An estimate of plant biomass and assessment of the ecological balance capacity of the Hanoi green corridor.pdf

1. VIETNAM NATIONAL UNIVERSITY, HANOI
VIETNAM JAPAN UNIVERSITY
HOANG DINH VIET
AN ESTIMATE OF PLANT BIOMASS
AND ASSESSMENT OF THE
ECOLOGICAL BALANCE CAPACITY OF
THE HANOI GREEN CORRIDOR
MASTER’S THESIS
Hanoi, 2019

2. ANNEX two. LIST OF FORMS FOR MANAGEME
VIETNAM NATIONAL UNIVERSITY, HANOI
VIETNAM JAPAN UNIVERSITY
HOANG DINH VIET
AN ESTIMATE OF PLANT BIOMASS
AND ASSESSMENT OF THE
ECOLOGICAL BALANCE CAPACITY OF
THE HANOI GREEN CORRIDOR
MAJOR: MASTER IN INFRASTRUCTURE ENGINEERING
CODE:
Dr. LE QUYNH CHI
Hanoi, 2019

3. i
TABLE OF CONTENTS
TABLE OF CONTENTS.................................................................................i
LIST OF FIGURES .......................................................................................iv
LIST OF TABLES .......................................................................................... v
LIST OF ABBREVIATIONS .......................................................................vi
ACKNOWLEDGMENT...............................................................................vii
INTRODUCTION........................................................................................... 1
1. The necessity of the research topic ................................................... 1
2. Contributions and objectives of the thesis.......................................... 4
3. Methodology......................................................................................... 5
4. Thesis’s structure................................................................................. 5
5. Terms and concepts ............................................................................. 5
5.1. The concepts of Green space, Green corridor, Greenbelt are
recognized by the world.............................................................................. 5
5.2. Concept of GS, GC, GB according to the Master Plan of Hanoi
Capital in 2011 ........................................................................................... 6
5.3. Concept of plant biomass..................................................................... 7
CHAPTER 1: LITERATURE REVIEW ......................................................... 8
1.1. Overview and assessing the effectiveness of the green space
models outside urban centers in the world................................................ 8
1.1.1. London’s metropolitan greenbelt, Britain.................................... 8
1.1.2. Beijing area’s Greenbelt, China .................................................. 9
1.1.3. Seoul’s greenbelt, Korea ............................................................11
1.1.4. Tokyo’s greenbelt, Japan............................................................12
1.2. Overview of research related to the topic ......................................15
1.2.1. The role of carbon pools in climate change mitigation .............15
1.2.2. Studies on estimating urban plant biomass................................17
1.2.3. Studies on biomass estimation using remote sensing data.........21
CHAPTER 2: METHODOLOGY AND DATABASE..................................22
2.1. Research content .................................................................................22

4. ii
2.2. Methodologies......................................................................................22
2.2.1. Perspective anh methodologies ......................................................22
2.2.1.1. Perspective on environmental science......................................22
2.2.1.2. Perspective on biomass research and ground carbon
accumulation based on satellite image data. ........................................22
2.2.1.3. The theoretical basis of LiDAR ................................................23
2.2.2. Research method diagram. .............................................................25
2.3. Process of calculation .......................................................................26
2.3.1. Site description ...........................................................................26
2.3.2. Data sources of satellite image.......................................................27
2.3.2.1. Landsat 8 satellite images data ................................................27
2.3.2.2. LiDAR data products................................................................29
2.3.2. Identification of green corridor vegetation using GIS...............30
2.3.3. Segments canopy according base on height...................................32
2.3.4. Plant biomass estimate base on height of canopy ..........................33
2.2. Methodology and sources of greenhouse gas inventory data .........34
2.3. Land use/land cover (LULC) of Hanoi’ Green Corridor ...............35
CHAPTER 3: FIDDING AND DISCUSSION...............................................37
3.1. Fidding .................................................................................................37
3.1.1. Results of estimate plant biomass in Hanoi Green Corridor (No
consider land use change) ........................................................................37
3.1.2. Change in LULC of Hanoi’s Green Corridor.................................39
3.2. Discussion ..........................................................................................42
3.2.1. Assess the 𝐶𝑂2 balance capacity in the air of Green Corridor
Hanoi 42
3.2.1.1. Results of estimating 𝐶𝑂2 absorption capacity of GC
compared to total of Hanoi 𝐶𝑂2 emission. ...........................................42
3.2.1.2. Comparison of 𝐶𝑂2 absorption capacity of Hanoi GC with
similar models in the world. ..................................................................42
3.2.2. Enhance the ecological balance ability of the Green Corridor in
Hanoi. 43

5. iii
3.2.3. Assess the ecological balance of the Green Corridor in the future
44
CHAPTER 4: CONCLUSION AND RECOMMENDATIONS....................46
4.1. Conclusion............................................................................................46
4.1.1. Thesis’s structure............................................................................46
4.1.2. Limitations of thesis........................................................................47
4.1.2.1. Methodology.............................................................................47
4.1.2.2. Database....................................................................................47
4.2. Recommendations...............................................................................48
REFERENCES..............................................................................................50

6. iv
LIST OF FIGURES
Fig 1: Green Corridor Functional Map............................................................ 4
Fig 1.1: London’s metropolitan greenbelt........................................................ 8
Fig 1.2 a, b: Beijing’s green belt (a), Beijing’s green belt in phase II...........10
Fig 1.3: Seoul’s greenbelt...............................................................................11
Fig 1.4 a, b: Tokyo’s greenbelt in planning project 1958 (a), Tokyo’s green
space in planning project 1968........................................................................13
Fig 1.5: Carbon Cycle.....................................................................................17
Fig 2.1: LiDAR working principle..................................................................24
Fig 2.2. Products of LiDAR technology..........................................................25
Fig 2.3. Research method diagram.................................................................26
Fig 2.4: Location of the Green Corridor in Hanoi.........................................27
Fig 2.5: Landsat 8 images were taken on June 4, 2016 .................................29
Fig 2.6: nDSM model in the Green Corridor area.........................................30
Fig 2.7 a,b,c: NDVI map 2015, 2016, 2019....................................................31
Fig 3.1 a,b: Biomass map of Hanoi’s Green Corridor in 2015, 2016 ...........39
Fig 3.2 a,b,c : Change in LULC of Hanoi’s Green Corridor in 2015, 2016,
2019.................................................................................................................41
Fig 3.3: Change in LULC of Hanoi’s Green Corridor in 2015, 2016, 2019
diagram. ..........................................................................................................44
Fig 3.4: Relationship between propotion of tree land and amount of 𝐶𝑂2
absorption........................................................................................................45
Fig 4.1: Compare biomass estimation results by using satellite images of
different resolutions. .......................................................................................48

7. v
LIST OF TABLES
Table 1.1: The goal of developing GS outside urban centers in some cities in
the world..........................................................................................................14
Table 1.2: location and scale of green space outside urban centers in some
cities in the world............................................................................................15
Table 2.1: Landsat 8 images used in the thesis ..............................................28
Table 2.2: Statistics of total pixels for each type of tree in the GC area in
2015.................................................................................................................32
Table 2.3: Statistics of total pixels for each type of tree in the GC area in
2016.................................................................................................................33
Table 2.4: Statistics of total pixels for each type of tree in the GC area in
2019.................................................................................................................33
Table 2.5: Statistics on 𝐶𝑂2 emissions of Hanoi in 2015...............................35
Table 2.6: Characteristics of land types classified by IPCC 2006.................36
Table 3.1: Biomass value estimated and 𝐶𝑂2 in 2015...................................38
Table 3.2: Biomass value estimated and 𝐶𝑂2 in 2016...................................38
Table 3.3: Biomass value estimated and 𝐶𝑂2 in 2019...................................39
Table 3.4: Summary table of LULC classification results 2015, 2016, 2019.40
Table 3.5: 𝐶𝑂2 absorption capacity in Hanoi’s GC, Seoul’s GB and Dakota’s
GS....................................................................................................................42

8. vi
LIST OF ABBREVIATIONS
WWF-World Wildlife Fund
IPCC - The Intergovernmental Panel on Climate Change
AEBIOM - European Biomass Industry Association
IPCC - The Intergovernmental Panel on Climate Change
MNRE - Ministry of Natural Resources and Environment
REDD+ - Deforestation and Forest Degradation (REDD+)
VIAP - Vietnam Institute of Architecture and Urban and Rural
Planning
USGS - United States Geological Survey
GSO- General Statistics Office of Vietnam
UHI - Urban Heat Island phenomenon
GIS - Geographic Information System
LiDAR- Light Detection and Ranging
nDSM - normalized Digital Surface Model
NDVI - Normalized Difference Vegetation Index
LULC – Land use, Land cover
GHG- Greenhouse gas
GC- Green Corridor
GS- Green space
GB- Greenbelt
C - Carbon
𝐶𝑂2 - Carbon dioxide
𝐶𝑂2e - Carbon dioxide equivalent

9. vii
ACKNOWLEDGMENT
This master thesis has conducted in February 2019. At that time, I was still
studying at Kanazawa University, Japan. After 5 months of internship in Japan,
I returned to Vietnam to complete the thesis. Under the guidance of Dr. Le
Quynh Chi, from National University of Civil Engineering (NUCE). Therefore,
I would like to express my deep gratitude and special thanks to Dr. Le Quynh
Chi for her support, giving me the necessary guidance and valuable lessons to
carry out my research. I would like to give these first lines to acknowledge her
contribution most respectfully.
I would like to send my best wishes and deepest gratitude to Professor Kato,
Tokyo University and Prof. Nguyen Dinh Duc, Vietnam National University,
Hanoi and Dr. Phan Le Binh, lecturer, JICA has long been an expert at VJU,
Dr. Nguyen Tien Dung, a lecturer for their careful and valuable support, which
is extremely valuable for my research both in theory and in practice.
Moreover, I look forward to expressing my deep gratitude to Prof. Zhenjiang
SHEN, a very talented and humble person who has only facilitated my study
and work in his Urban Planning Laboratory. I also give my sincere thanks to
the doctoral students, masters, and students at the laboratory who have helped
me a lot in knowledge that very useful fot my thesis during my internship in
Japan.
Last but least, my master thesis also a present to my parents for always being
by my side.
Sincerely,
Hoang Dinh Viet

10. viii
ABSTRACT
The Green Corridor (GC) is a new concept of the Master planning of Hanoi to
2030, vision 2050. The role of the GC is to become an urban logistics area to
preserve the landscape and ensure urban living environment. In particular,
balancing urban living environment is a very esential goal. The GC accounts
for 68% of Hanoi's natural land. The tree land in the GC is the ideal carbon sink
to assist the city reduce the nagative impact of Urban Heat Island (UHI), 𝐶𝑂2
balance in the air.
However, under the pressure of urbanization and the existence of urban,
industrial development projects and other ongoing activities . The area of trees
in the Hanoi’s GC has been declining rapidly, which reduces the ability to
absorb 𝐶𝑂2 that human activities discharge.
By applied the concept of plant biomass. This thesis provides an approach
through quantifying carbon contained in vegetation in the GC and the ability to
balance 𝐶𝑂2 in the air of GC. Combined with remote sensing images, which is
currently the strongly tool to apply for estimating biomass in large scale and
complex terrain like Hanoi city.

11. 1
INTRODUCTION
1. The necessity of the research topic
In Hanoi, Vietnam, the long-term urban development plan has been
prioritized to implement, namely the "Hanoi Master Plan to 2030, vision 2050"
which has been approved and implemented by the Vietnamese Government in
2011 with the goal of developing the city to become a sustainable capital in
Asia (Comprehensive Report; VIAP: Hanoi, Vietnam, 2011.). In the Master
Plan, Hanoi's population is expected to increase from 6.4 million in 2010 to 9.2
million in 2030. One of the main objectives of the master plan is to protect
environmental through maintaining the natural environment leads to the
establishment of a wide range of Green Space (GS) networks in the city,
including Greenbelt (GB), green buffers and Green Corridor (GC) (Trihamdani
et al, 2015). Being the 2nd
largest city in Vietnam and the first city to apply the
GC model in the capital development orientation. According to the general
planning explanation of Hanoi, the role of the Green Corridor is mentioned with
four main functions, namely:
- The Green Corridor is a functional area that supports the development
control for urban areas: The Green Corridor must create functional areas with
low and stable construction density, which is able to limit the spread of urban
development.
- The Green Corridor is an area that preserves the landscape and natural
values: Protecting the values of landscape of rivers and lakes, forest and
mountain areas.
- Green Corridor is a logistics area for Hanoi urban: providing and ensuring
food and ration for the city.
- Green corridors are an important component to help the environment
balance the urban environment: Creating an ecological environment for
people and creating biodiversity.

12. 2
In particular, the fourth function is to create an urban ecological
environment. This is a very esential task and also a general direction in
establishing the urban GS system of Hanoi.
However, difference with the GS models outside core city areas of some
developed countries, the GC model in the Hanoi’s Master Plan still has many
shortcomings, potentially threatening to break down the proposed targets.
Invasion of the GC is not only due to a large number of existing urban projects
but also the village population system with high density and many other forms
of ongoing activities. The creation of the GC or even a GB including residential
areas or natural public spaces is not enough to ensure a strong or long-term
sustainability transition (Leducq, et al, 2018). In addition, the construction of
highways through this area, including the Thang Long express to the satellite
city in Hoa Lac can lead to spontaneous urbanization along the roads. This
causes unwanted problems beyond the control of urban planners (Nghi, 2008).
On the scientific side, the GC systems have been recognized around the
world as a solution to protect biodiversity and landscape, bringing many
benefits to people (Shaw et al., Eds. 2004). The benefits of GC create large
natural areas, balance urban environment, create urban connection with
suburban areas and suburban agricultural areas. At the same time, the GC also
facilitates the establishment of strongly management policies to limit the
development of central cities, avoiding spontaneous sprawling urban expansion.
Trees play an important role in reducing urban heat island phenomenon
(UHI) by reducing the amount of 𝐶𝑂2 in urban environments (McHale et al.,
2007). Therefore, the vegetation in the Hanoi’s GC is an esential factor that
suport the "Fourth target" of Hanoi Green Corridor to promote efficiency.
However, the impacts of the green network in general and the Green Corridor
in particular to minimize the negative impacts of theUHI has not been
scientifically evaluated in the overall planning scheme (Andhang, 2015).

13. 3
Besides, Hanoi's green land fund is being seriously damaged under the pressure
of urbanization, which lead to the GC’s 𝐶𝑂2 absorption capacity less effective.
At present, there are many studies mentioning in terms of trees in Hanoi’s
GC as research on the natural framework structure of GC. However, there has
not been any quantitative research and assessment of the equilibrium role of
𝐶𝑂2 in the air of the Green Corridor. In other words, the balance capacity of
the ecological environment in terms of air.
Master thesis: "AN ESTIMATE OF PLANT BIOMASS AND
ASSESSMENT OF THE ECOLOGICAL BALANCE CAPACITY OF
THE HANOI GREEN CORRIDOR” using tools are plant biomass in the
Green Corridor area of Hanoi. The assessment of the ability to balance 𝐶𝑂2 in
the air (the amount of 𝐶𝑂2 isolated by urban trees and the amount of 𝐶𝑂2
emission into the environment through human activity) is essential factor and
a scientific basis for this study to answer the following question :
1. Does the Green Corridor's role meet the expectations in the Master plan
of Hanoi urban?
2. How has Hanoi urban development affected the Green Corridor?
3. How to enhance the effectiveness of the Green Corridor in balancing the
air environment in Hanoi urban?
Case study, scope of research
a. Case study: The above biomass of vegetation (upper part of the ground)
belong to the Hanoi Green Corridor according to the Master Plan of
Hanoi, to 2030, vision 2050 construction was approved by the Prime
Minister in 2011.
b. Scope of research: According to the general plan, this "Green Corridor"
focuses mainly from ring road 4 to Day River and Tich River, in the
districts of Phuc Tho, Dan Phuong, Thach That, Hoai Duc, Quoc Oai
and Chuong My, Thanh Oai, Ung Hoa and Phu Xuyen - adjacent to

14. 4
satellite towns such as Son Tay, Hoa Lac, Xuan Mai and Phu Xuyen.
The GC also has a part in the north of Me Linh district, the hill area of
Ham Loi mountain near Soc Son.
2. Contributions and objectives of the thesis
a. Contributions
- The estimation of biomass and 𝐶𝑂2 balance capacity in the air of the
Hanoi Green Corridor provides a scientific basis and facilitates the
adjustment of land use planning in the future. This also improve the
Fig 1: Green Corridor Functional Map
Source: Master Plan of Hanoi to 2030, vision 2050.

15. 5
ability to remove carbon in the air towards limiting the effect of UHI
effect.
b. Objectives:
- Estimated plant biomass in Hanoi Green Corridor.
- Assessing the ability to balance 𝐶𝑂2 in the air based on the ability to
absorb 𝐶𝑂2 and 𝐶𝑂2 emissions of the whole city of Hanoi.
3. Methodology
Research on the use of high-resolution satellite image data in combination with
plant biomass (an important term on environmental science now widely
applied in urban planning field) to estimate vegetation’s biomass in the Hanoi
Green Corridor area. The study also uses data on the total amount of 𝐶𝑂2
emissions to the environment of Hanoi City. From there, assess the ability of
𝐶𝑂2 balance in the air of the Green Corridor area.
4. Thesis’s structure
In addition to the contents such as: Acknowledgments, Table of Contents,
List of Tables, Images, List of abbreviations; List of references. The main
part of the thesis has the following structure.
Chapter 1: Literature review
Chapter 2: Methodology and database
Chapter 3: Finding and discussion
Chapter 4: Conclusion and recomendation
5. Terms and concepts
5.1. The concepts of Green space, Green corridor, Greenbelt are recognized
by the world
Green space (GS): The green space refers to the lands surrounded by natural
or artificial vegetation in the construction area and planning areas (George
WU, 1999). However, Bayram Cemil and Ercan Gokyer, 2012) defined GS
from another vision, taking into account human impacts on nature, GS is

16. 6
defined as the urban area where the transition occurs. Change in natural or
semi-natural ecosystems into urban space under human activities.
Green Corridor (GC): The origin of the GC planning method is introduced
with the aim of preserving and providing the continuity of urban open space,
based on Olmsted Nott's "Parkway" concept in the US and the concept "Garden
City" by Ebenezer Howard in England in the twentieth century. From the
middle of the last decade, some landscape architects have identified a very
wide green corridor as a network of linked landscape elements that bring
ecological, recreational and cultural benefits to the community (F.Ndubisi,
DMTerry, DDNiels, 1995).
Greenbelt (GB): The concept of greenbelt was popular in the 1950s. The
concept of evolution has evolved according to the stages of urban formation
and development in the world. So far, the basic definition of the GB is
understood as the following are: Open space is an open space including natural
area, agricultural and forestry land areas with low density functional areas such
as amusement parks, eco-tourism areas, heritage protection areas. Literature,
GB has the main task of preventing the expansion and lack of control of large
cities, creating urban sustainable development (Huifeng Peng, 2015).
5.2. Concept of GS, GC, GB according to the Master Plan of Hanoi Capital in
2011
According to the Decision No. 1259/QD -TTg dated July 26, 2011 of the Prime
Minister, GS, GC, GB of Hanoi capital is defined as follows:
Green space: GS in Hanoi City includes "Green Corridor, Greenbelt along
Nhue River, green buffer and urban parks".
Hanoi Green Corridor: Including "rural areas, river and lake systems, natural
forests and mountains in agricultural areas ... are strictly protected to become
urban logistics areas, preserve landscape and ensure urban living
environment, etc.”. The Hanoi Green Corridor covers the entire suburban

17. 7
area, a role that restricts the spread of the central urban area and accounts for
nearly 68% of the city's natural land area.
Hanoi Greenbelt: "The location along the Nhue river is a buffer zone between
the core city and the urban area extending south of the Red River".
5.3. Concept of plant biomass
Biomass is defined as all organic matter in the life form (also in the tree) and
dies on or under the ground (Brown, 1997). It is also the total amount of
organic matter obtained per area at a time and is calculated in tons/ha by dry
weight (Ong et al., 2004). Biomass can be defined as the total volume of live
or dead, above and under ground, expressed in tons of dry matter per unit area.
In this paper, the Green Corridor's biomass concentrates on the part of
vegetation above the ground.

18. 8
CHAPTER 1: LITERATURE REVIEW
1.1. Overview and assessing the effectiveness of the green space models
outside urban centers in the world
1.1.1. London’s metropolitan greenbelt, Britain
Development process: In 1935, GB was first proposed in a planning policy of
the London Planning Commission, including open spaces and recreational
areas; In 1955, the GB policy was established, oriented to managing and
establishing GB in other cities in the UK (Fig 1.1).
Fig 1.1: London’s metropolitan greenbelt
Source: Robert L. Gant, 2011

19. 9
Development Goals: According to the Public Policy Guide 2, GB of London
has the following objectives: Controlling the limited expansion of large cities;
Prevent neighboring towns from merging together; support in protecting
invaded rural areas; Protecting historical structures and cultural values; Support
in urban regeneration, by encouraging the use of wasteland and other urban
lands.
Location and scale: Located in suburban area and covering the center of the
city. GB area ratio accounts for 76.5% of the total natural land area.
Structure model: The GB structure covers the entire suburbs.
Functional components: Includes forest land, agricultural land, water surface,
other land construction land (parks, squares. etc.). The largest area is
agricultural land, followed by forest land and water surface.
1.1.2. Beijing area’s Greenbelt, China
Development process: The Greenbelt construction idea in Beijing was first
proposed in the Beijing Capital Region planning in 1988. However, in 1983,
the new greenbelt planning model was implemented in the planning of the
Beijing Capital Region (Huifeng Peng, 2005). The proposed type of structure
consists of two layers of greenbelt covering the central city. In 2003, the Beijing
Capital Region Planning continued to be adopted. The first GB class continued
to change to add more functionality, not only limiting the spread of central
urban development to outside cities.

20. 10
Objective: According to the GB idea in the Beijing Capital Region Planning in
1958, the goal of the GB is determined as follows: Helping to separate core
urban areas from new urban areas; Preserving areas of agricultural land, trees
and water; Control the development of urban areas according to planning and
establish urban boundaries with rural areas (Jun Yang, Zhou Jinxing, 2007).
Location and scale: The first GB is located between the fourth and fifth ring
roads, covering an area of about 140 km2; The second one is located between
the fifth and sixth ring roads, to separate central urban areas and rural areas,
with an area of about 1,620 km2, up to 1 km wide. Minimum width of GB is
about 0.5 km (Jun Yang, Zhou Jinxing, 2007).
Structure model: Is a two-layer GB form (fig 1.2 a, b). The first GB mainly
consists of 5 forest parks and 9 restricted areas, with cities functional parts such
as forests, parks, agriculture, farms, water surfaces. The second GB includes
new plantations covering many different areas such as: Areas for landscaping
a b
Fig 1.2 a, b: Beijing’s greenbelt (a), Beijing’s greenbelt in phase II.
Source: Nguyen, 2016

21. 11
(20%), ecological service areas (20%), active areas economic activity
(accounting for 60%).
1.1.3. Seoul’s greenbelt, Korea
Development process: In 1971, GB was proposed in the Seoul Master Planing.
The GB model in the Master Plan of Seoul is based on the idea of London's GB
(1935) but with additional development objectives, the function will be
appropriate to the Korean context. In 1976, the GB was redefined the boundary
and the size and area were enlarged four times. Seoul's GB has 1,566.8 km2
(accounting for 27.5% of Seoul's total land); The population living in the GB
is very low (accounting for 1.66% of Seoul's total population). In 2002, the
regional manager had to quickly develop a master plan to eliminate 123.86 km2
from the GB (Marco, 2016).
Fig 1.3: Seoul’s greenbelt
Source: Haoying Han, Haifeng Xu, 2016

22. 12
Location and scale: The ratio of the total area of urban areas accounts for 27.5%
of the total natural land area, expanding the area of the area by 4 stages. The
fourth and final phase, the total area of the GB is expanded to 247.6 km2,
surrounding the new towns of Ansan in the southwest, close to the suburbs of
Incheon, Anyang and Suwon. The final result of the four stages, the total area
of the GB is 1,566.8 km2, the farthest area of the rural up to 40 km from the
city center (David N. Bengston and Youn Yeo-Chang, 2004) (fig 1.3).
Structure model: There is a single-layer GB structure, open spaces that
surround the core city. Functional components in the Seoul GB are diverse.
Including functional areas such as: river and lake areas scattered and cut
through urban areas; Agriculture area in the year; Entertainment and tourism
areas; Forest and hill areas. In particular, forest accounts for the largest
proportion.
1.1.4. Tokyo’s greenbelt, Japan
Development process: Japan's GB development can be divided into the
following three main phases: The first period from 1932 to 1968: The definition
of GB similar to the London area plan in 1935. The urban government put the
GB concept into the Tokyo Regional Planning Project in 1958. The second
period from 1968 to 1977: The new city planning law was issued, according to
which GB has been replaced by the new concept: Area of urbanization control.
The third phase from 1977 to the present: The urban GB planning system was
established and a master plan for the park and GS was built, whereby the main
point in the stage is to build a system of "Green buffer "In some small areas
(Andre Sorensen, 2001).
Development objective: According to the Tokyo Regional plan of 1958, GB's
goals are similar as London’s GB (1935).

23. 13
Location and scale: According to the Tokyo Regional Planning proposal of
1958, Tokyo's GS consists of a large one GB area of 13,730 ha, 40 large parks
with a total area of 1,695 ha and 591 small parks with a total area of The area
is 6,741 ha (Andre Sorensen, 2001).
Structure model: There is a change of structure model from 1958 to 1968. In
the Tokyo Regional Planning proposal in 1958: One-layer GB format, is the
urban enclosed open spaces, intermingled between urban areas. In the 1968
Tokyo Area Planning Adjustment proposal: GB was adapted to a Green
Network structure, including a system of green points as urban parks (fig 1.4
a,b).
Fig 1.4 a, b: Tokyo’s greenbelt in planning project 1958 (a),
Tokyo’s green space in planning project 1968.
Source: Nguyen, 2016

24. 14
Target London Beijing Seoul
environment,
landscape
 support to protect
rural areas.
 control the
expansion of
urban
boundaries.
 prevent the
merger of
neighboring
towns.
 protect
agricultural
land, trees and
water areas.
 separating
satellite cities
and core cities
 control the
development
of urban areas
according to
the planning
and establish
boundaries
between
urban and
rural areas.
 Reserve land
for
environmental
purposes.
 Secure
agricultural
land fund.
 Restricting
Seoul urban
expansion into
neighboring
cities such as
Incheon,
Suwon and
Euijeongbu
Economy  Support urban
regeneration by
encouraging the
use of bare land
and other urban
land types
 Ensuring
balanced
growth between
Seoul and the
cities
Table 1.1: The goal of developing GS outside urban centers in
some cities in the world

25. 15
Cultural  Protect historical
and cultural
values
City London Beijing Seoul Tokyo
Location Open space
for the
entire
suburbs
The first GB
is between
ring road 4
and 5, the
second GB is
between ring
road 5 and 6
Open space
surrounds the
core urban
area
Parks
intermingled
in urban
areas
Area 4860 𝑘𝑚2
1760 𝑘𝑚2
1566,8 𝑘𝑚2
137,3 𝑘𝑚2
Ratio
compared to
the total city
area
76.5% 10.4% 27.5% 6.3%
1.2. Overview of research related to the topic
1.2.1. The role of carbon pools in climate change mitigation
Carbon dioxide is a GHG that accounts for over 50% of the GHG composition.
The increased atmosphere of 𝐶𝑂2 is mainly due to burning fossil fuels (about
80 to 85%) and deforestation worldwide (Schneider, 1989; Hamburg et al.,
Table 1.2: location and scale of green space outside urban
centers in some cities in the world
Source: Nguyen Van Tuyen, 2018

26. 16
1997). 𝐶𝑂2 in the atmosphere is estimated to increase by 2600 million tons per
year (Sedjo, 1989). Plants act as a carbon sink by producing oxygen during
photosynthesis and storing carbon in the form of biomass. The amount of
carbon stored in the tree changes over time as the plant grows, dies and decay.
𝐶𝑂2 balance in the air in urban areas has become a major challenge for
researchers and policies in efforts to resolve human-induced climate change.
Urban green trees play an important role in the global carbon cycle (fig 1.3)
because they contribute 80% of the above ground biomass, 𝐶𝑂2 or GHG
because it has a great impact on global climate change. Since 1850, people have
emitted about 480 billion tons of 𝐶𝑂2 into the atmosphere through fossil fuel
burning and changing land use. Human activity has caused an increase in
atmospheric 𝐶𝑂2 levels and disrupted the global carbon cycle. However, the
carbon nature has a mechanism to be recalled and stored in isolated carbon
pools such as forests and trees. The Intergovernmental Panel on Climate
Change (IPCC) identifies carbon pools in ecosystem biomass, namely above-
ground biomass, underground biomass, litter, wood debris and organic matter.
in the soil. Among all carbon pools, above-ground biomass accounts for the
majority. Many authors believe that carbon stocks account for 50% or 45% of
the dry biomass of parts of plants and forest ecosystems that store about 72%
of the earth's carbon weight on the earth (Malhi, 2002). According to a report
by the World Wildlife Fund (WWF) and the European Biomass Industry
Association (AEBIOM), biomass can reduce 𝐶𝑂2 emissions (the main gas that
causes global warming) by nearly 1,000 tons/year - equivalent to the annual
dispersion of Canada and Italy combined (Bauen et al., 2004). In the global
carbon cycle, the amount of carbon stored in plants is about 2.5 billion tons,
while the atmosphere only contains about 0.8 billion tons (Watson, 2000).

27. 17
In general, the researchers are interested in the increase of 𝐶𝑂2 in the
atmosphere, its effects on the environment and emphasize the role of greenery
in reducing Urban Heat Island phenomenon (UHI) . This suggests that the study
of biomass, carbon storage capacity and 𝐶𝑂2 absorption of plants is essential,
it is a scientific basis for planners and managers to assess the role of GC for
Hanoi urban environment.
1.2.2. Studies on estimating urban plant biomass.
Plant ecosystems can play an important role in mitigating the effects of climate
change by reducing carbon dioxide in the atmosphere. Liu's study (2012)
quantifies the carbon storage of urban forests and assesses the actual role of
Fig 1.5: Carbon Cycle
Source: https://ucanr.edu

28. 18
urban forests in reducing atmospheric 𝐶𝑂2 . The study introduced a case study
of urban forests in Shenyang, a strong industrialized city in northeastern China.
Carbon storage and sequestration is estimated by biomass equations, using field
survey data and urban forest data obtained from high resolution QuickBird
images. The benefit of carbon storage and sequestration is converted by
monetary values, as well as the role of urban forests in compensating for carbon
emissions from fossil fuel burning. Results showed that urban forests in
Shenyang's third ring road area stored 337,000 tons of carbon (equivalent to
13.88 million USD), with a carbon sequestration rate of 29,000 tons/year (1.19
million USD). Carbon stored by urban forests is equal to 3.02% of annual
carbon emissions from fossil fuel combustion and carbon sequestration can
offset 0.26% of annual carbon emissions in Shenyang. In addition, Liu's results
indicate that carbon storage and sequestration rates vary between urban forest
types and species composition and age structure. These results can be used to
help assess the actual role and potential of urban forests in reducing
atmospheric 𝐶𝑂2 in Shenyang. In addition, Liu has provided insight to decision
makers and the public to better understand the role of urban forests and provide
better management plans for urban forests.
According to the study of David J. Nowak on carbon storage and isolation by
urban greenery in America. Green biomass has been quantified to assess the
extent and role of urban trees related to urban heat islands. Information on
urban trees has been provided from 28 cities and 6 states to determine the
average carbon density per unit area of canopy. This information is used for
measurements of canopy cover on the study area to determine total urban forest
carbon stocks and annual quarantine by state and country. The total tree carbon
stock density is 7.69 kg C/m2 on average and the average density of 0.28 kg
C/m2/year. Total tree carbon stocks in US urban areas (2005) are estimated at

29. 19
643 million tons (worth US $ 50.5 billion; 95% CI, 597 million and 690 million
tons) and estimated annual estimates. 25.6 million tons (US $ 2.0 billion;% CI,
23.7 million to 27.4 million tons).
A study by Jo (2011) quantified carbon emissions from energy consumption
and carbon storage by GS for three cities in Korea: Chuncheon, Kangleung and
Seoul. Carbon emissions are estimated according to the guidelines for using
carbon emission factors for fossil fuels. Woody plants are the subject to
calculate the amount of carbon stored and absorbed by applying the biomass
equation and the annual growth level of the trees. Annual carbon emissions are
370 t/ha/year in Kangleung, 472 t/ha/year in Chuncheon and 264 t/ha/year in
Seoul. The average carbon stock of woody trees ranged from 26.0 to 60.1 t/ha
for natural land in the studied cities and from 4.7 to 7.2 t/ha for urban land. The
annual average carbon absorption capacity of woody trees ranges from 1.6 to
3.91 t/ha/year for natural land in the city and from 0.53 to 0.80t/ha/year for
urban land. There is no significant difference (95% confidence level) in carbon
stocks and per hectare increase in urban land between cities. Woody plants have
stored carbon equivalent to 6.0 to 59.1% of total carbon emissions in cities and
absorbed the total carbon emissions by 0.5 to 2.2% of the total annual 𝐶𝑂2
emissions. The ability of trees to store carbon in Chuncheon and Kangleung is
more efficient, where the natural land area is larger and the population density
is lower than in Seoul. Strategies to increase carbon storage and absorption by
urban green space have been explored.
Recently, in Beijing City, Yujia Tang (2016) uses data from field surveys, using
the results of tree growth and government statistics yearbook to estimate
storage capacity and carbon isolation ability of street trees in Beijing. The
results show that carbon density and carbon sequestration rate in Beijing's
urban street trees are equal to 1/3, 1/2 of the corresponding magnitude of non-

30. 20
urban forests in China. However, the total amount of streert trees carbon
sequestration in urban districts of Beijing was 3.1 ± 1.8 Gg/ year (1Gg = 10^9
g) in 2014, equivalent to only about 0,2% of annual 𝐶𝑂2 equivalent (𝐶𝑂2e)
emissions from total energy consumption show a rather limited role in offset
the overall artificial emissions in China.
In Vietnam, along with participating in the Reducing Emission from
Deforestation and Forest Degradation (REDD+) program, scientists have
conducted numerous studies to determine the amount of carbon accumulated in
ecosystems and land use types to determine the carbon quotas in reducing
emissions and obtaining financial resources from carbon-absorbing
environmental services (Ministry of Agriculture and Rural Development
(2011)). Although there have been many works, some guidelines for the
investigation and determination of national carbon stocks, studies only stop
evaluating the carbon sequestration capacity of forest land, but not much.
Determine the carbon stock of urban trees. Therefore, this study was conducted
primarily to determine the carbon stock of urban trees. Currently, the world's
new approach to climate change is to study climate change adaptation and
adaptation measures that are not only global and regional, but also focused on
violations.The local to propose measures to significantly reduce the amount of
carbon in the atmosphere by using land, using land management technology to
reduce greenhouse gases. The Pham Quoc Trung study (2018) aims to assess
the possibility of perennial trees carbon accumulation in Bo Trach district,
Quang Binh province. To accomplish that goal, the study combined the results
of classification of Landsat remote sensing images with field survey data to
determine biomass, accumulated carbon stocks of perennial trees in Bo Trach
district. Research results show that the area of perennial crops accounts for
11,362.62 ha, mainly rubber trees. The biomass and carbon stocks on the image

31. 21
of rubber trees in the standard plots have an average biomass value of 40.53
tons/ha, an average carbon value of 20.28 tons/ha.
Thus, through the studies of the authors in the world and Vietnam, the
determination of biomass and carbon stocks of urban trees is a widely applied
trend, providing scientific basis and creating cashew. favorable conditions for
the adjustment of land use planning in the future to improve the ability of
carbon accumulation in the soil to limit climate change.
1.2.3. Studies on biomass estimation using remote sensing data
High-resolution urban biomass and vegetation maps are useful tools for
planning architects and research teams seeking to minimize the impact of
urbanization and UHI effects. urban and GHG mitigation impacts.
Steve M.Ractiti (2014) applied high-resolution remote sensing images to
create an urban trees biomass map, assessing the accuracy of scales in biomass
estimation, comparing the results of achieved with lower resolution estimates
in Boston City. By method of overlapping satellite data layers (including Lidar
data on tree height estimation) and field-based observations for mapping
canopy cover and carbon storage of trees on the ground Space resolution ~ 1 m.
The coverage of the average canopy was estimated to be 25.5 ± 1.5% and the
carbon stock was 355 Gg (28.8 Mg C/ha) for the city. The study of Ractiti
(2014) proved that, the urban areas have considerable carbon stocks and recent
advances in high-resolution remote sensing have the potential to improve urban
character and vegetation management.

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CHAPTER 2: METHODOLOGY AND DATABASE
2.1. Research content
Research on biomass and carbon storage using Lansat remote sensing image
data, Lidar data and supporting software (ENVI, ArcGIS).
Creating biomass mapping, carbon accumulation of Hanoi Green Corridor by
remote sensing and GIS methods.
Create land use maps over the years by remote sensing data and GIS methods
2.2. Methodologies
2.2.1. Perspective anh methodologies
2.2.1.1. Perspective on environmental science
Based on the biology of plants to absorb 𝐶𝑂2 to produce biomass (C6H12O6)
and release oxygen through photosynthesis and only in plants can this ability.
The biomass and the amount of carbon accumulated in the reservoirs in the
trees ecosystem are organic. Therefore, biomass and carbon trees accumulation
is generally based on this principle.
2.2.1.2. Perspective on biomass research and ground carbon accumulation
based on satellite image data.
In order to support the rapid and timely calculation of biomass, many countries
in the world have conducted research to calculate the biomass reserves of
remote sensing-based vegetation such as Landsat, SPOT, AVHRR NOAA,
ALOS, ... There are many methods of estimating biomass from satellite images
through values such as radiation coefficients, reflectivity, and standardized

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indexes of different plants (The Normalized Difference Vegetation Index -
NDVI ).
NDVI is calculated based on the difference of reflected near infrared light and
red light on plants. Because the leaves reflect strongly with near-infrared
radiation, the leaves' chlorophyl strongly absorbs the red light of the radiation
in the visible region. NDVI is often used to estimate primary productivity as
well as plant biomass. as well as monitoring forests and plants. The higher the
value of NDVI (from -1 to 1), the stronger the photosynthetic activity (Rouse
et al., 1973; Gamon et al., 1995; di Bella et al., 2004).
Hanoi Green Corridor is known for its rich and diverse vegetation. Due to the
complex terrain, the calculation of biomass by manual method takes quite a
long time and is outside the scope of the master thesis. The thesis proposes a
solution using Landsat 8 satellite image with a resolution of 30m space and a
LiDAR data product with a horizontal accuracy of 100 cm and a vertical
direction of 15 cm to calculate indicators related to birth. grade level.
2.2.1.3. The theoretical basis of LiDAR
LiDAR (Light Detection And Ranging), is a term for a new, active remote
sensing technology, using lasers to survey objects remotely. The data obtained
by the system is a collection of laser reflecting point clouds from the object
being investigated. A typical LiDAR system is usually fixed on a suitable type
of aircraft. The working principle of the system is similar to other active remote
sensing systems. When the plane flies over the area under investigation, the
laser sensor will emit laser beams towards the object, the laser signal receiver
attached to the sensor will receive the reflected signal from the object. The
LiDAR system often uses scanned mirrors to examine objects in strips with the
width of the data range specified by the scanning angle of the mirror. The
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density of data points obtained depends on many factors such as plane velocity,
flight altitude, rotation level of the sweep. The distance is determined by the
calculation of laser travel time. broadcast. The received data points usually
include the parameters of the 3-dimensional position of the object (X, Y, Z)
and the response laser intensity. The precise 3-dimensional position of the
scanning device, the mirror rotation angle and the distance obtained by the set
of points will then be used to calculate the 3-dimensional position of the points
on the surface of the survey object. The LiDAR system is often attached to
navigation devices (GPS) and inertial identification devices (IMU/INS) and 1
ground locator station (GPS Base station) to collect the full calibration
parameters for data processing later. Every second of the survey, LiDAR
technology can help collect hundreds of thousands of data points with very high
accuracy, so the product made from this data set is rated to be VERY accurate.
position (X, Y, Z) (+/- several centimeters to a few dozen centimeters).
Fig 2.1: LiDAR working principle
Source: https://www.yellowscan-lidar.com

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Advantages of LiDAR remote sensing technology: With an average frequency
of 5,000 to 33,000 rays per second, the resulting data allows mapping the
topographic surface and canopy surface with a high density of data and high
precision. Some LiDAR systems also allow the reception of intermediate
feedback signals (between the start and end signals) to allow the analysis of the
object structure (canopy structure).
2.2.2. Research method diagram.
Fig 2.2. Products of LiDAR data
Source: www.yellowscan-lidar.com
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2.3. Process of calculation
2.3.1. Site description
According to the “Master Planning Project of Hanoi to 2030, the vision of
2050”. The Hanoi Green Corridor area has a total area of 68% of Hanoi's
natural land (2,273.2 km2
). Figure 2.4 depicts the location of the Green Corridor
in Hanoi.
Fig 2.3. Research method diagram.
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