2010

GIS Training: Module 5 Geocoding and importing health data

IER/HSI/GIS

ii

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this publication is complete and correct and shall not be liable for any damages

incurred as a result of its use.

Module 5: Geocoding and Importing Health

Data

Aim

The aim of this module is to introduce and understand the principals of geocoding

health data at country level, sub-national level, and city or settlement data.

Overview

Geocoding is a GIS operation that matches attribute data in one database with

similar attributes in a georeferenced database. The result can be displayed as a

feature on a map or used for analytical purposes. In practical terms, health data

must be associated with a spatial location in order to make it "mappable" and to

conduct geospatial analysis on it. Thus, the majority of disease data and health

care data must be linked to a spatial component in order to view it in a GIS

environment.

Learning Objectives

By the end of this module, you should be able to:

Understand the basis and importance of geocoding.

Learn about country level coding systems.

Learn about sub-national level reference datasets.

Understand how to access standard geocodes.

Adequately prepare a database for mapping.

Apply global standards for geocoding a database

Exercises

Geocoding country level health data

Geocoding sub-national level health data

Geocoding city/settlement level health data

ii

5-1 Geocoding and importing health data

November 4, 2010

5.1. Understanding Geocoding

5.1.1 What is Geocoding? The majority of disease data and health care data must be linked to a spatial

component to view them in a GIS environment. Simply put, to make health data

mappable and to subsequently conduct geospatial analyses the health data must

be associated with a spatial location.

Geocoding refers as a GIS operation that matches attribute data in one database

with similar attributes in a georeferenced database. The result can be displayed as

a feature on a map or used for analytical purposes.

There are two methods used to geocode data:

1. Joining health data to geographical areas – This process means

linking health data with geographic features (countries, regions,

subdivisions). The association is based on a common coding system that

must be part of both the health data and the geographic data.

2. Address matching to locate a health event – This process means

assigning geographic coordinates (latitude and longitude) to health data so

that it is readily mappable. It requires a reference dataset, which is the

underlying geographic database containing geographic features, and a

program or a specialized software application that calculates location of the

health events.

5.2. Country level coding systems In many instances, standard codes are already attached with health data. If not,

you may choose any one of the standard coding systems. This code allows for the

health data to be associated with a spatial location on a map and is the attribute

used for the spatial join.

Different country level coding systems are available and adopted by different

agencies. The standard coding systems used by WHO include ISO 3166-1 alpha-2

code and ISO 3166-1 alpha-3 code.

ISO 3166-1 alpha-2 code

ISO 3166-1 alpha-2 codes are two-letter country codes defined in ISO 3166-1, part

of the ISO 3166 standard published by the International Organization for

Standardization (ISO), to represent countries, dependent territories, and special

areas of geographical interest.

ISO 3166-1 alpha-3 code

ISO 3166-1 alpha-3 codes are three-letter country codes defined in ISO 3166-1,

part of the ISO 3166 standard published by the International Organization for

Standardization (ISO), to represent countries, dependent territories, and special

areas of geographical interest. They allow a better visual association between the

codes and the country names than the two-letter alpha-2 codes.

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The WHO standard map templates contain both ISO-2 and ISO-3 codes in the

geographic layers. It is important to note that the ISO-2 codes are two-letter

country codes and are most widely used. However, the ISO-3 code, the three letter

coding system, is recommended for thematic mapping at the national level.

5.3. Sub- national level coding systems For administrative or health subdivision, reference datasets used for geocoding are

composed of polygon data. There are many geographic databases for the world

administrative divisions that are often difficult to maintain up-to-date as sub-

national entities change on a regular basis.

The data sources can vary greatly in terms of coverage and accuracy. Most of the

time, different agencies within the country use different coding systems and might

have different numbers of units. This makes mapping sub-national data quite a

challenge. There are some standard reference databases and coding systems for

sub-national level at global scale. These are SALB codes, FAO GAUL codes,

GADM codes, and WHO HealthMapper codes. It would be advisable to receive

reference geographic data during the data collection process from the respective

countries. Use the codes attached to the geographic data to assign to your health

data. If this is not possible, one of the above reference geographic data can be

used. Each of the standard reference data sets has certain pros and cons. It is

advisable to contact the data owners of these reference data before deciding which

coding system to adopt for your health data. WHO generally seeks out sub-

national data from the sources in the following order: SALB, GAUL, GADM,

HealthMapper.

SALB

SALB is a UN project, which has been launched in the context of the activities of

United Nations Geographic Information Working Group (UNGIWG) to provide the

international community with a global standardized GIS layer containing the

delimitation of the administrative boundaries down to the 2nd sub-national level.

SALB is the data received from national mapping agencies of WHO member states

and is considered a UN official source. SALB contains a record of historical

changes of boundaries since 1990. In many cases, the codes are available, but not

the spatial data.

FAO GAUL

The Global Administrative Unit Layers (GAUL), an initiative implemented by

FAO, compiles and disseminates spatial information on administrative units for all

the countries in the world, providing a contribution to the standardization of the

spatial dataset representing administrative units. The GAUL always maintains

global layers with a unified coding system at country, first (e.g. regions), and

second administrative levels (e.g. districts). The GAUL is released once a year

and the target beneficiary of the GAUL data is the UN community, universities,

and other authorized international and national institutions/agencies.

Data might not be officially validated by authoritative national sources and cannot

be distributed to the general public.

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November 4, 2010

GADM dataset

GADM, the Database of Global Administrative Areas, is a spatial database of the

location of the world's administrative areas for use in GIS and similar software.

Administrative areas in this database are countries and lower level subdivisions

such as provinces, departments, districts, counties, etc. GADM describes where

these administrative areas are (the "spatial features"), and for each area it

provides some attributes, foremost being the name and variant names.

GADM was developed to support various activities, including georeferencing of

textual locality descriptions (the BioGeomancer project) and for mapping census

type data. The development is led by Robert Hijmans, in collaboration with Nell

Garcia and John Wieczorek. Major contributions have also been made by Arnel

Rala, and Aileen Maunahan at the International Rice Research Institute and by

Julian Kapoor at the Univeristy of California, Berkeley, Museum of Vertebrate

Zoology.

WHO HealthMapper dataset

The WHO HealthMapper dataset contains comprehensive data in terms of global

coverage. This is a collection of geospatial data from countries through various

health data collection mechanisms. These data are good for mapping, but require

further cleaning for advanced geospatial analysis. The purpose of this dataset is to

cater to the WHO health community and provide data visualization, not to

generate a standardized global coverage. It contains layers on a country-by-

country basis, down to third, fourth, and lowers levels. Updates are performed as

per request and need from the community.

The table below provides a brief overview of each of the reference datasets.

5.4. How to access standard geocodes Standard geocodes can be located in a variety of places. Below you will find

specific for finding geocodes at the country, sub-national, and city/settlement

levels. In addition, information is provided on a geocoding web services tool being

developed by WHO which will give access to geocodes used by WHO or the UN.

Country level geocodes

ISO 3166-1 alpha-2 code

SEARCH

ORDER NAME INFORMATION

1 FAO GAUL Description

Global Administrative Unit Layers (Levels 1

and 2)

Coverage Worldwide

2 SALB Description UN Second Administrative Level Boundaries

Coverage Worldwide but sparse

3 GADM Description Global Administrative areas

Coverage Worldwide

4 WHO

HealthMapper

Description Administrative divisions (Levels 1 to 4)/

Health Divisions (Levels 1 and 2)

Coverage Worldwide/

Worldwide but sparse

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A complete list of ISO-2 codes can be found on the International Organization

for Standardization website:

http://www.iso.org/iso/country_codes/iso_3166_code_lists/english_country_name

s_and_code_elements.htm

A complete list of ISO-3 codes is available by request from the International

Organization for Standardization (http://www.iso.org/iso/country_codes). A list

is also available on Wikipedia at

http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3

Sub-national level geocodes

FAO GAUL

The GAUL layer can be downloaded from the FAO Geonetwork site at:

http://www.fao.org/geonetwork/srv/en/metadata.show?id=1269

SALB

The SALB layer can be downloaded from the UNGIWG SALB website at:

http://www.unsalb.org/

GADM

GADM layers are available for download from the GADM website at:

http://www.gadm.org/

WHO HealthMapper

The HealthMapper geocodes provide details of the exact location of

geospatial points (UNITID) or geospatial polygons (LVLID).

Units/points

Units are the smallest entities: towns, villages, schools, safe water points,

hospitals and health service centres

Different unit levels for the same country are hierarchically linked e.g. town

village school

Each unit has its unique identifier or UNITID (8 digits). For example:

MLP00234 : country=Mali, hierarchy type=Politic, sequence

no.=00234

ETH00234 : country=Ethiopia, hierarchy type=Health, sequence

no.=00234

Select the symbology tab and click on the box labelled symbol.

Select the image for Square 1

Polygons

Polygons are administrative areas and health districts.

Different polygons are hierarchically linked and the highest levels (admin1,

health1) are directly linked to the respective country code.

Up to 4 levels possible (admin1, ..., admin4 / health1, …, health4) (Levels 5

and 6 exist in the db, but are not used yet.)

Each polygon has its unique identifier (21 digits): LVLID

The table below provides several examples of polygon or LVLID codes:

5-5 Geocoding and importing health data

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S

e

q

u

1. S

1. Sequence number 324 of administrative sub-district level 3 in Mali.

2. Sequence number 324 of health sub-district level 3 in Ethiopia. No

health district level 2 defined, as surely not yet traced.

3. Burkina Faso country level.

You can get access to all the HealthMapper geocodes from views in SQL

server. The geocodes correspond to a global database containing geographic

data for all countries. The views are stored in a database on a production

server. You will find below the parameters to connect to it:

Server: GVA1SWLULUS

User: HealthmapGeocodeUser

Password: HealthmapGeocodeUser

SQL views for polygons:

Healthmap.dbo.vw_AdminLevel1

Healthmap.dbo.vw_AdminLevel2

Healthmap.dbo.vw_AdminLevel3

Healthmap.dbo.vw_AdminLevel4

SQL views for points:

Healthmap.dbo.vw_units

City/settlement level geocodes

There are various web services available for city level geocoding purposes. The

most frequently used geocoding web services are Google maps, Geonames, and

Yahoo map. These are available through various web sites. It is advisable to use

one of these web sites if you have few events to be geocoded.

You can use any of the following URLs to find the latitude and longitude of a place:

http://itouchmap.com/latlong.html

http://www.backups.nl/geocoding/index.html

http://www.opengeocoding.org/geocoding/geocod.html

http://www.gpsvisualizer.com/geocoding.html

http://www.mapchannels.com/GeocoderSimple.aspx

WHO geocoding services

Geocoding services will be created on the WHO web map server (ArcGIS server) to

give access to geocodes used by WHO or UN. This online service will work like the

ISO

country

code

Hierarchy

code

1 2 3 4 5 6 Note

ML P 002 001 324 000 000 000 (1)

ET H 002 000 324 000 000 000 (2)

BF P 002 000 000 000 000 000 (3)

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ArcGIS Online address locator and users will be able to access it with ArcGIS

desktop within WHO.

This geocoding framework will provide composite address locators and/or geocode

services. For administrative or health subdivision, the main reference datasets

used for geocoding will be made available through this service:

FAO GAUL

SALB

GADM

Healthmapper

At the moment, you can search the geocodes using the REST interface. REST,

shorthand for Representational State Transfer, is used as a mechanism to identify

and work with any Web resource, such as Web pages and Web resources.

Essentially, REST enables users to issue a series of operations or commands

against URLs and other Web resources (for example, URIs).

Step 1. Type the server URL http://gva1swjuno/ArcGIS/rest/services

Step 2. Click on Global_places

Step 3. Click on SALB admin2. You should see all the details concerning this

layer such as the geometry type and the list of fields.

Step 4. Click on Query layer.

Step 5. Enter Zambia as the CNTRY_NAME.

Step 6. For the result options, enter the return fields names with comma

separated: CNTRY_NAME,ADM2_NAME,ADM2_CODE

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Step 7. Click on Find. You should see the list of all the admin2 names and codes

for Zambia from the SALB reference dataset.

5.5. Preparing health data The more carefully you format your table, the better the geocoding process will

work. It is important that your data formatting is consistent throughout the

database. If you are using a spreadsheet to create this data set, make the first row

the field names, and start your actual records on the second row. Do not put in

other formatting or rows or columns, e.g., no titles, or spacer rows. The field names

should not include spaces or odd characters in the field name, and a maximum of

10 characters. Each row of data should contain only one province or one district

name.

It is advisable to use the geocodes from the reference dataset during the data

collection process. If it is not possible, you will need to format the dataset in order

to assign geocodes to the health data.

The Cholera Outbreaks 2010 table below is a good example of many of the issues

that can come up when dealing with geocoding sub-national level data. Can you

find some of the potential problems with this data set?

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CHOLERA OUTBREAKS 2010

Disease Start End Country Provinces / Districts WHO Region

Cholera 19-Oct-09 28-Mar-10 Zambia Lusaka, Copperbelt,

Southern

AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Cabo Delgado, Niassa,

Zambezia, Sofala,

Nampula

AFRO

Answers:

1. No title and no spacer rows. The first line of the spreadsheet should be the

column names.

2. There should be no spaces in the field names.

3. There should only be one province/district per row.

A correct table should look like the following:

DISEASE START END COUNTRY PROVINCE/DISTRICT WHOREGION GEOCODE

Cholera 19-Oct-09 28-Mar-10 Zambia Lusaka AFRO `

Cholera 19-Oct-09 28-Mar-10 Zambia Copperbelt AFRO

Cholera 19-Oct-09 28-Mar-10 Zambia Southern AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Cabo Delgado AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Niassa AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Zambezia AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Sofala AFRO

Cholera 01-Jan-10 10-Apr-10 Mozambique Nampula AFRO

5-9 Geocoding and importing health data

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Exercises: Geocoding health data The first step in geocoding health data is to determine the granularity or

resolution of available data. Is your data country level, sub-national level, or

city/settlement specific data? This set of exercises will explain how to geocode all

three types of health data.

Exercise 1: Geocoding country level data

For this exercise we will be geocoding a IMCI training coverage dataset

called IMCI_training_country_geocoding which can be found in the

MDX_geocoding folder.

Mostly disease data or health data are only represented at country level.

Capturing these data in GIS involves spatial joining. A spatial join is like

joining two tables by matching attribute values. In order to accomplish

this, both tables must have a common attribute. You will be using the

joining method for country level data.

Task 1. Choose reference data/standard coding scheme.

In many instances, standard codes are already attached with health data.

If not, you may choose any one of the standard coding schemes. This code

allows for the health data to be associated with a spatial location on a map

and is the attribute used for the spatial join mentioned above.

For this exercise we will be using the ISO-3 coding system.

Task 2. Task 2: Assign geocodes to the data.

The most common format of input data is Excel or MS Access but it can

also be from a variety of databases with OLEDB capabilities. You can

assign geocodes by transforming your input data (manual assignment) or

by using an excel spreadsheet with standard geocodes. For this exercise

we will review both methods.

Option 1: Modify your input data manually

To modify your input data manually take the following steps:

Step 1. Open the IMCI_training_country_geocoding data file.

Step 2. Create a new column called ISO3 in your data table.

Step 3. Add a unique country code for each country from the selected coding

system to the column. You can access a complete list of ISO-3 codes at

http://en.wikipedia.org/wiki/ISO_3166-1_alpha-3

Step 4. When you have completed entering data, you can save the excel

spreadsheet and close it.

Once the ISO3 columns have been added, your data table should look like

the following:

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NAME VALUE ISO3

Afghanistan 35.000 AFG Armenia 35.000 ARM Benin 65.000 BEN Bolivia 85.000 BOL Brazil 15.000 BRA Cote d'Ivoire 5.000 CIV Cameroon 5.000 CMR

Option 2: Use the data entry template with ISO codes

Another option is to use an excel worksheet created by WHO called the

DataEntryTemplate which will help to automate the process of assigning codes.

To modify your input data using the DataEntryTemplate, take the following steps:

Step 1. Open the excel spreadsheet called DataEntryTemplate.xls under the

folder MXD_geocoding, The list of countries is already populated along

with the ISO codes.

Step 2. You can enter your data in the last columns: indicator1, indicator2,

indicator3, indicator4. Enter the data from

IMCI_training_country_geocoding into the column indicator1.

Step 3. When you have completed entering data, you can save the excel

spreadsheet and close it.

Your data is now ready to be mapped.

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Exercise 2: Geocoding sub-national level data

For this exercise we will be geocoding a cholera outbreak dataset called

healthdata_subnational_formatted_result.xls which can be found in the

MDX_geocoding folder.

Disease data or health data can be reported by area name (administrative

subdivision, province, district, health subdivision, etc.). Capturing these

data in GIS involves geocoding using world administrative divisions as a

reference dataset then doing a spatial join to link the health data to the

geographic data.

Task 1. Choose reference data/standard coding scheme.

In many instances, standard codes are already attached with health data.

If not, you may choose any one of the standard coding schemes. This code

allows for the health data to be associated with a spatial location on a map

and is the attribute used for the spatial join mentioned above.

For this exercise we will be using the WHO HealthMapper coding

system.

Task 2. Assign geocodes to the data.

Step 1. Open the excel spreadsheet called

healthdata_subnational_formatted_result.xls

Step 2. Add a column 'GEOCODE' to your data sheet

Step 3. Your table should be similar to the one below

Step 4. Without closing Excel, save your excel spreadsheet.

Step 5. Start ArcMap and open the Global_detailed template located in the folder

MDX_geocoding.

Step 6. Save the map file with a new name under MXD_geocoding. Under File,

select Save as and name the file subnational_geodocoding.

Step 7. Click the Add Data button.

Step 8. Click the Connect to folder button.

Step 9. Connect to the folder corresponding to the GIS curriculum data sources

and click OK.

Step 10. In the Add Data dialog box, double-click on Geodatabase.mdb and select

the layer Merge_Admin1and2. Click Add.

Step 11. This layer contains all the administrative divisions for Africa with a

unique geocode (LVLID) for first, second, third and fourth administrative

levels.

Step 12. Right-click on the Merge_Admin1and2 layer and select Open attribute

table.

Step 13. In the table options menu, select Find and replace.

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Step 14. Enter the name of the administrative division to search "Lusaka" and click

Find Next.

Step 15. You should find the row corresponding to the Lusaka province.

Step 16. Right-click on the LVLID (ZMP001000000000000000) and select copy.

Step 17. Switch to your excel spreadsheet

healthdata_subnationallevel_formatted.xls

Step 18. Paste the LVLID for Lusaka in the column Geocode.

Step 19. Repeat the same operation for each row.

Step 20. At the end of the process your table should correspond to the one below.

Disease Start End Country Provinces

/ Districts

WHO

Reg.

Geocode

Cholera 19-

Oct-

09

28-

Mar

-10

Zambia Lusaka AFRO ZMP0010000

00000000000

Cholera 19-

Oct-

09

28-

Mar

-10

Zambia Copperbelt AFRO ZMP0020000

00000000000

Cholera 19-

Oct-

09

28-

Mar

-10

Zambia Southern AFRO ZMP0080000

00000000000

Cholera 01-

Jan-

10

10-

Apr-

10

Mozambique Cabo

Delgado

AFRO MZP0060000

00000000000

Cholera 01-

Jan-

10

10-

Apr-

10

Mozambique Niassa AFRO MZP0070000

00000000000

Cholera 01-

Jan-

10

10-

Apr-

10

Mozambique Zambezia AFRO MZP0100000

00000000000

Cholera 01-

Jan-

10

10-

Apr-

10

Mozambique Sofala AFRO MZP0080000

00000000000

Cholera 01-

Jan-

10

10-

Apr-

10

Mozambique Nampula AFRO MZP0010000

00000000000

Step 21. Save the excel spreadsheet and close it.

Your data is now ready to be mapped.

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Exercise 3: Geocoding city or settlement level data

Some health events are geo-referenced at the city or village level. The

place name can be converted to a point on a map by capturing latitude and

longitude. Capturing these data components requires address matching.

It is also possible to geocode a street address.

In case you have to geocode a list of place names in Excel or Access, you

can use the online geocoding tasks from Arcgis online. The World Places

Locator service can be used to geocode world places including countries,

states and provinces, administrative areas, cities, landmarks, water

bodies, and more. It is limited to 1,000 batches geocodes in a year.

For this exercise we will be geocoding a list of GOARM partners using two

different methods: ArcView address locator and alternative web services.

Option 1: Assign geo-codes using the ArcView address locator method.

Step 1. Open the excel spreadsheet called GOARN partners in the

MDX_geocoding folder and look at the file structure. You will notice that

there is a column called LOCATION with place names. Close the file.

Step 2. Start ArcMap and open the Global_detailed template located in the

MDX_geocoding folder.

Step 3. Click the Add Data button.

Step 4. In the Add Data dialog box, browse to where your data is stored and

highlight the appropriate file GOARN Partners.xls. The worksheet is

called Partners. Click Add.

To add an ArcGIS Online address locator to an ArcMap document:

Step 5. Click the Tools menu, point to Geocoding, then click Address Locator

Manager.

Step 6. Click Add in the Address Locator Manager dialog box.

Step 7. In the Look in drop-down menu, select GIS Servers, click Add ArcGIS

Server to highlight it, and click Add.

Step 8. In the Add ArcGIS Server wizard, Select Use GIS Services and click Next.

Step 9. Select Internet and enter the following Server URL:

http://tasks.arcgisonline.com/arcgis/services Click Finish.

Step 10. In the ArcGIS Server list, select "arcgis on tasks.arcgisonline.com" and

click Add.

Step 11. Select the Locators folder and click Add.

Step 12. Select the locator you want to add to the ArcMap document

ESRI_Places_World and click Add.

Step 13. Click Close.

Step 14. Right click on the table Partners in the TOC and select Geocode addresses.

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Step 15. Select the Address locator to use Locators/ESRI_Places_World and click

OK.

Step 16. In the PlaceName dropdown list select LOCATION.

Step 17. Select the folder and the name of the output shapefile that will be created

and click OK.

Step 18. A new shapefile should be added in ArcMap.

Step 19. After a table of addresses is geocoded and saved in a geocoded feature

class, you may need to review matched addresses or geocode ones that

went unmatched. When the geocoded feature class is added to the map,

the Review/Rematch Addresses button on the Geocoding toolbar is

enabled. Clicking the button opens the Interactive Rematch dialog box,

where you can review and select records to rematch.

Option 2: Assign geo-codes using a web service.

Step 1. Open the excel file city_web_geocoding and take a look at the fields:

NAME, LATITUDE, AND LONGITUDE. All of the cities need latitude

and longitude coordinates.

Step 2. Open a web browser and open the geocoding web site:

http://www.backups.nl/geocoding/index.html

Step 3. Enter the place name you are looking for and click on search.

Step 4. The geocoding web service will return the geographic location as 'latitude

(lat)' and 'longitude (long).'

Step 5. Copy the value that appears under the latitude box to your data file under

the latitude column.

Step 6. Copy the value that appears under the longitude box your data file under

the longitude column.

Step 7. Repeat for all the cities on your list. Save and close the file when

complete.

Step 8. Start ArcMap and open the detailed template located in the

MDX_geocoding folder.

Step 9. Click the Add Data button.

Step 10. In the Add Data dialog box, browse to where the city_web_geocoding file

and highlight then click Add.

Step 11. Right click on the data table you have added and select Display XY data.

Step 12. Indicate the longitude column for the X field.

Step 13. Indicate the latitude column for the Y field.

Step 14. Click OK.

Step 15. The places should be displayed on the map.