EOPOWER – FP7 European project Earth Observation for Economic Empowerment http://www.eopower.eu        

EOPOWER project is co-funded by the European Commission under the Grant Agreement 603500; THEME [ENV.2013.6.5-2 ENV.2013.6.5-2]

 

   

Updated and extended portfolio of success stories for the SADC region

Title : Updated and extended portfolio of success stories for the SADC region

Creator :Naledzani Mudau Creation date :25 April 2015 Date of last revision :28 May 2015 Subject :Report on updated and expected portfolio stories for the SADC

region Status :Final Type :Other Description :Report about D5.20 Contributor(s) :Paida Mangara Rights :The South African National Space Agency Identifier :SANSA-EOPOWER_D5.20 Language :English Relation :EOPOWER Partner  

   

   

AUTOMATED METHODOLOGY FOR HUMAN SETTLEMENT MAPPING USING HIGH RESOLUTION

IMAGERY- SOUTH AFRICA

 Human settlement is one of the most dynamic land use activity. This is evident in developing countries as a result of population increase and urbanization than in developed countries. Urbanization is one of the major contributors to land degradation and service delivery problems in South Africa and SADC region. Recent studies reveal that most of the global population growth will occur in smaller towns and

cities in the developing countries in the next 30 years. South

Africa’s five fastest-growing urban areas experienced average annual population growth rates of between 1.6% and 2.9% over the last decade. There is a need to spatially map human settlement developments to support decision making. The South African government has a number of initiatives that are aimed at improving the livelihoods of its citizens through creation of an environment for sustainable human settlement development. Most of these activities require information on human settlement during planning phase. As a result, there are a number of projects initiated by government departments that are aimed at mapping human settlement data. The methodologies used in these projects are either manual digitization or pixel based classifications which are time consuming and resources extensive. To respond to this challenge, the South African National Space Agency (SANSA) has initiated a human settlement project which is aimed at developing methodology that (semi) automatically extracts human settlement data from available satellite imagery.

KEYS TO SUCCESS

• COLLABORATION Collaboration with JRC, custodian of GHSL system, a human settlement detection system.

• FEASIBILITY

Using data that is available to the South African community, the system can be customised to process other open access data

• REPLICATION POTENTIAL The methodology can be customised to suit open access data. Processing hardware requirements depend on the size of the input data.

• SOCIETAL BENEFIT Improves decision making on sustainable human settlement development

Figure1: SPOT 5 mosaic of South Africa

Figure 2: Automatically human settlement (in white) data from SPOT 5 imagery

Figure 1 above represents a picture of SPOT 5 mosaic of South Africa which is acquired by SANSA and distributed to all government users at no additional cost. The current phase of the human settlement project focuses on the automation of extraction of human settlement data from SPOT 5 imagery.  

SUCCESS STORY

SUCCESS STORY

Human settlement detection using SA-GHSL system SANSA in collaboration with European Commission, Joint Research Centre (JRC) has developed a SA-GHSL system that automatically detects human settlement data from SPOT 5 imagery. This is a customized version of the Global Human Settlement Layer (GHSL) system developed and maintained by JRC. The system uses the textural, morphological and radiometric properties to detect human settlement. Using this system the first South African National Human Settlement Layer was developed using SPOT 5 imagery acquired in 2012. See Figure 2 for a picture of building structures extracted using this system. The product is resampled to 5m spatial resolution. This layer shows the location of human settlement structures in the country. Figure 3 shows human settlement and basic land cover classification generated using the SA-GHSL system. Land cover classification results enable users to assess the impact of human settlement on the environment. The success of this project means that users will now have access to free, consistent and up-to-date human settlement data required in spatial decision making. Figure 3 shows a building density map derived from this human settlement layer. Building density maps can support population estimation and service delivery demand amongst other applications. This human settlement layer is currently being used by various government departments and public entities that require human settlement data. This layer will also contribute to the Global Human Settlement Layer (GHSL) project.

Figure 4: Density map derived from SA-GHSL

RESULTS ü High resolution national human

settlement data of South Africa ü Human settlement types and land

cover classification ü Possibility to develop human

settlement value added products ü Contribution to global initiative on

human settlement information

CONTACT INFORMATION The South African national Space Agency Enterprise Building, Mark Shuttleworth Street, Innovation Hub, Pretoria, 0087, South Africa www.sansa.org.za

Figure 3: land use classification results