GIS and Decision Making: The key to Durban’s challenges

EThekwini Municipality

2297 square kilometers

Population: ~ 3 500 000

House holds: ~ 800 000

Informal Dwellings: ~ 235 000

Formal Households: ~ 600 000

Employees: ~ 18 000

Watermains: ~ 11354.367 km

11175.646 km street network

Internal and external customers

Desktop and web GIS environments

~125 GIS data sets

The question is:Is the GIS used to help make decisions, or is it used to justify

decisions made for many other reasons?

Easy access to information

"Knowing where things are and why it is there, is essential to rational decision making"

Geographic Information System

Planning

Data Collection/ Analysis

Service Provision

Revenue Collection

Monitoring & Evaluation

Our GIS Strategy

• To make best use of information and communications technology to support integrated systems and sharing of municipal information

• To ensure appropriate organisational infrastructure to support the vision and objectives of our IDP and ICT strategy

• To ensure that interested and affected individuals and our Service Centers have the information they require to enable them to make informed decisions

• To ensure that appropriate information to underpin decisions for improving provision of our services is available.

Our Uses of a GIS• A Management tool in all aspects of infrastructure

management• Planning and Monitoring • A visualisation tool for improved identification• Environment of seamless, paperless interaction between

departments• Improved property information management and analyses• Improved efficiency as data is made centrally available

via an integrated GIS infrastructure

Improved business processes and better decision making

Directs our corporate Geographic Information Systems policy and provide spatial information and support to all users within eThekwini Municipal area in order to facilitate informed decision making and enable users to achieve their objectives

Our Central Hub

Corporate GIS

Special Consent Decisions Spatially Captured

Decisions on Subdivisions Spatially Captured

AREAS COVERED BY A FORMALISED SCHEME

Existing Scheme ‘District’ Map

Zoning Maps and Scheme Controls

Land Use

Zoning

Land Use

Environmental Management

Knowing Our Consumers

Informal SettlementsFormal Settlements

ETHEKWINI MUNICIPALITY

APPROVED SPATIAL DEVELOPMENT PLANS 2011

GIS METHODOLOGY

Income Levels

1:15000 A0 maps with the MrSid Images (Aerial Photography), Cadastral, Future Residential Income, Informal Settlements and the 5 Year Housing Projects were plotted for the Framework Planning Staff to use to identify proposed housing developments in the North Spatial Development Plan.The Future Residential Income shapefile was copied and renamed to Future Residential Income Levels. A field called Income Level and Name was added to the attribute table.

Planning Units

The Planning Units in the North Spatial Development Plan identified by the Framework Planning Staff were classified as Low, Low to Medium, Mediumand High (R. Dyer, email dated 7 May 2008). These income levels were added to the attribute table.

Informal Settlements and 5 Year Housing Projects

Proposed residential developments was digitized in the Future Residential Income Levels, using the Informal Settlements and the 5 Year Housing Projects as a base layer in the North Spatial Development Plan identified by the Framework Planning Staff were classified as Low, Low to Medium, Medium,

Medium and High (R. Dyer, email dated 7 May 2008).

AGRICULTURE

Fazal Ebrahim used the Bioresource Research Program to identify agriculture areas for the SDP's in 2009. Fazal Ebrahim, A Nansook, A. Zungu, F. Ngcobo and K. Singh met with Dept of Agriculture, Brent Forbes in February 2009 at Cedara and Brent Forbes confirmed that the SDP Agriculture areas aligns with Dept of Agriculture.

The SDP data and documents were hand delivered to the various provincial departments in October 2009. No comments were received. Fazal obtained an updated version of the BRU in 2010. Piers Whitwell confirmed that no changes were made to the data. In February 2011 second set of SDP data and documents was given to the various Provincial Depts. No comments.

ETHEKWINI MUNICIPALITY SPATIAL DEVELOPMENT PLANS 2011

SDP LAND USE CATEGORIES

INCOME INCOME LEVEL

LOW R 120 000.00

LOW TO MEDIUM R 120 000.00 – R 450 000.00

MEDIUM R 450 000.00 – R 1 000 000.00

MEDIUM TO HIGH R 1 000 000.00 – R 2 000 000.00

ETHEKWINI MUNICIPALITY SPATIAL DEVELOPMENT PLANS 2011

SDP LAND USE CATEGORIES

Field Name Description

GIS_ID A unique ID for the polygon used during calculations

AREA_HA Area of the polygon in hectares

LU_PROP The ultimate landuse of the polygon

UNIT_TYPEThe type of unit used for infrastructure loading calculations, e.g. dwelling units for residential and hectares for commercial

Not that landuse type MIXED USE has both dwelling units and hectares

DENS_PROP The ultimate dwelling unit density of the polygon

DEVELOPABL

The proportion of land (as a percentage) within the polygon that can be developed.

Oversteep areas (slope > 1:3), 100 year floodplains, major road reserves and railway reserves have been considered.

Note: the area of local roads, i.e. 25-30% of the polygon has not been included in this figure, but has rather been accommodated in the density number.

DEV_EXIST The current proportion of developable land (as a percentage) within the polygon that can be developed.

ULT_DU The calculated ultimate number of dwelling units in the residential landuse polygons given the polygon areas, developable land and ultimate densities.

ULT_HA The calculated ultimate number of developed hectares in the non-residential landuse polygons given the polygon areas, developable land and ultimate densities.

INCOME The anticipated income categories for residents of residential polygons.

PHASING The anticipated development date of the polygon.

LU_DETAILS Miscellaneous details on landuse.

COMMENTS Brendan Magill comments for consideration by Planning Unit.

ETHEKWINI MUNICIPALITY SPATIAL DEVELOPMENT PLANS 2011

SDP LAND USE CATEGORIES

FIELD NAME TYPE WIDTH DECIMAL DESCRIPTION

Developable Numeric 5 0 The developable area of the polygon (as a % of the polygon)

Dev_Exist Numeric 5 0 The percentage of the polygon developed (as a % of the developable area)

LU_Details String 25   If applicable

LU_Exist String 25   If applicable

LU_Prop String 25   The ultimate landuse of the polygon

Dens_Ex Numeric 5 1 A single figure shows existing densities

Dens_Prop Numeric 5 1 A single figure that can be used to calculate ultimate number of units in the polygon

Units_Ult Numeric 5 0 The calculated proposed number of dwellings in the polygon

Income String 25   High, Medium to High, Medium and Low

Phasing String 12   Timing 2010

ETHEKWINI MUNICIPALITYAPPROVED SPATIAL DEVELOPMENT PLANS 2011

North SDP South SDP

ETHEKWINI MUNICIPALITY SPATIAL DEVELOPMENT FRAMEWORK 2012

ETHEKWINI MUNICIPALITYAPPROVED SPATIAL DEVELOPMENT PLANS 2011

Central SDP North South SDP

ETHEKWINI MUNICIPALITY SPATIAL DEVELOPMENT FRAMEWORK 2012

Wards & Councilor Details

Electricity Network

Electricity

Watermains and fittings

Internet as means to providing public information

• Today’s decision needs to be information driven• Our systems and tools needs to contribute towards

fulfilling the objectives of the IDPs• Geographic information should be the bases for

monitoring, evaluation systems and performance management

Conclusions

The eThekwini Municipality Thanks You!!

www.durban.gov.za

19 September 2012