Applying gis and remote sensing to determine potential distribution area of turtle in nam dong natural reserve, thanh hoa province

MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT
VIETNAM NATIONAL UNIVERSITY OF FORESTRY

STUDENT THESIS
Applying GIS and remote sensing to determine potential distribution
area of Turtle in Nam Dong Natural Reserve, Thanh Hoa province
Major: Natural Resources Management
Code: D850101
Faculty: Forest Resources and Environmental Management

Student: Ho Thu Phuong

Student ID: 1553090573

Class: K60 Natural Resources Management

Course: 2015 – 2019

Advanced Education Program

Developed in collaboration with Colorado State University, USA
Supervisor: Assoc. Prof. Tran Quang Bao
Prof. Luca Luiselli

Ha Noi, 2019


ACKNOWLEDGEMENTS

To complete this research, apart from my own efforts, I also receive a lot of
enhance and help from my teachers, organizations and individuals.

First and foremost, I have to thank my first supervisors, Assoc. Prof. Dr. Tran
Quang Bao. Without his assistance and dedicated involvement in every step
throughout the process, this research would have never been accomplished. I would
like to say thank for his support and understanding.
Also, I would like to thanks for the encouraging words, and suggestions of my
second supervisor Prof. Luca Luiselli and his team in Turtle Sanctuary
Conservation Center for supporting during getting data in field trip and writing
thesis.
My sincere thank also goes to Mr. Pham Van Thong who shed the light for
me to follow this research for my final thesis. It also thanks for your valuable
comments for the manuscript.
I sincerely thank to Vietnam National University of Forestry that has given
me an opportunity to apply the knowledge I learned from the school. I have got new
and useful experience that is helpful for my future work.
Last but not least, I would like to thank my family and my friends for
supporting and encouraging me spiritually throughout my life.
Because of the time limitation as well as my own lack of knowledge and
expertise, certainly the study still has some mistakes. Therefore, I look forward to
receiving the comments, evaluation and feedbacks of lecturers and friends to
enhance the quality of the study and improve not only my professional knowledge
but also the lack of skills in this study.
I sincerely thank all of you!

i


TABLE OF CONTENTS
Page
CHAPTER 1.

INTRODUCTION....................................................................................... 1
CHAPTER 2. LITERATURE REVIEW ........................................................................... 3
2.1. GIS and remote sensing.......................................................................................................... 3
2.1.1. The concept of GIS, remote sensing and GPS ......................................................... 3
2.1.2. Landsat image ............................................................................................................ 4
2.1.3. Status map of forest resources .................................................................................. 5
2.2. Application of remote sensing and GIS in forestry ............................................................. 6
2.2.1. In the world ................................................................................................................ 6
2.2.2. In Viet Nam .............................................................................................................. 10
2.2.3. Application of GIS and Remote sensing in determine habitat species ................ 15
CHAPTER 3. STUDY GOAL, OBJECTIVES AND METHODOLOGY ...................... 18
3.1. Goal and Objectives .............................................................................................................. 18
3.2. Scope ...................................................................................................................................... 18
3.3. Contents ................................................................................................................................. 18
3.4. Methodology .......................................................................................................................... 18
3.4.1. Investigate current status in Nam Dong Natural Reserve ................................... 18
3.4.2. Construct thematic maps of distribution of turtle by factors in Nam Dong Natural
Reserve ...................................................................................................................... 24
3.4.2.1. Collect primary data .................................................................................. 24
3.4.2.2. Construct thematic maps of distribution of turtle by factors ..................... 27
3.4.3. Conduct suitable habitat map of turtle in Nam Dong Natural Reserve ............. 28
CHAPTER 4. NATURAL, SOCIO-ECONOMIC CONDITIONS ................................. 29
4.1. Natural condition .................................................................................................................. 29
4.1.1. Geographical location .............................................................................................. 29
4.1.2. Topography, geomorphology .................................................................................. 30
4.1.3. Climate and hydrology ............................................................................................ 30
4.1.3.1. Climate ....................................................................................................... 30
4.1.3.2. Hydrology .................................................................................................. 30
4.1.3.3. Land ........................................................................................................... 30
4.2. Basic characteristics of forest resources ............................................................................. 31

4.2.1. Current status of land, forest resources................................................................. 31
4.2.2. Forest status and distribution by functional subdivisions ................................... 32
4.2.3. Forest type of reservation........................................................................................ 33
4.3. People's living conditions, socio-economic.......................................................................... 34
4.3.1. Economic .................................................................................................................. 34
4.3.1.1. Agricultural production ............................................................................. 34
4.3.1.2. Industry, small industry, trade, services .................................................... 35
4.3.1.3. Natural Resources – Environment ............................................................. 35
4.3.2. Culture, society, infrastructure .............................................................................. 35

ii


4.3.2.1. Education, medical .................................................................................... 35
4.3.2.2. Population and labor ................................................................................. 35

CHAPTER 5. RESULTS AND DISCUSSIONS .............................................................. 38
5.1. Current status and flora, fauna composition in Nam Dong Natural Reserve ................. 38
5.1.1. Flora .......................................................................................................................... 38
5.1.2. Fauna ........................................................................................................................ 40
5.1.2.1. Mammalia .................................................................................................. 40
5.1.2.2. Aves ............................................................................................................ 41
5.1.2.3. Reptilia and Amphibia ............................................................................... 42
5.2. Vegetation map, elevation and river system of Nam Dong Natural Reserve .................. 43
5.2.1. Vegetation cover map .............................................................................................. 43
5.2.2. Elevation level map .................................................................................................. 46
5.2.3. River system map ..................................................................................................... 48
5.3. Distribution of turtles by factors ......................................................................................... 49
5.3.1. General distribution of turtles ................................................................................ 49
5.3.2. Distribution of Turtle by vegetation cover ............................................................ 50

5.3.2.1. General distribution by vegetation cover................................................... 50
5.3.2.2. Distribution of each species by vegetation ................................................ 52
5.3.3. Distribution of Turtle by elevation level ................................................................ 53
5.3.3.1. General distribution by elevation level ...................................................... 53
5.3.3.2. Distribution of each species by elevation level .......................................... 55
5.3.4. Distribution of Turtle by river system ................................................................... 56
5.3.4.1. General distribution by river system .......................................................... 56
5.3.4.2. Distribution of each species by river system .............................................. 57
5.4. The suitable habitat map of turtle in Nam Dong Natural Reserve .................................. 58
5.4.1. Suitable habitat map for turtle ............................................................................... 58
5.4.2. Cuora mouhotii ........................................................................................................ 60
5.4.3. Geoemyda spengleri ................................................................................................. 62
5.4.4. Cuora galbinifrons ................................................................................................... 64
5.4.5. Platysternon megacephalum ................................................................................... 66
CHAPTER 6. CONCLUSION, LIMITATIONS AND RECOMMENDATIONS ......... 69
6.1. Conclusion ............................................................................................................................. 69
6.2. Limitations............................................................................................................................. 71
6.3. Recommendationa ................................................................................................................ 71
REFERENCES .................................................................................................................... 72
APPENDIX

iii


LIST OF FIGURE
Page
Fig 3.1. Steps to build the current status map in the study area ...................................................... 20
Fig 3.2. Transect method .................................................................................................................. 25
Fig 3.3. Map of survey transects in Nam Dong Natural Reserveand surroundings ........................ 27
Fig 3.4. Process create maps of habitat suitability of turtle in Nam Dong Natural Reserve ........... 28

Fig 4.1. Map of geographical location of Nam Dong Natural Reserve ........................................... 29
Fig 4.2. Current status map of Special-use Forest Nam Don Natural Reserve ............................... 33
Fig 5.1. Current status of vegetation cover in Nam Dong Natural Reserve .................................... 39
Fig 5.2. Flowchart of establishing vegetation cover map of Nam Dong Natural Reserve............... 44
Fig 5.3. Current status map of vegetation cover of Nam Dong Natural Reserve 2019.................... 45
Fig 5.4. Current status map of elevation level of Nam Dong Natural Reserve ................................ 47
Fig 5.5. Flowchart of establishing river system map of Nam Dong Natural Reserve ...................... 48
Fig 5.6. Current status map of river system of Nam Dong Natural Reserve.................................... 49
Fig 5.7. Map of distribution of turtle by vegetation cover in the study area .................................... 51
Fig 5.8. Map of distribution of each species by vegetation cover .................................................... 52
Fig 5.9. Map of distribution of the various turtle species by elevation level in the study area ........ 54
Fig 5.10. Map of distribution of each species by elevation level ..................................................... 55
Fig 5.11. Map of distribution of turtle by river system in the study area ......................................... 56
Fig 5.12. Map of distribution of each species by river system ......................................................... 57
Fig 5.13. Process to create suitable habitat map for turtle in the study area .................................. 59
Fig 5.14. Suitable habitat map for turtle in the study area .............................................................. 60
Fig 5.15. Process to create suitable habitat map for Cuora mouhotii ............................................. 61
Fig 5.16. Suitable habitat map for Cuora mouhotii ......................................................................... 61
Fig 5.17. Process to create suitable habitat map for Geoemyda spengleri ..................................... 63
Fig 5.18. Suitable habitat map for Geoemyda spengleri .................................................................. 63
Fig 5.19. Process to create suitable habitat map for Cuora galbinifrons........................................ 65
Fig 5.20. Suitable habitat map for Cuora galbinifrons .................................................................... 65
Fig 5.21. Process to create suitable habitat map for Platysternon megacephalum ......................... 67
Fig 5.22. Suitable habitat map for Platysternon megacephalum ..................................................... 67

iv


LIST OF TABLE
Page

Table 2.1. Sensor characteristics of Landsat 7 and Landsat 8 satellite image .................................. 5
Table 3.1. Satellite image ................................................................................................................. 19
Table 3.2. Field data sheet used to collect information ................................................................... 26
Table 3.3. The total length of ten transects ...................................................................................... 26
Table 4.1. Current forest status in Nam Dong Natural Reserve ...................................................... 32
Table 4.2. Land use area of communes in the buffer zone of the Natural Reserve .......................... 34
Table 4.3. Summary of population and labor of communes in the buffer zone of Natural Reserve . 36
Table 4.4. Population statistics of villages adjacent to the Natural Reserve ................................... 36
Table 5.1. Vegetation ecosystem in Nam Dong Natural Reserve ..................................................... 38
Table 5.2. The proportion of distribution of vegetation cover in study area.................................... 45
Table 5.3. Accuracy assessment of NDVI method and field trip ...................................................... 46
Table 5.4. The proportion of distribution of elevation level in study area ....................................... 47
Table 5.5. The proportion of Turtle distribution in study area ........................................................ 50
Table 5.6. The proportion of Turtle individuals observed by vegetation cover in the study area .... 51
Table 5.7. The proportion of turtle individual distribution by elevation level in study area ........... 54
Table 5.8. The proportion of suitable habitat area for turtle in the study area ............................... 60
Table 5.9. The proportion of suitable habitat area for Cuora mouhotii .......................................... 62
Table 5.10. The proportion of suitable habitat area for Geoemyda spengleri ................................. 64
Table 5.11. The proportion of suitable habitat area for Cuora galbinifrons ................................... 66
Table 5.12. The proportion of suitable habitat area for Platysternon megacephalum .................... 68

v


CHAPTER 1
CHAPTER 1. INTRODUCTION
Tropical and subtropical forests are among the most important environments
on Earth, as they house among the richest communities of animals and plants in the
terrestrial ecosystems. Tropical and subtropical forests play an important role in
human’s life and environment. Forests provide wood, firewood; provide oxygen;

regulate water and are the place where animals live; forests also contain many
valuable and rare species of mammals, birds, reptiles, amphibians and invertebrates.
Terrestrial turtles and tortoises are among these species.
The Socialist Republic of Vietnam is ranked 9th among the most biodiverse
countries of the world in terms of turtle species richness with a total of 32 species,
27 being freshwater and terrestrial and 5 being marine (Dijk et al., 2014).
Unfortunately, the conservation status of the Vietnamese turtle fauna is threatened
as 85.1% of the native freshwater and terrestrial taxa are currently listed as
Threatened in the IUCN Red List (IUCN, 2018). For most species, habitat loss and
overhunting (for consumption as human food, traditional medicine, religious merit)
have been the main threats (Stanford et al., 2018). Indeed, the forest cover in
Vietnam has decreased from 43% to 36% from 1945-1990 (De Jong & Hung,
2006), although the country’s forest cover has been recently increased due to the
national-scale reforestation of Vietnam since 1992 that is assumed to contribute to
this recovery, the forest quality still remains poor (Meyfroidt & Lambin, 2009).
Indeed, the recovery of forest coverage was due in part to the ban of industrial
logging from natural areas and the displacement of wood extraction to neighboring
countries, but mainly to extensive programs of homogenous tree plantations
(Meyfroidt & Lambin, 2009). These plantation habitats are clearly unsuitable for
turtles, whereas the suitable remnant natural forest is still heavily fragmented and
isolated (Fox et al., 2004). The second main threat to Vietnamese turtles is trade for
domestic consumption, with massive numbers of individuals being exploited in the
1980s- 2000s (Van Dijk et al., 2000; Nijman, 2010) also to supply the food and
traditional medicine markets of China (Cheung and Dudgeon, 2006; Turtle
Conservation Fund, 2002).
1


According to IUCN (2018) assessments, the populations of most Vietnamese
turtle species have declined by about 50-90%. The Black-breasted leaf turtle

(Geoemyda spengleri) is one of main targets of this study. To protect the turtle and
also forest, the world in general and Vietnam in particular, there are many laws,
circulars and decrees. Moreover, to carry out these Legal instruments effectively,
we would need support arising from technology.
Nowadays, the development of science and technology as well as technical
science, in particular, the advent of satellite imagery and GIS remote sensing
technology supported people to make a lot in research. Remote sensing data with
multi-time, multi-spectral and wide-area coverage allows us to update research
information quickly, effectively for saving time and effort. The combination of
using high-resolution remote sensing images in resource management has been a
new direction for natural resources planning in general.
Nam Dong Natural Reserve is a protected area in the central of Vietnam.
The area of this natural reserve is 646,95 ha. The area is one of the typical forest
ecosystems on limestone that still remaining in the northern lowlands of Vietnam,
which harbors a high level of the endemic and rare fauna and flora. According to
the evidence of the result of investigation, there are 18 species of animal that
reported in Vietnam Redlist and Red Data Book, 2007 and IUCN Red List of
Threatened Species, 2012.
Recently, with the development of remote sensing and image interpretation
technology, that enable users to capture, store, analyse and manage spatially
referenced data of the different objects in the Earth surface. Especially, the remote
sensing technology has been a powerful application in distribution of turtle.
Moreover, the management have not been noticed that it has practical significance,
be scientifically with the development, protection and management of protection
turtle. Therefore, I conducted the present study entitled: “Applying GIS and
remote sensing to determine potential distribution area of Turtle in Nam Dong
Natural Reserve, Thanh Hoa province”.

2

CHAPTER 2
CHAPTER 2. LITERATURE REVIEW
2.1.

GIS and remote sensing

2.1.1. The concept of GIS, remote sensing and GPS
Remote sensing: is the process of acquiring information about an object or
phenomenon without making actual physical contact with it, as opposed to onsite
observation or onsite sensing. This often requires the use of aerial sensor
technologies such as those used in reconnaissance airplanes and satellites in order to
detect and analyze objects on the Earth, usually on the surface.
Remote sensing is used to receive objective information about the Earth’s
surface and atmospheric phenomena thanks to sensors installed on aircraft, artificial
satellites, spacecraft or in orbit station. Remote sensing technology allows to record
changes in natural resources and the environment making monitoring and inventory
of natural resources and environment more effective.
Remote Sensing quickly provides high resolution digital data for the
establishment and adjustment of the national mapping system and geographic
database.
Separation of information in remote sensing can be classified into five categories:
- Classification: is the process of separating and aggregating information
based on spectral, spatial and time properties given by picture of objects to be
studied.
- Dynamic detection: is the detection and operation of fluctuations based on
multi-image data time.
- Separation of physical quantities: Extraction of natural information such as
measurement of temperature, atmospheric state, height of objects based on spectral
characteristics or parallax of stereoscopic images.

- Separation of indicators: Calculation and determination of new indices
(NDVI plant index…).
- Identification of natural disasters signs in service of archeological searchers.
GIS (Geographic Information System) that origin from three concepts
geography, information, and system.
3


“Geography”: is related to spatial characteristics. They can be physical,
cultural, and economic and so on in nature.
“Information”: refers to data managed by GIS. It is the data about attributes
and space of the object.
“Systems”: is a GIS system constructed from modules. Creating modules
helps conveniently in management and consolidation.
GPS (Global Positioning System): is a satellite navigation system used to
determine the ground position of an object. GPS technology was first used by the
United States military in the 1960s and expanded into civilian use over the next few
decades.
2.1.2. Landsat image
Landsat satellite is the common name for the system of satellites used
exclusively for the purpose of exploring earth recourse. Landsat satellite system can
be said to be an international satellite system. The first satellite was designed to
monitor the surface of the earth, Landsat-1 satellite, was launched by NASA in
1972. Originally knowing as ERTS-1 (Earth Resource Technology Satellite)
Landsat, Landsat us designed as a test to test the feasibility of collecting
multisprectral earth observation data Since then the program has collected abundant
data from around the world
Next, the satellite generations Landsat 2 - 1975, Landsat 3 - 1978. These two
types of landsat images are only equipped with MSS (Multispectral Scanner
System): an optical sensor designed to receive receive spectral radiation from

sunlight shining into the earth's surface in 4 different spectral channels, integrated
by optical systems and sensors). Landsat 4 was launched in orbit in 1982 and
Landsat 5 in 1984, both satellites were equipped with TM sensors (Thematic
Mapper), used to observe the earth in 7 spectral channels with a range from the
viewing range. see to infrared. Landsat 6 and 7 were launched in 1993 and 1999
with the new improved ETM (Enhanced TM) sensor. Landsat 8 satellite was
successfully launched into orbit on February 12, 2013, with the task of monitoring
forest changes and ecosystems on earth.

4


Table 2.1. Sensor characteristics of Landsat 7 and Landsat 8 satellite image
Wavelength

Resolution

(µm)

(m)

Band 1

0.45 – 0.52

30

Band 2

0.52 – 0.60

30

Band 3

0.63 – 0.69

30

Landsat 7

Band 4

0.77 – 0.90

30

(ETM+)

Band 5

1.55 – 1.75

30

Band 6

10.40 – 12.50

60*(30)

Band 7

2.09 – 2.35

30

Band 8

0.52 – 0.90

15

Band 1 – Coastal aerosol

0.43 – 0.45

30

Band 2 – Blue

0.45 – 0.51

30

Band 3 – Green

0.53 – 0.59

30

Band 4 – Red

0.64 – 0.67

30

Landsat 8

Band 5 – Near Infrared (NIR)

0.85 – 0.88

30

(OLI and

Band 6 – SWIR 1

1.57 – 1.65

30

TIRS)

Band 7 – SWIR 2

2.11 – 2.29

30

Band 8 – Panchromatic

0.50 – 0.68

15

Band 9 – Cirrus

1.36 – 1.38

30

Band 10 – Thermal Infrared (TIR) 1

10.60 – 11.19

100*(30)

Band 11 - Thermal Infrared (TIR) 2

11.50 – 12.51

100*(30)

Satellite

Bands

(Source: />2.1.3. Status map of forest resources

Forest status map is a topical map of forest resources drain on the basis of a
topographic map of the same scale, which fully and accurately shows the location
and area of across forest types in accordance with the results. Statistic and inventory
of forest resources periodically. By using the appropriate colors and symbols to
show the difference in forest conditions, topography and terrain, it clearly shows the
distribution of the entire area.
Forest status map is an important and necessary document for the management
5


and development of forest resources and for other economic and technical sectors
that are using and exploiting forest resources and for other economic
Forest status maps are developed for each administrative level: commune,
district, province and the whole country and are an important tool in assessing
changes in forest resources.
2.2.

Application of remote sensing and GIS in forestry

2.2.1. In the world
GIS started being built in Canada in the 1960s and is applied in many fields
around the world. In 1972, the launch of Landsat satellite 1 opened a new era for the
use of remote sensing in earth observation and research. So far more than 40 years
of development using remote sensing images and GIS for many different uses have
been very popular around the world.
Remote sensing technology, one of the achievements in space science has
reached a high level and has become a popular technique widely applied in many
socio-economic fields in many countries around the world. The demand for remote
sensing technology application in the field of research, exploitation, use and
management of natural resources and environment is rapidly increasing not only

within the country but also within the country. International. The findings from
remote sensing technology help scientists and policymakers make strategic options
for using and managing natural resources and the environment. Therefore, remote
sensing is used as a dominant technology at present.
The satellite observation technique has developed rapidly and formed the
global satellite meteorological observation system. Earth observation and space
monitoring have entered a new phase, enriching the scope and content of
monitoring. From localized observation at lower levels of the atmosphere to
monitoring of the entire atmospheric system. Many factors, locations in the
atmosphere and on the earth that previously used to be difficult to observe are now
possible with meteorological satellites. Remote sensing technology has provided a
lot of data for the fields: astronomy, meteorology, geology, geography, marine,
agriculture, forestry, military, information, aviation, space, ...
During World War I, there was an application of aviation photography to
6


create forest maps in the Maurice region of Canada, forest vegetation maps in
England (1924), inventory of forest reserves from US aviation photos (1940).
Experimental methods of measurement, height measurement on photos of Seely,
Hugershoff, ... However, this stage has not built a complete theoretical system as
well as methods of reading and guessing aviation photos.
Monitoring results from 1972 to 1991, thanks to the application of RS and GIS
in assessing forest changes and forest cover, showed that in India, the forest area
from 14.12 million hectares to 11.72 million. ha, a decrease of 2.4 million hectares.
As a result, India has developed a status system of maps with 2-year cycles for
effective forest management, protection and development. (Dutt, Udayalakshmt,
1994).
From 1979 to 1991, the satellites NOAA 6, NOAA 7, ..., NOAA 12; NOAA I and 1992 NOAA - J provided updated photos with a spatial resolution of 1.1 km.
France launched satellites SPOT 1 (February 22, 1986), SPOT 2 (January 22,

1990) and SPOT 3 (September 26, 1993) with HVR (High Resolution Visible)
sensors with 3 spectral channels with resolution. 20m resolution with a full color
channel with 10m resolution. Counting on March 24, 1998, SPOT 4 was launched
into orbit with the new HRVIR (High Resolution Visible and Infrared) sensor and
SPOT 5 (2002) with the upgraded HRVIR sensor, capturing images up to 5m.
In addition, India successfully launched the IRS-1A resource monitoring
satellite in 1998 (followed by IRS-1B satellites in 1001, IRS-1C in 1995 and IRS1D in 1997) with the LISS sensor. (Linear Imaging Scanner System) has similar
technical features to MSS. Japan also launched the resource satellite JERS-1D in
1992 with SAR sensors (Synthetic Aperture Rada), VNIR (Visible and Near
Infrared Radiometer) and SWIR (Short Wavelength Infrared Radiometer). In 1996,
ADEOS (Advanced Earth Observation Satellite) of Japan was put into orbit with
700m OCTS (Ocean Color & Temperature Scanner) sensors, AVNIR (Advanced
Visible and Near Infrared Radiometer) resolution of 16m and low-spatial resolution
sensors. Japan has also made a concerted effort with the United States to build the modern
ASTER (The Advanced Spaceborne Thermal Emission and Reflection Radiometer)
sensor on the Terra satellite launched by NASA in orbit in December 1999.
7


Currently, high-resolution satellite images (1: 4m) are being used by experts in
the direction of integration with GPS (Global Positioning System) and GIS
(Geographical Information System) to exploit spatial data effectively. serving the
establishment of city maps, traffic planning, land use change monitoring, ... In
particular, IKONOS satellite launched in April 1999 provided images with a spatial
resolution of 1m and in particular, the Quickbird satellite, launched in October
2001, provided images with a spatial resolution of 0.61m. This make an important
contribution to the development of remote sensing applications in many fields,
meeting the demands of providing accurate and detailed information.
In addition, the development in the field of earth research by remote sensing is
accelerated by the application of new scientific and technological advances with the

use of radar images. Active radar remote sensing, captures images by super longwave broadcasting and retrieves reflected beams, enabling independent, cloudindependent studies. Radar waves have the characteristics to penetrate clouds, thin
soil and vegetation and are sources of artificial waves, so it is capable of operating
both day and night, regardless of the source of solar energy. Photographs created by
the SLAR-type radar system were first recorded on the Seasat sensor. The
characteristic of radar waves is to receive reflected rays from the source with a
variety of oblique angles. This wave eliminates the swusc sensitivity to the
roughness of the surface of the object, which is emitted by the radar beam, so it is
used for structural study of an area. Today's computer technology has strongly
developed with specialized software products, facilitating analysis of digital satellite
images or radar images.
In forestry, Spurr S has divided the history of remote sensing in world forestry
into three main stages as follows: First stage: From the end of the 19th century to
before the first world war, marked by the creation of the life of aviation imagery,
stereoscopic glass, and sporadic trials of their use in forestry. For example, an
experiment by Rodolf Kobsa and Ferdinand Wang (Austria - 1982), Hugershoff R.
(Germany - 1911), Hand Dock (Austria - 1913). Second stage: From the first world
war to the end of the second world war. This period recognized the success of a
number of authors in several countries: Developing forest maps from aerial photos
8


in the Maurice region of Canada, forest vegetation maps in England (1924),
inventory of stock photos. not in the US (1940). Experimental methods of
measurement, height measurement on photos of Seely, Hugershoff, ... However, this
stage has not yet built a complete theoretical system as well as methods of reading
and guessing aviation photos.
The third stage: From the second world war to the present, along with the
development of science and technology, the study of remote sensing applications
has been growing widely in many countries. Remote sensing technology develops
in the direction of increasing abundance, sophistication, accuracy and updating with

the program "Interkosmos" and satellite "Landsat". In parallel with the above two
systems is the system of receiving and processing information in many countries
around the world such as Canada, Brazil, India, Thailand, China, etc. Recently,
satellite systems SPOT, ADEOS, TERRA, ... was born and with the strong
development of information technology, the methods of processing remote sensing
images by software have been studied by many advanced countries in the world
such as USA, Japan, France, Russia, ... Since then, remote sensing images have
been applied more and more widely in many different fields such as agriculture,
forestry, environment, geology ...
Su-Fen Wang (2004), when performing interpretation SPOT 4 and SPOT 5
images by the method of classification test for the northern region of Taiwan, the
results showed the accuracy of SPOT 5 images (74%) is higher than SPOT 4 images
(71%) because SPOT 5 images are more accurate. The results of classification into
3 states are Chamaecyparis formosensis forest, plantation forest of Tung family,
deciduous tree forest.
Hansen and DeFries (2004), using satellite images to track changes in forest
cover during 1982-1990, and finally concluded that, in contrast to the United
Nations Food and Agriculture Organization (FAO) reported a global increase in
forest cover. Latin America and tropical Asia are the two predominant deforestation
areas. Paraguay showed the highest percentage associated with deforestation, while
Indonesia had the largest increase associated with deforestation, while Indonesia
had the largest increase in deforestation from the 1980s to the 1990s.
9


Bodart et al (2009), tracking changes in tropical forest cover in Latin America,
South Asia and Africa in 1990-2000 using satellite imagery and developing an
active and robust approach. It is possible to pre-process a huge amount of data from
different conditions automatically to put multitemporal and multi-scene data on the
same scale and image segmentation before monitoring classification.

According to Devendra Kumar (2011), estimating changes in forest cover
based on satellite data can help researchers clearly see the potential for carbon
accumulation, climate change, and threats to multiple forests. biodiversity and
extent of forest change through satellite data. Forest cover maps of regions are
based on three types of data sources: expert opinion collection, remote sensing
products and national statistics [19].
2.2.2. In Viet Nam
Our country has many hills, terrains, meteorology, climate, and hydrography.
Along with global warming, unusual weather events such as drought, flood are
increasing with increasing levels of damage, rising temperatures in combination
with droughts lead to the risk of forest fires, the development of pests and diseases
on increasingly severe crops. Therefore, the use of remote sensing information
integrated with geographic information systems (GIS) and global positioning
systems (GPS) along with the observations obtained from the surface will be
objective and multifaceted. format of necessary information for the study,
supervision and forecast of hydrometeorology, agricultural meteorology and
environment, especially for monitoring and warning of natural disasters to have
preventive and timely response measures.
In Vietnam, it can be summarized according to the assessment stated in the
draft master plan on remote sensing technology application and development in
Vietnam in the 2001-2010 period as follows:
- From 1979 to 1980: Our country's agencies began to access remote sensing
technology
- In the next 10 years (1980 - 1990): experimental studies have been conducted
to determine the ability and method of using remote sensing materials to solve its
tasks.
10


- From the years 1990 - 1995: In addition to expanding research and testing,

many branches have put remote sensing technology into practical use and so far
have obtained some clear scientific results. technology and economics. In practical
applications, in addition to NOAA and GMS meteorological images, agencies have
used many optical satellite images such as LANDSAT, SPOT, KFA-1000, ADEOS,
and radar satellite images such as RADASAT, new ERT. have been tested in recent
years. Particularly high-resolution satellite images (1-2m) have hardly been
commonly used. Along with the application very early. In 1958, in cooperation with
the German GDR, used 1 / 30,000 full-color black and white aircraft images to
investigate the forests in the Northeast. It is a very basic technical progress,
facilitating the development of necessary tools to improve the quality of forest
inventory in our country. Since the end of 1958, an average of 200,000 ha of forests
have been surveyed annually, forests and hilly land have been explored, a simple
forest resource inventory was drawn and the forest resource distribution in the north
drawn. By the end of 1960, the total forest area in the north was estimated at about
1.5 million hectares. In the years of 1959 in southern Vietnam, aircraft images were
used in forest investigations and the total forest area in the south was 8 million ha.
In 1968, aircraft photos were used in forest inventory for Huu Lung and Lang
Son SFEs. Based on the photos of the aircraft, delineate the forest types, then go on
the field to check and measure for each forest type, build a map of the current forest
status.
In the period of 1970 - 1975, aerial photos were widely used to create status
maps, transport and transport network maps for many regions in the North.
From 1981 to 1983, during the first national forest inventory and evaluation
program with the help of the Food and Agriculture Organization of the United
Nations (FAO), for the first time in the history of the Forest Inventory and
Development Institute (FIPI), to conduct forest resources surveys and assessments
nationwide with the aim of providing data and information to the State in
formulating forestry policies and strategies and socio-economic development in the
period 1983-1990. In this program there is a combination of satellite images
supported by FAO in conjunction with ground surveys. The type of satellite image

11


used is Landsat MSS and the result is all data on the area, reserves of forest types by
province and nationwide.
Program of survey, assessment and monitoring of changes in forest resources
nationwide in 1991 - 1995 implemented under Decision No. 575 / TTg signed by
Deputy Prime Minister Phan Van Khai on November 27, 1993. In this program, the
current forest resource status map is based on existing forest status maps before
1990, then using Landsat MSS and Landsat TM satellite images with a resolution of
30 x 30m to update areas of land use change, places of deforestation or places with
newly planted or regenerated forests. Landsat MSS and Landsat TM satellite images
are in hardcopy format, scale of 1: 250,000 and are interpreted and delineated
directly on images to the naked eye. The interpretation results are converted to 1:
100,000 topographic map and checked at the status quo. Achievements of the
program are data on national forest resources, regions and provinces, ecological
map of forest vegetation at regions with scale of 1: 250,000; land form maps of
provinces with scale of 1: 100,000 and regions of 1: 250,000.
Program of survey, assessment and monitoring of changes in forest resources
in the whole country for 5 years in the period of 1996-2000, during this period, the
forest status map was built by remote sensing. The satellite image used is SPOT3,
with a resolution of 15m x 15m, suitable for building a 1: 100,000 scale map.
SPOT3 images are processed and color combination fake, printed on paper
(hardcopy).
Compared with Landsat MSS and Landsat TM, SPOT3 images have higher
resolution, the objects on the image are also shown in more detail. SPOT3 images
are still interpreted with the naked eye, so the results still depend greatly on the
experience of the interpreter and image quality.
The achievements of this program in terms of maps are: forest resource reporting and
data; explanatory reports and maps of regional and national ecological zoning of

vegetation; explanatory reports and land classification maps at provincial, regional
and national levels; explanatory reports and maps of forest status at provincial,
regional and national levels; general report on forest resource changes in the 19962000 period of the forest status map at 1: 100,000 scale; 1: 250,000; 1: 1,000,000.
12


The 5-year program of surveying, assessing and monitoring the development
of forest resources in the 2000-2005 period, in this program, the method of mapping
in the third cycle has been developed one step up. This time, the forest status map
was made from satellite images Landsat ETM +. The quality of this image is still
the same as the one used in cycle I. Its resolution is still 30m x 30m. Images are not
printed in hardcopy but in digital form and stored on a CD.
In the 2006-2010 period, to carry out the program on investigation, evaluation
and monitoring of forest resource developments in the 2006-2010 period (cycle IV).
In this program, the development of a system of maps and data on the current status
of forest resources using SPOT-5 satellite images of a resolution of 2.5 m
nationwide provided by the Ministry of Natural Resources and Environment is the
basis. to edit and refine the construction of various types of maps: current status of
forest resources, the rate of 1 / 25,000 for 1,000 key forestry communes; forest
status, 1 / 50,000 scale for districts; forest status, scales of 1 / 100,000; 1 / 250,000
and 1 / 1,000,000 for provincial, regional and national levels. Building a set of
photo-lock samples to serve the guessing and reading of satellite images. Develop
an updated data system, published every 5 years, checked and evaluated at the end
of the monitoring cycle (2010). Developing analytical report, assessing changes in
forest area between two research cycles in order to propose solutions for forest
management.
In the current period, the General Department of Forestry assigns "To organize
the implementation of statistics,

inventory and

monitoring of national

developments".
In addition to the programs of investigating, evaluating and monitoring
changes in forest resources nationwide, there are many other programs and topics
that also apply remote sensing such as:
Doctoral Thesis specialized in aerial photography of Chu Thi Binh (2001) with
the topic "Application of information technology to exploit basic information on
remote sensing data, to serve the study of some forest characteristics. Vietnam".
The project used NDVI plant index and total TRRI reflected energy with ADEOS
and Landsat TM remote sensing data to classify forest states and monitor forest
13


fluctuations from 1989 to 1998 for the two areas. forests in Quang Nam and Dong
Nai. The numerical processing method used in this thesis is a multi-spectral
classification method with tests.
Research of Nguyen Dinh Duong et al. (2004) "Using MODIS multi-spectral
image to assess changes in Vietnam's vegetation cover in the period of 2001 2003", the results are presented in the Association 14th Conference of Southeast
Asian countries on agriculture. The author has used the method of classification test
with MODIS satellite images of multi-time with low resolution to assess the
fluctuation of the coating throughout the territory of Vietnam from 2001 to 2003.
Ministry-level key project of PhD. Duong Tien Duc carried out from January
2005 to the end of December 2008 under the title "Research and application of
remote sensing technology and geographic information system (GIS) in assessing and
managing the current status of resources. forests belonging to the Da river protection
zone”. The achieved results are 01 Landsat 7 - ETM satellite image interpretation
course and 01 SPOT-5 satellite image interpretation course set for 03 research areas in
Hoa Binh, Son La and Dien Bien; Constructing 150 standard plots for systematic

determination, 90 semi-standard standard plots, 90 ground control points, 270 test
points and test areas at 03 research sites (Cao Phong - Hoa Binh; Thuan Chau - Son La;
Dien Bien - Dien Bien); Develop a GIS application model in analyzing and controlling
changes in forest status patterns.
The project "Application of remote sensing and GIS technology to create a
map of changes in forest vegetation cover in Phu Quoc island, period 1996-2001 2006" by Nguyen Quoc Khanh, Nguyen Thanh Nga of Center for Natural
Resources Monitoring and environment - National Remote Sensing Center
implemented in 2007. In this topic, the author uses SPOT Panchromatic (1996,
1997), Landsat 7 + ETM images (2001), Landsat (1992, 2001), aerial photos
(2005), Aster photos (2001, 2002) to create the change map.
KC.08.24 State project "Researching solutions to prevent and remedy forest
fire consequences for U Minh and Central Highlands" by Vuong Van Quynh University of Forestry have built software to automatically detect forest fires from
Landsat ETM + satellite images and MODIS. The software is built on the
14


combination of multi-spectral channels combined with GIS data to detect forest fire
points throughout the territory of Vietnam.
The project "Research on using satellite images and GIS technology in
monitoring the current status of forest resources and testing in a specific area" is
chaired and implemented by Nguyen Truong Son - National Remote Sensing
Center. in 2007. The project used Landsat ETM (1999), SPOT-5 (2003) and GIS
satellite images to develop a rapid reporting process of forest area changes in Yen
The area, Bac Giang province. The numerical processing method used is a validated
classification method with the Maximum Likelihood algorithm.
Tran Thi Bich Thuy (2013) studied the environmental movement mangrove
areas Beach Mac-Dinh Vu Family, Hai Phong using remote sensing technology.
This result indicated that besides normal classification method based on
electromagnetic spectrum values of the objects on samples of mangrove vegetation
cover when combined classification with NDVI will give us better results, accuracy

is also higher.
Nguyen Hai Hoa (2016) researched about use of remote sensing data to
conduct the biomass and carbon stock of Acacia hybrid in Yen Lap district, Phu
Tho province. The above-ground dry biomass of plantation forest was estimated
from 147÷192 ton/ha at the density of 33 stems/100m2 and average DBH. As a
result, the average CO2 absorbed by trees was 296.64 ton/ha which create a good
base for PFES and provide sustainable local livelihood.
Tran Quang Bao (2013) researched about the estimation of biomass and
carbon stock of different forest types in Kim Boi district, Hoa Binh province, as a
combination of remote sensing and field survey, the total carbon absorbed by the
forest in Kim Boi district is 2.3Mton. The highest carbon storage is in medium
forest accounting for 68%; fallow land and regeneration forest account for 24% and
the rest is grassland, agriculture, and plantations.
2.2.3. Application of GIS and Remote sensing in determine habitat species
The project “Assessing the potential distribution of invasive alien
species Amorpha fruticosa (Mill.) in the Mureş Floodplain Natural Park (Romania)
using

GIS

and

logistic

regression”
15

implemented

(2007)

by


Gheorghe Kucsicsa, Ines Grigorescu, Monica Dumitraşcu, Mihai Doroftei, Mihaela
Năstase, Gabriel Herlo. The resultant probability map can be used by the park’s
administration in implementing the Management Plan in terms of identifying the
areas with the highest occurrence potential of A. fruticosa according to the primary
habitats and ecosystems and setting up actions for its eradication/limitation.
Panetta FD, Dodd J (1987) researched about using remote sensing data for
bioclimatic

prediction

of

the

potential

distribution

of

skeleton

weed Chondrilla juncea L. in Western Australia.
Janet Franklin (2012) studied “Predictive vegetation mapping: geographic
modelling of biospatial patterns in relation to environmental gradients”. Predictive
vegetation mapping has advanced over the past two decades especially in

conjunction with the development of remote sensing-based vegetation mapping and
digital geographic information analysis. A number of statistical and, more recently,
machine-learning methods have been used to develop and implement predictive
vegetation models.
The project “Modeling the potential distribution of forests with GIS” worked
by Angel M Felicisimo (2009). One of the objectives of forestry planning is to set
out criteria for a territory's reforestation oriented towards the reduction of
fragmentation and the conservation of biodiversity. This objective may be attained
by establishing for each forest type appropriate suitability models, which express
the suitability of each point of the territory for the growth of each forest formation.
The suitability models may be constructed by utilizing spatial analysis methods,
which relate the current presence/absence of forest type to a set of environmental
variables.
Chen Hao (2014) studied about Predicting the potential distribution of
invasive exotic species using GIS and information-theoretic approaches: A case of
ragweed (Ambrosia artemisiifolia L.) distribution in China. Presented with the
challenge of developing a model based on presence-only information, we
developed an improved logistic regression approach using Information Theory and
Frequency Statistics to produce a relative suitability map. This paper generated a
variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic
16


regression models applied to herbarium specimen location data and a suite of GIS
layers including climatic, topographic, and land cover information.
A GIS Model Predicting Potential Distributions of a Lineage: A Test Case on
Hermit Spiders (Nephilidae: Nephilengys) created by Magdalena Năpăruş (2001).
The model is a customizable GIS tool intended to predict current and future
potential distributions of globally distributed terrestrial lineages. Its predictive
potential may be tested in foreseeing species distribution shifts due to habitat

destruction and global climate change.

17


CHAPTER III
CHAPTER 3. STUDY GOAL, OBJECTIVES AND METHODOLOGY
3.1.

Goal and Objectives
* Goal
This study aims to provide a scientific basis for monitoring using remote

sensing data and determining potential distribution of turtle in study site.
* Objectives
1. To investigate the ecological characteristics of Nam Dong Natural Reserve
2. To construct thematic maps of distribution of turtle by factors in Nam Dong
Natural Reserve.
3. To conduct probability maps of habitat suitability of turtle in Nam Dong
Natural Reserve.
3.2.

Scope
- The study focus on vegetation cover and turtle in Nam Dong Natural

Reserve, Thanh Hoa province.
- Using Landsat 8 (2019) to construct the training samples for classifying and
identify vegetation cover.
- Using ArcGIS 10.4.1 software to estimate potential distribution of turtle in
Nam Dong Natural Reserve.

- Using Excel, IBM SPSS software to find out the relation between measured
parameter.
3.3.

Contents

1. Determine of the current status and flora, fauna composition in Nam Dong
Natural Reserve
2. Build vegetation map, elevation and river system of Nam Dong Natural
Reserve
3. Determine distribution of turtle based on field survey.\
4. Estimate suitable habitat map of turtle in Nam Dong Natural Reserve
3.4.

Methodology

3.4.1. Investigate current status in Nam Dong Natural Reserve
Collecting and inheriting relevant documents: The information on forest
18


management activities of the study area and in Vietnam; basic information on
natural, economic and social conditions; local societies and humanities are collected.
Collecting documents related to the map
Paper maps, digital maps: Forest inventory map of the whole district
provided by the Forest Protection Department of Quan Hoa District and Quan Son
District.
Collecting related documents on forest status
Inheriting the annual summary report of the People's Committee of Quan
Hoa District and Quan Son District.

Inheriting the statistical yearbook of Thanh Hoa province, the annual
summary report of the big programs and projects implemented in the locality and
the legal documents of the State, the province and the District which is related to the
study area.
Documents about local natural, economic, social and human conditions:
hydrological climate documents, survey results, land, population and labor statistics,
socio-economic policies , village history, ...
Remote sensing technology (RS) application: Research using Landsat 8
remote sensing image data over periods with a resolution of 30x30m to build a map
of the entire forest status District. Research also uses ArcGIS 10.4.1 software to
interpret images.
Research is conducted by preliminary surveys, selecting field test points to
evaluate the accuracy of image classification methods; On the other hand, it also
uses the method of selecting random survey points to select points to identify the
objects of the entire study area. The location of survey points is determined by GPS devices.
Study used Landsat 8 satellite image in 2019 with a resolution of 30x30m to
establish a map of current status, determination of biomass distribution and
mangrove forest reserve in the study areas as shown in Table
Table 3.1. Satellite image
ID Image codes
1

Date

Resolution
(m)

LC08_L1TP_127046_20190525_20190605_01_T1 25/5/2019 30
Source: />19