Monitoring changes in coastal mangrove extents using multi temporal satellite data in period 2000 march 2018 in hai phong vietnam

VIETNAM NATIONAL UNIVERSITY OF FORESTRY FOREST RESOURCES & ENVIRONMENTAL MANAGEMENT FACULTY STUDENT THESIS MONITORING CHANGES IN COASTAL MANGROVE EXTENTS USING MULTI-TEMPORAL SATELLITE

VIETNAM NATIONAL UNIVERSITY OF FORESTRY FOREST RESOURCES & ENVIRONMENTAL MANAGEMENT FACULTY

STUDENT THESIS

MONITORING CHANGES IN COASTAL MANGROVE EXTENTS USING

MULTI-TEMPORAL SATELLITE DATA

IN PERIOD 2000-March 2018 IN HAI PHONG, VIETNAM

Major: Natural Resources Management Code: D850101

Faculty: Forest Resources and Environmental Management

Student: Tran Thi Ngoc Lan Student ID: 1453090210

Class: K59B-Natural Resources Management Course: 2014-2018

Supervisor: Assoc.Prof.Nguyen Hai Hoa

Advanced Education Program Developed in collaboration with Colorado State University, USA

Hanoi, 2018

ACKNOWLEDGEMENT

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 105.08-2017.05

With the consent of Vietnam National University of Forestry, Ministry of Agriculture

and Rural Development faculty, we perform the study: “Monitoring changes in coastal mangrove extents using multi-temporal satellite data in period 2000-March2018 in Hai Phong, Vietnam”

First of all, I am extremely grateful for the guidance and the support of Assoc.Prof.Nguyen Hai Hoa, who gave helpful advices and strong supports for me during the implementation and completion of this study

Secondly, I would like to thank for the encourage, and suggestions of the teachers of the Forest Resources and Environment Management Faculty, Vietnam Forestry University that helped me complete the thesis with the best quality

The thesis could not be finished and achieved good results without the enthusiatic help

of my friends, friendliness, and hospitality of the local authority and residents of Kien Thuy, Duong Kinh and Do Son districts, especially Dai Hop and Bang La communes, I would like to give a great thank and extreme appreciation to them

I also would like to thank my family who always supported and encouraged me to perform and complete the study

Because of the limited study duration as well as lacking awareness and knowledgewe are looking forward to receiving the comments, evaluation and feedback of teachers and friends

to raise the quality of study and improve not only the professional knowledge but also the lacking skills of me in this study

TABLE OF CONTENTS

ACKNOWLEDGEMENT i

TABLE OF CONTENTS ii

ABBREVIATIONS iv

LIST OF TABLES v

LIST OF FIGURES vi

CHAPTER I INTRODUCTION 1

CHAPTER II LITERATURE REVIEW 4

2.1 GIS AND SATTELITE LANDSAT IMAGE 4

2.1.1 Concept of GIS, remote sensing and GPS 4

2.1.2 Landsat and Sentinel 2 Satellite Images 5

2.2 OVERVIEW OF REMOTE SENSING APPLICATIONS 6

2.2.1 In the world 6

2.2.2 In Vietnam 8

CHAPTER III OBJECTIVES, CONTENTS AND METHODOLOGY 10

3.1 GOAL AND OBJECTIVES 10

3.1.1 Overall goal 10

3.1.2 Specific objectives 10

3.2 OBJECT AND SCOPE OF STUDY 10

3.2.1 Object 10

3.2.2 Scope 10

3.3 CONTENTS 11

3.4 METHODOLOGY 12

3.4.1 Investigate the current status and management scheme of coastal mangroves 13

3.4.1.1 Inheriting method 13

3.4.1.2 Field survey and sociological investigation method 13

3.4.2 Construct the thematic maps and area changes of coastal mangroves 14

3.4.3 Assessment the key driver of coastal mangrove dynamics 16

3.4.4 Proposing feasible solutions for mangrove forests 16

CHAPTER IV NATURAL, SOCIO-ECONOMIC AND CULTURAL CONDITIONs 17

4.1 NATURAL, SOCIO-ECONOMIC AND CULTURAL CONDITIONS 17

4.1 1 Natural characteristics 17

4.1.2 Socioeconomic and cultural conditions 19

CHAPTER V RESULTS AND DISCUSSION 22

5.1 Current status and management scheme of mangrove forests 22

5.1.1 Current status of coastal mangroves in Hai Phong 22

5.1.2 Management scheme of mangrove forests 23

5.2 Construct thematic maps and area dynamics of coastal mangroves during 2000- March 2018 24

5.2.1 Accuracy assessment 24

5.2.2 Thematic maps of coastal mangroves in period 2000 – March 2018 26

5.2.3 Dynamics of coastal mangroves during period 2000 – March 2018 29

5.3 KEY DRIVERS OF COASTAL MANGROVE CHANGES FROM 2000 TO March 2018 32

5.4 FEASIBLE SOLUTIONS TO IMPROVE COASTAL MANGROVE MANAGEMENT 33 CHAPTER VI CONCLUSION, LIMITATIONS AND FURTHER STUDY 40

6.1 GENERAL CONCLUSION 40

6.2 LIMITATION 41

6.3 FURTHER STUDY 41

REFERENCES 42

APPENDIX 51

DONREs Department of Natural Resources and Environment

GIS Geographic Information System

GPS Global Positioning System

J–M The Jeffries–Matusita Distance

KfW Kreditanstalt für Wiederaufbau (Germany)

LMIRE Law on Marine and Island Resources and Environment

MARD Ministry of Agriculture and Rural Development

MERC Marine Environment Research Center

MONRE Ministry of Natural Resources and Environment

NDVI Normalized Difference Vegetation Index

NGOs Non-Government Organizations

PAM Programme Alimentaire Mondial (French) or World Food Programme

SCM Supervised Classification Method

SID Spectral Information Divergence

UCM Unsupervised Classification Method

LIST OF TABLES Table 3.1: Landsat image collected in study 14 Table 5.1: Coastal mangroves in the study areas (ha) 22 Table 5.2: Accuracy assessments by using 3 classification methods 25

LIST OF FIGURES

Fig.3.1: Map of study sites 11

Fig.3.2: An overview of methods used for monitoring mangrove extents 12

Fig.5.1: Mangrove management scheme in Hai Phong City 24

Fig.5.2: Land use and land cover in Kien Thuy-Do Son districts from 200 to 2018 27

Fig 5.3: Land use and land cover in Do Son- Duong Kinh districts from 200 to 2018 28

Fig 5.4: Changes in coastal mangroves in Kien Thuy- Do Son districts and Do Son-Duong Kinh districts, Hai Phong during 2000-March 2018 30

Fig 5.5: Fluctuation of mangroves area in (a) Kien Thuy- Do Son and (b) Do Son- Duong Kinh during 2000-March 2018 31

CHAPTER I INTRODUCTION

Mangrove forests have been distributing in inter-tidal zones where oceans, freshwater, and land merge together (Giri et al., 2011) They are among the most productive and complex ecosystems on the planet, growing under environmental conditions that extremely different from others (Woodroff et al., 2016; Hong & San, 1993) Furthermore, mangrove forests are rich in biodiversity providing a habitat for wide varieties of animal and plant species, so it is considered as nursery of coastal areas by forming a unique intertidal forests at muddy, loose and wet soils and represented on all continents near the shore belonging tropical and sub-tropical areas (Asokan, 2012; Kuenzer et al., 2011; Primavera, 1998; Field et al., 1998) This structure creates an intricate network of habitat for numerous amphibious and marine animals (Field et al., 1998) Importantly, networks of these sediment-trapping forests buffer the coastline against wave-induced erosion and provide coastal ecosystems and coastal communities a vital line of defense against strong, tropical storms Moreover, the dual services

of coastal protection and habitat for commercially important species make mangrove forests one of the most valuable ecosystems in the world Unfortunately, like many coastal and marine ecosystems, they are being lost at an extremely rapid rate (Romañach et al, 2018; Spalding, 2010) Clear-cutting for coastal development projects (including construction of shrimp farms, hotels, and other structures), harvesting for wood, and pollution threaten mangrove forests Scientists estimate that at least one-third of all mangrove forests has been lost during the last few decades (Romañach et al., 2018) Without active policies that aim to reverse the negative trend and preserve this system, mangrove forests (and the valuable services that they provide) may disappear in some areas In the southern hemisphere, ranges extend further south on the eastern margins of land masses than on the western (Hogarth, 2015) In addition, mangroves are also sensitive and fragile related to the change in climate and sea level (Alongi, 2015) This

is because of the pattern of warm and cold ocean currents Indeed local anomalies

of currents and temperature and furthermore the local evolution can create local changes A disappearance would represent both an ecological and an economic loss in coastal areas that people cannot afford

Vietnam with its 3,260 km of coastline spreads across seven different climatic zones, which provides appropriate conditions for mangrove development However, consistent work has been piloted to plant and protect mangroves by mass organizations such as the Vietnamese Red Cross and Women’s Union because the expansion of the aquaculture industry was the main cause of mangrove loss in the 1990s (Jhaveri, 2017) It is forecasted that in the coming period, the management of forest protection and development in Vietnam faces many challenges such as impacts of climate change, sea level rise, salinity intrusion and extreme weather which are the risk of degrading forest ecosystems and biodiversity resources; The increase in population density and the demand for land for socio-economic development in Vietnam at a rapid pace put pressure on forest protection and development and monitoring of forest changes

Today, the Vietnam Government recognizes the importance of mangrove and other coastal forests including promoting adaptation, mitigation, and resilience in the face of climate change by reducing flooding, stabilizing coastlines, securing a range of coastal livelihood options, sustaining ecosystem services, increasing biodiversity conservation, and supporting carbon sequestration In response, the Vietnam government has recently been developing new laws and policies such as the Law on Marine and Island Resources and Environment (LMIRE)

in 2015 and the Coastal Forests (CF) Decree No 119/2016/ND in 2016 (Jhaveri et al., 2017)

Remote sensing technology is one of those accomplishments of aerospace science are imposed widely used in many economic sectors assembly in many countries around the world (Satyanarayana et al., 2018) Potential response the use of remote sensing technology and GIS

has helped scientists and major planners have alternative options of strategies in the use, management of talent natural resources and environment (Hu et al., 2018) As a result, remote sensing and GIS are used as an effective tool in management and control close to the current forest resources (Cissell et al., 2018; Giri, 2016) To strengthen the management of land use, the identification area and purpose of land use are significant including a map of land use and land cover status Many methods of mapping land use status used GIS technology due to its high efficiency in information processing, monitoring process change, update information, land use mapping and evaluation coastal land use changes (Mohammad et al., 2017; Areendran et al., 2013) In Hai Phong City, coastal land use planning is a key step of the assessment in land use status Although every year there are reports about mangroves status, most of the owners report based on drawing, mapping by raditional rudimentary methods, that is one complicated work, hard work and insistence ask a lot of time (Dat & Yoshino, 2011 & 2015) Furthermore, the construction of mangrove forest map requires high accuracy and up-to-date information Therefore, application of remote sensing images combined with geographic information system

to build a map of mangrove forest change will help local authorities to manage coastal mangrove forest effectively and efficiently Firstly, assess the current status and management scheme in coastal mangroves in Hai Phong City Secondly, the study evaluated the mangrove area change in the given period, finally, from which to propose solutions to raise highly effective mangrove forest management Starting from that the practical significance and

scientific, I built the study: “Monitoring changes in coastal mangrove extents using

multi-temporal satellite data in Hai Phong, Vietnam from 2000-March2018.”

CHAPTER II LITERATURE REVIEW 2.1 GIS AND SATTELITE LANDSAT IMAGE

2.1.1 Concept of GIS, remote sensing and GPS

GIS (Geographic Information System): An organized collection of computer hardware,

software, geographic data and personnel to efficiently capture, store, update, manipulate, analyze and display all forms of geographically referenced information about areas of the Earth (Dangermond, 1990)

Remote sensing: the use of satellite- or aircraft-based sensor technologies to detect and

classify information about an object or phenomenon without making physical contact with the object and thus in contrast to on-site observation and used in numerous fields, including geography, land surveying and most Earth Science disciplines (Lillesand et al., 2014)

GPS (Global Positioning System): is a satellite-based radio navigation system global

navigation satellite system that provides geo-location and time information to a GPS receiver anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites (Hofmann-Wellenhof et al., 2012)

NDVI (normalized Difference Vegetation Index): an indication of whether the density of

the vegetation from the reflectance infrared plant or not NDVI is based on the principle of spectral difference that based on strong vegetation absorbance in the red and strong reflectance

in the near-infrared part of the electromagnetic spectrum (Satapathy, 2007)

Supervised Classification method (SCM): Supervised classification required the analyst

to select training samples from the data which represented the themes to be classified (Jensen & Lulla, 1987) The training sites were geographical areas previously identified using ground-truth to represent a specific thematic class (Brewer, 2012) Then the statistics of the Digital Number (DN) associated with the training sites are used to classify each pixel in the satellite

imagery into the corresponding land use and land cover classes Several algorithms of the supervised approach are available viz., Parallelepiped, Minimum Distance to Mean (MDM), maximum likelihood (ML), Mahalanobis Distance, The Jeffries–Matusita (J–M) Distance, Linear Discriminant Analysis, Spectral Angular Mapping (SAM), and Spectral Information Divergence (SID) (Kantakumar & Neelamsetti, 2015) In this study, the widely used maximum likelihood classification technique was adopted for LULC classification

Unsupervised classification method (UCM): Due to time shortage, prior knowledge is

difficult to obtain due to the influence of a complex background, various character, and images noise Therefore, unsupervised classification is of great value in remote sensing images processing (Rozenstein & Karnieli, 2011; Le Hegarat-Mascle et al., 1997)

2.1.2 Landsat and Sentinel 2 Satellite Images

Landsat is moderate spatial-resolution imagery that provides large areas of repeated data coverage at a scale that enables users to see detailed human-scale processes, such as urbanization, but not individual houses Since 1972, Landsat program satellites have collected consistent spectral imagery of the Earth’s continents and surrounding coastal regions This historical archive is unmatched in quality, detail, coverage, and length, enabling people to study many aspects of the planet and evaluate the dynamic changes caused by natural processes and human practices

There are 8 Landsat satellites Landsat 5 was launched in 1984 and holds the world record for being the longest-serving Earth-observing satellite in operation, serving for more than 29 years, until 2013 Landsat 5 was utilized for longer than expected because Landsat 6 was unable to attain orbit following launch in 1993 Landsat-5 is recognized in the Guinness World Records for the longest operating Earth observation satellite in history operating for nearly 30 years With a three-year design life, no one could have imagined its longevity a quarter of a century after Landsat-5 collected imagery for major events including Chernobyl,

the devastating tsunami in South Asia, devastating snowstorms in Quebec, the Birmingham Tornado in 1998 and deforestation in tropical regions Landsat 7 remains in orbit after having been launched on April 15, 1999 Landsat 8, the newest Landsat, was launched on February 11,

2013 As it orbits the Earth in a north-south pattern, Landsat 8 captures imagery from approximately 438 miles (705 km) above the surface of the Earth Landsat complete a full orbit

of the Earth in about 99 minutes, allowing the Landsat to achieve about 14 orbits per day The satellites make a complete coverage of the Earth every 16 days (Rosenberg, 2017)

The Landsat satellites make loops around the Earth and are constantly collecting images

of the surface through the use of a variety of sensing devices Todays, the satellite image is the best tool to help people to observe the Earth and other planets in the solar system as well as serving for research monitoring, data collection

2.2 OVERVIEW OF REMOTE SENSING APPLICATIONS

2.2.1 In the world

Land use and cover changes are the concerned issues in sustainable development and global environmental changes of many countries in the world (Son et al., 2015; Long et al., 2013; Datta & Deb, 2012; Shalaby & Tateishi, 2007) In recent years, more and more researchers have been used Geographical Information Systems (GIS) and remote sensing (RS) techniques for monitoring land use changes Nevertheless, RS data and GIS techniques have been updated in order to serve large users The Landsat satellite program (formerly called Earth Resources Technology Satellite), has a > 40 year duration and has employed the use of six satellites (Landsats 1, 2, 3, 4, 5, 7) The Landsat data archive provides the unique ability to analyze particular areas on the Earth’s surface for a > 40 year period (1972 – present) (Burnett and Blaschke, 2003) Additionally, Ozesmi and Bauer (2002) have noted that ―middle infrared Landsat TM bands provide for much of the separability between wetland types‖ (Ozesmi and Bauer, 2002)

Remote sensing refers to the acquisition of information on a given target without making contact with the target It uses the entire electromagnetic spectrum, ranging from short wavelengths (for example, ultraviolet) to long wavelengths (microwaves) (Liang, 2007) Inherently, the products or images obtained from many remote sensing devices that can be used for mapping and classification purposes are stored digitally in a raster data structure In fact, there are a number of satellite imagery products that may be of value for forestry and natural resource management purposes Each satellite system was designed to collect data

representative of the spectral reflectance of features, and to store data in grid cells that have

spatial resolutions of various sizes, depending on the data capture protocol employed Landsat data have a wide variety of uses, from the identification of vegetation and topography to the identification of spatial patterns of disturbances (Keppel et al., 2012), forest structures (Hyde et al., 2006; Rouget et al., 2003; Lim et al., 2003), and biomass (Lu, 2006) Changes over time in forest cover and fragmentation have also been estimated using Landsat data (Hansen and Loveland, 2012; Yuan et al., 2005), as have the distribution of wildlife species and their habitat (Clevenger et al., 2002) Further, Landsat data have been used to study assess wildfire severity (Johnson and Gillingham, 2004) From its humble beginning, remote sensing technology has today grown in stature to influence virtually all aspects of human endeavor and the environment Coupled with the availability of historical remote sensing (time-series) data, the overall reduction in data costs and increased spatial resolution in remote sensing data, remote sensing technology appears poised to make an even greater impact in many socioeconomic and political endeavors of mankind To realize the full potential of this mapping technology, however, it is imperative to integrate remote sensing with other related technologies that deliver geospatial data and information (Awange and Kiema, 2013)

2.2.2 In Vietnam

Along with the race development of technology, Vietnam has applied the advanced scientific technology in the management, protection and development of forest resources in general and mangrove resources in particular In which, the application of remote sensing technology in the research of solutions to protect and manage natural resources and environmental monitoring is also necessary and priorities Since then, researchers and scientists have embarked on researching remote sensing technology and its application to problems related to mangroves Mangrove forests in Hai Phong province bring a number of benefits to not only local people but also entire province and country; the researchers caused concern and have interest in the subject Specifically, Hai Hoa Nguyen et al (2013) studied the relationship

of spatial-temporal changes in fringe mangrove extent and adjacent land-use in Kien Giang coast and Thanh Son Nguyen, Xuan Thanh Bui and Thi Da Chau (2016) monitored mangrove forest changes in Can Gio Biophere Reserve using multi-temporal Landsat Data These researches mentioned the essential roles of mangrove forests and outlined the awareness of people in coastal resource management as how mangroves effect and influence of people Tien Dat Pham (2011) was also involved in topic research monitoring mangrove forest using multi-temporal satellite data in the Northern Coast including Hai Phong as the results indicated the ability to protect sea dyke as well as directly economic benefits mangroves provide In addition, the project also pointed out the dynamics of mangroves over years Moreover, many different researches using remote sensing equipment research mangrove issues such as: Thu Pham Minh and Populus (2007) conducted the project of research and application of remote sensing and GIS technology to determine status and changes of mangroves in Tra Vinh As a result shows that the selection of remote sensing and GIS technology is the optimal solution in the work of mapping the current and changed areas of mangroves Remote sensing tool allows collecting information of objects on a wide area and in a short time, accurate, fast and efficient, meeting the requirements of information synchronized

Lam-Dao et al (2011) conducted the project of application remote sensing to detect the change of land use and river bank in Mekong Delta This study indicate that based on a combination of vegetation index allow the establishment of vegetation cover map in Mekong Delta from 1973 to 2008 quickly and accurate Especially, this study used Digital Shoreline

Analysis System package to analyze trend of changes in mangroves effectively

Tran Thi et al (2014) also studied at application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau to understand the change of mangrove shorelines and distance from 1953 to 2011 The results were important in predicting changes of coastal ecosystem boundaries and enable advanced planning for specific sections of coastline, to minimize or neutralize losses, to inform provincial rehabilitation efforts and reduce

threats to coastal development and human safety

Tien Dat Pham et al (2017, 2016, 2015, 2012 and 2011) did a numerous research about mangroves in Hai Phong city with different remote sensing data such as ALOS, ALOS-2 and PALSAR Hence, these researches gave readers the amount of aboveground biomass, mangrove loss from 1989 to 2001 and gain from 2001 to 2013 then indicated the potential for use of multi-temporal LANDSAT data together with image segmentation and a GIS approach for mapping mangrove forest in the coastal zone

In general, remote sensing and GIS technology have currently been applied in a wide range of in natural resources and environmental management Satellite remote sensing data can

be used for large areas over time and thus represent an indispensable tool for mangrove forests monitoring, as coastal wetlands spread over extended and inaccessible areas However, in Vietnam few studies have used satellite data to analyze mangrove forest change in different periods, especially on the Northern coast Prior research on mangrove forest using satellite data

in Vietnam is limited and there is a lack of available data Satellite remote sensing data can be used for large areas over time and thus represents an indispensable tool for mapping mangrove forests where access for survey is limited and inconvenient (Pham and Yoshino, 2015)

CHAPTER III OBJECTIVES, CONTENTS AND METHODOLOGY 3.1 GOAL AND OBJECTIVES

Objective 3: To identify key driver dynamics in selected coastal sites of Hai Phong city during 2000- March 2018

Objective 4: To propose solutions to enhance management of coastal mangroves in the

- Temporal scope: This study intends to use remote sensing data from 2000 - March

2018, including Landsat imageries (2000, 2006, 2010) and Sentinel 2 (2016 and 2018)

- Spatial scope: The study will cover all coastal areas where mangroves are distributing and existing in Dai Hop commune belonging to Kien Thuy district, Tan Thanh commune

belonging to Duong Kinh district and Bang La, Ngoc Hai, Ngoc Xuyen communes belonging

to Do Son district of Hai Phong City as shown in Fig 3.1

Fig.3.1: Map of study sites

- Object scope: Coastal mangroves are the target of study

3.3 CONTENTS

- Investigate current status and management board of coastal mangroves in Kien Thuy,

Do Son and Duong Kinh districts, Hai Phong

- Construct the thematic maps and area changes of coastal mangroves in study regions in

5 periods: 2000 – 2006, 2006 – 2010, 2010 – 2016, 2016 - March 2018 and 2000 – March

2018

- Assess the key drivers of coastal mangrove changes in study regions using in period 2000- March 2018

- Propose possible solutions for enhancing the efficiency of coastal mangrove protection and management in study regions

3.4 METHODOLOGY

To understand and follow easily, methodology were divided as Fig.3.1 below:

Fig.3.2: An overview of methods used for monitoring mangrove extents

Data collection

GIS data,

statistic data

Remote sensing image

Data information in the field

Analyses and process

years

Solutions for coastal mangrove forests management

3.4.1 Investigate the current status and management scheme of coastal mangroves

3.4.1.1 Inheriting method

To perform this study and improve efficiency, science and inheritance of the study, study used inherited data from the previous studies about remote sensing and GIS technology, and applications of it in the study mangroves in general and the training samples for classifying coastal mangroves in particular Study selectively used multiple documents, legal documents, scientific data, essays, and projects, scientific researches in the country and abroad to accurately give information and closest to reduce the amount of information included in the study but did not diminish the quality of the research

Study use inheritance to collect data with the following information:

- The study, texts, documents, data from the agency, the sectored level, books, dissertations, projects relating to the use of remote sensing and GIS technology to study forest mangrove in Vietnam and the world

- The researching, reports, thesis relating to distribution and structure, training the sampling for classify coastal mangrove, dynamic coastal mangrove in Vietnam and the world

- The natural conditions, economic and social of study area

- Characteristics of Landsat, Sentinel 2

3.4.1.2 Field survey and sociological investigation method

In order to have base for accuracy assessment process of coastal mangrove and other purposes also, GPS points were collected in Kien Thuy, Duong Kinh and Do Son, Hai Phong

After determining the location study area, we were conducting the sampling, while also conducting sociological surveys by interviewing local government and two of Dai Hop and Bang La, inhabitants to provide the most accurate information Also through feedback and suggestions as well as the local people, subjects can take measures to help local government, forest management and people improve efficiency of forest resources mangrove areas of

research, protection and development in parallel with mining, fishing products Sociological survey form is in appendix

3.4.2 Construct the thematic maps and area changes of coastal mangroves

3.4.2.1 Landsat and Sentinel 2 Data

In the study, subject used Landsat and Sentinel satellite images as Table 3.1 to monitor,

investigate, and classify coastal mangroves and monitor fluctuation mangroves as well as their changed

Table 3.1: Landsat image collected in study

(m)

Path/Row (GRIDS)

Landsat 5 and Sentinel 2 images were downloaded from Earth Explorer Image clustering channels was collected including individual spectral channels due to needing combination and composition to easy conduct steps later

Sentinel data conclude difference bands, so combination bands are necessary for image interpretation This study combine band 2, 3, 4, 8 which represent for blue (490 nm), green (560 nm), red (665 nm), and near-infrared (842 nm), respectively

ArcTool box => Data Management tools => Raster => Raster Processing => Composite bands

After having combinative and composited image, the study area not only coastal mangrove area but also including other areas, thus need to cut separating the study area or the study coastal mangrove to study and analyses image by the study area boundary in the newspaper and photographs To make it convenience for image processing, reducing waste time for processing unnecessary area, clip need to be done and by the following step:

ArcTool box => Data Management tools => Raster => Raster Processing => Clip 3.4.2.3 Analyses and processing of remote sensing image

The number of samples are built large enough to be representative for the state of the objects and are evenly distributed throughout study area During constructingtraining samples for classifying coastal mangroves, we conducted sampling of the total 6 representing samples

of objects in the study area

3.4.2.4 Accuracy assessment

Combined with the results of field surveys, visual interpretation and comparison on Earth Explorer and ArcGIS, we constructed training samples for classifying coastal mangrovesconsisting of 6 representatively typical samples for each area of study

Using of forestry surveying experience, we chose the actual picture corresponding to each object Each sample will help the study have highly scientific results

Identifying accuracy for

All in all, study based on collected data and documents for mapping mangrove fluctuation in the study areas The Landsat be used as Landsat satellite imagery in 2000, 2006, and 2010 while Sentinel 2 was used for mapping mangrove changes in 2016 and 2018 After determining the accuracy of the maps fluctuation, the highest classification methods was chosen to map mangroves fluctuation in the study area in 2000, 2006, 2010, 2016 and 2018 by integrating two maps of two years to complete the map fluctuation study area in 5 years

3.4.3 Assessment the key driver of coastal mangrove dynamics

The data collected from the study were supplemented with further researches on the literature, which initially pointed out the main factors affecting the change in mangroves In addition, the topic also uses the information obtained from interviews with local people to find out the key drivers which support to propose solutions

3.4.4 Proposing feasible solutions for mangrove forests

To propose solutions for better management situation, this study based on the information and results of mangrove fluctuation maps and other case studies The solution was

be proposed for a better management situation, enhance quality and quantity of mangrove and especially, rising local people’s livelihood and climate change mitigation

CHAPTER IV NATURAL, SOCIO-ECONOMIC AND CULTURAL CONDITIONs 4.1 NATURAL, SOCIO-ECONOMIC AND CULTURAL CONDITIONS

The extreme points of Hai Phong city are:

North Pole is Lai Xuan Commune, Thuy Nguyen District

The West is Hiep Hoa commune, Vinh Bao district

Southern pole is Vinh Phong commune, Vinh Bao district

Dong Dong is Ngoc Hai Ward, Do Son District

4.1.1.2 Topography, climate, hydrology and natural resources

The total area of Hai Phong is 1,519 km2, including two island districts (Cat Hai and Bach Long Vi) Mountains and hills occupy 15% of the area, distributed mainly in the North,

so the northern terrain has the geological structure and shape of the midland with hills and hills; the south has a low topography and is quite flat The terrain is typical of the delta plain, which tilts to the sea, with an elevation of 0.7 to 1.7 m above sea level The sea is Cat Ba island is like the pearl of Hai Phong, a beautiful island and the biggest island population has over 360

islands, small gathering and it next to the island of Ha Long Bay Cat Ba Island is 200 m above sea level, about 100 km2, 30 nautical miles from the city More than 90 km southeast of Cat Ba Island, Bach Long Vi Island is quite flat, with plenty of white sand

Mountain hills, plain

The northern terrain of Haiphong is midland, with hills interspersed with plains and descending south to the sea This hilly area is associated with the Quang Ninh mountain system, a relic of the ancient folded foundations below, where previously there has been a small scale depression, including sandstone, shale and rock Lime of different ages is distributed

in continuous bands in the direction of North West - Southeast from mainland to the sea of two main ranges The range runs from An Lao to Do Son, spanning about 30 km northwest-southeast Ky Son - Trang Kenh and An Son - Nui Deo ranges, consisting of two branches: An Son - Nui Deo, sandstone with north west and southeast direction, including Phu Luu, Thanh Lang and Nui Deo mountains; and the Ky Son - Trang Kenh in the northwest - southeast direction with many limestone mountains

Coast and sea

Hai Phong coastline is 125 km2 long, low and fairly flat, mostly sandy mud due to 5 main river mouths to the sea In addition, Hai Phong also has Cat Ba island which is a biosphere reserve world that has beautiful beaches, white sand, blue water and Lan Ha Bay Cat

Ba is also the largest island in the Halong Bay

River

The riverside in Hai Phong is quite high, with an average density of 0.6 - 0.8 km / 1 km² The slope is quite small, flowing mainly in the north-west direction This is where all the downstream of the Thai Binh River flows into the sea, creating a fertile lowland, abundant fresh water for human life here Hai Phong has 16 main rivers spreading over the city with a total length of over 300 km, the main rivers in Hai Phong include:

Da Bac - Bach Dang River is more than 32 km long, a tributary of the Kinh Mon River

flowing to the sea at Nam Trieu estuary, which is the border between Hai Phong and Quang Ninh

The Cam River, which is 30 km long, is a branch of the Kinh Mon river, flowing

through the inner city and flowing into the sea at Cam gate

Lach Tray River is 45 km long, is a branch of Kinh Thay River, from the canal to the

sea by Lach Tray through Kien An, An Hai and the inner city

Van Uc, 35 km long, flowing from Qui Cao, pours into the sea through the mouth of the Van

Australian River, forming the boundary between the two districts of An Lao and Tien Lang

Thai Binh River is part of the border between Hai Phong and Thai Binh

Bach Dang River is the boundary between Hai Phong and Quang Ninh

There are also other small rivers located in the of Hong Bang city

Weather

Weather is characterized by the weather in northern Vietnam: hot and humid, heavy rain, with four seasons spring, autumn, autumn, relatively clear From November to April next year is the climate of a cold and dry winter, winter is 20.3 ° C; From May to October is the climate of summer, cool and heavy rain, the average summer temperature is about 32.5 ° C

The average rainfall ranges from 1,600 to 1,800 mm / year Due to the sea, in winter, Hai Phong is warmer than 1oC and summer is cooler than 1oC compared to Hanoi The average temperature in the year ranges from 23 ° C to 26 ° C, the hottest month (June), the temperature can reach 44 ° C and the coldest month (January) Average humidity is about 80-85%, highest in July, August, and lowest in January and December

4.1.2 Socioeconomic and cultural conditions

4.1.2.1 Economic conditions

Industrial production index increased 26.73% compared with July 2017, 7 months increased 24.17% over the same period, in which some industries have high growth rate such as

production of communication equipment, production concrete and cement products, sectors decreased compared to the same period as shipbuilding and floating structures, animal feed production

Agricultural production: The city harvested all winter-spring rice with a total area of 34,264.8 hectares, paddy yield reached 240 thousand tons, and rice yield reached 70.05 ta / ha Total cattle and poultry do not change, the elite decreased The situation of cattle herd grows steadily Total aquaculture production and capture fishery increased 13.09% over the same period

Trade and services: Total retail sales and consumer services in July increased 16.15% Export turnover increased 27.84% Import turnover increased by 21.15% Freight transport increased by 14.99% Passenger carriage increased by 14.02% Total international arrivals are estimated at 87,000

4.1.2.2 Social and cultural conditions

Hai Phong consists of 15 administrative units, including Hong Bang, Le Chan, Ngo Quyen, Kien An, Hai An, Do Son, Duong Kinh, An Duong, An Lao, Bach Long Vi Hai, Cat Hai, Kien Thuy, Tien Lang, Thuy Nguyen, Vinh Bao The population of the city is over 1,837,000, of which the urban population is over 847,000 and the rural population is over 990,000 The population density is 1,207 people / km2

Red phoenix (phoenix) flower has become the symbol of Hai Phong city for a long time For each person of Hai Phong, whether old or young, whether living in the city or living away from home, always keep in mind a red glaucous flame of the two phoenix flowers on the banks of the Tam Bac each summer French phoenix was introduced into Vietnam from the late

19th century, with ecological characteristics is beginning to bloom in the early days of summer, the phoenix season lasts about 1 month (from the beginning of May to the end June) at the beginning of the sea tourism season of Hai Phong and the liberation of the city (May 13)

Although phoenixes are grown everywhere in Vietnam, but referring to Hai Phong people are

often referred to by the poetic name of the City of red phoenix flowers

Like everywhere in Vietnam, Hai Phong is also home to festivals bearing the cultural

identity of Vietnam For instance, Tourism Festival "Do Son Beach Calling" is taken place on

April 30 to May 2 every year with many exciting activities to promote tourism in Hai Phong

Especially, Buffalo Fighting Festival is the happiest day of the festival in Do Son because the

festival brings both martial spirit of the nation, as well as a symbol of the life of Vietnamese

agriculture; buffaloes are associated with rice farming Besides, Kim village (Kim Son, Kien Thuy) on the morning of January 6, Dragon Boat Festival on Do Son Beach, Cat Ba fishing village festival, Red Flower Festival and Voi Mountain Festival in An Lao District are also the

proud of Hai Phong people

CHAPTER V RESULTS AND DISCUSSION 5.1 Current status and management scheme of mangrove forests

5.1.1 Current status of coastal mangroves in Hai Phong

Hai Phong is a coastal city that has about 152,000 ha natural area Based on the analysis

of data on the mangrove area in Hai Phong is distributed in the region 2 – sub-area 1 that concentrate in 3 coastal districts are Kien Thuy, Do Son and Duong Kinh Through the funding

of rehabilitation program and international which fund for mangrove projects such as the planting program PAM 5325, the planting mangrove program of the Red cross, the action program resoration mangrove of ACMAMG organization (Japan).etc Therefore, the coastal

mangrove in Hai Phong increased from 293 ha to over 4,700 ha (2012), mainly Soneratia Caseolaris and Kandelia Obovata Study found out areas of mangrove in three districts Kien

Thuy, Do Son and Duong Kinh that was indicated in Table 5.1

Table 5.1: Coastal mangroves in the study areas (ha)

Districts Duong Kinh Do Son Kien Thuy Total area of forest 2,695.78 376.38 1,228.30 1,091.10

Forests are classified

Source: Decision on the approval of forest inventory results of Hai Phong City (2016)

5.1.2 Management scheme of mangrove forests

As one of the localities frequently affected by typhoons, in the past years Hai Phong city has always paid attention to mangrove planting to minimize the damage caused by natural disasters The planting of mangroves in Hai Phong not only contributes to preventive measures but also helps to improve the ecological environment and alleviate poverty

According to Fig.5.1 Ministry of Natural Resources and Environment (MONRE) are

responsible for land management, mapping and issuing land certificates and have departmental offices (DONREs) at the provincial and district levels Ministry of Agriculture and Rural Development (MARD) are responsible for forest and fisheries management, planning and allocation and have departmental offices (DARDs) at the provincial and district levels Provincial, district and commune People’s Committees are represent the executive arm of the state and evaluate and approve MONRE’s and MARD’s land and forest plans In protection forest, allocated or contracted households may cut not more than 20% of the area during any one period; the harvested area must be replanted and further harvesting cannot occur until the replanted area is at least 3 years old (Decision 178/2001/QD-TTg) Commune and villages cannot be allocated or contracted forestland

Fig.5.1: Mangrove management scheme in Hai Phong City 5.2 Construct thematic maps and area dynamics of coastal mangroves during 2000- March 2018

5.2.1 Accuracy assessment

Study used NDVI, SCM and UCM to construct the thematic maps Precision of image

classification for mapping the coastal mangroves are presented in Table 5.2

Table 5.2: Accuracy assessments by using 3 classification methods

Ground-truth in Kien Thuy-Do Son Ground-truth in Do Son-Duong Kinh

Classification

Water bodies Others Total

Producer's accuracy (%)

Mangroves Water

bodies Others Total

Producer's accuracy (%)

Overall accuracy of maps which were made by NDVI was 84.47% and 84.1 %, while accuracy of unsupervised classification image and supervised classification were 80.45%, 78.45% and 74.17%, 73.85% in Kien Thuy-Do Son and Do Son-Duong Kinh, respectively

Supervised, Unsupervised classification and NDVI shown the results of 3 objects as shown above and SCM and UCM were separated into 40 classes before regroup into 3 classes but their accuracy are not high Water bodies include water and aquaculture while Mangroves and Others (which include other plants) had the same color Others reasons may be due to error when selecting the classification model or some others such as: turbulence spectrum of the image, the effects of angle photography, the shaded topography cannot be removed all of the image processing However, NDVI for classifying coastal mangroves area can be used in the analysis and image interpretation in these areas and could be applied to other similar coastal features of mangroves in Vietnam with high accuracy

In conclusion, NDVI showed the result with the highest accuracy among three methods Therefore, this study used NDVI to quantify changes in coastal mangroves in study sites Based

on field surveys and status maps, the changes in areas of coastal mangrove forests are determined

5.2.2 Thematic maps of coastal mangroves in period 2000 – March 2018

The current status of coastal mangroves in Kien Thuy, Duong Kinh and Do Son between

2000 – March 2018 was analyzed using the results of the NDVI The total areas covered by

mangroves, water bodies and others are shown in Fig 5.2 and Fig.5.3

Fig 5.3: Land use and land cover in Do Son- Duong Kinh districts from 2000 to 2018.

As shown in Fig 5.2, the mangrove areas in Kien Thuy-Do Son has increased over years

Mangrove areas in 2000 was 87.5 ha, but 337.7 ha in 2006, 426.6 ha in 2010, 513.1 ha in 2016 and 671.7 ha in March 2018 It means that mangrove area increased 250.2 ha from 2000 to 2006, 88.6 ha from 2006 to 2010, 86.8 ha from 2010 to 2016 and 158.6 ha from 2016 to March 2018 Otherwise, non-mangrove including water bodies and others was fluctuated in each period Specifically, water bodies decreased 394.9 ha from 2000 to 2006 and 247.3 ha from 2016 to

2018 The area of others, because of tide’s impact, was changed over year such as: from 2006 to

2010 the area decreased 20.7 ha but sharply increased 165 ha from 2016 to 2018

Fig.5.3 showed that the mangrove areas in Do Son-Duong Kinh have changed but slower

than Kien Thuy-Do Son Mangrove areas in 2000 was 49.5 ha, but 68.9 ha in 2006, 116.5 ha in

2010, 180.4 ha in 2016 and 173.7 ha in March 2018 It means that mangrove area just increased slightly 19.4 ha from 2000 to 2006, 47.5 ha from 2006 to 2010, highest increase was 63.9 ha from 2010 to 2016 then declined 6.6 ha from 2016 to March 2018 Besides, water bodies still kept small change in total area Others was fluctuated in each period, smallest area was 16.4 ha in

2016 while highest area was 238.6 ha in 2010

5.2.3 Dynamics of coastal mangroves during period 2000 – March 2018

Fig 5.4: Changes in coastal mangroves in Kien Thuy- Do Son districts and Do Son-Duong

Kinh districts, Hai Phong during 2000-March 2018

The Fig.5.4 showed the situation of mangroves extend in research area, and also indicated

the increase or decrease of the water area, and other factors such as land availability, the other plants in the study area

In general, mangroves have relatively small fluctuations during the period 2000 to 2018

It showed the state encourages investment in forest development and protection

(a) (b)

Fig 5.5: Fluctuation of mangroves area in (a) Kien Thuy- Do Son and (b) Do Son- Duong

Kinh during 2000-March 2018

As shown in Fig.5.5, mangroves forests increased gradually over period 2000-2016 in

both study sites However, mangrove forests areas slightly declined 6.6 ha (- 3.7 %) from

2016-2018 in Duong Kinh-Do Son while mangroves kept raising 158.6 ha (30.9 %) in Kien Thuy-Do Son It was seen that water bodies and others were pretty similar in changes in study regions

because of differences in temporal fluctuation such as Sentinel 2 image captured in 2016 when tidal came in Therefore, wetland areas belonging to others were narrow and water bodies’ areas

were expended The mangrove forest areas increased by 918.8 % between the year 2000 and

March 2018 The change statistics indicate that Hai Phong gained 708.4 hectares of mangrove

forests over eighteen years As results of land use and land cover analysis, the study delineated key drivers that caused mangroves dynamics in each period

5.3 Key drivers of coastal mangrove changes from 2000 to March 2018

Period 2000-2006: Funded by Japanese Red Cross and implemented by Vietnamese Red

Cross Society, planting of mangroves was supported in Northern provinces to increase the resilience of communities to natural disasters signed individual agreements with households participating in planting or protecting mangroves; upon evaluation of results, the provincial Red Cross chapter made direct payments to local households Mangroves were planted by NGOs, Japanese Red Cross (JRC) in period 1997-2005 (about 1616 ha) and Action for Mangrove Reforestation (ACTMANG) in period 1994-2005 (about 1202 ha) (Viet Nam Red Cross, ACTMANG and Marine Environment Research Center MERC, 2016) In dense mangrove forested areas there was no damage; however, areas converted to shrimp aquaculture from mangrove forest by local people were devastated in 2005 After 2005, people realized the significance of mangrove in protecting the dike system and their livelihood Hence, this resulted

in people planting mangroves in vulnerable areas and thus, defending against the typhoons Mangrove forests have seen a rapid development ever since and through it all thanks to community-based forest management in cooperation with local authorities (Dat and Yoshino 2013)

Period 2006-2010: In 2009, the plan for mangrove restoration and development for

2008-2015 was approved by the Prime Minister of Vietnam, set a goal to increase the area of mangrove

in Vietnam from 209,741 ha to 307,295 ha, mainly by planting 29 coastal provinces were subjected to this plan Forest contracting and allocation to local households and communities were prioritized (The Government of Vietnam, MARD, 2008)

Period 2010-2016: In 2010, The National Strategy for Environmental Protection and

Vision until 2020 set a goal of increasing overall forest cover 43% by 2010, while improving forest quality and restoring mangrove forests The strategy recommended activities to increase

mangrove areas to 80% of 1990 levels The master plan on development of the fisheries sector until 2020 and vision through 2020 had a goal of promoting sustainable extraction of aquatic products and sustainable aquaculture development across 1.4-1.5 million ha of surface water and production centers in the Red River Delta (Hawkins et al., 2010)

Period 2016-March2018: On the other hand, this period was witnessed many storms

landed Hai Phong City, Vietnam, especially in 2017 (total 20 storms and tropical depressions)

As a result, mangrove areas slightly decreased in Duong Kinh-Do Son Therefore, policy on Coastal forest management, protection, rehabilitation, and development in response to climate change were launched (Decree 119/ 2016/ ND-CP)

In general, with a series of consecutive experimental plans, strategy, decree and projects, especially planting project of Japanese Red Cross in the study areas, the areas of mangrove forest have been expanded and the quality of mangrove trees has been improved As a result, the protection function of coastal mangrove forests has been well implemented However, in some short periods, mangrove areas were reduced by the negative impacts of tropical storms Comparing quantity and quality of mangroves in Kien Thuy, Do Son and Duong Kinh districts, the study found that Kien Thuy had the largest mangrove area and local people had high awareness of mangrove forests protection and development Followed by Do Son district with quite high mangrove forest areas where local people also clearly knew about the roles and benefits of mangroves Duong Kinh district had smallest mangrove areas among 3 districts, mangroves in Duong Kinh were thin and mangrove forests and aquaculture were mixed by the people Local people are less knowledgeable about the advantages of mangroves forests

5.4 Feasible solutions to improve coastal mangrove management

On propaganda and awareness raising