MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT
VIETNAM NATIONAL UNIVERSITY OF FORESTRY

STUEDENT THESIS
MAPPING LAND COVER CHANGE OF THE COASTAL AREA
IN KIEN THUY AND DO SON DISTRICTS, HAI PHONG PROVINCE
FROM 2001 - 2016

Major: Natural Resources Management
Code: D850101
Faculty: Forest Resources and Environmental Management

Student: Ho Thi Nhu Quynh

Student ID: 1253090028

Class: K57 Natural Resources Management

Course: 2012 – 2016

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

Supervisor: Assoc. Prof. Dr. Tran Quang Bao

Ha Noi, October/2016


ACKNOWLEDGEMENTS
With the consent of Vietnam National University of Forestry belonged to Ministry of
Agriculture and Rural Development faculty, I perform the study: “Mapping land cover

change of the coastal area in Kien Thuy and Do Son Districts, Hai Phong Province from
2001 - 2016”.
With this study, I are extremely grateful for the guidance, advice and the support of
many people. First, I would like to thank most sincerely and deeply to my mentor – Assoc.
Prof. Dr. Tran Quang Bao, who gave helpful advices and strong supports during the
implementation and completion of this study. Secondly, I also would like to give a big thank
to Dr. Nguyen Hai Hoa assisted the thesis to collect data and supported for me during
fieldwork time.
The study could not be finished and achieved result without the enthusiastic
assistance, friendliness, and hospitality of the local government and residents of two
provinces Dai Hop and Bang La, I would like give a big thanks and extreme appreciation to
them.
I also would like to thanks to the teachers of Forest Resources and Environment
Management Faculty, my friends and 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.
I sincerely thank you!


ABSTRACT
Mangrove forests are among the most important and productive of ecosystems,
provide habitat for wildlife and play an important role in coastal zones, which appear in the
inter-tidal zones along the coast in the tropical and semi-tropical regions, (Wolandski, Brinson
et al, 2009; Tuan, Oanh et al, 2002). Monitoring the change of land cover, the method to
identify which area covert mangrove forest to other land covers, is the more increasingly wide
application in health of mangrove investigation. The main objective of the thesis was mapping
land cover change of coastal mangrove in study site during the period of 2001-2007 and 20072016. Compared two techniques, which are Supervised Classification and Normalized

Different Vegetation Index (NDVI), get the higher accuracy for mapping and monitoring land
cover change in study area.

NDVI has the higher precision, around 87.6% (81.6% for

Supervised Classification), which established land cover map with four classes: mangrove,
wetland, water and others (grasses, dykes, road, field and non-identified). . The 15-year
survey showed an upward trend of the percentage of mangrove area, approximately 380ha
(increased 332%) while the proportion of water and wetland area slighly declines
approximately 133ha and 179ha, respectively (declined around 43% and 46%, respectively).
There are a set of causes, in which one reason of this change is government focuses on
mangroves protecting activities and propaganda activities. So, mangroves area and quality
increases continuously and mangrove allocation policy for local people to manage, protect
and obtain benefits from these resources, which increase coastal mangrove forest area but
also. Final reason is international cooperation with developing countries such as Japan. The
main solution discussed in this study is efficient participating of the officials in management
and protection
KEY WORDS
Supervised Image Classification, NDVI, Land Cover Change, Mangrove.


TABLE OF CONTENTS

ACKNOWLEDGEMENTS
ABSTRACT
TABLE OF CONTENTS
ACRNOYMS
LIST OF TABLES
LIST OF FIGURES
INTRODUCTION ....................................................................................................... 1

OBJECTIVES, STUDY AREA AND METHODOLOGY ........................................... 4
1. OBJECTIVES.......................................................................................................... 4
2. STUDY AREA ........................................................................................................ 4
3. METHODOLOGY .................................................................................................. 5
3.1. Data Sources ......................................................................................................... 5
3.2. Field survey method .............................................................................................. 7
3.4. Monitoring the land cover change of coastal area of study area during the period
from 2010 to 2016 ..................................................................................................... 11
3.6. Sociological investigation method ....................................................................... 13
RESULTS AND DISCUSSIONS .............................................................................. 14
1. SPATIAL STRUCTURE AND DISTRIBUTION OF COASTAL MANGROVES 14
1.2 Spatial mangrove structure in Dai Hop commune, Kien Thuy district .................. 15
1.3 Spatial mangrove structure in Bang La commune, Do Son district ....................... 16
2. MAPPING LAND COVER CHANGE .................................................................. 17


4. QUANTIFICATION OF LAND COVER CHANGE DURING THE PERIOD OF
2001-2016 ................................................................................................................. 24
4.1. Monitoring land cover change ............................................................................. 24
5. MAIN KEY DRIVERS OF LAND COVER CHANGE IN HAI PHONG DURING
THE PERIOD 2001-2016 AND SOME OF POSSIBLE SOLUTIONS ...................... 30
CONCLUSION ......................................................................................................... 33
LIMITATIONS ......................................................................................................... 34
REFERENCES
APPENDIX


ACRNOYMS
GIS


Geographic International System

GPS

Geographic Position System

NDVI

Normalized Different Vegetation Index

TM

Thematic Mapper

SIC

Supervised Image Classification


LIST OF TABLES

Table 4.1: Description of land cover classification used ............................................. 18
Table 4.2: NDVI’s values of object-based classification in 2016................................ 20
Table 4.3: ASSESSING the accuracy of NDVI in 2016 ................................................ 22
Table 4.4: Assessing the accuracy of Supervised Classification in 2016 .................... 22
Table 4.5: Coastal mangrove area at Hai Phong city over time................................... 24
Table 4.6: Changing land cover area of coastal area in Hai Phong from 2001 to 2016 ...... .25


LIST OF FIGURES


Figure 1.1: : Study area: (a) Vietnam map, (b) Hai Phong province, (c) Kien Thuy and
Do Son district and coastal mangrove distribution. ...................................................... 4
Figure 3.1: Size of sample plot establishment .............................................................. 7
Figure 3.2: Flow chart of methodology for image classification and change
mappingUsing Supervised Classification and NDVI mapping land cover change in
study area in 2016. In addition, we will take the change detection, which has the
highest accuracy to monitor the land cover change over time. ...................................... 9
Figure 4.1: Spatial mangrove distribution in Hai Phong ............................................. 15
Figure 4.2: Land cover map of Hai Phong coastal area with two techniques: NDVI and
Supervised Classification. .......................................................................................... 21
Figure 4.3: Object-based classification in 2016 .......................................................... 23
Figure 4.4.1: Land cover map coastal mangroves (a) Land cover in 2001, (b) Land
cover in 2007, (c) Land cover in 2016 ........................................................................ 25
Figure 4.4.2: Mangrove change in Hai Phong during the period of 2001-2007 ........... 27
Figure 4.4.3: Mangrove change in Hai Phong during the period of 2007-2016 ........... 27
Figure 4.4.4: Mangrove change in Hai Phong during the period of 2001-2016 ........... 28
Figure 4.4.5: Chart of land cover changes during 15 year from 2001 to 2016 ............. 28
Figure 4.4.6: Land cover change in 2007 and 2016 compared to area in 2001 ............ 29


INTRODUCTION
The coastal mangrove ecosystem is one of the most productive and biologically
important ecosystems, is rich in diversity compared to all ecosystems in the world. Mangroves
is not provide seafood products and forest products but also help stabilize shorelines and
reduce the devastating impact of natural disaster and provide fresh air, limit coastal erosion,
saltwater intrusion protection, mitigate the aftermath of the storms, maintain biodiversity.
(Giri, et al 2007). However, the significantly declining of forest remains in degraded
condition (Aizpuru et al 2000; Valiela, et al, 2001). In other hand, the over-exploitation for
economic value of intact mangroves is often higher than that of shrimp farming (Balmford et

al 2002) – and remaining mangrove forest are under immense pressure from clearcutting,
encroachment, hydrological alterations, chemical spills, storms and climate change (Blasco et
al, 2001). According to the survey of MA, 2005, from 1980 to 2013, the mangrove area of the
world was lost 20-35%, Vietnam also lost 80% of the mangrove area. Lack of meaningful
information about plant health, water content, environmental stress, and other important
characteristics are the reason of forest degradation. The policy of management and protection
mangrove resources has also many lacks of linkage among sectored and studies have not
brought specific solutions and practices. Such an efficient rehabilitation of situation requires
supported by changing mangrove ecosystem research and knowledge (Walters el at, 2008).
Hai Phong is one of the coastal provinces in the East-North of Vietnam that has a
mangrove area of about 4.742 ha (in 2012) and the coastline is about 125km length. With
such natural conditions, Hai Phong is one of the provinces of our country that has the
potential development and capacity to protect mangrove resources. Doan Dinh Tam and Dinh
Thanh Giang in 2010 outlined the awareness of people in coastal resource management as
how effects and influences of people to benefit and development of mangroves. Along with
Quang Ninh, Hai Phong built the planning, restoration and development the mangrove to

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promote people’s participation in the protection the mangrove. Besides that, some pilot
programs that were carried out in the local people. However with advantages, it seem to
having some disadvantages that are unresolved. While a long coastline and the mangrove area
that distribute along the coastline is very convenient for the development of marine economy,
the management is very difficult in the development and protection of the coastal mangrove
resources in Hai Phong.
With the widen application of remote sensing technology widely in people‘s lives
today, the use of that technological applications in the scientific reasearch is also widely
applied. Change detection and vegetable indices are the application of remote sensing and
GIS technology which is a powerful tool to help human-being go deeper, discover, describe,

identify, supervise and assess the natural resources problems and health in coastal mangrove.
Various fields have successfully applied the remote sensing technology to fully exploit their
advantages such as mapping, surveying the land, forest, environmental management, census,
survey and assess the forest, forest classification investigation, land use-cover change, etc. For
example, agricultural change in Nigeria using a combination of post classification comparison
and spectral comparisons between two multispectral scanner images of Pilon et al, 1988, or
Castellana et al (2007) showed a new approach to perform change detection analysis based on
a combination of supervised and unsupervised techniques. Especially in recent years, the
remote sensing technology has been a powerful application in the study of issues relate to
mangroves such as the mapping of status, investigating the change in forest, assessment study
the mangrove environment, forest classification survey. For example, Nguyen Hai Hoa et al
(2013) assessed spatial-temporal changes in the extent and width - change in adjacent land
use, fringe mangroves in Kien Giang Province. Or, Hanh Tran et al (2015) performed a study
to assess the spatio-temporal dynamics of land use-cover change in a coastal area of Ca Mau
Province. However the research application of remote sensing and GIS technology to sudy

2


about mangrove is quite less and the content is not copious, especially using change detection
and vegetable indices have not quite applied in this case. Moreover, the study of mapping land
use-cover change of coastal mangroves in Hai Phong have not been noticed much that it has
practical significance, be scientifical with the development, protection and management of
mangrove resource. Starting from that the practical significance and scientific, thesis built the
study: “Mapping land cover change of the coastal area in Kien Thuy and Do Son Districts,
Hai Phong Province from 2001 - 2016”.

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OBJECTIVES, STUDY AREA AND METHODOLOGY
1. OBJECTIVES
-

Investigating spatial distribution and structure coastal mangrove in study area.

-

Quantification the land cover of coastal mangroves in Kien Thuy and Do Son

Districts, Hai Phong City during the period from 2001 to 2016..
-

Identifying the key drivers of land cover change over 15 years and proposing possible

solutions for sustainable management of coastal mangrove in study area.
2. STUDY AREA
The study area is the coastal mangrove in two communes, including Kien Thuy and Do Son
Districts, coastal mangrove mainly distribution in Hai Phong City (figure 1.1).

Figure 1.1: : Study area: (a) Vietnam map, (b) Hai Phong province, (c) Kien Thuy
and Do Son district and coastal mangrove distribution.
Hai Phong in generally and Kien Thuy and Do Son Districts in particular in the coastal
areas of Gulf of Tonkin, the climate here is characterized by a tropical monsoon climate,

4


warm and rainy. The temperature range is between 20-23 degrees Celsius, the highest is 40
degrees C, and the lowest is 5 degrees C. The average humidity is from 80% to 85% in the

highest was 100% at July, August, and September and lowest in December and May. The
average annual rainfall is 1600- 1800mm. The average number of sunshine hours in the year
is approximatedly1700 hours.
Dai Hop Commune in Kien Thuy District has the total area is 1,097.78 ha of natural,
9,492 people (2009) with mangrove area about 450 ha. The number of households is 2,675
households with the average population density over 865 people per km2. Bang La
Commune, Do Son District has natural area around 4,237.29 ha and 51,417 people (2010)
with per capita income in 2005 of $ 1,100 (27 million VND).
3. METHODOLOGY
3.1. Data Sources
To perform this study and improve efficiency, science and inheritance of the study,
thesis used data from many sources, the study about remote sensing and GIS technology,
vegetation indices, its applications in the study mangroves in general. The mapping, land
cover change for coastal mangroves, change detection and vegetation indices in particularly
such as multiple documents, legal documents, scientific data, essays, projects, scientific
research in Vietnam and abroad.
Thesis collected data with the following information:
- The study, texts, documents, data from the agency, the sectored level, books,
dissertations, projects relating to the land cover change to study forest mangrove in Vietnam
and the world.

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- The researching, reports, thesis, which related to distribution and structure, land cover
change of coastal mangrove, dynamic coastal mangrove in Hai Phong Province, Vietnam and
the world.
- The natural, economic and social conditions of study area.
Landsat Data
Thesis used Landsat satellite images to monitor, investigate, and interpret the spatial

distribution and structure and land cover change of coastal mangrove in study area.
T ABLE 3.1: Landsat image collected in study.

Year

Landsat image code

Date

Resolution

Path/Row

2001

LE71260462001128SGS00

08/05/2001

30(15) m

126/46

2007

LT51260462007121BKT02

07/06/2007

30(15)m


126/46

2016

LC81260462016114LGN00

02/06/2016

30(15) m

126/46

-

Source:

Landsat Image Processing
We downloaded Landsat image from Earth Explorer. Image clustering channels were
been collected including individual spectral channels due to needing combination and
composition to easy conduct steps later.
After having combinative and composited image, the study area is 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
newspapers and photographs.

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3.2. Field survey method

Sampling method
To conduct map of distribution and assess structure of coastal mangrove, thesis
established plots with dimensions 30x30m (900m2), the length of the parallel plots with
contour line. The sample plots were been established according to the size and the following
figure:
\

30
m

1

2

5
30
m
10
m

3

4

10
m
Figure 3.1: Size of sample plot establishment
The length of the standard plots perpendicular to the sea and far others plot at least 100
meters. The first plot was be made from the outer edge of the forest range of 20 meter.
In order to select the location of plots, firstly thesis will entirely conduct reconnaissance

study area and then use a GPS, the navigation device to determine the coordinates of each plot
represented the typical state in study area, which is be evenly distributed throughout the area.

7


The sampling plots established throughout the study area that helped investigating the
health status of the subjects of mangroves and also helped study’s interpretation of reality and
verify the accuracy of the training samples for classifying coastal mangroves later.
During the investigation, thesis established 47 represented typically plots, evenly
distributed throughout the state for basic subjects in the study area.
With 47 sample plots, we investigated the following table form on the health status of
coastal mangrove study area.
Table 3.3. Table form on the health status of coastal mangrove in the study area.

No

Species

Age
Heightunder Heighttotal DBH
(Years)
(m)
(m)
(m)

Canopy
diameter
(m)


Canopy
Coordinate Note
cover (%)

1
2
Where:
Height under (m): The height will measured using calibrated meters, approximately,
from the base to the lowest living branch and joined the tree canopy.
Tree height (H total) (m): The height will be measured using calibrated ruler,
approximately, from the base to the highest branches of the tree growth and joined the tree
canopy.
DBH (m): Diameter at breast height 1.3 m: Calculating from the base by tape to 1.3m
in struck.
Canopy diameter (m): The diameter will be measured using calibrated meters, by two
directs W-E and N-S and the largest canopy of trees.
Canopy Cover (%): Calculating by the tube had diameter 2cm and judged by the
visual eye through the investigating experience.

8


Thesis will establish 47 sample plots and investigate the status of mangroves in the
field through GPS to define coordinates of the points, synthesize the survey will, process the
data to match and put on ArcGIS to assess mapping of the healthy status of coastal mangrove
forests in the study area.
3.3. Mapping land cover change
Study mapped the land cover of coastal mangrove forest in 2016 based on Landsat 8
and figure 3.2 will illustrate this process.
Step 1


Landsat image 2001, 2007 and
2016

Data sources

Step 2

Field survey

Step 3
Supervised Classification in 2016

Mapping land
cover change

NDVI analysis in 2016

Accuracy assessment

Monitoring Dynamic

Mangrove cover map
in 2001

Mangrove cover map
in 2007

Mangrove cover map
in 2016


Land cover change
2007-2016

Land cover change
2001-2007

Figure 3.2: Flow chart of methodology for image classification and change mapping

9


Using Supervised Classification and NDVI mapping land cover change in study area in
2016. In addition, we will take the change detection, which has the highest accuracy to
monitor the land cover change over time.
Assessment accuracy of mapping
Assessment the accuracy is the comparison degree of correctness of a map or
classification with real place (Foody, 2002). There are many methods of accuracy assessment
for a map or classification. A confusion or error matrix, however, used and promoted the most
widely, which is both describe classification accuracy and characteristics errors (Foody,
2002). Therefore, to assess the accuracy of classification classes in comparing different
vegetation indices with set of data point on the field in the state forests and other objects, the
study used error matrix table. In this study, a total of 335-reference points were surveyed in
the field to serve as validation samples for mapping. After that, 102 points (more than 30% of
total point) were selected randomly for accuracy assessment with three different vegetation
indices.
The study used Kappa coefficient, a discrete multivariate technique, representing the
percentage of chance agreement (Congalton, R. G; Foody Gile.M, 2002; and Foody Gile. M,
1992). The Kappa coefficient is been calculated in following formula:


Where r is the number of rows in matrix, xii is the number of observation in row I and
column i, xi+ and x+i area the marginal totals of row I and column I, respectively, and N is the
total number of observations (Bishop et al, 1975).

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The study will base on collected data and documents for mapping land cover change
in the study area. After determining the accuracy of mapping, the thesis conducted the
thematic mapping fluctuation the study area over time.
3.4. Monitoring the land cover change of coastal area of study area during the period
from 2010 to 2016
Change detection
There are two common uses of satellite images, which are mapping land cover (image
classification) and land cover change (change detection) (Bark el at, 2010; Song el at, 2001).
This study focused on those two uses to mapping land cover change of coastal area in Hai
Phong.
Supervised Classification and Unsupervised Classification are two approaching
techniques (Bark et al, 2010; Singh, 1989), in which a supervised technique requires ground
truth points to get training sets containing information about the spectral signatures during
two dates, and another is without any additional information besides the raw images
considered (Bark et al, 2010). However, unsupervised technique has also some critical
limitations about accuracy of ground truth points (Bruzzon and Prieto, 2002). In this case, the
study performed the higher change accuracy and efficiency is supervised classification with
the most commonly maximum likelihood classification used.
Vegetation indices
Vegetation indices play an important role in monitoring variations in vegetation
(Bunkei et al, 2007). Vegetation interacts with solar radiation in a different way than other
natural materials. The measuring the different spectral variations and studying their
relationship to one another can provide meaningful information about plant health, water

content, environmental stress, and other important characteristics across the spectrum (Harris
newspaper, 2010). Combinations of the measured reflectance properties at two or more

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wavelengths reveal specific vegetation characteristics, also known as Vegetation Indices (VIs)
(Harris newspaper, 2010). It designed to enhance the vegetation signal in remotely sensed
data and provide an approximate measure of live, green vegetation amount and been widely
used for the phonologic monitoring, vegetation classification, vegetation parameters, etc.
(Huter et al,1999). Vegetation indices based upon their robustness, scientific basis, and
applicability, including RVI/SI (Ratio Vegetation Index/Simple Ratio), EVI (Enhanced
Vegetation Index), DVI (Difference Vegetation Index), YVI (Yellow Vegetation Index), BVI
(Brown Vegetation Index) and NDVI (Normalized Difference Vegetation Index), and so on.
Among VIs, the NDVI is an index the most commonly used by its ratio properties,
which cancel out a large figure for the noise caused by sun angles changing, topography,
clouds and shadow, and atmospheric (Brunkei, 2007). It uses 2 channels to identify areas with
no vegetation and plants because it allows an accurate representation and discrimination based
on characteristics of chlorophyll in the leaves absorb light in the visible spectrum (0.4-0.7µ),
and reflects the network light on the near-infrared spectral range (0.7-1µ) (Journal of Science
and Technology of Nghe An, 5/2014). NDVI is been calculated as follow formula:
NDVI = (NIR - RED) / (NIR + RED)
Where, as before, NIR and RED (or VIS) are the response in the near-infrared and red
(or visible) bands respectively.
The difference between the near-infrared and red (or visible) reflectance is divided by
their sum. NDVI has a range limited to a value from -1 to +1, showing clearly the distribution
of vegetation cover in the study area. It also represents the different plant groups through this
value on each plant. There will usually divide into four levels:
From negative value to zero is water;
From the value is less than 0.1 usually soil, rock, sand or snow;

From the value of approximately 0.2 to 0.5 are bushes, grass or dry fields;

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From 0.6 to 0.9 ~ 1 as trees, plants.
NDVI is widely used for the study of vegetation such as estimating crop yields, the
ability to crop, convert fields. In addition, NDVI directly related to parameters such as surface
soil layer, the photosynthesis of plants, water, biomass calculation, and so on.
After assessing land use and land cover by two techniques, the thesis used supervised
image classification and NDVI to mapping and monitoring land cover change and compare
which technique has the higher accuracy for mapping land cover change of study area in
period 2010-2016.
3.6. Sociological investigation method
After determining the location study area, conducting the sampling and sociological
surveys by interviewing local government and two of Dai Hop and Bang La inhabitants is
essential to provide the most accurate information. With population of Dai Hop and Bang La
commune is 9,491 people (4/2009) and 8,765 people (2013), respectively, we constructed
survey with 30 households and 300 people sociological survey with each commune (about
30% of population) in which almost interviewed people have directly get benefit from
mangrove coastal. In addition, through feedback and suggestions of the local people, this
study can take measures to help local government, forest managers and people improve
efficiently mangrove forest resources areas of research, protection and development in
parallel with natural resources exploitation, fishing products.
Table 3.4: Sociological survey by interviewing.
No Name Address

History of

Benefits Damages Policies Expected


Other
exploits

mangrove (1997
to now)
1
2

13

Note


RESULTS AND DISCUSSIONS

1. SPATIAL STRUCTURE AND DISTRIBUTION OF COASTAL MANGROVES
According to research of Vu Doan Thai, Effects of mangrove on coastal sediment
deposition at Bang La commune, spatial mangrove distribution is likely to represent of two
coastal populations: Kandelia obovata and Sonneratia caseolaris (L.) Engl. Mix forest,
however, is not much in natural conditions at Hai Phong city. Hai Phong has the 125km dike
length with the natural area about 152,000ha. Such as some of other coastal districts, namely
Nam Dinh, Thai Binh, Quang Ninh, Hai Phong provinces is one of the local that has much
patential with tidal flats and mangroves.
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 4 districts and 3 counties coastal are Kien Thuy, Thuy
Nguyen, Tien Lang, Cat Hai, Do Son, Duong Kinh, Hai An. Through the funding of
international rehabilitation program for mangrove projects, namely the plsanting program
PAM 5325, the planting mangrove program of the Red Cross, the action program restoration
mangrove of ACMAMG organization (Japan). Through the field survey with transect line and

the using of Landsat 8 satellite images, the spatially ecological distribution of mangrove in
two provinces Dai Hop and Bang La, mangrove species compositions that are quite simply,
namely Kandelia obovata, Soneratia caseolaris, Bruguirea gymnorrhiza, Aegiceras
corniculatum, Acanthus Ebracteatus that is indicated in Fig 4.1

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Figure 4.1: Spatial mangrove distribution in Hai Phong
According to the result of study in spatial distribution at Bang La and Do Son commune
absolutely same with above hypothesis about spatial mangrove distribution of Dr. Thai.
1.2 Spatial mangrove structure in Dai Hop commune, Kien Thuy district
With 12km length of study area, the area of mangrove measured by ArcMap is 92.27ha,
the result of field survey showed the represent of two species: Kandelia obovate and Sonneratia
caseolaris. Combination of further field survey, interview and found data sources, mangroves in
2 areas have been planted since 1999 and regeneration layer has had a lot, mostly grown closely
sea dikes but majority is Kandelia obovata species at that time of study (7/2014).
Canopy diameter: The canopy diameter in average of Sonneratia caseolaris species is
largest going up 4.9m. In the forest stand, some Sonnereratia caseolaris trees have diameter
more than 7m. The canopy diameter average of Kandelia obovata species is 1.4m, in average.
Canopy cover: that shows a multipurpose ecological indicator which is useful for
distinguishing different plant, estimating functional variables, being a intermediate stage in
distinguishing the signals reflected from forest canopy and forest floor, and so on (Korhonen,
2006). At Dai Hop commune, Kien Thuy district, Kandelia obovate species was planted at a
density rate of 0.6m x 0.6m, spacing evenly trees, according to the mangrove plantation

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program in 1999. After field survey indicated that canopy cover of coastal mangrove was

nearly 87% in study sites and stretched over 410ha from 650m to 720m width toward the sea.
1.3 Spatial mangrove structure in Bang La commune, Do Son district
This study illustrated some of coastal mangrove species at Bang La commune, Do Son
district including Sonneratia caseolaris, Kandelia obovata, Bruguiera gymnorrhiza,
Avicennia marina, Acanthus ebracteatus. Two main species, however, with largest density in
study area are Sonneratia caseolaris and Kandelia obovata, where distributed along the dike
and the same mangrove plantation program in 1999.
Canopy diameter: As the result of study, the canopy diameter in average of Sonneratia
caseolaris species is largest, the same figure for Dai Hop commune 4.9m. In the forest stand,
some trees have diameter more than 7m. The canopy diameter average of Kandelia obovata
species and Bruguiera gymnorrhiza species is 1.4m and 1.9m, respectively. The lowest is
Avicennia marina species and Acanthus ebracteatus species, 0.9m and 0.2m respectively.
Canopy cover: Mangrove species at Bang La commune ranges from 90% to 95%.
In here Sonneratia caseolaris species has outstanding height so it is planted near the
sea to reduce the flow rate, especially in flood conditions. To get more information and easy
to following this contents, we put a table of 335 points in Appendix that have specific
characteristics and coordinate of those points.
In generally, spatial distribution and structure of coastal mangrove in the study is
divided into three stable parts, the common tree is Kandelia obovata, Sonneratia caseolaris,
Bruguirea gymnorrhiza that has a significantly effect in protect the sea dikes, livelihood with
local people, reducing the strong velocity, limiting the sediment transports, enhancing
deposition and sedimentation.

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2. MAPPING LAND COVER CHANGE
With an area of mangroves (2016) measured in ArcMap is 379.17 hectares.
The study chose four land cover classes to identify classify image, including
mangrove, water, wetland and others (Grass, Rice field, Drain, Dyke, Fish Farming, Nonidentified). Those chosen classes are represented in Table 4.1.


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