Luận văn landslide hazard and risk assessment for road network using rs and gis

1.4 Scope and limitation LITERARUTE REVIEW 2.1 Hazard, risk & vulnerability 2.2 Landslide Hazard mapping 2.3 Fundamental of Remote sensing 24 GIS overview 2.5 Global Positioning System G

LANDSLIDE IIAZARD AND RISK ASSESSMENT FOR ROAD NETWORK USING RS AND GIS: A CASE STUDY OF XINMAN

DISTRICT, VIET NAM

by

Lai Tuan Anh

A thesis submitted in partial fulfillment of the requirements for the

degree of Master af Engineering

Examination Committee: Dr, Kiyoshi Honda (Chairpeason)

Dr Mare Sous

Dr Ulrich Glawe

Nationality: Vietnamese

Previous Degroc, Bachelor of Euginvering in Geodesy

Hanoi University of Mining and Geology,

Vietnam

Scholarship Donor: AIT Fellowship

Asian Institute of Technology School of Engineering Technology

Thailand

May 2006

ACKNOWLEDGEMENT

This with delight that dhe author Gast of all extends his heaties gratitude to the Thesis research committee Chairperson, DR Kiyoshi onda for his professional gnidance advice, cncouragement throughout the study

The technical and conceptual support of Dr Mare Somzis, thesis committee member, helped me

to conduct the research for which I exprese my thanks to him

Valuable suggestions support of Dr Ulich Glawe and thesis committee member help me to work enthnsiastically so | am grateful to him

T would like to express my sincere thanks to DANIDA for the scholarship and Star program for the research grand, thereby making this study possible

Spocial thanks go to RSL staff, Mr Do Minh Phuong for providing all the necessary on tine Tam gralefid lo the local in Xin Man province who provided and guide ae go lo all the landslide points to measurcment GPS

My vole of dunks goes to all my fiends, Mr Tran Trung Kieu, Miss Dao Thi Chau Hu, for their helps, supports, sharing the difficulties to my life in ALL

Most of all, 1 want to express my deep appreciation to my family: Parents, my sister for their endless love, constant support and encouragement for the graduate study

ABSTRACT

Xin Man distict in de Soulh west Ha Giang has high Iuudslide hacwd However, the available information on landslide in Xin Man district iz still imited We constructed the essential spatial database of landslides using GIS techniques The quantitative relationships between laudsHdes and fetors affecting Iaudslides ure eslublished Ly the Certainty Factor (CF), The affecting factors such as slope, elevation, laudeover, gculogy, road distance, Tineament distance, drainage density are recognized By applying CF value integration and jandslide zonalion, the most significant aflecling factors are selecled,

By using RS.&GIS technology landslide ocenrrences om all these factors have been analyzed The vector based GIS has been used for digitizing to produce thematic maps, as analysis for study was based on the pixel based information therefore Raster based GIS has been used for the analysis

Pixel based calculation was nade by using the CF value Model, By using the CF model we obtain the CF value for all classes al all factor maps On the basis of these CF value all factor maps are recoded and matrix analysts was perform to produce a Landslide Hazard 7.onation mgp

‘Vhe Landslide Hazard Zonation map has been applied to develop a methodology ta prodnce hazard maps considering the behavior of landslide and to evaluate potential damage to infiastructure specific road system Different factors have been considered for this study

1.4 Scope and limitation

LITERARUTE REVIEW 2.1 Hazard, risk & vulnerability 2.2 Landslide Hazard mapping 2.3 Fundamental of Remote sensing

24 GIS overview

2.5 Global Positioning System (GPS)

2.6 Web Map Server 2.7 Landslide Studies DESCRIPTION OF THE STUDY AREA 3.1 Arca and situation

3.11 Landcover

METHODOLOGY AND ANALYSIS

41 General

4.2 Compilation of Required data

43 Field Survey by using GPS

4.4 Extraction of mups from the source data

iv

PACE

TABLE OF CONTENTS (CONT.)

4.5 Methodology and Analysis Data 38

48 Landslide 1lazard ⁄⁄mafion Map 43

5.1 Characterize several types of landslide in Xin Man district 44

5.2 Landslide |azard Zonation map 46 5.3 Landslide Hazard ⁄2onaion map 54 5.4 Accuracy Check for |.andelide Hazard ⁄onalion Map ó0 5.5 Develop a methodology to produce hazard maps considering the behavior of

5.6 Publish Landslide Hazard Zonation to Internet using Web Map Server 69

v

Landsal 7 ETM image characteristic Geology, majar litho-stratigraphic units with their corresponding classes Area under Geology

‘Area under Elevation Area under slope

‘Area der distance to lineament Area under distance to road

Area under drainage density Area under Landcover

Analysis data ftom different sources Harvard zones

CK value of Geological

CF valne of distance to lmeament

CF value of slope angle

CF value of elevation classes

CF value of drainage density

GF value of landvover layer

CF value of distance to road The Iazard value ranges used for road butler The hazard valne ranges used for whole area

% area for landslide hazard zone for buffer area

% area for landslide hazard zone for whole area Defining the risk

Classification risk level Result of the risk class based onbnffer analysis

vi

PAGE

LIST OF FIGURES FIGURE TITLE

Spectral reflectance of a green left

The image interpretation processing,

Dala Flow in Remote sensing The flow of geometric correction

Procedures of Classification

WIS Processing Request

‘Map of Jarge J.andslide areas of Vietnam

‘The yearly rainfall from 1961 to 2003 Location of Study area Xin Man district, Viet Nam Geology chart

Elevation chart

Slope chan in Xin Man district

Distance ta the lineament chart Road area under the buffer Drainage density chart

Landeover chart How Liagram For Landeover Map Flow Diagram for Digitized Map Flow Diagram for Landslide Map using GPS Flow Diagram For TIN and maps extraction fiom TIN Hlow Diagram For Landcover Map extracted From Satellite Data Flow Diagram for Buffered Road and lincament Maps

Methodology of thematic data layer preparation

Show the landslide attacked road

‘Wedge slip occur along the road

CF value of geological

CF value of distance to lineament Stalistical map of slope angle distribution in Xin Man District

CF value of slope angle layer

CF value of clevation layer

CF value of drainage density layer

CF valne of landcover layer

CF value for distance road

Bar chart showing the distribution of varions hazard zones for buffer area in Xin Man district

Bar chart showing the distribution of various hazard zones for whole aea in Xin

Relative distributions of various hazard zones and landslide probability within each zone in road buffer in Xin Man district, 60

LIST OF FIGURES

Relative distribntions of varions hazard zones and landslide probability within each zone whole area in Xin Man district 61

‘The description of the road buffer 62 Show the process landslide 6 Schematization the Landslide area 63 Flow chart for procedure risk map 64 Minnesota Mapserver Framework Using CGI 7

LIZ snap in Xin Man on MapBrowser 74

LHZ map on GMapFactory 7

Tin in Xin Man distriel Geological in Xin Man district Elevation in Xin Man district Slope in Xin Man district

Distance to lineament in Xin Man

Buffer road system in Xin Man Drainage density in Xin Man Landcover in Xin Man

Road system in Xin Man

Landslide distribution in Xin Man district

Landslide hazard zanation for buffer area in Xin Man Landslide hazard zonation for buffer area in Xin Man Risk of slope in Xin Man’s Road Network

Risk of distance fo Xin Man’s road network Risk in Xin Man

Risk assessment for road network in Kin Man

‘Triangulated Inegular Network

Digital Levation Model

Digital terrain Model Remote Sensing

Geographical Information System Global Fosition System

Geographical Mark Up Language

Join Photographie Experts Group

Unifonn Resource Lovator World Wide Web

‘Web Map Service

‘Web Feature Service

CHAPTER 1 INTRODUCTION 1.1 Buckground

Landslide has become oue of Ihe world’s major sutured disaslors for the fow yours in many counttice Landslides are Gic most common naturel lizard in mountazious (arrain Landslide can be a major threat to population in the mountainous area Fven when they accur away from the inhabited areas, landslide can be a significant hazard and have a serious economic impact

by blocking roads and river (Aniva, 1985; J Achache, B Frunean and C Delacowt 1995)

Landslides we widespread i many countries und cause greal economic losses, especially when enaineerng constructions are designed and erected without heeding the stability conditions of the slopes (Q.Zaruba, V.Mencl 1967)

Landslides become a problem when they iulerfere with human activity The frequency wd the magnitude of the slope failwes cun be increased due to human activitics such as deforestation or urhan expansion

Landslide hazard analysis is a ditficult task It requires large immber of parameters and techniques for analysis Remate sensing and GIS are the powerful analysis tools to handle ths type of problems A in the analysis of landslide spatial information e.g topography, geology, landeover, elc are involved, therefore application of Remote sensing and GIS will be otieetive,

1.2 Statement of problem

- Although Inndslide usually occur in Xm Man district, but people who live near or in the landslide's local do not illustrate the different betwcen them, But actually, there ae many types of landslide which can occur and each of them have separate characterize We need to give some information to describe characterize some lypes of landslide in Xin Man disuiet

- Landslide is a serions disaster in Viet Nam In recent 10 years, there are more than 10 areas occurred violent landslide, causing above 300 imman deaths and thousands of hectares

of solids was buried by stone, sand, pebble and rundrcäs of inhabitant setticments having to change Geir ving places ad locations These are responsible for considerably greater sucio- economic lose than is generally recognized ‘There are some projects and research applying for landslide but only for mid_center of Viet nam Up to naw, there is not hazard map, risk map about Iundslide in Xin Mau distivl, the leader of province only have measure lo prevent landslide every year and they have not had any project to study about landslide in the Xin Man district Hence, there is an urgent need to prepare landslide hazard zonation maps in the highly landslide susceptible mountainous train special is Xin Man disbict

- No other landslide investigation or risk assessment has been performed in Xin Man

disinict 10 date

- Understanding and prevent landslide hazard is very important for every people What can peopte do when lack of information about natural hazari? Nowadays, internet is popular and useful for every people People can update, download all information and all thing which they need to know In this tegard, we need to publish and share information ahout landslide on Intemet by using Web Map Sever

1.3 Objectives

The general objective of dis study is using Remole sensing and GIS tecluique to making landslide hazard zonation mapping in Xin Man district

The specific objectives of the study are

1 Characterize several types of landslide in Kin Man district

2 Create zoning maps for landslide hazard that usnally occurs in Xin Man district

3 Develop a methodology to produce hazard maps considering the behavior of landslides

4, Publish and share landslide hazard zonation map’s information on internet using,

Web Map Server

1.4 Scope and limitation

~ Laudslide hazard map zanatiun will be focuses on critical ploy

overlaying thematic maps

- To determine aud localize arca have high risk of landslide basc on investigation, study topology, acology, hydrology, and geomorphology

~ The lunitation is associated with the evailability of reliable and adequate data yels from secondary sources to support making landslide hazard zonation map

factors by using GIS

~ Risk assessinent ouly for road networks, nol consider about ihe othas as population,

econamics, social,

~ Data collection is not enough to be analysis

~ Landsal TM images will be used for analysis of landeover of the study area

~ Apply existing program to publish landslide hazard zonation map on internet using Web Map Server

tà

CHAPTER 2 LITERARUTE REVIEW

Natural Lazard is extreme events in the earth’s ecosystem [he concepts of hazard, risk, and

vulnerability aro often confused with one enother and with the cxtrome event itself Although the exfiame event is inhereut in Iuzed, risk aud vulnombility taminlogy, it is not synonymous with the terminology Therefoie it is uecessary to distinguish between the lenus hazard, risk and vulnerability

Hazard assessment determines the type of hazardous phenomenon, frequency, magnitude and the extent of the area that may be affected Vulnerability indicates the degree of loss caused to people, infrastructure, buildings, cconomies cte distinguishing physical (buildings, infkastuclure), functional difelines, communication) and social aspects (health, population density) Risk combines the knowledge abont hazard and vulnerability to make a quantitative yrediction of the elements at risk, like numbers of lives to be possibly lost, people ta be injured, cost of property being damaged and destroyed or economic activities a aifected

3.1 Huzard, risk & vulnerability

In order to provide a systematic approach to stndy the landslide, Varnes (1984) defined various types of hazard, risk & vulnerability

Nataral hazard the probability of occurrence of a potentially damaging, phenomenon within a specific period of time and within a given area

Vulnerability the degree of loss to a given element or set of elements resulting from the ocemrrence of a natnral phenomenon of a given magnitude

Eloment at risk the population, properties, econome activities etc at risk in a given area

Risk the expected degree of loss due to a particular natural phenomenon Hence it is a prodnet of hazard and vulnerability

Criteria for risk assessment is represented schematically as below (Figure2-1)

Funtional Vulnerability

Eiguuo 2.1: Criteria for risk assesment (Disuster Propareduess and Mitigation 2002)

3.2 Landslide Hazard mapping

2.1.1 Definition

Althongh by the ierm landslide is used for mass movements occurring along a well defined sliding, surface, it has been used in literate as the most general tenn for all kinds of mass movements, including some with litle or no true sliding such as rock- falls, topples, and debris flows (Vames, 1984) In this contexl, muss movement ig used subsequently us 4 synonymous tenn for landslide, sinilax to slope movenuent

‘Zanation refers to the division of the land surface into areas and the ranking of these areas according to deyces of uclual or potential huzad Hence landslide hazard zouslion shows potential hazard of landslides or other mass movements on a map, displaying the spatial distribution of hazard classes In general three basic principles or fundamental assumptions guide all zonation studies (Vames 1984)

> ‘The past and the present are keys to the future: Natural slop failures in the fiture will most likely ovcur whore geologie, geomorphic and hydraulic situation have led to past

and prosent failures Thus, we have the possibility to estimate the fealures of potential future failure The absence of past and present failures does not mean that failures will nol oeeur in the future,

» The main conditions that cause landslides can be identified: The basic cause of slope failures can be recognized, are fairly well known from several case stndies and the effects of them can ¢ rated or weighed It is possible to map correlate the contributing factors to each other

> Degree af hazard can be estimated: if the condition and processes that promate instability can be identified, it is often possible to ostimate their relative contribution and give them some qualitafive or semi-quanfitative measurement Thus, a summery of the dogiee of potential hazard in wn arva can be buill up, which depends on the number

of failure including factors present, their severity, and their interaction

2.2.2 Scale of mapping for landslide hazard zonation

here are several technique for landslide hazard zonation can be applied, making, use af GIS Therefore the appropriate scale on which the data is collected and the result presented varies considerably More detailed hazard maps requize more detailed input data ‘ins the objective

of the analysis and the requires accuracy of the input data determine the scale

‘Vhe following scales of analysis have been differentiated for landslide hazard zonation according to the definition by the Intemational Association of Lingineering geologists (1976)

= National scale(<1:1,000,000)

= Regional scale(1:100,000 — 1: 1,000,000)

= Medinm seale(1:25,000 — 1:100,000)

= Large scale 1:2,000 — 1:25,000)

2.3 Fundamental of Remote sensing

2.3.1 Concept of Remote Sensing

Remote sensing is defined as the science and technology by which the characteristics of the abjects of interest can be identified, measured or analyzed the characteristics of the objects

without direct coutact

Elochomugnotic radiation, which is reflected or omitted from an object, is the usual gouree of remote sensing data A device, to detect the electro-maguetic radiation, reflected or emitted, fiom au object is called a “remote sensox” or “sensor”? A vehicle to carry the sensor is called &

“platform”

Remote sensing is classified into three types with respect to the wavelength regions

> Visible and reflective Infrared remote sensing

> Theunal infrared remote sensing,

} Microwave remote sensing,

2.3.2 Spectral Reflectance of Landcovers

Spectal reflectance is ussumed to be different with respect lo the type of laidcover This is the principle that in many cases it allows the identificatiun of landcovers with remole sensing by observing the spectral radiance from s distance far removed from the surface

Fig.2.2 shows fliree curves of spectral reflectance for typical land covers, vegetation, soil and water As seen in the figure, vegetation has a very high reflectance in the near infrared region, though there are three low minima due to absorption

Soil has rather higher values for almost all spectral regions Water has almost no reflectance in the infrared 1egiơu

‘vegetation green to the luman observer

Near infrared is very usefill for vegetation snrveys and mapping because such a steep gradient

al 0.7-0.9 uin is produced only by vegetation

Becanse of the water content in a leaf, there are two absorption bands at about 1.5 1m and 19

vin, This is also used for surveying vegetation vigor,

Wavelength (jem) Figure 2.3: Spectral reflectance of 4 green left

2.3.3 Description of the data set-Landslide image

Dalabuge of emole seusing is usod:n this thesiy is Lundsal 7 ETM The application of satellite data has increased enormously in the past decade After the initial low-spatial resolution images of the LANDSAT MSS ( which were about 60 by 80 m), LANDSAT mow hay a

significant improve in its characteristics with thematic mapper (I'M) images It has a spatial

resolution image of the 30 m and excellent spectral resolution Landsat TM provides sevens bands to cover the entire visible, near infrared and middle infrared portions of the spectrum, with one additional band providing a lower resolution of the thennal infiwred (ble 21) Landsat satellite orbits are arranged to provide good coverage of a large partion of the earth’s surface The satellite passed over each lucation every 18 days, offering a theoretical temporal resohution of 18 days

Table 2.1; Landsat 7 ETM image characteristic

Band | Spectral range(um) | Spatial resalution(m)

2.3.4 Lage interpretation

Image inlerprelationis defined as the extraction of qualitative and quantilative infonnation in

the form of a map, about the shape, location, structure, fimetivn, quality, condition,

relationship of and between objects, etc by using human knowledge or experience

Change detection is the extraction of change between multidate images

Extraction of physical quantities corresponds to the measurement of temperatnre, atmospheric constituents, and elevation and so on from spectral

Ideubfication of spevilic features is the identification, for example, of disaster, lincament and other feaiure ote

Figure 2.4 show a lypical Dow of the image interpretation proccss

AVD conversion using &

film scanner ete

Primary Provessing D/D conversion

2.3.6 Geometric Correction

Geomettic comection is undertaken to avuid goomlic distortions from a distorted invage, and

is achieved by establishing the relationship between the image coordinale system aud the geographie coordinate system using calibration data of the sensor, measured data of position

and attitude, ground control points, atmospheric condition ete

The steps to follow for geometric correction are as follows

(4) Interpolation and resampling,

Eigure 2.6: The ow of geometric conection there are three methods of geometric correction as mentioned below:

2.3.7 Registration and Rectification

Refael C Gonzalez Rochard E Woods (1993) explained that the another important application

iy the image registration or Sinding correspondence Lelween lwo images, The provedure for image registation is the same as the method just illustrated for geometric conection However, the sauphasis is on transforming an image so Gal i will comespond with another image of the same science but viewed perhaps from other prospective

2.3.8 Classification

Classification af remotely sensed data is used to assign corresponding levels with respect to groups with homogencous characlerislics, with the umn of discrimuinaling multiple objecls fiom each other within the image

10

Mullislewel slot Clussifiee

| 3, ectstint ree obassitier Minismun discance etacsitier Maximum likelihood classifier

3 Other lassifiers sch a8 frzzy theory and exper x„ 580m

Verifying gf The so,cuey cr rehanlity Oể (he resuÏt

of Guining data should be made in order lo represeul the population correc

> The minimum distance classifier is uscd to classify unknown image data to classes which minimize the distance between the image data and the class in multi-feature space The

distance is defined az ax index of sunilanty so thal die uinimun distance is identical to the nreeoituit giiutlaily,

> The maximum likelihood classifier is one of the most popular methods of classification in remote sensing, in winch a pixel with the maximum likelihood is classified into the corresponding class ‘The likelihood is defined as the posterior probability of a pixel belunging to class k

2.3.9 Spatial Viltering

Spatial filtering is used to obtain enhanced images or improved images by applying, filter function or filter operators in the domain of the image space (x,y) or spatial frequency (xh) Spatial filtenmg in the domain of image space ams at image enhancement with so-called enhancement filters, while in the domain of spatial frequency it aims at reconstruction with so- called reconstruction filters, which is in the domain of spatial frequency it ams at reconsimetion with so called reconstruction filters An ontput image from filtering of spatial pass filters, band pass filter etc ae typical filters with fiequency control Low pass filters which out puts only lower frequency noise, while high pass are ured for example stripe noise

of low fiequeney

11

2.4 GIS overview

2.4.1 Geographic Information System

According to Burrough (1986), Geographic Information system (GIS) is a powerful set

of tools for collecting, retrieving, transforming, and displaying spatial data from the real world for a particular sct of perposes

AronolT (1993) stalos iat GIS is designed for tre collection, stomge and aualysis of objeets and plunomens where goographic location is caitical to analysis, For example, the location of a fire station or the locations where soil erosion is most severe are key considerations in using information, In each case, what iL is and where il is inust be taken into

CCOUIH,

2.4.1 Terrain XIodcling for Mountain

Mountain may be defined az dynamic system in which both the extent and variability

in relief are key controlling elements Altitude, aspect and slope strongly both the human and the physical charactenstics of mountain ecosystems such as the distribution of agriculture, the type of farcsixy, micro and local climates and the cxtent of the mass movement A model of relief is therefoxe an essential component of 4 mountain GIS At present the most powerful incthod of representing relief is to construct a mathematical model of die earth’: surlkec: a digital terrain model{ 191M) or digital elevation madel(1)EM) ‘Chis mathematical model can

be used to drive information on height, aspect, slope, angle, watersheds, hill shadows and cut and fill estimates which may be essential components of management plan or inputs to a process model

Any digital representation of continuons variation of relief over space is known ax a DEM DEMs were originally developed for modeling relief, they can of course be used tn model the continuous variation of any other attribute 7 over two dimensional surfaces (Burrongh, 1986)

2.5 Global Positioning System (GPS)

The U.S Department of defense developed 2 nuvigution system called Global Positioning System “GPS” It is based on the 24 satellites which orbit aronnd the earth at an altitude of 20.200 km the satellites are high enough to avoid land based system problems With this technology one can Gud the location of an object any where in the woild 24hrs day The accuracy for measurement with GPS is fom 5 to 10 sueters range With differential post processing the accuracy can be few millimeter

GPS is digital cloctronic equipment based on satellite ranging; it means we can figure out our position an earth by measuring onr distance from a group of satellites in space ‘Ihe satellites acl us a reference point

‘There are atom clocks on the satellites which are show accurate time, due to which we can climinals any exvor caused by the watch of the GPS receiver

2.6 Web Map Server

2.6.1 Introduction

Open Source software and its spocifications are the foundation of this study, PostgreSQL, the Object Oriented Relational databuse stores and manages the GIS database, PosiGIS is the

12

extension which makes the PstgreSQL comected lo the Minneyota MapServer in order to display the database in vations formats Minnesota MapServer is used to explore GIS data over World Wide Web (WWW)

Open Source technology is base on the premise that the programming source code is freely available to anyone who wishes ta read, add to, or even modify and redistribute the computer software code Open source technology offers a level of stability and flexibility that is not typically available with “out-of the-box” software

Benefit of Open Sonree 'Lechnologies

> Free to use- there are ny licensing Lees

> The software can be duplicated and installed on as many machines in as many environments, with no restrictions

% Pull access to sonrce code

> Highly responsive to end user requirements,

Open souree docs not just sean access to the source code, The distibution terms of open source software must comply with the following criteria:

a, Free redistribution

b Source Code

e Derived Works

d Integrity of the Avthor’s Somce Code

e No Discrimination against Persons or Groups

£ License Must Not Be Specific to a Product (Open GIS)

‘Minnesota Map Server provides Upen GIS Congortium’s (OGC) Web map Service(WMS) and Web Feature Service These two specifications will use operation on the client's request to produce maps of georeferenced data in various fonnats such as JPEG, PNG, GIF and GML

2.6.2 Open GIS Standard

The OpenGIS Standard specifies the behavicr of'a service that produces georeferenced maps ‘This standard specifies operations to retrieve a description of the map offered by a service instance, lo retrieve a map, und to query a server about fentures displayed on a map

OpenGIS Staudard is applicatile lo pictorial rouderinge of maps in a graphical fonuet, This standard is not applicable to retrieval of actual feature data or coverage data values

1 Web Map Service (WM 5) Implementation Specification

A Web Map Service produces maps of georeferenced data We defined a “Map” as a visual representation of geodata, a map is not the data itself ‘These maps are generally

rendered in a pictorial format such as PNG, Gill’ or JPG or accasionally as vector-hbaserL

graphical elements in Scalable Vector Graphics (SVG) or Web Computer Graphics Metafile

(WebCGM) formats ‘This specification standardizes the way in which maps are requested by

client and the way that servers describe their data holdings, The Girec operations are az fullows:

> GotCapabiliicy (Required); Obiain service-level mctadals, which is a machine readable jand human- readable) description of the WMS’s information content and acceptable request parameters,

> GetMap (required): Obtain a map image whose geospatial and dimensional parameter are well-defined,

} GetWeatureinfo( optional): Ask for information about particular features shown ơn a map

A standard web browser can ask a Web Map Service lo perform these operations simply by submitting requests 1n the form of Umform resource Location (URLs) The content of such URLs depends on which of the task is requested All URLs include a specification version auniber and a request type parameter, In addition, when invoking GetMap a WMS Cheat can specify the information to be shown on the map (one or more” Layers”), possihly the “style”

of those Layers, what portion of the Earth is to be mapped (a “* Bounding Box”) the projected

or geographic coordinate reference system to he used (the “ Spatial reference System, “or SRS), the desired output format, the output size (Width and Height), and background transparency and color When invoking Getfeaturetnfo the Client indicates what map is being qneried and which location on the map is of interest

2 Web Feature Service (WFS) Implementation Specification

‘Vhe OGC Web Map Service allows a client to overtay map imager display served from multiple Web Map Services om the Intemet In a similar fashion, the OGC Web ieature Service allows a client to retrieve geospatial data encoded in Geography Markup Langnage (GML) from multiple Web Feature Services

The WFS operations snpport INSERT, UPDATE, DELETE, QUERY and DISCOVERY

operations on geographic features using HTTP as the distributed computing platform

WES Request WFS Response

Web Feature Service

(WFS)

Figure 2.8: WFS Processing Request

2.7 Landslide Studies

-Kwang-Hoon Chỉ", Kiwon Lee**, and No-Wook Park*(2001), studied Landslide Stability Analysis and Prediction Modeling with Landslide Occurrences on KOMPSAT EOC Imagery In this study, Slope-Area plot methodology followed by stability index mapping with these hydrological variables is firstly performed for stability analysis with actnal landslide occurrences at Boeun area, Korea, and then landslide prediction modeling based on likelihood ratio model for landslide potential mapping is camied out; in addition, KOMPSAT EOC imagery is used to detect the locations and scarped scale of landslide occurrences These two tasks are independently processed for preparation of unbiased criteria, and them esults of those are qualitatively compared As results af this case study, land stability analysis based on DEM-based hydrofogical variables directly reflects terrain characteristics, however, the results

in the form of land stability map by landslide prediction model are not fully matched with those of hydrologic landslide analysis due to the heurstic scheme hased an location of existed landslide occurences within prediction approach, especially zones of notinvestigated ocewrences Therefore, it is expected that the results on the space robustnoss of landslide prediction models in conjunction with DEM-based landslide stability analysis can be offeetively ulilized lo search out umevealed or hidden landslide occurences

-D.Z.§eker, M.O.AHan2001)used varions types of data to extract relevant information Thus study is to determine a suitable methodology for predicting, possible landslide areas and prodncing landshde risk map in the study area of Sebinkkarahisar Township, whuch is located

at the northeastern part af Turkey ‘hese incinde the satellite sensor data taken in the year of

1987 and 2000, which are use for the extuction of land surface temperature and landuse information 1:25000 scale standard topographic map has been digitized and the obtained contours were nsed for the derivaHon of DI⁄M and slope map of the stndy site Satellite images, 101iM and slope map of the study wea were used to investigate the possible landslide risk arcag and reason of this mature hazard which Uccat the study arca Siequently

-Neuyen Quoc Phi, Bui Hoang Bac (2000) gives a view of landslide characteristics on nalimal terrain of YangSan area, Korea and developing a GIS approach to modeling slope instability ‘The relations between landslide distributions with the physical parameters such as lithology, elevation, slope gradient, slope aspect, linenment, drainage, vegetation, and land sue were analyzed by Bayesian statistical model A susceptibility map is modeled by incorporating, these in weight of evidence model using Bayesian approach

-Atsnshi Kajiyama, Takamato, Truang Xuan Luan and Nhu Viet Ha (2012) nsed

sterco-photogrammetry technique (using Fhotomodcler softwarc) application for monitering a

Jandslide twice in Monset area, northwestern part of Viet Nam in 2002 to 2003 this technique

has allowed us to deriver surface deformation maps of landslide with a high spatial resolution and acewacy Photomodcler sofware can teal il easily using reference point and the phologruph, which they have been laken plolograph with coummon digital canera Using this soflware, we estimuled the ainvunt of movements of whole Lundslide fox one year The result las been validated by couparing independent measurements canied out by laser lelemeter

“Mike Doratti, Chris McColl and Claire Tweeddale (002) applied GIS to predict landslide hazard sreas following clearcut logging events The landslide prediction study project sponsor is Tout Millard of BC Ministry of forest The objective of this project is to produce a report and maps identifying potential landslide hazard areas within the Cascade

18

Mountuin region, Britsh Columbia Historically, use of GIS welmologies in this area of Forest Resource Management have been hmited, therefore application of this software could potcutially improve current practices Slope stability faclors were daived fiem TRIM digital elevation models Algorithms were developed to create a landslide hazard model, This model waz compared to existing landslide data, and lo the cuzent terrain stability mapping standard

tp assess madel accuracy

-Amod Sagar, Takaaki Amoda and Masamu Aniya (1997) This paper presents the development of landslide susceptibility mapping using GIS The study area is Kulekhan walershed lying in the lesser Himalayan region of Nepal A landslide distibution mep produced from interpretation and field work was used to analyzed the important factors to landsliđes, employing Quantification scaling type (Q-S2) method The six factor used were slope gradient, slope aspect, elevation geology landuse/cover, and drainage basin orde Overlaying the factors with scores for their classes computed by the analysis, landslide susceptibility maps were produced with classes of high, moderate, less and least susceptible -Richard Kho Shu Yuan and Mobd Wrabim (1997) In this study, land surface temperate and Janduse information have been derived tiom Landsat thematic Mapper data The elevation and slope inclination have heen determined from IDKMs generated from acrial photographs Underground water level information has been obtain from the combination of above data From these data, simple algorithms were used to classify the area into different risk zones By combming all the risk maps usmg GIS techniques, final risk inaps were prodnced which take into accomnt all shove factors

-Purna, Dr kaew, Dr Jean Delsol, P Gupta, Prinya (1995) 1'he methodology is nsed

for landslide hazard zonation Landslide distribution is overlaid with other landslide influencing spatial parameters slope, aspect, and land aystam, landuse, bedrock, isohyetal and seismic zonation, amd fist order buffered stream map The slope and aspect maps were gencrated fiom the DTM The land we map and Iandslide map were produced Grom actial

pholo inlerprelation.

MAP OF LARGE LANDSLIDE AREAS

CHAPTER 3 DESCRIPTION OF THE STUDY AREA

3.1 Areaand situation

Xin Man district is situated in the South West of Ha Giang province The study area

lies geographically between 22°10" N to 23°30°N and 104°20°E to 105°34°E

Xin Man and Hoang Su Phi districts lie in the high land and accounting for 18.3% of the

total province's area and 17.2% of the population The potential for the area is to develop plants for derived resin

3.2 Climate

The climate is divided in two distinct seasons (rainy and dry), although it tends to vary

depending on altitude The annual average temperature varies between 24 and 28°C In winter,

the temperature is sometime -5°C_

3.3 Rainfall

The mean annual rainfall, according to the records of Metrological station, for the 20 years

(1985-2005) is about 1,695 mm Most of the rain comes in the months of August and

September In that time, the intensity rain fall is 2000-2500mm in some high mountains

(©1500m) and causing flash flood and landslide

‘The population census was carried out in 2000 Total area is 665.25sq.km and its population is

43926 habitants There are 22 communes in this district They are Ban Diu, Ban Ngo, Chien Pho, Che la, Chi Ca, Coe Pai, Coc Re, Khuon Lung, Ngan Chien, Na Chi, Nan Ma, Nan Xin,

Nam Dan, Pa Vay Su, Quang Nguyen, Thu Ta, Then Phang, Trung Thinh, Tan Nam, Ta Cu

Ty, Ta Nhiu, Xin Man

Figure 3.2: Location of Study area Xin Man district, Viet Nam

Map 3.1: Tin in Xin Man district

Elovalion and dope uapy we extacted fiom TIN which hag been oblained from die Contour map im Xin Man district The TIN is chow in the map 3.1

- The gravelly soil is not combining together and having different component, size live

in vale of river and stream, and the slope surface This gravelly soil group is very development in the watershed, including is sediment slope, sediment flood and smaller

than rising than level of sediment

- Rock weathering very strong incinding metamorphism two mica schist, granite ix compressed,

- All granite is not weathering

AH of group gravelly are also moved by the earth’s crust making many local are compressing, catalectic, breaking, and create advantage condition for landslide and debris flow

In the study area, the various litho-stratigraphic units were prouped into four categories, It is

shown in table 3.12 && figure 3.12

'Table 3.1: Geology, major litho-stratigraphic unite with their corresponding classes

Geology Major litho-stratigraphic units

C2phl Quarzbiotite schist, sericite-chlorite schist, shunggite,

green schist, marblezed limestone bearing oncolite, phyllite

Marble, motley limestone, clayish limestone, clay-sericite (C2hg2 schist

Kine-to medium- grained, porphyritic biotite granite

(Teal Coarse grained gneissuid bivlite granite,

11 e2 Graphite-bearing marble, two-mica schist, quart mica

Pha schist, quartzite, epidotehiobte schist, epidote-biobte-

hormblende schisl, thin beds of marble

Table 3.2: Area under Geology

Map 3.2: Geological map in Xin Man district

GEOLOGICAL MAP IN XIN MAN

3.6 Elevation

‘The area comprises of high mountain ranging fom elevation 200m to 2400m About 67% of study area lies in the range of elevation from 500m to 1500m Remaining 10% of area has a very high range of elevation from 1500m to 2400m The elevation range extracted from the digitized contour map of scale 1:50 000 is given in the following table 3.1 and illustrated in the figure 3.4, Elevation range for the study area is obtained from the Digital Elevation Model (DEM) And it is shown in the Map 3.1

Table 3.3: Area under Elevation

Elevationclasses(m) Total area (km2) Area in %

Total elevation area in %

37.01 30.5

Slope classes(degree) Total area(knr) Area in %

Source: Contour Map of scale 1:50 000 and Digital terrain model

From the digital information of slope it has been obverted that 76.3% of area has slope range

of 15-45 degree and only 5.17% has slope range more than 45 degree The percent of area under different slope range are given in table 3.6 and slope Variations are shown graphically in figure 3.5 The slope map has been extracted from the TIN and slope classes are shown in the map 3.3

Map 3.4: Slope map in Xin Man district

SLOPE MAP IN XIN MAN DISTRICT

-NW-SE trending faults system is developed contrentratesly in the northeast Together with NW-SE trending fault system they form faults of feather form in the southeast of the Chay river Granite Massif,

~ Sublatitudinal faults from the boundary between the Chay river Granite massif and Cambrian Devonian sediments

The lineament are buffered in different distance The distances to lineament factor was computed using analyst extension of arcview and were classified as table 3.5 below

Table 3.5: Area under distance to lineament

Distance classes(m) Total area Area in %

Map 3.5 shows the distance to lineament classes in different color

Map 3.5: Distance to lineament map in Xin Man

MAP OF DISTANCE TO LINEAMENT

0.500 1000-2000) 2000-3000 3000-1000

The study area has one major road having width of 8 m A large number of houses are

connected to the road So we must to create buffer to the road with different distance The

results are given in the table 3.6

Table 3.6: Area under distance to road

Distance classes(m) | Total area(km2) %Area

It has been observed that the 73.23% of road lies under distance range more than 150 m, only 2.51% of area belong to range 0-10m Total range from 10-150 m occupied nearly 25% of the area, Road network in Xin Man district is shown in the Map 3.6 The distance range variation for the buffer road is shown in the figure 3.7

3.10 Drainage density

Drainage density is defined as the ratio of sum the drainage length in the cell and the area of the corresponding cell (S.Sarkar, 2003), The under cutting action of the river may include the effect of this causative factor and converted into raster format, The drainage density (figure 3.10) was computed considering a 20 by 20 m cell and classified with intervals as show in

Map 3.7: Drainage density map in Xin Man

9.500

|] 1500-2000

2000-2500 2500-3500 500-4500 500-1800

Table 3.8: Area under Landcover