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

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”...

MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT VIETNAM NATIONAL UNIVERSITY OF FORESTRY

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

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!

TABLE OF CONTENTS

Page

INTRODUCTION 1

CHAPTER 1 LITERATURE REVIEW 3

CHAPTER 2 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

STUDY GOAL, OBJECTIVES AND METHODOLOGY 18

CHAPTER 3 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

NATURAL, SOCIO-ECONOMIC CONDITIONS 29

CHAPTER 4 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

4.3.2.1 Education, medical 35

4.3.2.2 Population and labor 35

RESULTS AND DISCUSSIONS 38

CHAPTER 5 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

CONCLUSION, LIMITATIONS AND RECOMMENDATIONS 69

CHAPTER 6 6.1 Conclusion 69

6.2 Limitations 71

6.3 Recommendationa 71

REFERENCES 72 APPENDIX

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

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

CHAPTER 1 INTRODUCTION

CHAPTER 1

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)

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”

CHAPTER 2 LITERATURE REVIEW

CHAPTER 2

2.1 GIS and remote sensing

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

“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

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

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

(µm)

Resolution (m)

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

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

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 IRS-1D 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

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 long-wave broadcasting and retrieves reflected beams, enabling independent, cloud-independent 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

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

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

- 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

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 1996-

2000 period of the forest status map at 1: 100,000 scale; 1: 250,000; 1: 1,000,000

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

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

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” 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

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

CHAPTER III STUDY GOAL, OBJECTIVES AND METHODOLOGY

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 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

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

(m)

1 LC08_L1TP_127046_20190525_20190605_01_T1 25/5/2019 30

Source: https://earthexplorer.usgs.gov/

Based on the coordinates identified by GPS and remote sensing images, researching and developing forest resource status maps by ArcGIS software 10.4.1 Methods of interpreting and classifying landsat images according to the following

diagram:

Fig 3.1 Steps to build the current status map in the study area

Step 1: Pre-processing Landsat remote sensing image:

Convert the numerical values on the image to the physical radiation value at the sensor and convert from the radiation spectral values at the sensor to the reflection spectrum of the object above the atmosphere

Inheriting the research provided by satellite manufacturer Landsat 8 at: http://directory.eoportal.org/web/eoportal/satellite-missions/l/landsat-8-ldcm

To determine the formula for converting digital value on the image to the value of physical radiation at the sensor and from the value of physical radiation at the sensor to the value of reflection in the upper atmosphere of the object be

According to the published research results for image landsat 8 of the image provider, the standardization/normalization process is done through 2 steps:

Converting the numerical values (DN) on the image to the value of physicalradiation at the sensor by the formula:

: reflections on the upper layer of the atmosphere : REFLECTANCE_MULT_BAND_x value

: The numerical value on the image (DN) : REFLECTANCE_ADD_BAND_x value

: zenith angle of the sun (degree)

Performing on ArcGIS with the following command: ArcToolbox/ Spatial

Analyst Tool/ Map Algebra/ Raster Calculator (Appendix 1)

Geometric correction: Before the analysis and interpretation of images, satellite images need to be geometric corrected to limit position errors and terrain differences, so that the images are close to the terrain in allowed maps most orthogonal projection The interpretation results depend on the accuracy of the image Therefore, this is a very important task for the next analysis steps

Rectification: The purpose of the rectification process is to convert scanned images in column coordinates of pixels to geodetic coordinates (real coordinates, geographic coordinates or flat coordinates) This work is to eliminate pixel position

errors caused by the image inclination angle and limit pixel errors due to high terrain differences

Grouping of image channels: The image data collected includes separate spectral channels, so it is necessary to collect image channels for image interpretation When the image collects remote sensing images from the satellites the images are located in different spectral channels and in black and white Therefore, to facilitate the interpretation of images and increase accuracy, people often conduct color combinations for remote sensing images Combining colors, mixing color photos with black and white photos to increase the resolution of the image and adjust the status map

Performing on ArcGIS with the following command: ArcToolbox/ Data

Management Tools/ Raster/ Raster Processing/ Composite Bands

Enhancing image quality: Remote sensing image after combining can be enhanced by adding one more color band (Band 8 for Landsat 8) to enhance the resolution of 15m x 15m

Performing on ArcGIS with the following command: ArcToolbox/ Data

Management Tools/ Raster/ Raster Processing/ Create Pan-Sharpened Raster Dataset

Cropping images according to the boundaries of the study area: Usually in a remote sensing image obtained, there is usually a very large area in the field, while the research object uses only a small part or small area in that scene To facilitate the fast image processing, avoid wasting time in processing and classifying images

in unnecessary areas, need to cut out the excess in the scene A data layer of boundary of the study area is used to separate the research area of the topic from the photo sheet

Performing on ArcGIS with the following command: ArcToolbox/ Data

Management Tools/ Raster/ Raster Processing/ Clip

Step 2: Classifying photos

Visual interpretation method (Visual Interpretation)

Visual interpretation is the use of the human eye and the intellect to extract information from remote sensing data in the form of images In the processing of

remote sensing information, visual interpretation (Visual Interpretation) is the first, most common job and can be applied in all conditions of equipment from simple to complex Visual image analysis is a job that can be applied easily in all conditions and can serve a variety of research content: ground cover research, forest research, soil, geology, geomorphology, hydrology, ecology and environment [7]

The method of image interpretation is based on the experience of the analyst and the available documents to interpret the image This method uses a number of support tools such as Google Earth, Google Map Interpretation can be considered as the most common method and still meet the required level of accuracy

NDVI Vegetation Index

NDVI (Normalized Difference Vegetation Index) reflects the distribution and coverage of vegetation An area with a high vegetation cover will have a high NDVI, an area with a low NDVI means a low vegetation cover in that area In this topic, the method of using the NDVI plant index is used primarily

The vegetation cover is very high at near-infrared, lower with mid-range and very low with that light, so use NIR (near-infrared) and RED channels to calculate NDVI Formula:

Legend:

NDVI: Normalized Difference Vegetation Index

NIR: Near-infrared reflectance spectroscopy

RED: Reflective spectrum of the red wave range

The purpose of NDVI imaging is to convert multi-spectral data into a channel image, thereby showing the distribution of forest plants The value of the plant index is the sequence of numbers from -1 to +1 The higher the NDVI value, the better vegetation coverage is in the area If the NDVI value is found, the area has low coverage If a negative NDVI value indicates that the area has no

single-vegetation Performing on ArcGIS with the following command: ArcToolbox/

Data Management Tools/ Raster/ Raster Processing/ Composite Bands

Step 3: Evaluating accuracy and process images after classification

Assessing accuracy after image classification: Used to evaluate the quality of interpreted satellite images or compare the reliability of the results of different methods in classification of remote sensing images

Accuracy evaluation samples are determined by field work using GPS devices The field results are saved as excel data files, statistics and information of the map field points: number of points, X coordinates, Y coordinates, current status

of forestry land and area at that location The data file is transferred to ArcGIS software and has a map of the field points After that, the field value is compared with the value on the classification image to evaluate the accuracy of image classification methods

In the research, we investigated 500 points for 5 subjects and used 40% of the survey points to evaluate the accuracy

Post-Classification Accuracy: Used to evaluate the quality of the satellite image to be interpreted or to compare the reliability with the results of different methods in the classification of remote sensing images

Post-Classification: After classifying, we need to carry out classifying procedures to create layers that can be mapped out by generalizing the information

Accuracy =

Step 4: Create current status map

Conduct to divide to 5 objects: Rich forest, Medium forest, Poor forest, Shrub, Bare land and water

Performing on ArcGIS with the following command: ArcToolbox/ Spatial

Analyst Tools/ Reclass/ Reclassify

The rule for calculating the relationship between the map scale and resolution

is to divide the sample of the map scale by 2 * 1000 to find the size with m The formula for calculating the map scale from resolution was developed as follows: Scale = Resolution (m) * 2 * 1000

Remote sensing data used in this project has a spatial resolution of 30m, according to the above formula, the appropriate map scale for the study area is 1: 60,000 In addition, in order to create a complete map, additional details such as the grid, legend, scale and title need to be added

3.4.2 Construct thematic maps of distribution of turtle by factors in Nam Dong

Natural Reserve

3.4.2.1 Collect primary data

Step 1: Structure interview

A random sample of 50 households in surrounded Nam Dong Natural Reserve

is selected in a survey Questionnaires are prepared before going to the field to get information about: General information of interviewees (age, gender, education level, main income, etc.); their knowledge about distribution of turtle and forest type in local area

Step 2: Semi-structure interview

Interviewing 15 staffs who work in Management board of Nam Dong Natureal Reserve by using checklist to get information and data on the issues: Current population, living standard of local communes; Local awareness about forest resources management The role and level of local community participation

in forest resources management in Natural Reserve

Step 3: Establish transects

Fig 3.2 Transect method

- The process of investigation on the route using GPS to determine direction of travel and length of the investigation

- The collected data is recorded in data sheet as the table below:

Table 3.2 Field data sheet used to collect information

Transect Species name Quantity Distance(m) Note

Field surveys were carried out during a period of 2 years (2017-2018) in Nam Dong Nature Reserve (20°18'07” to 20°19'38” N; 104°52'8” to 104°53'26” E)

V.Q Luu, O.V.Lo, N.V Ha, T.V Pham (hereafter V.Q.Luu et al.) Ten line

transects were established with a length of 3.5 – 21km in Lo and Bau villages (Nam Dong commune), Na Ho village (Son Dien commune), Phe and Kham villages (Tam Thanh commune), Bin village (Son Lu commune), Bang village (Trung Thuong commune), each line transect was marked the start and end points Investigator moved at

a speech of 0.8 to 1.0 km/h and carefully scanned, we applied opportunistic searching along temporary streams and ponds, open areas (trail, fields), caves, and forest wherever possible The searches were carried out in the evening from 19:00 to approximately 24:00h, the time when the majority of herpetofauna species are most active Otherwise, daytime surveys were also undertaken for the collection of diurnal species Upon detection of the subjects the following information is collected in the prepared datasheet including time, number of individuals, age/sex classes, location (GPS), habitats and most

of the specimens were collected by hand

Table 3.3 The total length of ten transects

From frontier post of Kham village to Pha Lo 14.5 km

Fig 3.3 Map of survey transects in Nam Dong Natural Reserveand surroundings

(Source: Lo.V.Oanh)

Step 4: Data analysis

- Applying descriptive statistic and using Excel and SPSS software to analyze the collected quantitative data, then, draw charts, graphs

- Classificating forest structure

- Finding out the distribution of turtles

3.4.2.2 Construct thematic maps of distribution of turtle by factors

To conduct thematic maps of distribution of turtle by factors, we use map of current status in part 3.4 and overlay the distribution of tutles

3.4.3 Conduct suitable habitat map of turtle in Nam Dong Natural Reserve

Fig 3.4 Process create maps of habitat suitability of turtle in Nam Dong Natural

Reserve

We continue using current status map to create map of habitat suitability of

turtle in Nam Dong Natural Reserve Following the steps in figure 3.3, we find the

area that it is suitable with total species and each species After that, we plus 3 layers of 3 factors to get final map

Performing on ArcGIS with the following command:

Step 1: ArcToolbox/ Spatial Analyst Tools/ Reclass/ Reclassify

Step 2: ArcToolbox/ Spatial Analyst Tools/ Map Algebra/ Raster Calculator

CHAPTER IV NATURAL, SOCIO-ECONOMIC CONDITIONS

Contiguous boundary: The North borders on plots 1, 2, 3, 4, 5 sub-zone 185; Plots 1 and 2, sub-zone 187, Quan Hoa district; The South borders Son Lu commune and Son Dien commune, Quan Son district; East: border with plot 3, 4 sub-area 187 (Quan Hoa district) and Trung Thuong commune, Quan Son district; The West is bordered by blocks 4 and 5, sub-area 185, Quan Hoa district and Son

Dien commune, Quan Son District

Fig 4.1 Map of geographical location of Nam Dong Natural Reserve

4.1.2 Topography, geomorphology

Complex mountainous terrain, rugged, dense network of rivers and streams Separated by fissures, valleys, and streams, the surface of the natural terrain changes erratically, creating a steep terrain typical of the karst mountain ecosystem The average height is from 700 - 900m, the slope is 10 - 450 and inclined from Northwest to Southeast

4.1.3 Climate and hydrology

4.1.3.1 Climate

Temperature: Climate characteristics are more influenced by the Northwest

region than the Central and the old quadrant Due to the high terrain, the temperature is low, the total annual temperature is only about 7,500 - 8,000 ° C The average temperature is from 23 - 25 ° C, the lowest average is 14 ° C, the highest is

38 ° C The temperature range of night and day ranges from 4 - 10 ° C

Wind: generally weak, wind speed in storms does not exceed 25m / s The

influence of hot and dry West winds is negligible Every year there are 3-5 days of hoarfrost, which is especially severe in some places

The sub-region has a low temperature, cool summers and heavy rain, very cold winter rain and little rain Natural disasters are mainly cold and hoarfrost, frost

Precipitation: the average annual is from 1,600 - 1,760 mm The annual average

air humidity is 86%, but unevenly distributed throughout the months of the year In general, the climate and weather of Nam Dong commune are relatively favorable

for the development of crop and husbandry, especially for forestry development

4.1.3.2 Hydrology

The complex terrain is divided by many waterways, valleys and streams, the surface of the natural terrain changes erratically, creating a steep terrain characterized by mountains and forests

It can be seen that the characteristics of the commune's natural conditions as described above are very convenient for forest fire prevention and fighting if it

occurs

4.1.3.3 Land

The complex terrain is highly divided by thick river systems and valleys so

there are many types of soil including:

River and alluvial soil (Pb): This type of soil is suitable for rice, crops Strong, medium alluvial soil (Pg): This is alluvial soil of Ma river, Luong river and streams, with low terrain, often flooded, with only 1 or 2 rice crops planted Mechanical components from medium to heavy meat

Feralite, modified by rice cultivation (Fe): is the Feralite that has been modified by wet rice cultivation, distributed in 18 communes throughout the district, and is a terraced field around the mountainside

Yellow red soil develops on acid magma soil (Fa): This type of soil develops

on Riolite, granite, with a layer of 1 - 1.5m thick and steep slope, once used as a natural forest into bare land

Red yellow soil develops on metamorphic rocks and clay rocks (Fs): Distributed in low hills (accounting for 2/3 of hills), developed on clay, mica, sandstone schist, with thickness from 1 - 1,5m, soil composition from moderate to heavy This type of land, is being used in plantation forests and natural forests

The soil is formed by two main sources: due to the accretion of rivers and

streams and the process of local weathering of rock, most of the soil layer is not very thick, just over 1m, much slope The terrain is complex and divided so agriculture is facing many difficulties, places below 170m and slopes below 300 have been largely cleared by the local people to clear forest for cultivation, leading

to soil erosion strong erosion, thin soil layer and changed soil quality

4.2 Basic characteristics of forest resources

4.2.1 Current status of land, forest resources

Through the results of the investigation and review of the status of soil types and forests of the NR, rare and precious conifer species in Nam Dong conifer by delineating plots of field conditions in combination with published forest change data Annually, the results of the current status of forests and land use of the Natural Reserve are summarized as follows:

Table 4.1 Current forest status in Nam Dong Natural Reserve

(Source: Reported data of the Natural Reserve establishment project and

re-examination results up to October 2014)

From the results summarized in Table 4.1 shows that:

- Forested land: Nam Dong Natural Reserve has forest area of 624, 71 ha, reaching 96, 56% coverage, this is a natural resource to conserve valuable conifer species, rare and ecosystems of the NR in which:

+ Forest area on rocky mountain is 502, 84 hectares, accounting for 77, 72% including the whole area of natural limestone mountain forests, adjacent to the region with almost primitive distribution of 6 conifer species

+ Forest area on land mountains is 121, 87ha, accounting for 18, 8% including forest states IIIa2, IIIa1, IIa, IIb

- Non-forested land: The area of non-forested land is 22, 24 ha, accounting for 3, 44% of the natural area of the Nature Reserve, the forest has a single-storey structure of timber trees, the composition of plants is mainly species Light demanding trees, some of the remaining trees are often short and crooked

4.2.2 Forest status and distribution by functional subdivisions

- Strictly protected sub-area: An area of 502.84 ha, including the whole area

of natural limestone mountain forests in the region with almost primitive distribution of 6 conifer species

- Ecological rehabilitation sub-area: The area of 144.11 hectares is an area

of mountainous land, adjacent to a strictly protected subdivision, belonging to elevation above 700 m

- Administration-Service Sub-zone: Nam Dong Nature Reserve of Nam Dong

Species and Rare Species Conservation Office at Nam Dong Ranger Station and the area where 3 Forest Protection Stations are planned to be built

- Buffer zone: The total area is 3 315.53 ha, which is defined as 12 villages

and villages bordering the NR, including 7 villages in Nam Dong commune, Quan Hoa district; 5 villages in 3 communes of Son Lu, Son Dien, Trung Thuong and Quan Son district

Fig 4.2 Current status map of Special-use Forest Nam Dong Natural Reserve 4.2.3 Forest type of reservation

- Tropical evergreen closed rain forest belt 700 - 1600 m: Mixed forest of broadleaf and coniferous trees on limestone mountains; Evergreen closed broad leaved tropical rainforest on limestone mountains; Evergreen closed broad leaved

tropical rainforest on earth mountains

- Tropical moist evergreen closed forest less than 700 m: Tropical moist evergreen closed forest on limestone mountains; Evergreen tropical moist rain forest on land mountains; Sub-type of tropical scrub on mountain land

4.3 People's living conditions, socio-economic

4.3.1 Economic

4.3.1.1 Agricultural production

In recent years, agricultural production has had encouraging development steps Cultivation is gradually shifting towards sustainable development, reducing shifting cultivation, focusing on intensive cultivation of paddy fields and specialized color fields The conversion of plant and animal breed structure has been effectively directed by the commune, which has resulted in increased production value, increased crop productivity over the years, and some agricultural products become the goods Hybrid rice varieties and hybrid maize have been put into widespread production, contributing to stabilizing food security in the area The average income currently is: 5.8 million VND/person/year, only reaching 0.67 times the average income in the province

Table 4.2 Land use area of communes in the buffer zone of the Natural Reserve

Land for agriculture production 83, 72 0, 5

Non-agricultural land (residential

Table 4.2 shows that the area of land used for agricultural production is very

small with 0.5% The lack of such productive land makes it difficult for people to develop their lives, increasing the risk of slash and burn cultivation and illegal hunting of forest animals for daily life