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BAKHAM CHANTHAVONG APPLICATION OF GEOSPATIAL TECHNOLOGY FOR FOREST RESOURCE MANAGEMENT IN THE NAM KA DINH NATIONAL PARK AREA, LAOS PEOPLE DEMOCRATIC REPUBLIC MAJOR: FOREST RESOURCE MANA

BAKHAM CHANTHAVONG

APPLICATION OF GEOSPATIAL TECHNOLOGY FOR FOREST RESOURCE MANAGEMENT IN THE NAM KA DINH NATIONAL PARK AREA, LAOS PEOPLE DEMOCRATIC REPUBLIC

MAJOR: FOREST RESOURCE MANAGEMENT

CODE NO: 9620211

SUMMARY OF PhD DISSERTATION

HANOI, 2022

Forestry

Supervisor: 1 Assoc Prof Dr Phung Van Khoa

2 Assoc Prof Dr Sithong Thongmanivong

This dissertation can be found at:

- National Library of Viet Nam

- Library of Vietnam National University of Forestry

PREFACE

1 The Urgency of dissertation topic

Laos is a country located in the tropics, with a natural land area of 23,680,000 hectares, forestry land accounting for 47% of the country's area Annually, the rate of forest changes is higher than the general average (2.5%) (MAFL, 2018) The process of change spread across regions, districts and provinces in which forests cover across the country In order to limit the fluctuation of forest resources, the Lao government has established a number of national parks and conservation areas in order to manage and sustainably exploit natural forest resources Nam Ka Dinh National Park (NKDNP), Bolikhamsay province was established in 1995, with a total natural land area of 168,550ha with 4 forest types divided by species composition (Statistical Yearbook of Bolikhamsay province, 2020) ) The area of natural forest in the National Park fluctuates with deforestation (MR) and forest degradation (STR) constantly increasing, causing the total area of natural forest to gradually decrease, the level of variation decreases by about 2.5%/year ( Bolikhamsay Department of Agricultura and Forestry -DARB, (2020)

The question: Why is the area of natural forest still fluctuating? How to determine that level of volatility? Currently, forest changes are often detected directly by the staff and organizations, forest owners and local people, etc., along with the strong development of information technology, which must be mentioned Geospatial technology has played an important role in detecting and assessing changes in forest resources

In Laos, the geospatial technology is increasingly being applied in the field of management, monitoring and assessment of changes in forest resources such as: forest inventory and survey; monitoring forestry activities (afforestation, logging, etc.) However, because it has not been widely applied in assessing changes in forest resources in some national parks and protected areas, including NKDNP, and there is little understanding of the current status of forest resources in the district, The main causes of fluctuations have not been identified as a scientific basis for forest management solutions, so the sustainable management of forest resources here is facing many difficulties, notably:

- It is not possible to determine the extent of changes in forest resources over time;

- The main factors causing the fluctuations have not been identified soon;

- Solutions for applying geospatial science and technology in forest resource management have not yet been proposed

In order to contribute to solving the above-mentioned problems, we conducted the

doctoral dissertation topic "Application of geospatial technology for forest resource

management in the Nam Ka Dinh National Park Area, Laos People Democratic Republic"

This conducted is very necessary and has high theoretical and practical significance

2 Objectives

2.1 General objective: Application of geospatial technology to early detect deforestation and

forest degradation contributes to improving the efficiency of forest management and protection and monitoring of forest resources changes in the Nam Ka Đinh National Park Area, Lao PDR

3 Subjects

application of geospatial technology in monitoring and early detection of deforestation, forest degradation and regrowning forest and solutions to promote the application of geospatial technology, improve the efficiency of forest management in the study area

4 Scientific and practical significance of the dissertation

- Scientific significance of the dissertation: The dissertation contributes to upplementing the relative index threshold reflecting the change of remote sensing index with the atmospheric resistant vegetation index (ARVI) on Sentinel 2 satellite images as a scientific basis for the development of satellite images early deforestation, forest degradation and regrowing forest in the area of Nam Ka Dinh National Park, Lao People's Democratic Republic

- Practical significance of the dissertation The research results of the dissertation initially proposed the technical process of applying geospatial technology in forest resource management in Nam Ka Dinh National Park, Lao People's Democratic Republic from satellite images Sentinel 2

5 New finding of dissertation

The dissertation has identified the relative index threshold for early detection of deforestation, forest degradation and regrowing forests in the Nam Ka National Park area with the use of the ARVI spy on Sentinel 2

6 Dissertation structure

In addition to the introduction and conclusions, references, appendices, the dissertation

is structured into 3 chapters

A total of 120 pages of dissertation, of which: Introduction - 4 pages; Chapter 1: Literature review – 20 pages; Chapter 2: Contents, research methodologies and Natural conditions of the Research area - 23 pages; Chapter 3: Results and discussion - 73 pages; Conclusion, existence, recommendation 4 pages; References 8 pages In this dissertation, there are 34 tables, 29 figures

CHAPTER 1 LITERATURE REVIEW

The dissertation has referred and summarized about 3 main related issues: (1) The concept of deforestation; forest degradation anh regrowed forest; (2) Scientific basis of geospatial technology; (3) Research and application of geospatial technology in forest resource management in the world, Vietnam and in Laos PDR

1 About the concept of deforestation; forest degradation anh regrowed forest

Overview of research problems has helped to correct and comprehensively aware of The concept of deforestation; forest degradation anh regrowed forest

2 About Scientific basis of geospatial technology

The overview of the research problem has helped to have a correct and comprehensive understanding of the scientific basis of Geospatial Technology Accordingly, the scientific basis of Geospatial Technology is a combination of many technologies applied in forest resource change assessment and management to meet the purposes of sustainable management and business

3 About Research and application of geospatial technology in forest resource

management in the world, Vietnam and in Laos PDR

The research problem overview helped identify outstanding achievements in using geospatial technology to assess variability Outstanding Achievements about:

- Measures using post-classification comparison techniques to determine changes in forest resources over time in the world, in Vietnam and Laos

- Measures using change detection algorithm to identify changes in forest resources over time in the world, in Vietnam and Laos

4 About limitation of the research

Although many achievements have been made, researches on the application of natural forest rehabilitations in the world still limited, which can summarize a number of key issues

Technology application has not been able to cover and exploit to the fullest the advantages brought by the geospatial technology system, the system of remote sensing image documents, new studies have only focused on using a number of remote sensing technologies remote sensing, GIS software and a number of remote sensing image documents, popular remote sensing indexes such as: Landsats; SPOT photo; MODIS photo; Sentinel 2 satellite images and some remote sensing indexes such as: NDVI, NBR

For some research of that in Laos, it is possible to summarize some of the main shortcomings about the application of geospatial technology in forest resource management

in general and in the Nam Ka Đinh National Park in particular as follows:

- There is little/no application of geospatial technology in defining characteristics and changes in forest (D, FD and FR) forest resources over time;

- The main factors causing changes in forest resources have not been identified;

- The main causes of D, FD and FR have not been classified and analyzed;

5 Identify research problems for this dissertation

The main products of this dissertation are: to define boundaries, demarcate and mark the functional subdivisions and buffer zones of the NKD National Park; clearly demarcate the planned land area for purposes other than those planned for the NKD National Park in order

to harmoniously develop forest protection, environmental protection, nature conservation and conservation of wildlife species endangered, precious, rare Proposing a process to guide the monitoring, inspection and monitoring of forest resources and biodiversity in the NKDNP in

order to effectively conserve and prevent deforestation, encroachment, and illegal conversion

of use purposes in the NP However, with the content of the thesis topic, the main approach

of the topic is: Applying geospatial technology in forest resource management in the National Park to provide periodic and regular information on: (i) Deforestation and degradation of forest resources; (ii) Regrowing forest area

This research dissertation has profound scientific and practical significance in order to overcome the shortcomings of previous studies, contributing to providing a technological process to ensure effective management and monitoring of forest resources

CHAPTER 2 CONTENTS, RESEARCH METHODOLOGIES AND NATURAL CONDITIONS

OF THE RESEARCH AREA 2.1 Research contents

2.1.1 Research on the current status of forest resources and factors affecting the management of forest resources in the Nam Ka Dinh National Park area

(a) Characteristic of the structure of forest plant communities

(b) factors affecting the management of forest resources

(c) Infrastructure for applying geospatial technology in forest resource management

in the area of NKDNP

2.1.2 Determining relative index threshold to detect deforestation and forest degradation

in the Nam Ka Dinh National Park

(a) Building datasets on deforestation and forest degradation:

b Determination of remote sensing index threshold

c Assessing the accuracy of detecting

2.1.3 Determining relative index threshold to detect regrowing forest in the Nam Ka Dinh National Park

(a) Building datasets on deforestation and forest degradation:

b Determination of remote sensing index threshold

c Assessing the accuracy of detecting

2.1.4 Proposing the applicable direction of geospatial technology to detect deforestation and forest degradation and regrowing forest in the NKDNP Area

(a) Proposing the applicable direction of geospatial technology to detect deforestation

and forest degradation and regrowing forest in the NKDNP Area

(b) Proposing a number of support measures to improve the efficiency of using

geospatial technology in forest resource management in the NKDNP Area

(c) Proposing solutions to improve the efficiency of forest management and protection

in the study area

2.2 Research method

2.2.1 Methodology

Scientific basis: The scientific basis of optical remote sensing image source is the spectral reflectance of natural objects, which can be analyzed and shown, especially can detect and separate the areas of deforestation with separate regions Based on the spectral reflectance characteristics of objects, by specialized models and software, remote sensing image data is processed to identify and separate each object Multi-temporal remote sensing image source allows to quickly determine changes in forest cover in general and forest loss

in particular in the time interval between the time of image acquisition After extracting

information about forest objects, it is possible to create maps of the current status and calculate specific areas at each time as well as synthesize and analyze results on distribution and changes

Atmospheric Resistance Vegetation Index (ARVI) represents the quality of green vegetation on the ground, this index value ranges from -1 to +1, the higher the value, the thicker the vegetation For forest objects, this index is quite high (about 0.6 to 1), when this value is reduced, plants are lost, or in other words, forests are lost Similar to other vegetation indices, the index's value will represent vegetation quality in one way or another

- Selection of research data

+ Method of extracting ARVI value for sample points on imagery: ARVI value is extracted at sample points on satellite imagery using Extract Multi Values to Points tool in ArcGIS 10.3 software

+ Used satellite imageries: the dissertation uses Sentinel 2 satellite imageries, Sentinel 2 satellite imageries are downloaded from GEE The satellite imagery has been converted to surface spectral reflectance value (SR) These imageries include 2 Bands Cloudy pixels in the imageries have been reverted to “No Data” through the commands in GEE

Experience in the world, in Vietnam as well as in Laos shows that almost no remote sensing index (NDVI; NBR; SAVI; ARVI; IRSI; NDSI; EVI) has outstanding advantages compared to other indicators other under all conditions Therefore, the application of remote sensing indicators depends on the specific conditions of each region as well as the existing measurement database system in that region

Applying The findamental points of the dissertation, a diagram of the research approach

of the dissertation is shown below

More details were explained in following sections:

Figure 2.1 An overview of the research methodology

2.2.2 Specific research methods

The methods are presented according to each research content of the thesis

2.2.2.1 Methods of investigation and assessment of forest status and forest fires in the study area

(i) Determine the type of forest / forest status distributed in the area:

Classification of forest types/states is determined according to the classification system prescribed in the Lao Forestry Law 2019 (Laos National Assembly, 2018)

(ii) Methods of characterization of forest states

In order to fully collect the characteristics of the forest structure and status, the thesis sets up survey routes The survey route is a typical route (typically according to the type of forest),

representative of the forest types, the length of the route is unknown (according to the length

of the forest type)

The extensive field surveys were conducted with munbers typical standard forest plots

2.2.2.2 Determining relative index threshold for detection of deforestation and forest degradation on Sentinel 2 imageries in the NKDNP

(1) Collection and Analysis of Secondary Data

Secondary data and information were collected by reviewing the relevant literature and documents obtained from Provincial and District Agriculture and Forestry Offices in Borlikhamxai, NKDNP offices and other agencies We also obtained data on community forest and forest encroachment from the Department of Forestry, Ministry of Agriculture and Forestry Statistical data and information is obtained from District Agriculture and Forestry Offices and village committees

Sentinel 2 Satellite dataset from 2016 and 2019 were used to map deforestation and forest degradation areas for the two periods and analyze the trends in forest area and its condition The Satellite images were freely downloaded from the Google Earth Engine (GEE) Two scenes were acquired (T48QVF and T48QUF) to cover the entire landscape of the study area

The image scenes were ortho-rectified with the help of ground control points and a digital terrain model to remove the distortions arising from variations in topography, and then projected into Universal Transverse Mercator 1984 zone 48N (WGS_1984_UTM_Zone_48N) datum The images were classified through visual interpretation Due to limitation and time availability for the classification and insufficient ground truth data The analyses were carried out in GEE and ArcGIS software

(2) Collection and Analysis of Primary Data

* Collection of deforestation and degradation samples: Samples of deforestation and forest degradation were collected in the NKDNP during the period from 2016 to 2019 Selected a total

of 212 deforestation samples The total number of selected forest degradation samples is 90 samples 75 The samples as shown in Table 2.2

Table 2.2 The mumber of samples to determine the threshold and assess the accuracy

Sample to

determine the threshold

Sample to assess the accuracy

Relative index is calculated by formula as follows:

ARVI = [NIR - (2 × RED) + BLUE] / [NIR + (2 × RED) + BLUE] (2.4)

The dissertation has used relative KB index to determine the threshold: forest degradation, deforestation through the use of remote sensing indicators (ARVI))

KB (ARVI) = (ARVIT2 - ARVIT1) × 100 / ARVIT1 (2.5) Where: T1 is the value of the remote sensing index at the time before the impact

T2 is the value of the remote sensing index at the time after the impact

2.2.2.2 Determining relative index threshold for detection of regrowing forest in the NKDNP

The samples as shown in Table 2.3

Tables2 3 Structure of the sample plots with the investigated forest:

3 Forest rehabilitation post planted tree log 20

4 Forest rehabilitation post shift cultivation 16

T2 is the value of the remote sensing index at the time after the impact

2.2.2.4 Methods of assessing the accuracy

Methods of assessing the accuracy of detecting deforestation and forest degradation The thesis uses 150 deforestation samples and 90 deforestation samples in 2018 in the Central Highlands

Percentage detected (%) = the number of detected examples

the total number of examples 𝑥100 (10) Where: M is rate of difference in area (%); n is the total number of examples; At is the realistic area (ha); Ft is the detected area in the imagery (ha)

2.2.2.5 Proposing the applicable direction of geospatial technology to early detection of deforestation and forest degradation and regrowing forest in the NKDNP

The results of establishing a scientific basis and determining the threshold of relative KB index for early detection of deforestation and forest degradation are used as the basis for proposing the direction of applying geospatial technology to early detection of deforestation,

forest degradation and regrowing forest in the NKDNP

2.3 Characteristics of the NKDNP area

- Natural conditions of the research area

The NKDNP is located in the Northwest region of Bolikhamsay province, about 173

km north-west of Vientiane, the capital of Laos (18015’–18055’N; 103049’–104031’E))(Figure 2.6) The total natural area is 808 hectares

Figure 2.6 Geographic location, boundaries and area of NKDNP

- Climate, soil and hydrological

Annual mean temperature ranges from 20,2°C to 22,5°C The 11 years mean temperature during survey was recorded at 21,1°C The total mean rainfall ranges from 124,5mm month-1 Rainfall is concentrated from May to November, accounting for 70 -75%

of annual rainfall

The NKDNP has two main stream systems They are headwaters of two rivers in the area: Pui River, Phun River and Loop River, Nham River There are many small streams, relatively high density, distributed evenly over the area of the national NKDNP The stream flow is often greater in the rainy season, and during the dry season they are not dry but have low water flow

The geological background of NKDNP is formed from the following four rock groups: acid magma rock group, mainly granite rocks; neutral alkaline magma group, mostly basalt; shale group, mainly clay schist, mica schist and accreting matter group along streams, mostly new alluvium

Brown-red feralit soil developed on neutral alkaline magma rock: About 40% of the total areas are these soils They often appear at Eastern slopes of NPNP range The soil layer

is thick, slightly acid with PHkcl

The geological formations consist mainly of a yellow - red lateritic loamy soil derived from quartz with pH varying between 3 and 5 The hills around the plain consist mainly of sandstone, granite, and schist, with medium - rich loams

- Biological resources

The original vegetation cover of the area consisted primarily of Dipterocarps Forest; Mixed Deciduous Broadleaf Forests; Semi - Mixed Deciduous Broadleaf Forests; The forest types correspond approximately to the Dipterocarps Forest (mainly Dipterocarpaceae Fabaceae), Mixed Deciduous Broadleaf Forests (mainly Fabaceae) and (mainly Leguminosae)

CHAPTER 3 RESULTS AND DISCUSSION 3.1 Characteristics of the current status of forest resources and factors affecting the management of forest resources in the Nam Ka Dinh National Park area

3.1.1 Characteristics of the current status of forest resources in the Nam Ka Dinh

National Park area

The ratio of the area of land resources and some types of forests distributed in the protection area is shown in Figure 3.1

Figure 3.1 Rate of forest status in Nam Ka Dinh National Park

Acronyms in the figure: 1 Medium RTNLRTX: Medium evergreen broadleaf natural forest; 2: Poor RTNLRTX: Poor evergreen broadleaf natural forest; (3) Rich TNLRTX: Rich evergreen broadleaf natural forest; (4); RT: Planted Forest; (5) ĐNR: Shift cultivation land and 6 TC, rocks, soil: Area of grassland, rocky mountains and fallow bare land

Nam Ka Dinh forest with 168.550 ha of natural land, evergreen broadleaf natural forest with an area accounting for 90% According to the results of classification of forest resources according to the origin and composition of tree species, forest resources in the National Park area are divided into 3 types of forests: (1) Evergreen natural broadleaf forest and (2) Forest

type secondary broadleaf evergreen restored and (3) Plantation type: Acacia mangium;

Eucalyptus Urophyla; Teak and rubber plantations

3.1.2 Some structural characteristics on evergreen broadleaf natural forest types in protection forests

3.1.2.1.Characteristics of 3 evergreen broadleaf natural forest types in the Nam Ka Dinh National Park area

The survey results on a number of forest survey factors are summarized in Table 3.1

Table 3.1 Average indicators of some forest survey factors on forest types

M bq

(m 3 /ha)

Quality (%) Good

quality

Bad quality

(±2,12)

22,14 (±3,23)

34,333 (±4,23)

224,817 (±13,56)

83,42 (±12,62)

16,58 (±4,19)

Medium RTNLRTX , 43,87

Poor RTNLRTX, 23,6

Rich RTNLRTX, 16,73

ĐNR ĐMN

M bq

(m 3 /ha)

Quality (%) Good

quality

Bad quality

2 Medium forest 12,83

(±2,88)

18,71 (±2,89)

27,925 (±5,20)

179,522 (±12,89)

85,76 (±12,42)

14,24 (±4,45)

(±2,88

17,71 (±2,89)

15,950 (±5,20)

79,89 (±12,89)

81,11 (±12,42)

18,89 (±4,45)

4 No volume forest 4,59

(±2,21)

5,7 (±0,71)

88,60 (±11,41)

11,40 (±3,77)

Acronyms in table 3.1, G: Mean basal area ha -1 ( m 2 /ha -1 ); M: Mean stand volume ha

-1 ( m 3 /ha -1 ) D1 3: Mean of diameter at breat height per year (cm/year -1 ); Hvn: Mean of height per year (m/year -1 );∆G: Mean variation of basal area per year (m 2 /year -1 ha) (± SD = standard error)

With the current forest status of the NKD National Park's resources and the characteristics of a number of indicators of tree layer structure according to the main natural forest type, the type of degraded forest is studied as a basis and the basis is not only used as a sample area for extracting Exporting remote sensing index values, but also helping to calculate and interpolate the relative threshold of atmospheric resistant vegetation index KB (ARVI) to detect areas of deforestation and forest degradation

3.1.2.2.Characteristics of planted forest in the Nam Ka Dinh National Park area

The survey results on a number of forest survey factors are summarized in Table 3.2

Table 3.2 Average indicators of some plant forest types

No Planted forest

types

Unit year

M bq

(m 3 /ha)

Quality (%) Good

quality

Bad quality

1

Acacia mangium 1 4,52

(±1,21

5,5 (±3,23)

95,42 (±12,62)

4,58 (±1,19)

Acacia mangium 2 7,52

(±1,21

18,55 (±2,26)

19,75 (±2,63)

87,4953 (±5,4)

87,55 (±9,12)

12,54 (±0,91)

Acacia mangium 3 12,65

(±1,21

21,80 (±3,23)

24,69 (±2,45)

98,735 (±3,14)

92,35 (±8,45)

7,65 (±0,13)

2

Eucalyptus

Urophyla 2 (±2,18 11,23 (±4,11) 21,46 (±3,43) 23,15 93,2553 (±6,56)

87,55 (±9,12)

12,54 (±0,91)

Eucalyptus

Urophyla 3 (±1,98 15,98 (±4,29) 26,55 (±4,63) 31,33 103,665 (±8,4)

95,42 (±12,62)

4,58 (±1,19)

3 Tectona grandis 2 9,77

(±3,01

16,65 (±5,02)

22,45 (±4,22)

63,6733 (±6,71)

92,35 (±8,45)

7,65 (±0,13)

No Planted forest

types

Unit year

M bq

(m 3 /ha)

Quality (%) Good

quality

Bad quality

Tectona grandis 3 14,70

(±4,65

21,45 (±6,62)

27,21 (±4,63)

89,433 (±6,22)

87,55 (±9,12)

12,54 (±0,91)

4

Hevea

Brasiliensi 2 (±3,67 10,43 (±2,25) 11,58 (±5,55) 10,609 (±5,93) 63,775

87,55 (±9,12)

12,54 (±0,91)

Hevea

Brasiliensi 3 (±4,43 13,75 (±5,33) 14,78 (±6,15) 15,955 (±6,07) 81,877

79,54 (±11,77)

20.46 (±3,56)

Acronyms in table 3.2, G: Mean basal area ha -1 ( m 2 /ha -1 ); M: Mean stand volume ha -1 ( m 3 /ha -1 )

D1 3: Mean of diameter at breat height per year (cm/year -1 ); Hvn: Mean of height per year (m/year -1 );∆G: Mean variation of basal area per year (m 2 /year -1 ha ) (± SD = standard error)

With the current forest status of the NKD National Park's resources and the characteristics of a number of indicators of tree layer structure according to the main natural forest type, the type of degraded forest is studied as a basis and the basis is not only used as a sample area for extracting Exporting remote sensing index values, but also helping to calculate and interpolate the relative threshold of atmospheric resistant vegetation index KB (ARVI) to detect areas of regrowing forest

(c) Infrastructure for applying geospatial technology in forest resource management

in the area of NKDNP

3.1.3 Current status of infrastructure for geospatial technology application in Nam Ka Dinh National Park

3.1.3.1 Current status of infrastructure

- No LAN system and no server system

- The Nam Ka Dinh National Park Management Board has an Internet connection

- Connection line: ADSL line type Transmission line providers: ETL and Mphone Number of transmission lines 02 Broadband (Kbps)

- Personal computer system

- Private email system (personal)

- There is no website address about Nam Ka Dinh National Park

With the results on the current state of the above infrastructure, it is an important foundation in the application of geospatial technology systems, the number of computers, network connection lines and desktop configurations to meet technical requirements minimum for the application of geospatial technology in forest resource management in NPKNP

3.1.3.2.Current status of application software

Current status of application software and usage status are summarized in Table 3.3