, aerial photographs, satellite images, and statistical tables, and other related documents And users have missions as designing of standards, updating data, analyzing information, and supplementing data for system

Applications of Remote sensing technique and GIS

11

Recent decades, remote sensing technique (RST) and GIS have applied on domains They present in activities of human, be integral tools in management, production, and also in study However, in this study, we only list some main fields which use RST and GIS as following:

Agriculture: RST and GIS are used for crop type mapping, crop monitoring and

damage assessment, and soil classification

Forestry: These tools are known in mapping clear cut and deforestation, identifying

species and type of forest, and mapping forest fire

Geology: They are applied on structural mapping and terrain analysis and geologic

unit mapping

2.1.3 MNDWI method

In order to compute MNDWI in the next step, which is necessary to separate land from water The experiments have shown that green band (0.519 – 0.601µm wavelengths for Landsat 7 ETM+ band 2 and in 0.533 – 0.590µm wavelengths for Landsat 8 OLI/TIRS band 3) is sensitive to water turbidity differences plus sediment and pollution plumes, because it covers the green reflectance peak from leaf surface It can be useful for discriminating broad classes of vegetation The short-wave infrared (SWIR) 1/2 bands are sensitive to the moisture content of vegetation and soil In this study, SWIR 2 band was used based on the wavelengths itself ( 2.064 – 2.345µm for Landsat 7 ETM+ band 7 and 2.107 – 2.294µm for Landsat 8 OLI/TIRS band 7)

12

Figure 2.2: Relative spectral response (RSR) profiles showing the spectral band difference between Landsat-8 Operational Land Imager (OLI) (solid curve) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) (short dot curve)

(http://landsat.usgs.gov/tools_spectralViewer.php) provided by the US Geological Survey (USGS) SWIR, short-wave infrared

13

2.2 Practical basis

A case study of Xuejie Li and Michiel C.J Damen: Coastline change detection with

satellite remote sensing for environmental management of the Pearl River Estuary,

China

For the analysis of the changes of the coastlines, multi-temporal Landsat images and a SPOT scene have been used, in combination with topographical and nautical data From the change analysis, it can be concluded that the largest variations in the position

of the coastline over time occurred in the Nansha Development Zone, situated in the Northern part of Lingdingyang bay Sedimentation and land reclamation was responsible for the growth of the islands in the period 1960 to 2000, which however decreased slightly in the years after Various large changes occurred also in the East of the bay along the coast of Shekou peninsula, caused by extensive harbour construction and growth of polder systems

Beach degradation and sustainable management of the sandy coast: the Yilan coast

of the Northeastern Taiwan

By: H M Lin, F M Chu and Y T Huang

The purpose of this research is to improve the knowledge of citizens towards the Yilan coastal area The basic ideas behind this project are to reduce the degree of usage of limited natural resources and to preserve the coastal area First, it is important to devise the evaluation of the degradation status for the region The study area is Yilan’s sandy coast The beach is the frontline among all the physical features regarding its function to the inner land protection Thus, this research is to establish the indicator

14

system to evaluate beach degradation which includes beach erosion, deforestation, seawater intrusion, shoreline retreat and increase of artificial structures on the beaches with the application of digital elevation models to simulate the study areas and to calculate the volumetric change between seasons and years

“The application of GIS and RS for coastline change detection and risk assessment

to enhanced sea level rise” research studied by MSc Tang Yanli

The purpose of this research is to improve the knowledge of citizens towards the Yilan coastal area The basic ideas behind this project are to reduce the degree of usage of limited natural resources and to preserve the coastal area First, it is important to devise the evaluation of the degradation status for the region The study area is Yilan’s sandy coast The beach is the frontline among all the physical features regarding its function to the inner land protection Thus, this research is to establish the indicator system to evaluate beach degradation which includes beach erosion, deforestation, seawater intrusion, shoreline retreat and increase of artificial structures on the beaches with the application of digital elevation models to simulate the study areas and to calculate the volumetric change between seasons and years

Water body extraction and change detection using time series: A case study of Lake

Burdur, Turkey by Gulcan S., Mehmet O

In this study, spatiotemporal changes in Lake Burdur from 1987 to 2011 were evaluated using multi-temporal Landsat TM and ETM+ images Support Vector Machine (SVM) classification and spectral water indexing, including the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI) and Automated Water

15

Extraction Index (AWEI), were used for extraction of surface water from image data The spectral and spatial performance of each classifier was compared using Pearson's r, the Structural Similarity Index Measure (SSIM) and the Root Mean Square Error (RMSE) The accuracies of the SVM and satellite-derived indexes were tested using the RMSE Overall, SVM followed by the MNDWI, NDWI and AWEI yielded the best result among all the techniques in terms of their spectral and spatial quality

Spatiotemporal changes of the lake based on the applied method reveal an intense decreasing trend in surface area between 1987 and 2011, especially from 1987 to

2000, when the lake lost approximately one fifth of its surface area compared to that in

1987 The results show the effectiveness of SVM and MNDWI-based surface water change detection, particularly in identifying changes between specified time intervals

Komeil R., Anuar A., Ali S and Sharifeh H authored a case study about “Water

Feature Extraction and Change Detection Using Multitemporal Landsat Imagery”

Lake Urmia is the 20th largest lake and the second largest hyper saline lake (before September 2010) in the world It is also the largest inland body of salt water in the Middle East Nevertheless, the lake has been in a critical situation in recent years due to decreasing surface water and increasing salinity This study modeled the spatiotemporal changes of Lake Urmia in the period 2000–2013 using the multi-temporal Landsat 5-TM, 7-ETM+ and 8-OLI images In doing so, the applicability of different satellite-derived indexes including Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalized Difference Moisture Index (NDMI), Water Ratio Index (WRI), Normalized Difference Vegetation Index (NDVI),

16

and Automated Water Extraction Index (AWEI) were investigated for the extraction of surface water from Landsat data Overall, the NDWI was found superior to other indexes and hence it was used to model the spatiotemporal changes of the lake In addition, a new approach based on Principal Components of multi-temporal NDWI (NDWI-PCs) was proposed and evaluated for surface water change detection The results indicate an intense decreasing trend in Lake Urmia surface area in the period 2000–2013, especially between 2010 and 2013 when the lake lost about one third of its surface area compared to the year 2000 The results illustrate the effectiveness of the NDWI-PCs approach for surface water change detection, especially in detecting the changes between two and three different times, simultaneously

Change detection of the coastal zone east using remote sensing – A case study of the

Nile Delta by El-Asmar, H M., Hereher M E

The coastal zone of the Nile Delta is a promising area for energy resources and industrial activities It also contains important wetland ecosystems This coastal area witnessed several changes during the last century A set of four satellite images from the multi-spectral scanner (MSS), thematic mapper (TM) and Systeme Pour l’Observation de la Terre (SPOT) sensors were utilized in order to estimate the spatio-temporal changes that occurred in the coastal zone between Damietta Nile branch and PortSaid between 1973 and 2007 Image processing applied in this study included geometric rectification; atmospheric correction; on-screen shoreline digitizing of the

1973 (MSS) and 2007 (SPOT) images for tracking the shoreline position between Damietta promontory and Port-Said; and water index approach for quantifying