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"
Planning
Monitoring
& Evaluation
Data
Collection/
Analysis
Geographic Information
System
Revenue
Collection
Service
Provision
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
Our Central Hub
Corporate GIS
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
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 Settlements
Formal 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, Medium
and 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
MEDIUM
R 450 000.00
MEDIUM TO HIGH
R 1 000 000.00 – R 2 000 000.00
–
R 450 000.00
– R 1 000 000.00
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
The type of unit used for infrastructure loading calculations, e.g. dwelling units for residential and hectares for commercial
UNIT_TYPE
Not that landuse type MIXED USE has both dwelling units and hectares
DENS_PROP
The ultimate dwelling unit density of the polygon
The proportion of land (as a percentage) within the polygon that can be developed.
DEVELOPABL
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
ULT_DU
ULT_HA
The current proportion of developable land (as a percentage) within the polygon that can be developed.
The calculated ultimate number of dwelling units in the residential landuse polygons given the polygon areas, developable
land and ultimate densities.
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 MUNICIPALITY
APPROVED SPATIAL DEVELOPMENT PLANS 2011
North SDP
South SDP
ETHEKWINI MUNICIPALITY
SPATIAL DEVELOPMENT FRAMEWORK 2012
ETHEKWINI MUNICIPALITY
APPROVED 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
Conclusions
• 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
The eThekwini Municipality
Thanks You!!
www.durban.gov.za
19 September 2012