Terefe Abel

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Tampere University Applied SciencesDepartment of Environmental EngineeringAbel Terefe

FINAL THESIS

Application and use of GIS in small Sanitation projects

in Developing countries

Supervisor: Head of the forestry degree program, senior lecturerEeva Sundstrm

ommissioned by: !eTu ry

Tampere "une #$%$

Tampere Universit of Applied sciencesDepartment of Environmental Engineering


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Author: Abel Terefe&ame of report: Application and use of '(S in small sanitation pro)ects in developing countries&umber of pages: *+Supervised by: Eeva Sundstrmommisioned by: !estv Tuulevaisuus ry -Tampere.

A!ST"A#T

Sanitation problems are prevalent in many developing countries/ 0opulation e1plosion and climate

change cause people to move from their home to cities fueling unemployment, the creation of slums

and illegal settlements 2ith 2hich also comes chronic sanitation problems/ To solve the problem of

personal sanitation and hygiene in areas 2here the population density is higher than normal, a

number of &'3s in Ethiopia had ta4en the initiative to build group toilets/ 'roup toilets are

basically built for a group of households on a certain part of a city/

(n the summer of #$$5, !eTu, a 6innish &'3, launched the 7ahir dar Sa8E pro)ect 2hich includes

a plan to build more sanitation facilities such as toilets, sho2er rooms and biogas digesters / The

pro)ect in its infancy also 2anted to study the e1isting sanitation conditions in selected pro)ect

areas/ The study 2as mainly through a survey that 2as meant to find out 2here and at 2hat

conditions the e1isting group toilets 2ere found in/

This report is part of the initial studies of !eTu and it is about ho2 '(S can be applied in assisting

decision ma4ing in small scale sanitation pro)ects in developing countries/ (t tries to analy9e the

data obtained from the baseline survey and sho2s ho2 simple information can be put to use to

ma4e important decisions such as 2here to build the ne1t group toilets, 2here are the hot spots and

cold spots/

Thus, the 4ey findings of this paper is more than simply identifying the 2hereabouts of group toilets

on maps/ 7ut it also sho2s ho2 '(S can be integrated into small scale sanitation pro)ects in

developing countries 2ith limited fund/ Thereby, it greatly enhances decision ma4ing and the 2ise

use of resources 2here budget constraint is an issue/

$e %ords: Sanitation and '(S, 'roup toilets, Sanitation in Ethiopia, Sanitation in 7ahir dar,

Developing countries, 0ublic toilets in Ethiopia

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Foreward

(n the summer of #$$5, the 7ahirdar sanitation, 2ater and energy-Sa8E. pro)ect 2as launched by a

6innish &'3 called !eTu -an acronym for Sustainable future in 6innish langauge. and an

Ethiopian &'3 called ;E< the environment and development society of Ethiopia/ The pro)ect 2asmainly aimed at helping the locals tac4le sanitation problems using simpler, cheaper yet 2or4able

technologies/ These includes the adoption of urban agriculture, construction of biogas digesters and

toilets and other sanitation facilities such as sho2er rooms/

During the actual pro)ect implementation, it 2as decided to carry out a baseline survey at the initial

stage/ The survey included the study of all group and public toilets in the selected pro)ect areas/

Ho2ever, an interesting aspect of the study 2as the use of 'eographic information system elements

in the survey/ (t 2as done in a manner such that all the toilets 2ere located 2ith a '0S receiver/ The

incorporation of '(S elements into the study has had several advantages/

;ater that year, ( 2as offered by !eTu to 2rite a comprehensive conclusive report on the survey/

This paper is part of the pro)ects report on the survey in #$$5/

Abel Terefe

"une #$%$, Tampere

ii


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Table of Contents

A7ST=AT//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////i6ore2ard///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////ii

;ist of tables///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////iv;ist of 6igures////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////iv

Acronyms/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////v%/ (ntroduction//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////%%/% Socio>economic problems and sanitation condition//////////////////////////////////////////////////////////////////%%/* Using '(S for decision ma4ing/////////////////////////////////////////////////////////////////////////////////////////////////*

#/ 'etting the relevant data///////////////////////////////////////////////////////////////////////////////////////////////////////////////////?#/% 3rgani9ation of data///////////////////////////////////////////////////////////////////////////////////////////////////////////////////@#/# 'eoreferenced data////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

* / Description of the 2or4 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////5*/% The 7ahirdar Sa8E preliminary survey and mapping//////////////////////////////////////////////////////////////5*/# E1porting data into Arc'(S/////////////////////////////////////////////////////////////////////////////////////////////////////%$*/* oordinate Systems/////////////////////////////////////////////////////////////////////////////////////////////////////////////////%#

*/*/% 'eographic coordinate system/////////////////////////////////////////////////////////////////////////////////////////%#*/*/# 0ro)ected oordinate system////////////////////////////////////////////////////////////////////////////////////////////%**/B Selecting features and SC; e1pressions//////////////////////////////////////////////////////////////////////////////////%B

B/ =esults////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////%?B/% 'eographic patterns spatial statistical analysis ///////////////////////////////////////////////////////////////////////%?B/# hallenges in '(S 2or4 in developing countries////////////////////////////////////////////////////////////////////%+

B/#/% Data availability and accessibility////////////////////////////////////////////////////////////////////////////////////%5B/#/# Data management/////////////////////////////////////////////////////////////////////////////////////////////////////////////%5B/#/* ;ac4 of '(S S4ills////////////////////////////////////////////////////////////////////////////////////////////////////////////%5

B/* Sources of error////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////#$?/ onclusion and discussion/////////////////////////////////////////////////////////////////////////////////////////////////////////////#%

=eferences://///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////#*

Appendi1 ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////#?A/ 7ac4ground data///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////#?7/ Hotspot Analysis result on 2or4ing group toilets using number of households//////////////////////#@/ 0ublic toilets 2or4ing and closed/////////////////////////////////////////////////////////////////////////////////////////#+D/ 'roup Toilets 8or4ing and losed////////////////////////////////////////////////////////////////////////////////////////#E/ Unemptied toilets Toilets built before #$$@ and never been emptied////////////////////////////////////#5

iii


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List of ta&les

Table %/ Toilet data field and descriptionTable #/ Some of the common factors that have been 4no2n to impede the efforts to implement'(S@

List of Figures

6igure %/ The modern planning process in '(S-Aronoff %55?#6igure #/


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Acronyms

!eTu !estv Tuulevaisuus ry -Sustainable future association.

Sa8E Sanitation 8aste and Energy

'(S 'eographic (nformation System'0S 'lobal 0ositioning System

SA entral Statistical Authority

SC; Structured Cuery ;anguage

ES=( Environmental Systems =esearch (nstitute

6(D 6eature (D

E0S' European 0etroleum Survey 'roup

UT< Universal Traverse


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Tampere University of Applied Sciences 6inal ThesisEnvironmental Engineering Department Abel Terefe I "une #$%$

1. Introduction

The 7ahirdar Sa8E-Sanitation 2aste and Energy. pro)ect is a pilot pro)ect being underta4en by!eTu ry in the city of 7ahirdar, Ethiopia/ (t constitutes the study of the sanitation conditions in

selected areas, urban agriculture and a biogas pro)ect/ The pro)ect 2as started after a deal 2as set

bet2een the various sta4eholders in Ethiopia and 6inland / The overall pro)ect is funded by the

6innish 6oreign ministry/ The pro)ect in Ethiopia is administered by a local &'3 called ;E< the

environment and development society of Ethiopia and overloo4ed by the municipality of 7ahir dar

as part of the citys development program/

The city of 7ahir dar is located in the north 2est of Ethiopia in the Amhara regional state/ (t is4no2n for hostingLake Tana2hich is the source of the longest river in the 2orld,Nile/ TheBlue

Nile, as opposed to the White Nilethat starts from la4e Jictoria, contributes to more than @$K of the

2aters of the &ile serving as an important source of fresh 2ater for many millions of people in

various countries along the river course*/ This ma4es the pro)ect area of some international

significance/

7ahir dar city suffers from recurrent seasonal flooding usually from the end of being of the la4e/ A

large number of people use the la4e 2ater for domestic use such as drin4ing and coo4ing food, on

the other hand, fishery is also another important source of income for a great deal of people living

along the la4e shore/ Tourism also plays an important role in the local and national economy/ The

diversity of 2ildlife and vegetation in the area generates a decent amount of income to the city and

the regionB/

1.1 Socio-economic problems and sanitation condition

The city has several socio>economic problems/ The rapid shift to urbani9ation and changes in the

living style of 7ahir dar city is challenging the municipality in providing the necessary services,

specifically sanitation and urban 2aste management GHin44anen B/ According to the entral

%


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Statistics Agency of the 6ederal Democratic =epublic of Ethiopia #$$@ census report, the

population of 7ahir dar city is estimated to be around %+? %?/ The population gro2th rate is about

*K due to migration of people from rural areas and high birth rate?/

The continuous increase in population number has caused a series of problems/ To mention fe2,

increase in illegal settlements and slums, poor urban 2aste management, unemployment and lo2

economic performance/


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integrates hard2are, soft2are, and data for capturing, managing, analy9ing, and displaying all forms

of geographically referenced information -ES=( ./


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imagination of the real 2orld scenario/ A large amount of different data becomes more conceivable

and easier to understand 2ith maps/

3ne of the most interesting and earliest e1amples of '(S and spatial analysis is the study on the

outbrea4 of cholera in the %?$s in ;ondon/ 8hen cholera 2as poorly understood, there 2ere large

scale outbrea4 at the time of the industrial revolution/ 3ne approach to studying the causes of

cholera 2as based on maps 2hich 2as done by "ohn Sno2/ Dr/ Sno2 noticed that the outbrea4

appeared to be centered on public 2ater pump in 7road Street and he thought that the cause of

cholera might have been due to the contaminated 2ater contrary to the then belief of people that

cholera is due to polluted air/ He then tried to establish trends bet2een the supposedly polluted

2ater pump and the causalities 2ho dran4 from the pump/ Upon his investigation it 2as discovered

that among the deaths of people situated farther from the 7road Street pump, half of the deceased

preferred the 2ater from the 7road Street pump to their nearer pump, and another third attended

school near the 7road Street pump5/ After presenting his findings to the community leaders, the

handle of the 7road Street pump 2as removed, and the epidemic diminished/ ;ater it 2as found

B

Fig. 1: The modern planning process in GIS(rono!! 1""#$%$&

Data Collection

Input of Data

Data retrieval

and analysis

Information for

decision making

Take actionReal World

Data Sources

Data

Management

Analysis

Users


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out that a se2er pipe underground 2as lea4ing ra2 se2age into the drin4ing 2ater of the 7road

Street pump/ (n the process of his discovery Dr/ Sno2 thought that a map 2ould be a useful tool to

his report/ 6igure # sho2s one of Sno2s original maps/

2. Getting the relevant data

3ne of the significant challenges in '(S 2or4 is obtaining relevant data/ After all, the data lies at

the heart of geographical information system/ The data used in '(S represents something about the

real 2orld at some point in time/ They are al2ays an abstraction of reality because 2e dont need or

2ant every bit of data, )ust the ones 2e thin4 2ould be usefulGAronof %55?#/ The data that 2e

consider relevant is the first constraint on the capabilities of the '(S/ This in fact means that

ultimately the result depends on the Fuality of the data/

?

Fig. %: 'ap o! holera deaths in London )* +ohn Sno, $"$


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The most important aspects of data Fuality are accuracy, precision, time, currency, and

completeness/ Accuracy is about ho2 often, by ho2 much, and the predictability of the correctness

of the data/ 0recision indicates the fineness of the scale 2ith 2hich the data 2as described/ The timeindicates the interval at 2hich the data 2as ta4en or the point 2hen the data 2as ta4en/ Time can

usually affect the Fuality of data critically/ Let currency tells about ho2 recently the data 2as

collected/ And completeness refers to the portion of the area of interest for 2hich data is available

GAronof %55? #/

Data Fuality is al2ays costly to achieve/ (n fact, there is an inverse relation ship bet2een data

Fuality and data cost/ The follo2ing figure sho2s the relation ship bet2een the data Fuality and

cost/

2.1 "rgani#ation of data

Data organi9ation is another important factor that needs to be done for a good use of '(S/ There are

several spatial data models to ta4e care of data organi9ation/ Some of the traditional data models

are:

%/ overages -sometimes referred to as layers or themes%%. are one of the basic spatial data

models/ (t is a georelational data model that stores vector data/ overages contain spatial

@

Fig. -: The relationship o! data ualit* and data cost

(dapted !rom rono! 1""# $%$&


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information representing location and and an attribute data for geographic featuresGES=(

%#/

#/ Shapefiles: is one of the most common spatial data model for Arc'(S/ A shapefile stores

nontopological geometry and attribute information for the spatial features in a data set/ (n

other 2ords, a set of vector coordinates are used to store the geometries of a feature as a

shape/ Shapefiles are easier to read and 2rite and reFuires less dis4 space/ (n addition, they

have advantages over other data models in such a 2ay that they have faster dra2ing speed

and edit ability%$/ A shapefile in Arc'(S consists of three file systems/ These are main file,

inde1 file and a d7ase table/ The main file is a direct access, variable>record>length file in

2hich each record describes a shape 2ith a list of its vertices/ (n the inde1 file, each record

contains the offset of the corresponding main file record from the beginning of the main file/

The d7ASE table contains feature attributes 2ith one record per feature/ The naming

convention suggests that all the files have the same name and the name must start 2ith

alphanumeric characters -aM, $5., follo2ed by 9ero or up to seven characters -aM, $5, N,

>.GES=(, %$ / 6or e1ample a Toilet shape file 2ould loo4 li4e the follo2ing/


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2.2 Georeferenced data

'eographic data is usually composed of t2o 4inds of information/ The first and obvious

information is the location data on the surface of the earth, i/e/ 1>coordinate and y>coordinate valuesor longitude and latitude values/ The second is the phenomenon being reported at the given

location/ 6or e1ample, the population si9e at area A%, the public toilets in a given section of a city,

height of forest canopy, soil type etc #/ Additional to the t2o attributes though, time is also an

important component of geographic data/ That is because data has a period of validity/ A certain

geographic data for e1ample may only be valid for a specific period of time/ Ho2ever, the data can

be used to trace history of the given location/ 6or instance, a land area 2ith a pine forest may be

given for property developers to become a settlement for a group of people/ (n this regard, thehistory of this particular place can be traced bac4 by the data before and after the settlement/

'eographic data can be represented in maps through points, lines or area features called polygons/

See 6igure B/

0oints are used to represent features that have insignificant area compared to their surrounding or

the scale of the map/ 6or e1ample, houses, trees, even cities on small scale maps can be represented

as points/ ;ines are used to represent ordered set of connected points/ 6or e1ample, boundaries of

countries, rivers, roads etc/ (t should also be noted here that the scale of the map is one of thedetermining factors as to ho2 to represent features on the map/ An area feature is a region enclosed

by line feature/ Area features are represented by polygons/ An area 2ith a curved boundary can be

closely appro1imated by ma4ing the line segments of the polygon continuously smaller/ These three

features are mainly represented using the vector data model %/

Fig. /: 0epresentation o!

points lines and pol*gons


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Several boo4s define georeferenced data in many 2ays/ 3ne definition of it is a uniFue data 2here

only one location is associated 2ith a given georeferenceG;ongley, 'oodchild,


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6igure ? sho2s the survey form in its original form/

3.2 &porting data into *rcGIS

7efore e1porting the data to Arc'(S, it is necessary to prepare the data to be fed to the Arcmap

program in a usable and simpler form/ The toilet data 2as sorted into several column of fields/

These fields are the 4ey features of the toilet/ They should be able to provide the most important

information about the toilets for our study/ The longitude and latitude values 2ere converted from

degree minute second format to decimal degrees format %B/ 3n top of that, the large volume of

data 2as condensed using numbers and easily recogni9able 4ey terms to facilitate ease of use of the

data/

The ra2 data is a mi1ture of all 4inds of data typesGSee Appendi1 A/ 6or e1ample, the location,

number of rooms and number of households are interval data types since the values can be correctly

determined/


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2ere represented by Te1t or String data types/ 6inally, ordinal or categorical data types 2ere used to

represent the building and hygiene condition of a particular toilet/ These 4inds of data are described

relative to each other/ 6or instance, the condition of the building of one toilet can be described asbad 2hile another toilets condition of building might be e1tremely bad/ This 2ay of categorical

classification 2ould help us to 4no2 sub)ectively 2hich toilets are in really bad condition and

2hich are better of/

Ta)le 1: Toilet data !ield and description

Field name Description Data Tpe

O ;ongitude value e/g/ E$*+o#*#/BP Double

L ;atitude value e/g/ &%%o*?$+/P Double

4ebele The 4ebele 2here the particular toilet isfound in

Te1t

buildingNc The condition of the building/ e/g/ failingroof, failing 2all,

Te1t

rooms &o of rooms in a single toilet building Short (nteger

usersNroom &o of households that o2n a 4ey of asingle room - &o/ of households per one

room.

Short (nteger

empNfreFNy Ho2 often the septic tan4 is emptied inone year

Short (nteger

convenNnam onventional name is a name of a popularperson or place near the toilet/ (t is used asa conventional 2ay of identifying thetoilet 2ithin the locals/

Te1t

hygieneNc The hygiene condition of the toilet/ Te1t

onNDate The year the toilet is supposed to have

been constructed/

Date or Te1t

builtNby The organ responsible for the constructionof that particular toilet

Te1t

type (f the toilet is group or public toilet/ Te1t

(n addition to the above listed fields, arcmap 2ill also add fe2 columns of fields by default/ 3ne of

these is the 6(D 2hich is the ob)ect (D and guarantees a uniFue (D for each ro2 in the table/ !ey

functions, such as scrolling and displaying selection sets, depend on the presence of this field

%%


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GES=( %?/ (n other 2ords, if a table lac4s an ob)ect (D field, it 2ill not be possible to select

features in the layer on the map in any2ay/ And the other field that is created by default is the

SHA0E field 2ith type 'eometry/ The geometry data type indicates the type of geometry, that ispoint, line, polygon, multipoint, or multipatch 2hich the table stores/

3.3 +oordinate Systems

(n the process of e1porting data to Arc'(S, it is also important to understand the underlying

coordinate system that the data is based on/ There are t2o main classes of coordinate systems/

These are 'eographic coordinate system and 0ro)ected coordinate system/

'('() Geograp*ic coordinate sstem

(t is a method of describing a geographic location on the earths surface using measure of angles

from the center of the sphere to the point on the surface/ The method mainly uses the longitudes and

latitudes to locate a point on the surface of the earth/ See 6igure @/

(n the geographic coordinate system, the sphere is divided into eFual parts 2hich are called degrees/

Each degree is subdivided into @$ minutes, 2ith each minute subdivided into @$ seconds/ The

longitude 2hich runs bet2een north and south measures angles from >%$oto Q%$o east or 2est

%#

Fig. 4: 5sing the latitude and longitude to

locate a point on the sur!ace o! the

earth6Source:7S0I$14$8
http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=132&pid=103&topicname=Geographic_Coordinate_Systemhttp://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=132&pid=103&topicname=Geographic_Coordinate_Systemhttp://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=132&pid=103&topicname=Geographic_Coordinate_System


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from the prime meridian/ And latitudes run bet2een east and 2est and measure angles bet2een >5$

to Q5$ north or south of the eFuator/

Users 2ith global datasets often use geographic coordinates to store and manage their data on a

global frame2or4 but pro)ect the data into a local planar coordinate system for editing and analysis

%@/ The '0S uses the geographic coordinate system to locate points on the ground/

'('(+ ,rojected #oordinate sstem

A pro)ected coordinate system is a flat, t2o>dimensional representation of the earth/ (t is based on

the geographic coordinate system that mainly models the spheroid/ Ho2ever, it uses linear units of

measure for coordinates to simplify area and distance calculations/ (n pro)ected coordinate system,the latitude and longitudes are converted to O and L coordinates on a flat pro)ection/ ES=( suggests

that 2hen 2or4ing 2ith data in a geographic coordinate system, it is sometimes useful to eFuate the

longitude values 2ith the O a1is and the latitude values 2ith the L a1is/

The three>dimensional geographic coordinate system therefore is transformed into a flat t2o

dimensional coordinate system using mathematical formulas and the process is called map

pro)ection/ See 6igure +/

According to the E0S's geodetic parameter registry, 7ahirdar under the pro)ected coordinate

system lies in the Adindan UT< Mone *+&/ The underlying polygon 4ebele layers and the 4ebele

boundary layers 2ere produced in this coordinate system/ Ho2ever, the toilet locations 2hich 2ere

read from the '0S receiver 2ere under the geographic coordinate system/ (n importing data to

Arc'(S, it should be made sure that the t2o coordinate systems are compatible and the toilets are

%*

Fig. 9: Simple

representation o!

proected coordinate

s*stem6Source:7S0I

$19$8
http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=91&pid=90&topicname=About_projected_coordinate_systemshttp://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=91&pid=90&topicname=About_projected_coordinate_systems


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represented at the correct places/ To handle this 4ind of coordinate system incompatibility, Arc'(S

has a function that is capable of ma4ing conversions of 'eographic coordinate systems into any

form of pro)ected coordinate systems/

3., Selecting feat'res and S epressions

Selection is a very common operation in '(S/ 8e often need to select a group of features from a

large data/ (t enables us to build relationships 2ithin the data and ma4e classifications of the large

data into finer and simpler groups/ There are several 4inds of selection techniFues in Arc'(S/ (

2ould only discuss here about selection by attributes using SC; e1pressions/

SC; -Structured Cuery ;anguage. is a standard computer language for managing data in relationaldatabases/ A SC; Fuery is a reFuest for data from a database using a SC; e1pression/

Selection by attributes is one such prominent feature of Arc'(S that is handy 2hen it comes to

selecting features using their attributes from a layer/ 6or e1ample, from all Toilets, one may be

interested in the toilets that 2ere built four or more years ago and had never been emptied/ Using

the Select by attribute feature of Arc'(S 2e can 2rite a SC; e1pression to retrieve the toilets that

2ere built before #$$@ and never been emptied/

SELE#T-F"./toilets0HE"E:

RonNDateR 12#$$@ ANDRempNfreFNyR 2 $ AND- RbuildingNcR2bad ."RbuildingNcR 2

e1tremely bad ."RbuildingNcR 2good ."RbuildingNcR 2tolerable ."RbuildingNcR 2very

good .

8hat the above SC; e1pression does is, from the T3(;ETS layer it selects the toilets 2here the

attributes are such that construction date is in #$$@ or before #$$@P 2ith 9ero emptying

freFuencyP and those toilets that are operational/ (n other 2ords, the building conditionbuildingNcP can have all values e1cept closed/

After selection, 2e can e1port the selected features to a separate shapefile that can be added as a

ne2 layer into the map/ Such functionality is very handy 2hen dealing 2ith a large bul4 of data and

2hen a separate analysis of the portion of the data is reFuired/

The other 4inds of selection techniFues includes, selecting interactively 2hich is by clic4ing a

feature on the map and selecting that particular feature/ Select by location also has a lot more

advanced capability to determine spatial relationships/

%B


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#. $esults

,.1 Geographic patterns spatial statistical analysis'eographic patterns are essential to decision ma4ing/ !no2ing if there is a pattern in a large

amount of data is useful to get a better understanding of a geographic phenomenon, to monitor

conditions on the ground, compare patterns and trac4 changes %/'eographic patterns could be

completely clustered or they can be randomly dispersed/ lusters might be statistically significant

phenomena to analy9e/ 8henever clusters e1ist, it might imply that there is a cause for the clusters

in 2hich 2e can be interested in/ 6or e1ample, a cluster of group toilets is one such e1ample/ 8hy

do 2e have more group toilets in one part of the city than in the other This might lead us to thecause of the clusters 2hich in our case could be individuals income level or education etc/ 3n the

other hand, for a retail company, study of the clusters of customers 2ould help them to 4no2 2here

to build their supermar4ets/ 6or the toilets data, it might be necessary to e1amine if the group

toilets data and the number of households tend to be clustered or dispersed/ Arc'(S has the average

nearest neighbor distance tool to test geometric clustering/ That means, 2ithout ta4ing the attribute

values of the data into account, it 2ill only measure the distance bet2een each feature and its

nearest neighbor/ (t then calculates the mean for all these distances and compares it to a hypothetical

%?

Fig. ;: Screenshot o! the 3erage Nearest Neigh)or distance anal*sis

result !or group toilets (rcGIS


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random distribution %5/

And the result as sho2n in figure says, there is less than %K li4elihood that this clustered pattern

could be the result of random chance/ Therefore, 2e can conclude that the group toilets are

geometrically clustered/

Ho2ever, in the above analysis 2e didnt ta4e into account the important attribute of the group

toilets data 2hich is the number of households using the toilets/ Therefore 2e also need to chec4 if

the number of households using the toilets are indeed clustered or not/ The High;o2 lustering

tool indicates if either high or lo2 values tend to be clustered 2ithin the data/ (n figure 5, The

higher the 'eneral ' value is, the more clustered the high values are in the data/ The lo2er the

'eneral ' value is, the more clustered the lo2 values are in the data/ The M Score sho2s the

strength of the association/ (f the M Score is very high -or very lo2., there is a strong association/ (f

the M Score is near $, it indicates that there is no apparent clustering 2ithin the data %5/

The result sho2s that the number of households 2ithin the data are random 2hile there may be

some clustering to2ards the high values/

3nce 2e have done the cluster analysis, 2e use the hotspot analysis tool to find 2here the spatial

%@

Fig. ": =igh$Lo, lustering tool result !or num)er o! households in

,orking group toilets6rcGIS


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clusters of high and lo2 attribute values are located/ (n hotspot analysis, areas 2ith larger number of

households than the average or areas 2ith lo2er number of households than the average and tend to

be found near each other are statistically calculated/ 6igure %$ sho2s the results of hotspot analysisof number of households using group toilets in the study area/ The hot spots are the points in red

2ith relatively large number of households using a single toilet near each other/ And the cold spots

are the light blue points 2hich are clusters of households 2ith lo2 number of users/

As 2e see from the above e1ample, hotspot analysis is a very po2erful tool in studying spatial

patterns/ (t thus can strongly aid decision ma4ing in sanitation pro)ects by sho2ing 2here the real

problems occur and 2here e1actly action is needed %5/

,.2 +hallenges in GIS /or! in deeloping co'ntries

The application of '(S in developing countries has many challenges/ The challenges are diverse

and of varying degree/ ;ac4 of infrastructures and s4illed human po2er , lac4 of a2areness and

fund are some of the 4ey challenges to mention/ There is a lot of inter>connectivity bet2een these

%+

Fig. 1>: =otspot anal*sis !or num)er o! households using group toilets


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challenges/ (n fact, it is virtually impossible to loo4 at the one 2ith out describing the other/

'(S is a fairly e1pensive technology to use in developing countries/ The cost of data collection, cost

of soft2are hard2are and costs of employing and training '(S staff is beyond 2hat most African

countries can do at a local level/ ;ac4 of internet connection or its limited speed ma4es

communication and data transfer difficult/ Ho2ever, shortages of staff 2ith the appropriate s4ills

and training is the biggest constraint even above shortages of funding @/

;ac4 of support from institutions and lac4 of a2areness among senior managers of 2hat '(S can

actually do to help empo2er decision ma4ers 2ith a more reliable and simpler model of the real

2orld scenario is by itself another problem/ 8ith very little 4no2ledge of the senior managers

about '(S, it is virtually impossible to get their support to allocate resources to the development of

'(S/ Therefore, it is essential to 2or4 to raise a2areness of the governing bodies to convince them

allocate resources to2ards the development of the technology/

Ta)le %: Some o! the common !actors that ha3e )een kno,n to impede the e!!orts to implement GIS

6dapted !rom 'aking GIS ,ork in de3eloping countries: 3ie,s !rom practitioners in !rica8

(nfrastructure Suitability and security of buildings ;imited communication and access to information EFuipment hard2are and soft2are problem

Data ;imited availability Cuality and currentness of data ;ac4 of adeFuate base mapping Difficulty in sharing data 0oor data management e1isting data is hard to find

Human =esources ;ac4 of trained staff ;ac4 of a2areness ;o2 priority for staff training

0oorly developed self>help net2or4s6inancial ;imited budget for maintaining the pro)ect

High cost of proprietary soft2are (nsufficient budget for staff training

(nstitutional &o political or legislative support &o government policy ;ac4 of a2areness 2ithin the government bodies onflict of interest

%


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3(+() Data availa&ilit and accessi&ilit

The lac4 of spatial data infrastructures-SD(. is the biggest challenges to get bac4ground materials

for the pro)ect/ Data relevant to the 7ahir dar SA8E 0ro)ect 2as obtained through surveys andfrom the 7ahir dar cadastre office/ These includes, the toilets data 2hich 2as obtained through a

baseline survey conducted by !eTu ry and 4ebele boundary and base map from the cadastre office/

Ho2ever, much relevant data such as population number in the 4ebeles and the income distribution

is not available/ To ma4e a reasonably good use of '(S in the pro)ect there needs to be more

physical data collection in different areas of the city/

(n addition, there is lac4 of clear administerial responsibility as to 2ho ta4es care of the data

concerning the conditions of sanitation and other related issues/ (n principle, it is the responsibility

of the 7ahirdar 2ater bureau to 4eep data about the sanitation issues in the city/ Ho2ever, it is

impossible to 4no2 2hich department really has the relevant data 2ithin the bureau/

3(+(+ Data management

The municipality of 7ahirdar has no identifiable library for relevant sanitation data in digital form

or paper form 2ithin the city/ And there is no formal 2ay for sharing data and information 2ithin

the government organi9ations themselves/


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build capacity and on the other side, the lac4 of a2areness of the senior management groups to

allocate resources, preventing those interested in driving '(S for2ard to ma4e managers a2are of

its relevance and potential creates a vicious cycle that goes no 2hereG@/

,.3 So'rces of error

(n this basic and preliminary 2or4 there is e1pected to be fairly some amount of errors/ These errors

could be related to the challengers mentioned above/ Some of these are:

%/ Cuality of data: in the 7ahir dar SA8E pro)ect a calculated ris4 2as ta4en due to limitations

of fund, s4illed labor and lac4 of eFuipments/ 6or e1ample, the location of the toilets varies

bet2een *m and *$m in the actual sites/ This is due to the use of fairly old and simple 4indof '0S receiver device and it 2as decided to go 2ith 2hat 2e have from the outset than to

spend more money to get a better receiver/

#/ Survey techniFues: During the survey of the entire group and public toilets, the information

2as obtained by intervie2ing the locals/ And there 2as no single documented data used

from any government office or other non>governmental institutions/ (n most cases, during

the intervie2, 2hen people 2ere unable to tell 2hat 2as as4ed they tend to appro1imate

numbers or guess facts/ This 2ould definitely have a conseFuence in the Fuality of data

obtained/ Ho2ever, this techniFue has also enabled us to see 2hat e1actly peoples need is

and 2hat facts lie on the ground/

*/


27/35


threshold or the distance band 2as set to default/ These ris4s 2ere ta4en by assuming that

the area under investigation 2as so small and thus the difference in result using the

'eographic coordinate system 2ouldnt be significant/

B/ (nterpretation of results: (n the final interpretation of results, it is necessary to note the

combined effect of all other potential sources of uncertainty/ The final results are the

products of the various factors involved in the study/ This includes personnel, data,

eFuipments, methods , and bac4ground information used/ Each of this factors uniFuely

influence the results of the analysis/

%. Conclusion and discussion(n this essay, the intent 2as to sho2 ho2 '(S can be put to use in small scale sanitation pro)ects in

developing countries especially in the 7ahir dar Sa8E pro)ect/ The use of '(S can systemati9e the

decision ma4ing process for a proper resource distribution over the pro)ect areas/ (t has also been

sho2n that the integration of '(S can be done 2ithout spending a large amount of money/ After

conducting the study of the sanitation facilities, '(S has enabled us to have a more conceivable

picture of the area/

%/ The results have sho2n 2hich areas have the highest density of users per toilet room/ This is

sho2n in the hot spot analysis/ And it 2as possible to see 2hich areas are better of

compared to the 2orst toilets/ This has the advantage of 4no2ing 2here to build e1tra toilets

to relieve the problem/ (n the mapGAppendi1 7, it 2as sho2n that the 'ishabay 4ebele is

the 2orst affected in terms of toilet inadeFuacy/ This can actually be sub)ectively proved

from our observation/ The 'ishabay 4ebele is one of the oldest 4ebeles in the city of 7ahir

dar/ (t has a population of about % 5+* inhabitantsGHin44anen #$$5/ The chairperson of the

4ebele, Ato Eyaya &egatu says the 4ebele has a lot of small enterprises and a severe

sanitation problem/ The distribution of toilets compared to the number of people living in

the 4ebele is totally unmatchable/ This is mainly because a lot of people live in a small piece

of land 2here the land isnt legally issued to them or by illegally e1panding their bloc4 of

land and 2ith the lac4ing supervision of the concerned organ from the 4ebele

administration, every open space has been inhabited/ (n this 4ebele, more than 5? K of

toilets are in real bad condition/ (t 2as also noted that most of the toilets 2ere lac4ing either

roof or the floor slab 2as deteriorating/ This on the other hand, raises the issue of safety

#%


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concerns especially for children/

#/ Secondly, the use of maps has e1plicitly sho2n us the distribution of public and group

toilets, closed and 2or4ing toilets over the study area/ This provides a general picture as to

2hich 4ebeles have the largest number of group toilets or public toilet/ (t 2as also sho2n

2hich 4ebeles has e1tremely bad toilets, bad toilets, good toilets or very good toilets/ (t

is no 2onder that this 4ind of analysis can be done 2ith other 4inds of statistical methods/

&evertheless, maps have the advantage of enabling us to 4no2 the location in the real 2orld/


29/35


$eferences&

Books:

%/ ;ongley, 0aul A/, 'oodchild, +$$%>O paperbac4

#/ Aronof, Stan, %55?, 'eographic information systems: A management perspective, (S7& $>5#%$B>5%>% paperbac4

rticles:

*/ 7loc4, 0aul "/, #$$+, (ntegrated +

+/ is>gisinde1/html

5/ "ohn Sno2, (nc/and "S( research and training institute, (nc/ G3nline cited April #$%$/Availablehttp:222/)si/com"S((nternetAbout"S(drsno2/cfm

%$/ ES=( Shapefiles technical description: An ES=( 2hite paper X "uly %55 G3nline citedApril #$%$/ Available http:222/esri/comlibrary2hitepaperspdfsshapefile/pdf

%%/ '(S ;ounge, (nformation about 'eographic (nformation Systems, '0S, cartography, andgeography G3nline cited April #$%$/ Available http:gislounge/comcoverage

%#/ Spatial Data


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%@/ ES=( Arc'(S 5/# des4top help, 'eographic coordinate systemGonline cited


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%. 0otspot *nalysis res'lt on /or!ing gro'p toilets 'sing n'mber of ho'seholds


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. Gro'p $oilets Wor!ing and +losed


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&. nemptied toilets $oilets b'ilt before 2445 and neer been emptied

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