SPOTS QUANTIFIES RAPID URBAN CHANGE 
S. L. Ferreira * *, M. de Meyer", H. Loots ^, N Keyise“ 
* GeoTerralmage, 53 de Havilland Crescent, Persequor Technopark, Pretoria, South Africa - (fanie.ferreira, 
marizette.demeyer, nozuko.keyise) ? geoterraimage.com 
? Geospace International, Glenwood Road , Lynnwood Ridge, Pretoria, South Africa - henniel 9 geospace.co.za 
KEY WORDS: Urban, Change Detection, SPOT, Land Use, Mapping. 
ABSTRACT: 
The rapidity of urban dymanics has a significant impact on the spatial patterns associated with the growth and expansion of 
metropolitan areas. High resolution satellite imagery with equally rapid image update capabilities offers significant potential for 
helping to maintain the accuracy of associated cadastre, municipal subdivision boundaries, voting districts and enumeration areas 
(population census zones) in these urban areas. This paper demonstrates the value of combining new high resolution satellite image 
sensors such as Spot5 with enumeration areas (EA's) in a geographical information system to identify urban change as well as 
quantifying the type of change in a metropolitan area in South Africa. 
Spot 5 images were recorded during August 2002 for the Pretoria metropolitan area in South Africa in all three modes (10m, 5m & 
2.5m). All of these images were combined with enumeration areas (EA's) from the October 2001 Population and Housing Census in 
South Africa, as produced by Statistics South Africa. To map urban growth and model associated change, the urban EA’s 
(consisting of appoximately 200 households per EA) were selected as a base framework around which change would be determined. 
As a next step, all new areas of growth were assessed in terms of using SPOTS for more quantitative house counts in order to 
demarcate new EA’s boundaries. The results indicate that both the Spot5 Colour (10m) and Panchromatic (5m) are sufficient to 
detect and classify urban growth, while the colour enhanced Supermode and the Supermode can be used with confidence to detect 
individual house structures in formal residential areas and to use this to demarcate new EA's. 
1. INTRODUCTION possibilities to use a more cost efficient approach, by reducing 
the amount of imagery required. This study is aimed at 
The rapid growth in metropolitan areas in South Africa over the evaluating these options available from the range of Spot5 
last decade is a direct result of legislation implemented by the sensors and its associated use and applications for updates of 
previous government for 40 years. This legislation limited enumerator areas used in Population and Housing Census 
migration to metropolitan areas and when the new government surveys. 
came to power in 1994 and abolishing such regulations, the 
increased flow of people resulted in the creation of informal 
housing areas around the urban perimetre. 
2. SCOPE 
As a result metropolitan areas in South Africa are very 
  
  
  
dynamic, which result in rapid change of the spatial patterns 
and land use associated with such areas. A significant impact of 
this growth and expansion is that a number of jurisdictional and 
legislative boundaries become outdated very quickly. One of 
these data layers is enumerator areas (Census Zones) used for 
Population and Housing Census surveys, which requires 
updates very 10 years. 
Normal census intervals are not frequent enough to incorporate 
this rapid change, and therefore the requirement for other 
methods to capture this growth. High resolution satellite 
imagery such as Spot5 offers the possibility to capture rapid 
urban change on a regular interval, and allows quantification of 
such change through counting individual residential structures. 
This study is investigating the use of the Spot 5 high resolution 
sensors in the population census domain. Census survey zones 
(enumerator areas) are usually updated form high resolution 
aerial photography, but with the launch of Spot5 it provides 
  
Corresponding author 
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This study has two components which relate to census 
cartography. Firstly, census cartography requires the 
identification of any change in urban patterns. This change 
mostly occurs on the urban perimeter, but could also occur 
within metropolitan areas. Secondly, once change in urban 
patterns have been identified, these areas have to be quantified 
which then allows update of the demarcation of enumerator 
areas (EA’s) 
To address the first component namely the identification of 
change, the first aim of this study was to assess all the sensors 
and derived data sets (colour enhanced merged images) for use 
in urban change detection. Areas of urban change were then 
classified into urban structural classes. The second component 
was to assess the value of the image data for quantification and 
that could allow the update and demarcation, of EA’s. The 
images were therefore assessed for its use on the following 
three factors: 
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