Application of geographic information system remote sensing on assessing soil erosionin some protection plantation models at hong linh town ha tinh province

Proposing some solutions to raise the effective of erosion control of some protection plantation forest in Hong Linh town.. Assessing the ability of soil protection against soil erosion

MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT

VIETNAM NATIONAL UNIVERSITY OF FORESTRY

STUDENT THESIS

Title

APPLICATION OF GEOGRAPHIC INFORMATION SYSTEM

PROTECTION PLANTATION MODELS AT HONG LINH TOWN,

HA TINH PROVINCE

Major: Natural Resources Management

Code: D850101

Faculty: Forest Resource and Environmental Management

Student: Phan Thi Thuy Linh Student ID: 1453090571

Class: K59A Natural Resources Management Course: 2014 – 2018

Advanced Education Program Developed in collaboration with Colorado State University, USA Supervisors: Dr Bui Manh Hung

Assoc Prof Bui Xuan Dung

Ha Noi, 2018

ACKNOWLEDGEMENT

The research has been supported by many individuals as well as organizations First

of all, I would like to thank to Dr Bui Manh Hung and Assoc Prof Bui Xuan Dung who are my advisers for supporting me during conducting my thesis for their motivation, enthusiasm and immense knowledge

Second of all, I also thank Board of Hong Linh protection forest management, People‘s Committee of Hong Linh town.` Especially, I would like to thank to Mr Nguyen Hai Van and Mr Ho Phuc Trung in Board of Hong Linh protection forest management for their useful, enthusiasm and providing helpful data on this study

I am so thankful for the supporting of Nguyen Thuy Duong, Nguyen Dieu Huyen,

Le Sy Hoa in conducting map and sample plot establishment To complete my thesis, I also received a lots of helps from Mr Le, Mr Thanh, Ms Phuc who work in the Laboratory of Vietnam National University of Forestry, therefore I would like to say thank you to all of them for lending some equipments to measure the parameters

Lastly, my family and my friends are a large motivation for me to complete my thesis I really thankful for all of you

I sincerely thank you!

CONTENTS

LIST OF ABBREVIATIONS i

LIST OF TABLES ii

LIST OF FIGURES iii

ABSTRACT 1

INTRODUCTION 2

CHAPTER I 4

LITERATURE REVIEW 4

1.1 Geographic information system and remote sensing 4

1.2 Studies on soil erosion 6

1.2.1 General of soil erosion 6

1.2.2 Impact factors to soil erosion 7

1.2.3 Effect of soil erosion 9

1.2.4 Research on erosion 9

CHAPTER II 12

GOALS, OBJECTIVES AND STUDY SITE 12

2.1 Goals 12

2.2 Objectives 12

2.3 Study site 12

2.3.1 Natural conditions 12

2.3.2 Economics 15

CHAPTER III 17

METHODS 17

3.1 Assessing the status of some protection plantation in Hong Linh town 17

3.1.1 Factor investigation 17

3.1.2 Plot investigation and collection data 17

3.1.3 Strip transect 22

3.1.4 Data analysis 24

DBH 25

3.2 Creating potential erosion map and erosion map of protected plantation forest in HL town 29

3.2.1 Method approach 29

3.2.2 Data investigation 32

3.2.3 Creating maps 34

3.3 Assessing the ability of soil protection against soil erosion of protection plantation in HL town 38

3.3.1 Standard TCVN5299:2009 about ―Soil quality‖ 39

3.3.2 Two standard soil to protect forest based on Hundson 1971 40

3.4 Proposing some solutions to raise the effective of erosion control of some protection plantation forest in Hong Linh town 41

CHAPTER IV 42

RESULTS AND DISCUSSIONS 42

4.1 The characteristics of protection plantation in Hong Linh town 42

4.1.1 Information about protection plantation in Hong Linh town 42

4.1.2 Stand information 44

4.1.3 Descriptive statistics results 46

4.1.4 Quality of tree statistics 48

4.1.5 Frequency distributions 49

4.2 Creating potential erosion map and vegetation cover map 50

4.2.1 Potential erosion map (C2) 50

4.2.2 Vegetation Cover Map (C1) 54

4.3 Assessing the ability of soil protection against soil erosion of protected plantation forest in Hong Linh Town 55

4.4 Proposing some solutions to raise the effective of erosion control of some protected

plantation forest in Hong Linh commune 60

4.4.1 Silviculture approach 60

4.4.2 For within threshold erosion 60

4.4.3 For over threshold erosion 61

CHAPTER V 62

CONCLUSION AND RECOMMENDATION 62

5.1 Conclusion 62

5.2 Limitation 63

5.3 Recommendation 63

REFERENCES 64

APPENDIX 66

1.1 Stand information for plots 66

1.2 Value of frequency distribution of DBH and Height in all forest types 67

1.3 Descriptive information 67

1.4 Frequency distribution in five representative plots for each forest type 68

1.5 Information about DEM 30*30 72

1.6 Non-spatial data uses to create map 73

ii

LIST OF TABLES

Table 3.1 Assessing the quality of the tree 21

Table 3.2 Tree position inventory 22

Table 3.3 Survey of Canopy closure (CC), ground cover (GC), liter cover (LC) 24

Table 3.4 Calculation for stand information 25

Table 3.5 Methods of descriptive statistics 26

Table 3.6 A measure of dispersion and variability [20] 26

Table 3.7 The ways to statistic frequency distribution 29

Table 3.8 Data collection of porosity 33

Table 3.9 Classifying current erosion 40

Table 4.1 Descriptive statistics for diameter variable 47

Table 4.2 Statistics of tree quality in each status 49

Table 4.3 Slope analysis in Protection plantation at Hong Linh 51

Table 4.4 Value of vegetation structure in each forest type in protection plantation 55

Table 4.5 Classification of current erosion in protection plantation at HL 56

iii

LIST OF FIGURES

Figure 2.1 Location of protection plantation in Hong Linh town, Ha Tinh 13

Figure 2.2 Land use and distribution area in Hong Linh town 14

Figure 3.1 Shape, location of investigation plots and measuring distance in plot 18

Figure 3.2 Definition of breast height [18] 19

Figure 3.3 Using Fiberglass tape to measure DBH (a) and Blume-leiss to measure H (b ) 20

Figure 3.4 Measuring tree height 21

Figure 3.5 The processing of using gap light analysis 23

Figure 3.6 Types of Skewness [18] 27

Figure 3.7 Interpolation method [11] 31

Figure 3.8 Processing of creating map C1 and C2 32

Figure 3.9 Flowchart of building C1 and C2 map 34

Figure 3.10 Flowchart of S factor in ArcGIS 10.3 36

Figure 3.11 Flowchart of P factor in Arc-gis 10.3 36

Figure3.12 Flowchart of C2 map 37

Figure 3.13 Flowchart of C1 map 38

Figure 3.14 Processing of creating current erosion map 39

Figure 4.1 Types of forest in Hong Linh town 42

Figure 4.2 Classification of forest status in protection plantation at Hong Linh town 43

Figure 4.3 Distribution of stand density in protection plantation area at Hong Linh 45

Figure 4.4 Distribution of DBH, height, commercial height of the tree in each plot 45

Figure 4.5 Total BA for stand and stand volume per hectare 46

Figure 4.6 Frequency distribution of DBH and height in all forest types 50

Figure 4.7 Slope distribution in protection plantation at Hong Linh town 51

Figure 4.8 Soil porosity distribution of protection plantation in Hong Linh (P factor) 52

iv

Figure 4.9 Map of potential erosion in protection plantation area at Hong Linh 53

Figure 4.10 Vegetation cover of protection plantation area at Hong Linh 54

Figure 4.11 Distribution of current erosion in protection plantation at Hong Linh 56

Figure 4.12 Distribution of erosion area 57

Figure 4.13 Amount of over soil erosion in protection plantation in Hong Linh 58

Figure 4.14 Current erosion in each forest types at protection plantation Hong Linh 59

1

ABSTRACT

Soil erosion is one of serious environment problem in the world so protecting forest plays an important role in reducing erosion in which each forest type has the different ability of protecting soil With aim of improving the effect of erosion, in this study we conducted field observation in 20 plots & 80 random areas and assessed soil erosion in some protection plantation models at Hong Linh town, Ha Tinh province by using soil loss prediction equation of Quynh et al (1996) and applying of GIS & RS Soil loss is predicted from rainfall erosivity index (564 mm/year), slope, porosity and vegetation structures A map of potential erosion was generated from slope map, and soil porosity map by using spatial interpolation and calculate to rainfall index by map algebra techniques in ArcGIS Vegetation index, a function of CC, H, GC and LC are classified into five groups After we conduct slope factor, porosity factor and vegetation factor map, we built current erosion map by using equation of Quynh et al (1996) The results show that (1) There are five

main forest types (Pinus merkusii, mixed Pinus merkusii & Acacia auriculiformis, Acacia

auriculiormis, Eucalyptus, mixed Eucalyptus & Acacia) in which pinus merkusii is a

native species and dominant in protection plantation with 47.65% (665.96 ha); (2) Potential erosion in this study is not high, from 0- 3.75 and the erosion rate is highest in other forest and somewhere of pinus merkusii from 1.57 to 3.75, vegetation cover is from 0.9 to 1.53 that means C1 coefficient map of each forest type isn‘t much different; (3) Current erosion based on TCVN 2009 are classified into 5 levels in which almost area is eroded slightly and be medium; Assessing amount of current erosion based on standard of Hundson (1971), there are 364.74 hectares in protection plantation are exceed eroded threshold (>0.8mm/year) occupied 26.22% in which erosion area of other forest is highest Almost area of each forest type belongs within eroded threshold and Pinus merkusii dominant with 51.9 %; (4) Keep ground cover and planting replaced species is one of solution to reduce erosion in protection plantation at Hong Linh

2

INTRODUCTION

Soil is the movement of soil particles from one place to another under the influence

of water or wind Soil erosion by water is one of the most serious environmental problems

in the world [1] Worldwide, soil erosion rate are highest in Asia, Africa, and South America, averaging 30 to 40 tons ha-1yr-1, and lowest in Europe and the United States, averaging about 17 tons ha-1yr-1[1] However, erosion rates are low on land with natural vegetation cover, about 2 tons ha-1yr-1 in relatively flat land and about 5 ha-1yr-1 in mountainous areas [2] In tropical regions where mean annual sediment yield estimated is greater than 250 tons km-2 [1, 3], upland areas are usually protected from erosion by a dense vegetation cover The Food and Agriculture Organization estimates that the global loss of productive land through erosion is 5-7 million ha/year Zeuro et al (2011) estimated global soil loss to erosion to be 26 million Mg/year According to land use analyzed, Vietnam has about 25 million of steep land, with huge potential of erosion, about 10 tons/ha/year [4, 5] According to systematic monitoring from 1960 until now, there is 10 - 20% of area affected by erosion from moderate to strong [5, 6]

There are many different approaches and methods in researching soil erosion, the one is field observation such as small slope, erosion transect, hillslope and catchment This way measure soil erosion in long-term with small scale so it is not efficiency The other is using soil loss prediction such as: MUSLE (William, 1975), ANSWERS (Beasley et al, 1980), SLEMSA (Elwell, 1981), SOILOSS model (Rosewell, 1993), RUSLE model (Renard, 1997)[5] Using modeling to predict soil erosion will save time and money, moreover it also measure erosion faster in big scale In practice, the Revised Universal Soil Loss Equation (RUSLE) model initially developed by Wishchmeier and Smith (1965) has been most widely used However, this equation has some disadvantage in Vietnam, amount of erosion is predicted in long-term average annual rate of erosion (more than 30 years) and suitable in slope topography less than 20%; applying on sheet erosion and small rill erosion; the experimental plots were designed in a small range of the factors Due to the

3

complexity of defining factors of RUSLE for a given region, the application of the RUSLE

in Vietnam has been challenging in term of prediction accuracy and its validation [1, 7] Soil loss prediction equation of Quynh et.al resolved these disadvantage of RUSLE that are applying this equation is suitable in slope topography of Vietnam (5-360) and predict soil erosion in short-term average annual rate The most important of this equation is that shows the relationship between soil loss prediction and rainfall, slope, vegetation cover and soil porosity factors Traditionally, soil loss was predicted at the local scale based on the factors usually calculated from field measurement Soil erosion prediction at large scale is often difficult due to spatial and temporal variability of model‘s factors.[1] In recent decades, the development of GIS techniques has facilitated the estimation of soil erosion and its spatial distribution over large areas Spatial analyses and interpolation techniques in GIS are used for this study The input data layers for mapping include DEM, rainfall and vegetative cover

Soil erosion is a significant problem in the uplands of the Central Coast, Vietnam

so that it is important to pinpoint estimated locations where soil erosion occurs in order to prevent substantial soil loss By 2017, Ha Tinh province has 360,700 ha of forest and forest land, with forest cover reached 51.3% [8] In which Hong Linh protection forest plays an important role in protecting the environment, regulating the climate in the north of

Ha Tinh province[9] At Hong Linh town, area of protection plantation is about 1390.89 ha occupied 77.6% of plantation[10] Moreover, there are not report about erosion control though the equation of erosion prediction in Hong Linh Stemming from such perceptions,

topic is chosen: “Application of Geography Information System and Remote Sensing on

assessing soil erosion in some protection plantation models at Hong Linh town, Ha Tinh province” Hopefully, it will make some contributions and bring some solutions to

improve the management for protection forests in Hong Linh town in particular and

Vietnam in general

4

CHAPTER I LITERATURE REVIEW

1.1 Geographic information system and remote sensing

A geographic information system (GIS) is a framework for gathering, managing, and analyzing data Rooted in the science of geography, GIS integrates many types of data

It analyzes spatial location and organizes layers of information into visualizations using maps and 3D scenes With this unique capability, GIS reveals deeper insights into data, such as patterns, relationships, and situations helping users make smarter decisions GIS is

a computer-based tool for mapping and analyzing feature events on earth [11] GIS technology integrates common database operations, such as query and statistical analysis, with maps GIS manages location-based information and provides tools for display and analysis of various statistics, including population characteristics, economic development opportunities, and vegetation types GIS allows you to link databases and maps to create dynamic displays Additionally, it provides tools to visualize, query, and overlay those databases in ways not possible with traditional spreadsheets These abilities distinguish GIS from other information systems, and make it valuable to a wide range of public and private enterprises for explaining events, predicting outcomes, and planning strategies GIS integrates many different kinds of data layers using spatial location Most data has a geographic component GIS data includes imagery, features, and base maps linked to spreadsheets and tables

The field of GIS started in the 1960s as computers and early concepts of quantitative and computational geography emerged Early GIS work included important research by the academic community Later, the National Center for Geographic Information and Analysis, led by Michael Goodchild, formalized research on key

5

geographic information science topics such as spatial analysis and visualization These efforts fueled a quantitative revolution in the world of geographic science and laid the groundwork for GIS GIS gives people the ability to create their own digital map layers to help solve real-world problems GIS has also evolved into a means for data sharing and collaboration, inspiring a vision that is now rapidly becoming a reality—a continuous, overlapping, and interoperable GIS database of the world, about virtually all subjects Today, hundreds of thousands of organizations are sharing their work and creating billions

of maps every day to tell stories and reveal patterns, trends, and relationships about everything Jack Dangermond (CEO, Esri) said that: ―GIS is about uncovering meaning and insights from within data It is rapidly evolving and providing a whole new framework and process for understanding.‖

Remote Sensing (RS) is the art and science of acquiring information about the earth surface without having any physical contact with it This is done by sensing and recording

of reflected and emitted energy Remote sensing is used in numerous fields, including geography, land surveying and most Earth Science disciplines (for example, hydrology, ecology, oceanography, glaciology, geology); it also has military, intelligence, commercial, economic, planning, and humanitarian applications Remote sensing makes it possible to collect data of dangerous or inaccessible areas Remote sensing provides fast, high-resolution digital imaging The quality of remote sensing data consists of its spatial, spectral, radiometric and temporal resolutions They are spatial resolution, spectral resolution, radiometric resolution, temporal resolution, radiometric correction, topographic correction Some remote sensing applications are land cover and land use, agriculture, forestry, geology, geomorphology, hydrology, mapping, ocean & coastal monitoring and monitoring of atmospheric constituents

6

Remote sensing technology combined with geographical information system has been applied to perform scientific research and projects related to survey natural conditions and natural resources, expertise environment monitoring, reduce to minimum the number

of natural disaster in some regions

1.2 Studies on soil erosion

1.2.1 General of soil erosion

Erosion is a natural process where energy provided by water, wind and gravity drives the detachment, transport and deposition of soil particles [12] Detachment occurs when the forces hold a soil particle in place is overcome by the forces of raindrop impact, moving water or [5] There is two type of erosion water erosion and wind erosion Soil erosion by water is one of the most serious environmental problems in the world [1]

The soil water erosion process is detachment and deposition Rainfall, and the surface runoff which may result from rainfall produces four main types of soil erosion by water: splash erosion, sheet erosion, rill erosion, and gully erosion Splash erosion is generally seen as the first and least severe stage in the soil erosion process, which is followed by sheet erosion, then rill erosion and finally gully erosion (the most severe of the four) [12] In splash erosion, the impact of a falling raindrop creates a small crater in the soil, ejecting soil particles The distance these soil particles travel can be as much as 0.6 m (two feet) vertically and 1.5 m (five feet) horizontally on the level ground If the soil is saturated, or if the rainfall rate is greater than the rate at which water can infiltrate into the soil, surface runoff occurs If the runoff has sufficient flow energy, it will transport loosened soil particles (sediment) down the slope

The second type is sheet erosion is defined as the uniform removal of soil in thin layers from sloping land It happens when rainwater flows into lower elevations, carrying

7

sediments with it Sheet erosion is the transport of loosened soil particles by overland flow Detachment and movement of soil particles due to a relatively smooth, thin sheet of water flowing across the ground surface [12]

The third erosion type is rill erosion refers to the development of small, ephemeral concentrated flow paths which function as both sediment source and sediment delivery systems for erosion on hill slopes Generally, where water erosion rates on disturbed upland areas are greatest, rills are active Flow depths in rills are typical of the order of a few centimeters (about an inch) or less and along-channel slopes may be quite steep This means that rills exhibit hydraulic physics very different from water flowing through the deeper, wider channels of streams and rivers

Gully erosion occurs when runoff water accumulates and rapidly flows in narrow channels during or immediately after heavy rains or melting snow, removing soil to a considerable depth

1.2.2 Impact factors to soil erosion

a Rainfall erosion index

Elision (1940) is the first person pointed out that raindrop caused erosion In 1985, Hudson N.W concluded that raindrop has a dynamic of 256 times more than it surface flow [5] So mainly the impact of the raindrop is the structural break topsoil by its own kinetic energy, this very activity made the grain detected from the ground In addition, rain also made the flow to transfer grain to sediment

b Slope factor

The length and steepness of slope are two essential features of topography relating

to soil erosion and surface runoff Topography steepness is a significant factor affecting sediment yield Soil erosion increase with slope length and steepness as a result of

c Porosity

Soil texture also influences surface runoff and soil erosion Soil erodability is a factor to estimate the ability of soil to resist erosion based on the physical characteristic of each soil Soil has a mixture of sand silt and clay and in many soil the ratio is very similar However, even with soils with similar ratios of sand, silt and clay may have drastically different soil erodability Soil with good soil structure will allow more water infiltration, thereby reducing surface runoff water and erosion

d Vegetation structure

Vegetation cover is the most significant factor to determine the severity of erosion process, is a function of canopy closure, height, ground cover, and litter cover Plant and litter cover play an important role in soil surface protection or soil erosion prevention

―Plant slow down water as it flows over the land (surface runoff) and this allows much of the rain to soak into the ground Plant roots hold the soil in position and prevent it from washed away Plants break the impact of a raindrop before it hits the soil, thus reducing its ability to erode Plant in wetlands and on the banks of rivers are particular importance as they slow down the flow of the water and their roots bind the soil, thus preventing erosion‖(NDA) [14]

1.2.3 Effect of soil erosion

Soil loss and nutrient loss make the amount of soil loss by erosion is very big it

reduces the soil source for agriculture production Nutrient in soil surface is eroded so that trees do not have nutrient to growth Besides nutrient loss also changed the physicochemical characteristic of soil.[5]

Harmful for environment and ecosystem: Nutrient is washed away by flow with soil particle which was abort by plant (usually algae) When algae die, the decomposition of organic matter by microorganism reduce oxygen in water and threat to the living of fish and other animals Finally, it will destroy the balance of water ecosystem Soil erosion also causes water pollution because soil particle contain phosphorus, nitrate or it absorbs pesticide which harms people‘s health [5]

1.2.4 Research on erosion

a In the world

According to Baver (1939), studies about the issue of soil erosion carried out by German scientists in 1877 [5] In 1907, researcher on soil erosion has been carried out when America‘s Ministry of Agriculture announced the policy of protecting soil sources The first detailed researches performed by Law (1941) analyzed the mechanical of raindrops on soil and then gave out the erosion process Zingg (1940) introduced a mathematical equation to access the effect of the slope and the length of downhill slope on erosion

10

In 1947, Musgrave et al developed an empirical equation called Musgrave equation, this equation had been applied until it was replaced by the universal soil loss erosion (USLE) in 1958 [5] Science the mid-1980s to the early 1990 different erosion models had been developed based on USLE in many places in the world such as Soil Loss Equation Model for South America-SLEMSA (Elwell, 1981) SOILOSS model (Rosewell, 1993) was developed in Australia and ANSWERS model was expanded in the late 1970s

to assess the level of aggradation at river basin (Beasley et al, 1980)

The rates of surface erosion depend on the extent dynamic management practices disturb and compact soil, alter ground cover, and modify soil properties Therefore, accurate estimation of soil loss or evaluation of erosion risk has become an urgent task Erosion studies in the world has solved that problem

b In Vietnam

In Vietnam, forests have long been recognized to provide an important role in environmental protection [1, 7, 15] Erosion in Vietnam occurs gradually because the country has mountainous topography so researcher about this problem has been carried out early Soil erosion studies have started in Vietnam in the 1960s Tung and Moorman (1958) had some basic researcher about researcher about soil erosion After completing the study, they concluded that terraced farming method help to reduce soil erosion Up to 1960 erosion researcher raised the influences of slope to soil erosion, which contribute to making the soil protection criteria, using and exploiting steep soil, Chu Dinh Hoang (1962, 1963) had researcher about the effect of rain of on soil erosion and how to prevent erosion

by farming methods [5]

From the 1980s, researcher works have begun to use USLE of Wischmenier and Smith (1978) such as Dung (1991) researched about ―Application of university soil loss

in Vietnam are not widespread by using model approach Therefore, it is necessary to promote further to bring about the efficiency studies of erosion

12

CHAPTER II GOALS, OBJECTIVES AND STUDY SITE

2.1 Goals

The research will contribute a number of scientific bases to improve the effect of erosion control of some protection plantations in Hong Linh town, Ha Tinh province

2.2 Objectives

- To assess the status of protection plantations in Hong Linh

- To create potential erosion map and vegetation cover map in Hong Linh

- To determine the ability of soil protection against soil erosion of protection plantations in Hong Linh

- To propose some solutions to raise the erosion control efficiency of some protection plantations in Hong Linh

13

Figure 2.1 Location of protection plantation in Hong Linh town, Ha Tinh

- On the border:

+ In the North with Nghi Xuan district and Nghe An province

+ In the South with Can Loc district

+ In the East with Hong Linh mountain (mainly in Nghi Xuan district)

+ In the West with Duc Tho district

Hong Linh has 6 administrative units including 5 wards (Nam Hong, Bac Hong, Dau Lieu, Trung Luong, and Duc Thuan) and 01 commune (Thuan Loc), with a natural area of 6031.895 hectares and a population of approximately 40000 people The figure 2.2 shows the status of Hong Linh town‘s area

Plain is located in the western part of the town, stretches from north to south, with

an average elevation of 3-5 meters

b Climate

Hong Linh is characterized by tropical and monsoon climate of Vietnam that is affected by the transition climate between North and South, divided into two distinct seasons: Cold winter with north-easterly winds and hot and dry summers with strong south-west winds

Observation data at the North Central Meteorological Station show:

- Average annual rainfall is from 2,200mm to 2,300mm The highest monthly rainfall is 639 mm (September) and Maximum daily rainfall is 550 mm The rainy season

15

usually lasts from August to December, is affected by many storms, tropical low pressure, causing great flood concentration from September to October every year September has the highest rainfall, accounting for 45% of the annual rainfall, fluctuation amplitude approximately 1,000mm / year The dry season is from May to August (driest month is July)

- The average annual temperature fluctuation 23-240 C, the average temperature of the hottest month is 410 C (July) and the coldest month is 6.80 C (January) Average temperature fluctuation day and night: 6.2 ° C and average annual sunshine hours is 1,800h / yr

- Relative humidity is relatively high, from 84 to 86% The wettest season in the winter months (January to March), the driest month is July

- Annual humidity in Hong Linh is 86% The highest monthly humidity is 90% and the lowest monthly humidity is 72%

- Prevailing wind direction in summer is west and southwest, northeast winter winds Average wind speed is 1, 5¸ 2,5m / s and Maximum wind speed when the storm can be from 30-40m / s

16

value of industry, small industry in the first 4 months of 2017 is estimated at VND 336.07 billion, reaching 30.8% of the plan In the area, there are about 2,286 individual business households operating in the field of trade and service providing more than 3,285 laborers and stable incomes; Total retail sales reached 164.83 billion VND, up 1.27% over the same period in 2016 and up 1.82% compared to March 2017

17

CHAPTER III METHODS

3.1 Assessing the status of some protection plantation in Hong Linh town

3.1.1 Factor investigation

We collected DBH, H, Hc, quality of tree in some protection plantation (Pinus

merkusii, mixed Pinus merkusii & Acacia auriculiformis, Acacia auriculiormis, Eucalyptus, mixed Eucalyptus & Acacia) at Hong Linh town

3.1.2 Plot investigation and collection data

a Plot setting

We set up 20 plots (500 m2) in which 10 plots for Pinus merkusii, 6 plots for Pinus

merkusii & Acacia, 1 plot for Eucalyptus, 2 plots for Acacia auriculiformis and 1 plot for

mixed Eucalyptus & Acacia depending on area of each species The plot locations were

based on positions of forest types Based on the map of classification forest types from a database of secondary data to determine the position of each plot The size and the shape of the plot is a trade-off between accuracy precision time and cost for measurement In this study, the plot were rectangular We choose a central point at a random point and take note for it From a central point, we make two directions the line AB (25m) is perpendicular to the CD (20m) (Figure 2.3)

c Measure DBH by Fiberglass tape

In principle, diameters are measured by default at 1.3m height The measuring unit for the diameter is cm with one decimal Some typical situations occurring when measuring diameters and their corresponding measurement points are illustrated in below Figure

19

Figure 3.2 Definition of breast height [18]

Reference is the ground level (soil), litter and tree debris at the base of the tree needs to be removed first To get the correct breast height during the measurements, it is highly recommended to use a ranging rod, a stick of accordant length or to measure 1.3m

at the own body by keeping the height in mind or marking it somehow Note that an error

in diameter measurement highly influences volume calculation [17]

In this study, we used Fiberglass tape -A girth tape measures diameter indirectly The tape is wrapped around the tree to measure the circumference (C= 3.14*d) This value

is divided by PI (3.1415 ) to estimate diameter (d = C / 3.14) Often the tape has normal units (mm and cm) on one side and PI units on the other side The tape should be held relatively firmly (but avoid stretching) The tape should also be wrapped around the bole in

a perpendicular plane to the stem axis [19]

20

(a) (b)

Figure 3.3 Using Fiberglass tape to measure DBH (a) and Blume-leiss to

measure height (b)

d Measure tree height using Blume-leiss

The total tree was measured by using Blume-leiss, a height measuring instrument of medium size and weight [19] When measuring height, great care is needed to avoid errors Therefore, observe the following points: Search a point where both the top and the base of the tree are clearly visible This point is 15m or 20m or 30m or 40m depended on the total tree height

To measure total height, the following steps were implemented [19]:

- Selected a position, 20 m horizontal distance from the base of the tree where the tree trip and base can be seen

- Released the pointer by pressing the button on the side of Blume-leiss

- Looked at the tree tip, waited for a moment for the pointer to settle then pulled trigger

- Read the height directly from the 20m scale

- Looked at the tree base and repeated above steps

21

- Based on results from above steps to decide total tree high:

+ Add the 2 height together if surveyor looked up to the tree tip in step 3 and down

to the base in step 5

+ Subtracted the height to the base from the height to the tree tip if surveyors were

on sloping ground and had to took up to both the tree tip and the tree base

- Checked all reading and records

Figure 3.4 Measuring tree height

e Assess the quality of the tree

The quality of every tree with a DBH larger or equal to 5 cm is assessed independently [17]

Table 3.1 Assessing the quality of the tree

22

Table 3.2 Tree position inventory

Plot number:……… Inventory date:………

Surveyor:……… Forest type:………

1

2

……

3.1.3 Strip transect

a Measure canopy closure

A gap was defined as an expanded gap That is a canopy gap plus adjacent area extending to dominant trees bases surrounding the gap [18]

The plot was divided into 5 strips A gap was investigated if at least one base of surrounding trees lay in the plot That means that a gap was selected if at least one tree base was intersected by the plot boundaries

At the random point author used Gap Light Soft-ware to measure canopy closure

By analyzing in telephone, we had results The process of image analysis in the field starts after selection of the from camera button (Fig 3.5A) the photograph is then taken (Fig 3.5B and 3.5C) The camera must be held in the horizontal position, pointed upwards Most smartphones have a built-in camera both on front and rear side of the phone It does not matter which camera will be selected It is then possible to rotate or flip the taken photograph (Fig 3.5D) On photographs were taken with a narrow-angle lens the definition

of the hemispherical border has not relevant (Fig 3.5E) The hemisphere center and diameter are usually defined using the first photograph (Fig 3.5F) Also, lens projection is

Figure 3.5 The processing of using gap light analysis

24

b Measure ground cover and litter cover

Observation in ground cover and litter cover see the ground or dried litter it means the value of ground cover (or dried litter) is 1.0 If not, the value of ground cover (or dried litter) equals 0.0

Plot count is applied in this method It is simple and straightforward Each plot was divided into 5 strips, spacing between transects and distance between 4m We invested in

10 points in each strip belong to plot Then we estimated average value for each factor

Table 3.3 Survey of Canopy closure (CC), ground cover (GC), liter cover (LC)

Investigation Place:……… Investigation Date:………

Area of Date:……… Investigator: ………

1

2

25

Table 3.4 Calculation for stand information

m3 Gi is a basal area of the tree; Hi

is the height of the tree; F is tree form For plantation f= 0.55

Nha = Nplot * trees/ha Nplot is the number of trees in a

plot Splot is the area of each plot

in m2 Total basal area

of the stand per

h(Gha)

Gha= ∑

m2/ha Gi is a basal area of the tree;

Splot is the area of each plot in

m2 Stand volume

per ha (Mha)

Mha = ∑

m3/ha Vi is the volume of each tree;

Splot is the area of each plot in

m2

b Descriptive statistics for height and diameter variables

Descriptive statistics were calculated for diameter, height, and height commercial variables There are three types of descriptive statistical values They are a central tendency, statistical dispersion, and distribution characteristic values

26

Table 3.5 Methods of descriptive statistics

Central tendency Dispersion and variability

This refers to one number that best

summaries the entire set of measurements

That means that central tendency values

describe the most typical value in the

dataset

Measures of dispersion summarize the amount of spread or variation in the distribution of values in a variable There are many different measures of dispersion and variability of the set They are shown in the following table

Table 3.6 A measure of dispersion and variability [20]

Range R= Xmax - Xmin Different between the highest and lowest

values in the set

S= √ The square root of sample variation It will

also show the dispersion and variability of the

set

Coefficient of

Variation

S%= Indicates how much variation occurs

within the dataset

from the mean or uncertain of measurement Skewness is a measure of the asymmetry of the distribution If the skewness is positive, the peak curve will lie on the left compared to the mean and it is called positive skew Meanwhile, if the skewness is negative, the peak will move to the right

27

Figure 3.6 Types of Skewness [18]

Kurtosis is the degree of peakedness of a distribution A normal distribution is mesokurtic that is a bell-shaped curve A distribution having a relatively high peak is called leptokurtic with heavier tails, while the curve which is flat-topped is called platykurtic with lighter tails

- Using IBM-SPSS software to analysis

We assessed descriptive statistics in status plantation types at Hong Linh town

+ Firstly, we used a split file with Group based on Status

+ Secondly, we computed DBH, height, and commercial height variable into

descriptive analysis:

DATASET ACTIVATE DATASET1.DESCRIPTIVES VARIABLES=D1.3 HVN HDC STATISTICS=MEAN SUM STDDEV VARIANCE RANGE MIN MAX SEMEAN KURTOSIS SKEWNESS

c Quality of tree statistics

To assess the quality of the tree in each status, we also used IB-SPSS software in Custom table The algorithm following shows the ways to statistic quality of trees

28

Custom Tables

CTABLES /VLABELS VARIABLES=Status Quality DISPLAY=LABEL/TABLE Status [COUNT F40.0, ROWPCT.COUNT PCT40.1] BY Quality /CATEGORIES VARIABLES=Status ORDER=A KEY=VALUE EMPTY=INCLUDE/CATEGORIES VARIABLES=Quality ORDER=A KEY=VALUE EMPTY=EXCLUDE

d Frequency distribution

Frequency distribution of diameter and height variables were generated for the next analysis and discussions In order to generate frequency distribution for a continuous

variable, the five following steps were applied [18]

- Step 1: Selecting a class with width and calculate the number of classes Class limits are usually selected and fixed in order to compare the frequency distribution of plots more easily Therefore, in this research for the diameter variable, the minimum value was 4

cm, the class width of the diameter is 2 cm the class width of the height is 1m

- Step 2: Tallying data: Put each number into a suitable class A number was counted in a particular class if it equal to or less than the upper limit of classes

- Step 3: Computing frequency, percent, cumulative frequency for every class

- Step 4: Drawing frequency charts They will be bar chart or line chart

The following command shows the ways to statistic frequency distribution

3.2 Creating potential erosion map and erosion map of protected plantation forest in

HL town

3.2.1 Method approach

Method approach in this research concludes applying soil loss prediction of Quynh et.al 1996 and GIS & RS

a Soil loss prediction equation

The amount of soil erosion by water is an integration of the effects of vegetation cover, topographic features, climatic variables, and soil characteristics [1, 21] In this study, to define required forest areas for soil erosion protection, average soil loss per unit areas was spatially predicted for Vietnam by applying a soil loss equation prediction developed for Vietnam [1, 7]

Assessing the soil protection and erosion tolerance of some plantation forest types base on erosion prediction of Quynh et al The relationship between soil loss prediction and rainfall, slope, vegetation cover structures, and soil porosity factors can be found expression in the following equation [1]

CC is canopy closure (Max 1)

GC is ground cover (Max 1)

LC is litter cover (Max 1)

K is rainfall erosivity factor, calculating based on monthly rainfall

K = Σ (Ri /25.4)*{916+331lg [(-5.8263+2.481ln (Ri))/25.4]}/100 (2)

Ri is the amount of rainfall in month i (mm)

P (max 1) is Porosity is determined by the Bulk Density and Particle density of the soil

P= [1 - (BD / PD)]*100 (3) Where: P is Porosity; BD is Bulk Density; PD is Particle density

The Bulk Density (BD) with a capacity of 100 cm3

BD = M / V (4) Where: BD is Density (g/cm3); V is the volume of density tube (V=100 cm3); M is the dry weight of soil (g) Because we only knew bulk density so we can assume particle density is equal to 2.65g /cm3 (Base on Brady & Weil, 1996 and Liesch, 2013)

31

b Applying Arc-Gis in region scale

Area study is a region scale so applying GIS & RS will get high efficient in space simulation After linking the spatial or non-spatial data into Arc-gis, we use the IDW (Inverse Distance Weighted) interpolation To create a surface grid in Arc-GIS, the spatial analysis extension employs one of several interpolation tools Interpolation is a procedure used to predict the values of cells at locations that lack sampled points It‘s based on the principle of spatial autocorrelation or spatial dependence, which measure the degree of relationship/dependence between near and distant objects The characteristic of an interpolation can be controlled by limiting the input points used in the calculation of output cell values [11]

―IDW based on the extent of similarity of cells while methods such as Trend fit a smooth surface defined by a mathematical function The IDW function should be used when the set of points is enough to capture the extent of local surface variation needed for analysis IDW determines cell values using a linear-weighted combination set of sample points The weight assigned is a function of the distance of an input point from the output cell location The greater the distance the less influence the cell has on the output value.‘‘ [11]

Figure 3.7 Interpolation method [11]