SVY818 SDS Lab Report1

8/6/2019 SVY818 SDS Lab Report1

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Contents

1.0 Introduction

Nowadays Geographic information systems (GIS) are widely used in different applications. GIS

has been confirmed to be a very efficient tool for processing and analyzing real life spatially

distributed linear and positional objects such as railways, roads, pipelines, hospitals and also taxi

parks to mention but a few. It is related to an evaluation in detail of physiographic factor,

landscape, engineering-geological and others requirements for the investigation area. It includes

the study of all relevant parameter such as; length of the route, calculation of intersections with

local government boundary lines, roads and existing railways.

An existing GIS spatial analysis capability gives possibility of operative evaluation. Modern GIS

software allow to automate complex operations such as intersection with different linear and

polygonal objects, positioning of new taxi parks, estimation of transport costs during

construction and operational service of taxi route, calculation of integrated construction cost etc.

A lot of studies around the world have focused on the issues of digitizing geospatial and

acquiring attribute information about our environment since the US Vice president Algore

mention the concept Digital earth. (Y.C Ding, C.C Hung Beijing 2008.)

The major components of Digital Earth are:

i. Collection of all kinds of information from different sources, especial from satellites, to

build geodatabase.

ii. Storing and retrieving this data efficiently.

iii. Sharing this information efficiently via the internet infrastructure and

iv. Presenting data in 2D and 3D formats.

Various GIS applications have been developed to solve real-life problems examples of which

are: Land information system, Geo resources Information system, and Route Network

information system to mention a few.

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1.2 Objectives

The objectives of this lab include:

i. To download and georeference raster images of the study area.ii. To acquire GPS observations of taxi parks in the study area.

iii. To digitize and populate taxi park, route and local government dataset of the study area.

iv. And finally to create spatial data structure of the participating datasets.

1.3 Study area

The study area for this lab is Ikeja and Ifako-Ijaye Local Government Area of Lagos State,

Nigeria. The two Local Governments are located in the Northern part of Lagos state. It covers anapproximate area of 12.5 square kilometers. They are both densely populated local government

areas of Lagos state. Moreover, Ikeja local government is the state capital of Lagos. Ifako-Ijaye

borders Ikeja to the north.

The vector base map of the study area will be acquired and studied carefully to determine visible

points, line and polygonal features. Non-spatial attributes of these features will be compiled into

the geodatabase.

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Fig. 1. Vector map of the study area.

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2.0 Methodology: Principles Behind

A GIS can be said to be a software package with components and tools used to enter, manipulate,

analyze, visualize and present spatial data (Kufoniyi 1998). The components as earlier mentioned

consist of the Hardware, Software, Spatial data, Attribute data, management and analysis

procedure and the people to operate the GIS.

The performance distribution of GIS is subject to a list of data requirements. The sources of data

used in the GIS came from several different sources such as:

Field Survey: This involved going to the various locations of taxi parks in the study area

to capture their coordinates with a hand held GPS.

Attribute data: which involves going to these parks to collect other relevant non-spatial

data.

2.1 Database Design

The major effort in developing a GIS application package is the establishing of a spatial

database. The database design in this case consists of the conceptual design and logical data

model:

Conceptual Design

This refers to the human conceptualization of reality; where REALITY refers to the

phenomenon, as it actually exists including all aspects, which may or may not be conceived by

the individual. The VIEW OF REALITY is the mental abstraction for a particular application or

group of applications (Kufoniyi 1998). The entities and attributes which constitute the

conceptual design in this case are:

Road Network

Taxi Parks locations

Local Government Boundaries of the study area

And other attribute data

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1

N N

N 1

1

Fig. 2.0 Conceptual model of Taxi parks created in the geodatabase.

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Taxi Parks

Ikeja_IfakoIjaye

Ikeja_Ifako_Local

Connects

Contai

ned

with

in

Located

within

ObjectI

D

TName

Eastings

Northings Addres

s

Picture

Contac

tn

RD_Na

me

Type

RD_ExtSpeed

Disp_T

ype

ObjectI

D

ObjectI

D

ID

Name Capital

State

Area

Popula

tionID

RD_Na

me_F

RD_Na

me_

Shape

_Len


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2.2 Implementation Strategy

The methodology of this project can be divided into two parts: Data collection and Data analysis.

2.3 Data Acquisition

The street map data was extracted from Lagos street map available on Map Source standalone

application and from existing Lagos acquisition map (Source: Lagos State Surveyor general

office). GPS coordinates of the taxi parks were downloaded from GPS 76CS device onto

mapsource application.

In the course of this project, two types of data were acquired namely; Spatial and Attribute data.

2.4 Spatial Data

Spatial data stores information about location, shape, and attributes of real life objects. These

data includes;

Taxi parks directory of Lagos state.

Lagos street map

Lagos Land Use

Taxi Point data of the study area.

This was done with the aid of GPS Garmin 76CS.

Maps as an origin of information have two types of functions:

i. Positional, i.e. give information about the exact location of objects

ii. Informational, i.e. give information about data type, name and class of objects

including topological properties and relationship of objects

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2.5 ATTRIBUTE DATA

Attribute is the characteristic of an entity selected for representation (DCDSTF 1988) usually

non-spatial but related to spatial character or phenomena under study. Attribute value is the value

of the attribute that has been measured and stored in the database.

A geodatabase was created to hold feature datasets and non-spatial data. All geographic objects

have attributes. Attributes of geographical objects have been collected at the same time as the

vector geometry, e.g.:

i. Name of the taxi parks

ii. Addresses of these parks

iii. Contact numbers and

iv. Photographic data to graphically identify the parks.

These attributes have been manually entered into the geodatabase.

Development of a Logical Data Model

After the data needs assessment had been completed, the physical design of the data began. The

data that had been deemed necessary were described and grouped by function or type. This led tocreation of themes in much the same way the geographic layers were grouped into themes. These

themes were arranged into an Analysis Diagram that exposes the relationships between features

and objects.

Keyboard Entry

The keyboard entry often referred to as key coding, is the entry of data into a file at a computer

terminal using the keyboard as an input device. This technique was used for the attribute datathat are on paper e.g. statistical data of Lagos state.

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Scanning

Scanning is the most commonly used method of automatic digitizing. It is an appropriate method

of encoding when raster data are required. Although street data were not scanned for digitizing,

photographic data were scanned and saved on disk for onward attachment to spatial data.

2.6 Coordinate System

Before selecting a coordinate system for GIS it is necessary to consider existing national

reference systems. In Nigeria the GCS WGS 1984 coordinate system, based on Clark 1880

datum is used. It is on this datum that the WGS 1984 UTM zone 31 projected coordinate system

is based. In this work the data used has the following coordinates system:

Projected Coordinate System: WGS 1984 UTM zone 31

Projection: UTM

Geographic Coordinate System: GCS WGS 1984

Datum: Clark 1880

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2.7 Software and Tools

2.8 AutoCAD

The AutoCAD2006 produced by AutoDesk based in the USA was used in this work. The

package was used to vectorise some scanned paper maps. It was also used to extract point data

from DXF file format and finally used to compile all data before converting to shape file format.

2.9ArcGIS 9.3

ArcGIS software was deployed in designing and implementing this project. ArcGIS desktop is

well known in the world and its' the most used GIS software. It was developed by Environmental

System Research Institute Inc. (ESRI), Redlands, USA. In this work the components of ArcGIS

desktop like ArcMap, ArcCatalog, and ArcToolbox have been deployed extensively to create the

geodatabase, for editing, for data management and storage, georeferencing data from different

sources, performing spatial analysis and visualization of output data, implementation of geo-

processing functions for different tasks. One of the ArcGIS extension that was used is the

Network Analyst. These extensions have been strategically deployed to solve certain problems

during and after implementation.

The spatial features contained in the geodatabase comprise feature datasets, feature class,

geometric network data, network dataset and table. The feature class identified are:

1. Point

2. Line and

3. Polygonal features

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3.0 Data Processing and Analysis

3.1 Geodatabase creation.

The features identified were used to create a geodatabase to enforce topological and geometric

rules on the resulting feature classes. The ArcGIS 9.3 ArcCatalog was used to create a

geodatabase created in C:\Spatial Data Structure\SpatialDS.mdb and populated with a

Dataset feature dataset having point, line and polygon feature classes in GCS_WGS_1984

coordinate system. Subtypes were also created for these feature classes. Below is a table showing

the feature classes, subtypes, fields and other attributes.

Features

Class

Layers Field

Point Taxi Parks ObjectID, Shape, TName, Easting, Northings,

Address, Contact No., Picture

Line Ikeja Road ObjectID, Shape, Type, RD_NAME, RD_EXT,

ROUTE, FW, SERVICE, RD_ID, SPEED, ID,

DISP_TYPE, RD_NAME_F, RD_NAME_U

Shape_Lenght,

Ifako-Ijaye Road

Polygon Local Government ObjectID, Shape, ID, Name, Capital, State,

Zone_, Area, Population, Shape_Lenght,

Shape_Area

Land Use ObjectID, Shape, ID, Landuse, Count, Shape-

_Lenght, Shape_Area

Table 3.0 Showing the contents of the geodatabase, feature dataset, classes, Layers and fields

created.

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Fig 3.0 Showing the created geodatabase, feature dataset, feature class and geometric network

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3.3 Vectorizing

This simply means conversion of raster image features into digital format using the Point, line

and polygonal feature classes. ArcGIS ArcMap provides the necessary tool to digitize features

easily and accurately. The subtype classifications help to fast-track this process. Before

digitizing, selectable layers were enabled so as to select only one feature at a time. The snapping

tolerance had been specified during the feature dataset creation, all that remained was to indicate

which layer(s) is to be snapped to enforce network topology on the system.

After setting and activating all the necessary parameters, digitizing commenced with point

feature positioning i.e taxi parks, street map and data entry. The road and polygonal features

were also digitized.

Fig 3.1 Showing digitizing snapping parameters of the feature classes in ArcMap

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Fig 3.2 Showing the processes involved in digitized feature classes and editing attributes on

georeferenced vector maps.

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3.4 Topology analysis.

Topology network was built for the network involving point, line and polygonal features. Some

of the rules enforced include:

i. No polygon must overlap another polygon

ii. Points must be covered by end point of road features

iii. Road feature must not overlap it self

Fig 3.3 Showing topological rule enforce on the taxi parks and road network

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Fig 3.4 Showing the network after topology analyses were carried out on the network.

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3.5 Network dataset analysis

As mention earlier, topological capability has been built into the network when creating the

feature classes by enforcing geometric network rules. To test this capability, one will need to

build network dataset on the system.

The coordinate system would have been projected in the UTM system if it were not in UTM, but

this important step was not done because the system was already in the UTM system. This is

important to facilitate easy calculation in meters and kilometers. The network dataset was created

from the point and road feature classes.

The network dataset was built and validated after setting appropriate parameters and evaluators

such as snap tolerance, complex edge, connectivity and direction.

The ArcMap environment was deployed for the last time to add the newly created network

dataset and to perform network queries on the system.

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Fig 3.5 Showing the network after topology analyses were carried out on the network.

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4.0 Results and Conclusion

4.1 Results

Many spatial and non-spatial queries were carried out on the system. Network-based queries

were also carried out. Some of the queries executed include attribute queries. Examples of these

queries are shown below.

The attribute table of the Taxi Parks were also populated and shown below:

Fig 4.0 Showing the attribute table of the Taxi Parks including its coordinates, Park name,

address, contact detail and picture of the parks.

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Fig 4.1 Showing a spatial query to search for and locate Oremeta Taxi Park.

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Fig 4.2 Showing a spatial query to search for and locating Ojota International 2 Taxi Park.

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4.2 Topological queries

Queries were carried out to test and validate the accuracy of the network. These queries include,

displaying the coordinates of individual vertices that makes up an edge in a route network. Query

showing relationships among participating junctions and its adjoining edges was also shown.

Fig 4.3 Showing participating egdes and nodes on a section of commercial Road.

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4.3 Network queries

As described earlier, network analyses were carried out on the system with emphasis on shortest

route between taxi parks and stops in the study area. Some of these queries were shown below:

Fig 4.4 Showing the shortest route between Oluwole Taxi Park through agidingbi rd to ojota

retail market taxi parks.

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Fig 4.5 Showing the shortest route from Daddy salvage Taxi Park to Oluwole Estate Junction

close to Oluwole taxi park.

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Fig 4.6 Showing the shortest route from Central Mosque Iju Ishaga Taxi Park to Oluwo Estate

Taxi Park.

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Taxi Park pictures hyperlinking were carried out to further describe and identify the parks

graphically. Some of these were shown below:

Fig 4.7 Showing picture of the motor way central taxi parks near the old toll gate area.

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Fig 4.8 Showing picture of Abule taxi parks in GRA area of Ikeja.

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Fig 4.9 Showing picture of Ojodu retail market taxi parks in ojodu berger area.

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Fig 4.10 Showing picture of Ogba oluwole taxi parks near the ogba area.

Fig 4.11 Showing picture of another taxi park in Ogba area.

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4.4 Conclusion

In this work, GIS capabilities have been used to create a spatial data structure of taxi parks

located in Ikeja and Ifako-Ijaye local government areas of Lagos state, Nigeria. The study

attempts to resolve some of the challenges faced in locating existing taxi parks and creating new

taxi parks in the stated study areas and describes in detail the implementation and capabilities of

GIS for managing routing to and from the taxi parks.

The existing taxi parks in the local government areas have been shown and managed with

ArcGIS 9.3 (by: ESRI). The study has successfully demonstrated the effectiveness of Geographic

Information System for creating and managing taxi parks spatial data structure. The technology

adopted will enable easy data capturing, processing, updating and visualization and expansion of

the data structure to other local government area so long the WGS_UTM 84 coordinate system

was used.

Graphic data was also captured and attached to the appropriate taxi parks for clear description

and identification.

The built in topology had made it possible to build network analysis query on the system and

described interactions between these connecting nodes and edges. Stops were created to mimic

route navigation from one location to the other within the study area.

Some of the challenges encountered include inaccurate Taxi Park-local government classification

as some of these parks do not fall in the stated local government areas, software and hardware

configuration, difficulty experienced during data capture, groundtruthing, technical nature of

coordinate transformation process and time expended in creating and digitizing the spatial

attributes.

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5.0 References

The establishment of high resolution geodatabases for webGIS: from digital campus to

digital national park. Y.C Ding, C.C Hung, Beijing 2008.

Using GIS in strategic planning and execution at FedEx express Jacquelyn Haas- FedEx

services, Jeff Mcleod- FedEx services, Rick Dezemplen- FedEx services, Rodney

Conger-ESRI 2010.

O. Kufoniyi. (1998): Principle and Application of Geographic Information System. 1st

Edition Vol.1, Lagos: Panaf Press, 1998.

A GIS Based Route Determination in Linear Engineering Structures InformationManagement (LESIM) Volkan YILDIRIM, Recep NISANCI, Selcuk REIS,

Turkey 2006.

W.A YINKORE (2005): Legends of the Nigerian Railway Corporation Since 1955 A

Chronicle. Promocomms Limited. 2005.

Omogunloye O. G and Oni A. M, (2005): A GIS Analyses of junior secondary school

certificate examination performance distribution in Lagos Mainland LocalGovernment Area.

Obianwo oluwatobi 020405023 Dec, (2007): Application of GIS to property management

(case study of Pat Obianwo and Co operations within Lagos state).

Documents

SVY818 SDS Lab Report1