remote sensing data and gis application study on landslide risk management in cho don district backan province vietnam

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY LE THI THU THAO REMOTE SENSING DATA AND GIS APPLICATION STUDY ON LANDSLIDE RISK MANAGEMENT IN CHO DON DISTRICT, BACKAN PROVI

THAI NGUYEN UNIVERSITY

UNIVERSITY OF AGRICULTURE AND FORESTRY

LE THI THU THAO

REMOTE SENSING DATA AND GIS APPLICATION STUDY ON LANDSLIDE RISK MANAGEMENT IN CHO DON DISTRICT,

BACKAN PROVINCE, VIETNAM

MASTER THESIS Study mode : Full-time

Major : Environmental Science and Management Faculty : Advanced Education Program

Thai Nguyen, July /2023

DOCUMENTATION PAGE WITH ABSTRACT

Thai Nguyen University of Agriculture and Forestry

Cho Don district, situated in the mountainous region of Bac Kan province in Northeastern Vietnam, experiences frequent landslides that have a significant impact on the life of local residents To develop a comprehensive understanding of the landslide risks in this district, a study was conducted utilizing various factors, including slope, rainfall, geological fault, soil types, land cover, and proximity to roads These factors were used as input data to generate a landslide risk map for Cho Don district in Bac Kan province The study employed a weight number estimation method to assess the landslide risks in the area and used ArcGIS to produce the landslide risk map The landslide risk map reveals that the southern regions of Cho Don, specifically eight communes including Yen Thinh, Ngoc Phai, Bang Lung, Phuong Viem, Dong Thang, Nghia Ta, Yen Phong, and Binh Trung, have medium, high, and very high landslide risk zones These areas account for approximately 21.92% of the total area of Cho Don On the other hand, the remaining 77.79% of the district, covering almost the entire area, consists of low and very low-risk zones for landslides

Date of Submission:

July 4th, 2023

ACKNOWLEDGEMENT

I would like to sincerely thank my adviser, Dr Nguyen Van Hieu for his tremendous advice and assistance during my master's thesis His knowledge and support enabled me to finish this thesis

I also want to thank Mr Tung and every member of the Geoinformatics Center for all the materials they gave and their enthusiastic assistance with my thesis

I am appreciative of the DAAD fellowship for enabling me to pursue this research and study in such an excellent program

I would like to express my profound gratitude to the Headmaster, the Advanced Education Program Officer, and all of the faculty at Thai Nguyen University of Agriculture and Forestry for their passionate instruction and dissemination of important information to me, which helped to create favourable circumstances for my success in university studies

In addition, I want to express my gratitude to my family for their kindness and encouragement during this process They made this trip feasible, without them it would not have been

LIST OF FIGURES vii

LIST OF ABBREVIATIONS viii

PART II LITERATURE REVIEW 5

2.1 Theoretical basis about Landslide 5

2.1.1 Landslide definition 5

2.1.2 Landslide types 5

2.1.3 Landslide reasons 9

2.2 GIS and Remote sensing definition 10

2.3 Application of GIS on landslide analysis in the world 11

2.4 Application of GIS on landslide analysis in Vietnam 12

PART III MATERIALS AND METHODS 14

3.1 Materials 14

3.2 Methods 14

3.2.1 Data collection 14

3.2.2 Inheritance method 16

3.2.3 Multi-criteria analysis method (MCA) 16

3.2.4 Flow chart of applying the model to build landslide risk map 20

3.2.5 Synthesizing, analyzing and processing data methods 20

PART IV RESULTS 21

4.1 Natural and socioeconomic condition assessment in Cho Don district, Bac Kan province 21

4.1.1 Natural condition 21

4.1.2 Economic and social development situation 24

4.2 Building landslide risk map, assessing the correlation between factors and landslide disaster in Cho Don district 24

4.2.1 Influence of slope on landslide 24

4.2.2 Influence of geological fault on landslide 27

4.2.3 Influence of traffic on landslide 30

4.2.4 Influence of soil types on landslide 33

4.2.5 Influence of land use on landslide 37

4.2.6 Influence of rain fall on landslide 40

4.2.7 Mapping landslide risk in Cho Don district 43

4.3 Proposing measures to reduce landslide risk in Cho Don district, Bac Kan province 48

4.3.1 Planning measurements 48

4.3.2 Technical measurements 52

4.3.3 Education measurements 54

PART V DISCUSSION AND CONCLUSION 55

5.1 Discussion 55

5.2 Conclusion 57

REFERENCES 59

LIST OF TABLES

Table 2.1: Landslide types and a condensed taxonomy of slope motions according

to Varnes (USGS, 2004) 6

Table 4.1: Classification of effects of slope on landslide formation 25

Table 4.2 Classification of effects of geological fault on landslide formation 28

Table 4.3: Classification of effects of traffic on landslide formation 31

Table 4.4: Classification of effects of soil types on landslide formation 34

Table 4.5 Classification of effects of land use on landslide formation 38

Table 4.6 Classification of effects of rainfall on landslide formation 41

Table 4.7: Results of the weighted calculations of the layers in the causing factors 44

landslide-Table 4.8: Landslide hazard hierarchy according to landslide susceptibility index 46

LIST OF FIGURES

Figure 2.1: Components of a landslide (David J Varnes, 1978) 5

Figure 2.2 Diagrams showing the main categories of landslide movement (United States Geological Survey, 2004) 7

Figure 3.1: Sentinel satellite image 2 in 2022 15

Figure 4.1 The administrative map of Cho Don district, Bac Kan province 21

Figure 4.2 The slope map of Cho Don district, Bac Kan province 26

Figure 4.3 The Influence map of the slope to the landslide 27

Figure 4.4 The geological fault map of Cho Don district, BacKan province 29

Figure 4.5 The Influence map of the geological fault to the landslide 30

Figure 4.6 The Traffic map of Cho Don district, BacKan province 32

Figure 4.7: The Influence map of the traffic to the landslide 33

Figure 4.8 The soil map of Cho Don district, BacKan province 36

Figure 4.9 The Influence map of the soil to the landslide 37

Figure 4.10: The Land use map of Cho Don district, Bac Kan province 39

Figure 4.11 The Influence map of the land use to the landslide 40

Figure 4.12: The rainfall map of Cho Don district, Bac Kan province 42

Figure 4.13: The Influence map of the rainfall to the landslide 43

Figure 4.14: Landslide risk map in Cho Don district, Bac Kan province 45

Figure 4.15: Landslide percentage by levels 46

Figure 4.16: Landslide risk area by levels 46

LIST OF ABBREVIATIONS

GISUSGS

MRI AHP MCA LRSM SOEM

CDB JICA

GEO

Geographic Information Systems United States Geological Survey Magnetic resonance imaging Analytical Hierarchy Process Multi-Criteria Analysis Landslide Risk Map

Seattle Office of Emergency Management

City of Diamond Bar

Japan International Cooperation Agency

Geotechnical Engineering Office

PART I INTRODUCTION

1.1 Research rationale

Bac Kan is a mountainous province in the Northeast region of Vietnam, with complicated topography, primarily hills and high mountains, a deep interior and upstream of the Cau River, Nang River system, and other rivers Due to its rugged terrain characterized by steep hills and mountains, Bac Kan Province is consistently vulnerable to the dangers of land and rockslides, which have a significant impact on the local living conditions In the province, there are approximately 300 locations where over 2,000 households reside in areas highly prone to landslides, especially during the prolonged rainy season The majority of families residing in these areas face safety hazards due to inadequate infrastructure investment and the presence of high slope, which increases the potential risk of landslides

Cho Don District is located in the western part of Bac Kan province, characterized by a rugged terrain with more than 90% of the area comprising hills and mountains The mountains have heights ranging from 400 to 1000 meters The average slope is approximately 25 to 30 degrees, while some mountain slopes reach as high as 45 to 50 degrees This is the major factor influencing the susceptibility to landslides in the area The vegetation cover is quite good Many areas still have natural forests with large trees, wide canopies, and minimal disturbance The geological characteristics of this area mainly consist of shale, clay, limestone, quartzite, and cemented sandstone belonging to the Phu Ngu, Mia Le, Pia Phuong, and Khao Loc stratigraphic formations There are also scattered

granite blocks of the Phia Bioc complex and small magma blocks of the Cho Don complex along the Northeast-Southwest fault line The degree of weathering here is quite strong, with thickness exceeding 10 meters in many places The primary weathering products are clay and loose silt, which tend to become muddy when exposed to water

The main rivers in Cho Don district are Nam Cuong in the north, Cau River, Pho Day River, and Binh Trung River in the south and the district has a dense network of rivers and streams, with their flow varying with the seasons The steep and rugged terrain creates waterfalls, deep gorges, and during the rainy season, there is a high velocity of water flow, making it prone to flash floods and landslides along the riverbanks During the dry season, many streams have turned into deep gorges The reduced water coverage has negatively impacted agricultural productivity The main flow of the streams is from north to south When the flood season comes, it frequently causes erosion along the riverbanks The majority of the terrain in the district has steep slopes, causing surface water to accumulate quickly Therefore, during the rainy season, there are often flash floods in the hilly areas and along the riverbanks, leading to overflow onto cultivated land and temporary flooding in the area near the streams Recently, there has been a decrease in forest area due to land use conversion, resulting in water scarcity, soil nutrient depletion, and erosion along the riverbanks (particularly in areas where rice is grown)

Under the influence of climate change and rapid urbanization in recent times, natural phenomena such as landslides, flash floods have been occurring

more frequently and with increasing severity Therefore, it is necessary to have the appropriate tools and timely solutions to minimize the damages caused by these natural disasters and landslides Building a map of landslide hazard zones to identify areas with a high risk of landslides is a necessary task and it is a useful tool to enhance the effectiveness of natural disaster management, landslide prevention and mitigation efforts With the support of remote sensing and Geographic Information Systems (GIS), the use of GIS will provide an effective solution for mapping and organizing data on the current status of landslides in a scientific and comprehensive manner

Derived from the reality and the aforementioned reasons, the study

researched on the subject: “Remote sensing data and GIS application study on

landslide risk management in Cho Don district, Backan Province, Vietnam”

1.2 Research objectives

 Mapping and Zoning areas of landslide risk in Cho Don district using

remote sensing data and GIS application

 Identifying the main factor causing landslides in Cho Don district

 Providing strategies to reduce the probability of landslides

1.3 Research questions and hypothesis

1.3.1 Research questions

 What elements significantly contribute to landslides in Cho Don district?

 What is the level of landslide risk in Cho Don district?

 What is the technique to assess the risk of landslides?

 What are the measurements to lessen the landslides in Cho Don district?

PART II LITERATURE REVIEW 2.1 Theoretical basis about Landslide

2.1.1 Landslide definition

The surface of earth is shaped by a variety of natural processes, one of which is land sliding Landslides are a subset of mass movement, a considerably larger category of slope dynamics "Landslide" denotes downward and outward movement of slope-forming materials composed of natural rock, soils, artificial fills, -or combinations of these materials (Varnes, 1978)

2.1.2 Landslide types

The kind of materials used and the method of movement can be used to distinguish between the many types of landslides Figure 2.1 displays a graphic representation of a landslide along with the terms used to describe its characteristics (Varnes, 1978)

Figure 2.1: Components of a landslide (David J Varnes, 1978)

Based on the type of movement and the type of material involved, distinct

types of landslides can be identified In a nutshell, the components of a landslide mass can be either rock or soil (or both); the latter is referred to as debris if it is mostly made up of coarser fragments and is defined as earth if it is mostly made up of sand-sized or smaller particles The type of movement refers to the internal mechanisms that really cause the displacement of the landslide mass: falls, slide, topples, or flow Table 2.1 illustrates clearly a classification scheme based on these factors and Figure 2.2 depict the main categories of landslide movement

Table 2.1: Landslide types and a condensed taxonomy of slope motions according to Varnes (USGS, 2004)

Topples Rock topple Debris topple Earth topple

Slides

Rotational

Rock slide

Debris slide ( soil creep)

Earth slide ( soil creep)

Translational

Lateral Spreads Rock spread Debris spread Earth spread

Flows

Rock flow (deep creep)

Complex Combination of two or more principal types

Figure 2.2 Diagrams showing the main categories of landslide movement (United States Geological Survey, 2004)

Slides: Although the general term "landslide" encompasses a wide range of

mass movements, the more specific use of the term only refers to mass movements where there is a clear zone of weakness that divides the slide material from more stable underlying material Rotational slides (fig 2.2A) and translational slides (fig 2.2B) are the two primary categories of slides A block slide is a translational slide in which

the mass that is traveling downslope is made up of just one unit or a small group of closely linked units (fig 2.2C)

Falls: Falls are sudden movements of geologic material masses, such as rocks

and boulders, that separate from cliffs or steep slopes (fig 2.2D) Separation takes place along discontinuities like joints, fractures, and bedding planes, and movement happens through free-fall, bouncing, and rolling

Topples: The forward rotation of a unit or units about a pivot point that is below

or low in the unit, under the influence of gravity, forces from neighboring units, or fluids in fissures, distinguishes toppling failures (fig 2.2E)

Flows: There are five primary types of flows, and each one differs significantly

from the others

a Debris flow: A debris flow is a type of swift mass movement in which a slurry made of loose soil, rock, organic matter, air, and water moves downhill (fig 2.2F) About <50 percent of debris flows are fines When there is significant precipitation or rapid snowmelt, which erodes and mobilizes loose soil or rock on steep slopes, debris flows are frequently the result

b Debris avalanche: This is another name for an exceptionally quick to very quick debris flow (fig 2.2G)

c Earth flow: Earth flows typically take the shape of an "hourglass" (fig 2.2H) A bowl-shaped dip or runout from the slope material creates the slope's head It typically happens in fine-grained materials or rocks that contain clay, on moderate slopes, and in saturated conditions The flow itself is elongate

d Mudflow: A mudflow is an earth flow that comprises at least 50 percent of sand, silt, and clay-sized particles and is sufficiently moist to flow quickly

e Creep: The gradual, continuous downward movement of soil or rock that forms a slope Shear stress that is large enough to create permanent deformation but not enough to cause shear collapse is what causes movement Curved tree trunks, twisted fences or retaining walls, tilted poles or fences, and minor soil ripples or ridges are all signs of creep (fig 2.2I)

f Lateral spreads: Lateral spreads are distinctive because they usually occur on very gentle slopes or flat terrain (fig 3J) The dominant mode of movement is lateral extension accompanied by shear or tensile fractures The failure is caused by liquefaction, the process whereby saturated, loose, cohesionless sediments (usually sands and silts) are transformed from a solid into a liquefied state Failure is usually triggered by rapid ground motion, such as that experienced during an earthquake, but can also be artificially induced When coherent material, either bedrock or soil, rests on materials that liquefy, the upper units may undergo fracturing and extension and may then subside, translate, rotate, disintegrate, or liquefy and flow Lateral spreading in fine-grained materials on shallow slopes is usually progressive The failure starts suddenly in a small area and spreads rapidly Often the initial failure is a slump, but in some materials movement occurs for no apparent reason Combination of two or more of the above types is known as a complex landslide

2.1.3 Landslide reasons

There are two main factors that cause landslides Preparatory factors and Triggering factors in which Preparatory factors are dynamic factors that by definition reduce the margin of stability in a slope over time without actually initiating movement (JF Shroder Jr, 2021), for instance: reduction in strength by weathering

(Samuel T McColl, 2022), climate change (Jun Lim Wong et al., 2021), and tectonic uplift (Chenxiao Tang et al., 2019), operate over long periods of geomorphic time whereas others may be effective in shorter time periods, for example, slope overstepping by erosional activity (Maurizio Lazzari et al., 2019), deforestation (Ilenia Murgia et al., 2022), or slope disturbance by human activity (Melanie J Froude et al., 2018) and Triggering factors are those factors that initiate movement, it means shift the slope from a 'marginally stable' to an 'actively unstable state The most common triggering factors are intense rainstorms, prolonged periods of wet weather or rapid snowmelt, seismic shaking and slope undercutting (JF Shroder Jr, 2021)

2.2 GIS and Remote sensing definition

Natural disaster assessment has received a lot of attention because to Geospatial Information Systems (GIS), a computer-based system for data capture, input, manipulation, transformation, visualization, combination, query, analysis, modeling, and output (Carrara, 1983) The 1960s saw the creation of the geographic information system, which has advanced significantly during the last ten years Today, GIS is a vital tool in the socioeconomic and defense sectors of many nations across the world GIS can help managers, enterprises, and individuals to analyze the state of processes, natural resources, and socio-economic institutions through on the basis of the coordinates of the input data, a consistent geometry (map) is associated with the functions of information gathering, management, querying, analysis, and integration

Remote sensing is the process by which a recording device that is not physically in contact with the features being observed gathers and measures data

about specific characteristics of occurrences, objects, or materials This is a fairly inclusive definition that includes, for example, medical technologies like X-rays and magnetic resonance imaging (MRI) Remote sensing is a term used to describe a variety of methods used to capture electromagnetic radiation coming from places or things on (or in) the surface of the Earth, including its oceans and atmosphere (Short, 2010)

2.3 Application of GIS on landslide analysis in the world

Several studies on the use of GIS, remote sensing in warning of natural catastrophes like flash floods and landslides have been conducted recently throughout the world

In 2003, Mowen Xie and their team created a new way to study slope stability using a special computer model They combined the spatial analysis function of geographic information systems (GIS) and a hydrologic analysis and modeling tool with a column-based three-dimensional (3D) slope stability analysis model The minimum 3D safety factor for each slope unit can be produced by using this hydrologic analysis and modeling tool, dividing the entire research area into slope units, and using each slope unit as a study object The landslide hazard can then be mapped for the entire study region (Mowen Xie et al., 2003)

In 2004, Lan et al conducted research on the application of GIS in the modeling of landslide hazards In this study, author Lan and colleagues used remote sensing to investigate the primary elements for landslides to occur and make predictions about the likelihood of landslides in the future (Lan et al., 2004) In 2010, Biswajeet Pradhan used a Geographic Information System (GIS) and remote sensing data to map the susceptibility to landslides in a portion of the

Selangor area, Malaysia, utilizing fuzzy logic relations The findings demonstrate that maps of landslide susceptibility created using a fuzzy gamma operator exhibit comparable tendencies to those discovered using logistic regression (Biswajeet Pradhan, 2010)

In 2018, Barira Rashid and Javed Iqbal studied the application of remote sensing and GIS in changing forest cover along Karakoram Highway In this study, the author has applied remote sensing, using satellite images to determine different types of land use and forest cover and its spatial distribution in the study area, thereby establishing forest cover map in different time periods in the study area to assess the extent of causing landslides and forest degradation (Barira Rashid and Javed Iqbal, 2018)

2.4 Application of GIS on landslide analysis in Vietnam

Due to the rapid advancement of information technology, remote sensing and GIS have made some progress in scientific study in Vietnam nowadays The classification of the cover and the provision of warnings for natural catastrophes like as storms, floods, landslides, etc have been accomplished precisely and

effectively by remote sensing in several studies

In 2013, An information system to enable landslide hazard warning was built using GIS technology and the AHP hierarchical analysis method, according to research by Nguyen Tan Khoi and Bui Duc Tho The research findings aimed at early warning by merging two types of data: static data, which are hazard maps of all levels, and dynamic data, which are recorded rainfall in real time from hydrological stations This system was implemented in a trial in Quang Ngai province The trial results demonstrated the feasibility of the application (Nguyen

Tan Khoi & Bui Duc Tho, 2013)

In 2014, Researchers Mai Thanh Tan & Nguyen Van Tao have used remote sensing, GIS and MCA method to examine landslides in the Thua Thien Hue region A landslide risk prediction map was produced in Thua Thien Hue province by the author using remote sensing technology and satellite image data (Mai Thanh Tan & Nguyen Van Tao, 2014)

In 2014, The steep regions of Phu Loc district, Thua Thien Hue province, where research on landslides was concentrated, where research on landslides was concentrated Nguyen Huy Anh and Ho Ngoc Anh Tuan identified it as landslide zones by using Landsat satellite pictures and remote sensing technology A map of the research area's present landslide situation has also been created (Ho Ngoc Anh Tuan & Nguyen Huy Anh, 2014)

In 2018, Dang Thi Ha et al used the Analytic Hierarchy Process (AHP) integrated with ArcGIS software to develop a landslide hazard map for Van Yen district, Yen Bai province The research results showed that areas with high and very high landslide hazards accounted for 21% of the total area of the district (Dang Thi Ha et al., 2018)

In 2021, Nguyen Huu Ha investigated the state of affairs and the causes of landslides along important thoroughfares in the province of Binh Dinh In order to assess areas that are at danger of landslides on some important routes, research using density statistics, logistic regression, and artificial neural network models is being done combining the research on rain thresholds that trigger landslides to give early warning of dangers on several important highways in Binh Dinh province (Nguyen Huu Ha, 2021)

PART III MATERIALS AND METHODS 3.1 Materials

The data serves for the establishment of a landslide risk map for Cho Don district, Bac Kan province, including: 30-meter-high digital model (DEM), Sentinel satellite image 2, the data on precipitation in the Cho Don district, 5 element maps used: Traffic map, Land use map, Soil types of map, Geological fault zone map, Vegetation map and the data on landslide points in Cho Don district

3.2 Methods

3.2.1 Data collection

Data collection is the process of gathering and measuring information on variables of interest, in an established systematic way that enables one to answer stated research questions, test hypotheses, and evaluate outcomes (Kabir & Syed Muhammad, 2016)

In this study, DEM and sentinel satellite image 2 which are free downloaded from website https://earthexplorer.usgs.gov/ and https://scihub.copernicus.eu/

Figure 3.1: Sentinel satellite image 2 in 2022

To achieve more precise research outcomes, it is important to carefully choose and download Sentinel satellite image 2 which possesses superior quality with high contrast and exhibits minimal cloud coverage about below 10 percent or no clouds

The data on precipitation in the Cho Don district was obtained from the meteorological station in Bac Kan

Traffic map and Land use map from the Department of Natural Resources and Environment in Bac Kan

Geological fault zone map and the data on landslide points in Cho Don district was inherited from the report of the project "the Study and Assessment of Landslides in Bac Kan Province by the Geoinformatics Research Centre in 2020”

3.2.2 Inheritance method

A technique called the inheritance method builds and develops the essential data for research by utilizing and inheriting existing papers on study topics This study utilizes data that has been collected from earlier research on landslides and the use of GIS (geographic information system) in landslide studies in Vietnam, such as the study and assessment of landslides in Bac Kan province by the geoinformatics research center in 2020 and the research and assessment of landslides in Thua Thien Hue province by Mai Thanh Tan and Nguyen Van Tao in 2014

3.2.3 Multi-criteria analysis method (MCA)

Multicriteria analysis (MCA) is a set of systematic procedures for designing, evaluating, and selecting decision alternatives on the basis of conflicting and incommensurate criteria (Malczewski, 2018) In this methodology, preferable targets and goals are particularized and corresponding characteristics and indicators are recognized (Dodgson et al, 2009)

The input variables for this study were the elements that directly affected the landslide problem in Cho Don district, Bac Kan province (forest cover, slope, rainfall, soil, geology, transportation system, etc.) and were determined using the multi-criteria analysis approach

In order to score the input data layers in the map, input data and weights wew supplied based on study and field survey on landslides that have happened throughout the whole province The listed formulas were used to calculate the scores of input data classes

The Xi score of an input variable is given between 1 and 9 on the basis of normalizing the landslide density according to the formula:

Xi = + ( )− − ( )( ) *8 (Formula 1)

Where:

- Xi: Evaluation score for class i of a variable (class i is the data class inputs, including forest cover, slope data, rainfall, traffic system , geology, soil)

- Mi: The landslide density of layer i;

- Min(M): The smallest landslide density value in the area; - Max(M): The largest landslide density value in the area;

Evaluate the role of the input variables determined by the weights Wj:

Wj = ( Formula 2)

Where:

- Wj - weight of variable j;

- Nj - Number of landslides that can be caused by factor j

The landslide warning was done based on the landslide hazard zoning map, which was quantitatively evaluated through integrating input variables according to the following formula:

H= ∑ (Formula 3)

Where:

- H- the risk of landslides

- Xij-Score of class i of in factor j

- Wj-Weight of variable j

Input factors affecting landslide risk was classified according to criteria and levels as shown in the table below

Table 3.1: Classification of factors affecting landslide risk

After the computation, the H-index, which measured the risk of landslides, was determined and then create a map depicting landslide danger of Cho Don district The attribute table of landslide risk map included the H-index, and using that, 5 categories was classified from landslide risk data (Very high, high, medium, low, very low) The H-index and the risk of landslide is directly inversely correlated, meaning that the danger of landslides will increase as the H-index rises and vice versa

The threshold values for the four risk levels are as follows: very low (<2), low (2-4), moderate (4-6), high (6-8), and very high (>8)

3.2.4 Flow chart of applying the model to build landslide risk map

Figure 3.2: Flow chart of applying the model to build landslide risk map

3.2.5 Synthesizing, analyzing and processing data methods

Once the data was computed using Excel, the outcomes were condensed and assessed in a tabular form

Collecting data, Conducting field surveys

Sentinel satellite image 2, DEM

Soil map

Geological fault zone

map The data on

precipitation

Land use map

Processing data, normalizing map

Landslide points

map

Calculating weights using the multi-criteria method

Weight of average

rainfall

Weight of different types

of land cover

Weight of distance from both sides of the road

Weight of distance from geological fault zones

Weight of slope

Weight of different types of soil

Layering data, calculating raster

Landslide risk map

PART IV RESULTS

4.1 Natural and socioeconomic condition assessment in Cho Don district, Bac Kan province

4.1.1 Natural condition a Geographical location

Figure 4.1 The administrative map of Cho Don district, Bac Kan province

Cho Don district is located in the west of Bac Kan province, has a natural area of 91,115.00 ha, accounting for 18.75% of the natural area of Bac Kan province Cho Don district has one town (Bang Lung) and 21 communes With geographical location from 105 25' to 105 43' East longitude, from 21 57' to 22 25' North latitude The center of the district capital is Bang Lung town, about 46km from Bac Kan town along provincial road 257 Cho Don district has a fairly complete traffic system with provincial roads 254, 254B, 255, 257 relative inter-commune routes completing and creating favorable conditions for the district in trade exchanges, socio-economic development, tourism

b Topographic

Cho Don district is a mountainous district of Bac Kan province, with the altitude decreasing from north to south, from east to west with common terrain types:

Limestone terrain: The northern communes belong to the limestone plateau extending from Ba Be district to Bang Lung town The terrain is complicatedly divided by limestone mountains with an altitude of over 1000m (Phia Khao Mountain, Ban Thi commune) interspersed with narrow valleys, with an average slope of 25 to 30 m This is where the headwaters of rivers flow to Ba Be Lake

Mountainous terrain: The communes south of Bang Lung town are mostly dirt mountains with a common height of 400m to over 600m, the average slope from 20 to 25 m The terrain is strongly divided by a rather dense system of rivers and streams

Valley topography: distributed along rivers and streams interspersed between high mountains The natural conditions are generally quite favorable for the development of agroforestry farming, fruit trees, and specialty trees

c Hydrometeorology

The winter (from October of one year to April of the next) is cold, low air temperature, dry, with hoarfrost; the summer (from May to September) is hot and humid, with a lot of rain These weather patterns are caused by the high temperature of the Tropic of Cancer and the replacement of large seasonal circulations, combined with topographical conditions The average yearly air temperature is 23.2oC, with the greatest average air temperature being 26.5oC and the lowest being 20.8oC

The average annual precipitation is 1,115 mm The months with heavy rainfall are June and July with rain days up to 340mm/day; the lowest is in December and January next year 1.5mm/day The rainy season is from May to October and accounts for 75-80% of the annual rainfall The average air humidity is 82%, the lowest in February with 79% and the highest in July to 88%

Cho Don district has a dense system of rivers and streams, but most of them are tributaries upstream of Cau River, Nang River, Pho Day River, and Binh Trung River with common characteristics of watershed, short riverbed, sloping, erratic hydrodynamics River traffic is less developed due to steep rivers and streams, many waterfalls and rapids Some streams dry up in the dry season, but in the rainy

season, flash floods can occur, which adversely affects life of people

4.1.2 Economic and social development situation

The economy of Cho Don district is still dominated by agriculture because the terrain is in an extremely difficult economic area, so the development ability in industry and services is still limited In recent years, Bac Kan province has focused on economic development in the district, which calls for investors to conduct exploration and exploitation of mineral resources (most are iron and lead ores, data on reserves of these minerals are not yet available) Therefore, the economy has made great progress, contributing to the general development of Bac Kan province Over a long period of formation and development, today, Cho Don's population has reached about 50,000 people, with 5 ethnic groups living together: Tay, Nung, Dao, Kinh and Hoa The largest number in the district is the Tay ethnic group (about 70%) The Tay people appeared earlier and were the subjects of this land

4.2 Building landslide risk map, assessing the correlation between factors and landslide disaster in Cho Don district

4.2.1 Influence of slope on landslide

The most crucial factor in determining how landslides start and progress is the topographic slope The stability of the slope decreases with increasing slope angle, and vice versa; a landslide cannot occur at a slope of zero

The slope map is built from the elevation digital model (DEM) Then, divide the classification into five categories in accordance with the rising slope interval; the danger of landslides is inversely proportional to the steepness of the slope (Table 4.1, figure 4.2)

Table 4.1: Classification of effects of slope on landslide formation

Factor Classification Landslide

points Areas (ha) Density

Landslide Susceptibility

The area with a slope of 5° -15° has only 17% of the landslide density, the smallest of all 5 levels, distributed mainly in the valleys of Nam Cuong, Dong Lac, Bang Phuc, Nghia Ta, Binh Trung and Yen Phong communes followed by a slope of 15° - 30° accounting for 17.5% of the landslide density which is assessed as having a low average influence on landslides

Notably, despite the fact that the slope 5° is the least prone to create landslides,

it has a density of 21.7% on average This slope level is present throughout the district, but landslide occurred only 7 points Therefore, it is rated as having a medium level of influence

Accounted for 18.47% of the total area, there are 70 points of landslide occurred, slopes ranging from 30 to 45 degrees considered to be a high risk of triggering landslides, mostly in Yen Thinh, Yen Thuong, Bach Thi, Xuan Lac, Nam Cuong, Dong Lac, Tan Lap, Bang Phuc, and Dong Thang

Figure 4.2 The slope map of Cho Don district, Bac Kan province

After creating a partition map of the data layers, assign sensitivity levels to the

map and edit it to form a map that evaluates the influence of slopes on landslides (Figure 4.3)

Figure 4.3 The Influence map of the slope to the landslide

4.2.2 Influence of geological fault on landslide

Landslide dangers are frequently caused by fault density, which has a direct impact on the density and size of the slip point The degree of shattered, cracked rock is what defines this element when examining individual sliding blocks The landslide process, however, is greatly impacted by this element when considered inside a territory Because the soil and rock in these places are typically easily