July 14th, 2016, Published in Articles: EE Publishers, Articles: PositionIT

by Rufus Ramotlou, University of Salzburg

 

This article focuses on how spatial data was gathered, put together and was used by the Housing Development Agency in 2012 to address informal settlement growth in Limpopo urban towns, particularly informal settlements with residents without legal land rights.

The Millenium Development Goals of the United Nations (UN) provide a platform for the nations of the poor communities to improve lives by 2020 as attested by the National Housing Code in South Africa [1]. South Africa is part of the UN so it adheres to the UN habitat programmes, which are: The Vancouver Declaration on Human Settlements, the Istanbul Declaration of Cities and other Human Settlements, and the Habitat Agenda. The Department of Human Settlement (DOHS) in South Africa has introduced two programmes – the National Upgrading of Informal Settlement Programme (NUSP) and the Upgrading of Informal Settlement Programme (UISP) – which are consistent with the DOHSs National Housing Code’s programmes.

Both programmes’ main objectives are to cater for the special development requirements of informal settlements in the country and the National Housing Code programmes provide for in situ upgrading of informal settlements which involve the provisioning of grants to municipalities to carry out the upgrading of informal settlements within their jurisdiction, mainly for the facilitation of the upgrading versus relocation with the following objectives: tenure security, health, security and empowerment [1].

Background

According to the South African Yearbook, the human sector in South Africa remains one of the most challenging areas in the social and economic environment. South Africa is seen as a country where population continues to create an increasing demand within the property market for well-located land and housing. The South African Yearbook confirms that President Jacob Zuma changed the Department of Housing in 2009 to the DOHS, and changed the focus – shifting from housing being just a roof over people’s head to providing integrated human settlements [2].

The mission of the DOHS is to facilitate the creation of sustainable human settlement and improve the quality of household lives by financing, promoting, communicating and monitoring the implementation of housing and sanitation programmes. It was also emphasised in an article in City Press by the then minister of Human Settlements, Tokyo Sexwale, that the growth of informal settlements which compounded the problem of meeting the demand for housing resulted in undesirable urbanisation driven by less economic growth and more by rural urban migration of the poor and unemployed [3].

The Housing Development Agency was commissioned to investigate the availability of data and to analyse the data relating to the profile, status and trends in informal settlements nationally, provincially as well as for some larger municipalities [4]. As per the research project’s terms of reference the scope of analysis included:

• Establishing the national, provincial and local databases and information sources where the necessary information can be obtained.
• Highlighting the limitations of each data source as well as possible refinement and further work that would be required to improve data quality on an ongoing basis, specifically for informal settlements depending on data provided interalia: number of informal settlements, growth and development of settlements, etc.

It is noted in the Housing Development Agency Informal Settlement Status of Limpopo research report that “there has been a noticeable increase both in stated ownership and rentals for those who live in shacks not in backyards, and however, data on tenure status can be difficult to interpret”. The report points out that there was no indication as to whether the settlement is formal or informal (i.e. whether there is title deed). See Fig. 1 for the demonstration of dwelling tenure in Limpopo as outlined in the research report.

Taking into consideration the decision that there has been a noticeable increase of both in stated ownership and rentals who live in shacks, not in backyards, and tenure status being difficult to interpret, the research project was initiated with the Department of Geoinformatics at the University of Salzburg as thesis research to try and explore how government entities in South Africa use spatial data to analyse informal settlement growth, particularly for Limpopo urban towns with residents or households without legal land right. The project proposal was submitted during June 2015 and approved by the university.

Data collection and quality assessment

The data collection was done both in the form of primary and secondary data collection. Secondary data collection included revisiting the Housing Code of 2009 [1] to reflect on the 2020 Millennium Development Goals, the South African Yearbook [2] which shows human settlement as a continued challenging area in the social and economic environment and the City Press article reflecting on the growth of informal settlement which compounded the problem of meeting the demand for housing and undesirable urbanisation [3]. As outlined in the thesis, the primary data was sampled in the form of questionnaire interviews with organisations involved in the project, which included three government entities and one consulting firm. The questions raised focused on how information was gathered, circling three concepts:

Information on datasets

• What spatial data did data collectors gather?
• Was there any standard put in place for data to be collected?
• What standard was used?

Methodologies used on data sets

• How did you use all spatial datasets in the project to analyse growth?

Justification of the end results

• In applying the methodology to analyse data, what in particular has informed the decision that indeed Limpopo is one of the provinces with a number of informal settlements with residents without legal land right?
• If data standards were put in place for analysis, did data producers meet those standards?
• If standards were not met, how severe was the shift?
• Which towns have experienced growth in terms of informal settlements?

National Department of Human Settlement

The use of spatial data to study informal settlement growth in the Limpopo urban towns report acknowledges that the DOHSs “Informal Settlements Change Assessment Report” outlined the collaborative project initiated between the DOHS and the South African National Space Agency (SANSA) for the development of an atlas reflecting on spatial perspectives of informal settlements in the country [6]. The available informal settlements datasets used as reference were: NDHS IS Atlas, 2009; Eskom’s SPOT Building Count, 2008; StatsSA Dwelling Frame, circa 2006; Northwest IS dataset, 2008; IS data from some municipalities, and the Department of Water Affairs, 2011.

Table 1: Summary of findings [6].

Province	No. of IS Polygons in 2006	No. of IS Polygons in 2011	Change: No. of IS Polygons	IS 2006 Area (km2)	IS 2011 Area (km2)	% Change (Area)
Eastern Cape	260	269	+9	19,633	20,237	3,08
Free State	95	114	+19	12,893	19,111	48,23
Gauteng	295	315	+20	57,555	57,803	0,43
KwaZulu-Natal	398	429	+31	39,01	49,794	19,95
Limpopo	39	50	+11	11,832	12,482	5,49
Mpumalanga	80	75	-5	14,395	16,121	11,99
Northern Cape	32	48	+16	4,285	6,865	60,21
North West	77	132	+55	9,623	10,944	13,73
Western Cape	326	361	+35	13,461	15,405	14,44
Total	1602	1793	+191	182,687	205,762	12,63

At the same time, the following datasets were used during the environmental and access to road infrastructure analysis of settlements: Wetland, updated in 2011, at 1:50 000 scale; Rivers, updated in 2011 at 1:50 000 scale; Roads, updated in 2012, NDHS; and Cadastral, updated in 2012.

According to the thesis report, SANSA used SPOT5 satellite imagery at the spatial resolution of 2,5 m to do the following research: Map the spatial location of informal settlements between 2006 and 2011; assess the development status of informal settlements between 2006 and 2011; conduct analysis on environmental status of informal settlements in 2011; and conduct analysis on access to road infrastructure. It was also reported that due to time constraints and availability of relevant municipal officials, only settlements in Limpopo municipalities and the Northern Cape were verified through two separate interactive workshops. The data gathering exercise involved adding information about settlements in a table, relating to the name of the settlement and the status of upgrade and existing services. A unique ID was created for each informal settlement.

Nevertheless, the study did not measure the density or number of structures within the informal settlement atlas. See Table 1 for the summary of the findings. Challenges in reference data included different sources of imagery, acquisition dates and mapping scales, therefore made it difficult to map a large area overview.

Housing Development Agency-Head Office

The Housing Development Agency Head Office (HDA-HO) reported that the appointed consulting firm, Eighty20, embarked on the exercise of door-to-door administration of data collection using an electronic enumeration system using electronic devices to collect real time data and real time data for tracking data inputs throughout the process [6]. HDA-HO contracted service providers to manage field work done by Eighty20 using rapid assessment reports, and aerial photos from Google Earth to understand the layout of the study area to demarcate the area. Once an entire settlement was enumerated, GPS coordinates of each structure were mapped on Google Earth to ensure that coordinates are within the demarcated study area. The surveys were checked by project inspectors to ensure quality and where, for argument sake, photographs were found not to be compliant with field work, a field worker had to revisit the structure to take a new photograph [6].

Limpopo Provincial Department of Cooperative Governance, Human Settlement and Traditional Affairs

Limpopo Provincial Department of Cooperative Governance, Human Settlement and Traditional Affairs (COGHSTA) contracted the Housing Development Agency Limpopo Programme (HDA-LP) to assist it in the project [6]. It is attested in the thesis that HDA-LP hired two consulting firms, Molemotheo and Kayamandi Development. The two companies used Android cell phones loaded with a questionnaire. They took photos for structures and logged GPS coordinates. It is noted that data was loaded on the latest Google maps. However, there was no standard set for data collection and therefore no reference was used in that regard.

How spatial data was used to do the analysis

NDHS

The image interpretation and manual digitisation were used to map the location of informal settlements in a GIS environment [6]. The extent of informal settlements was captured as a polygon based on 2011 imagery at a mapping scale of approximately 1:10 000. The 2011 polygons were used to generate a 2006 informal settlement polygon layer. It is also reported that key challenges included being able to establish whether a polygon covering the area indicating informality represents a single informal settlement or a cluster identity. The only way to address that was through the use of inputs by local knowledge.

HDA-HO

The HDA-HO report is based on the data enumerated by Census 2011, the data of the Informal Settlement Atlas of 2009 by NDHS, the enumeration by HDA-HO from 2012, and a comparative analysis was done and the results indicated informal settlement growth [6].

ArcGIS was used and because informal settlements are complex in nature, settlements in old borders of townships such as in Polokwane remained fairly stable whilst settlements where there was booming economic activities such as Lephalale that experienced a significant growth due to mining activities. HDA-HO carried situational analysis qualitatively supported with mapping where settlement profile as well as land tenure arrangement to determine the legality of the land tenure. The settlement profile information included settlement patterns, growth and development of the settlement, accessibility, access roads, positioning of structures, and economic base of settlement: access to economic opportunities, and communities’ economic initiative [6].

COGHSTA

As described in the report, data collectors used Android cell phones to capture photographs for structures and login GPS coordinates as well. The report also outlines that the information was loaded on the latest Google maps and compared with old Google maps to determine growth. It is confirmed in the report that, there was no GIS at the time and therefore it became difficult to furnish how growth was determined [6].

Findings

The objective of the research was to explore how government entities use spatial data to determine new informal settlement growth in South Africa with an ambition to understand how data was used to determine growth in Limpopo urban towns to study the informal settlement growth with households without land tenure. The hypothesis included three concepts: information gathering, methodologies used and the justification of the end results. The results indicate:

• The project between NDHS and SANSA involved the use of SPOT5, where satellite images were captured in a period of eight and ten months in 2011. The challenges experienced were insufficient referenced data due to data captured with different purposes and at different times. The only data verified was for the Limpopo and Northern Cape provinces.
• Polygons of informal settlements were digitised and workshops in both provinces provided attributes including an informal settlement name, status of upgrading, services and unique ID’s were captured.
• Analyses were carried out in ArcGIS and Limpopo was amongst the provinces that indicated informal settlement growth. See Table 1 and Fig. 2.
• HDA-HO used the data collected by Eighty20 from its enumerated areas, enumerated data by Census 2011, and the Information Settlement Atlas of 2009 by NDHS. As noted in the report the qualitative situational analyses were supported with mapping where a settlement profile was done. According to the report [6], there was no standard or reference used so far. The only data collected and verified during their project was the door-to-door survey done by Eighty20.
• COGHSTA through HDA-LP had Molemotheo and Kayamandi Development doing household data collection using Android cell phones. Data was loaded on Google maps and compared with the old Google maps. However, there was no reference for their data, nor any means of data verification done. It is also reported that Deeds search was used to verify tenure, however there was no information evident nor any map-related information provided.

Discussion

In discussing the results above, it is taken into consideration the provisions of the South African Spatial Data Infrastructure Act, No. 54 of 2003, that data custodians must capture and maintain metadata for any spatial information held by it in accordance with the Act [7]. Section 17 of the act urges that a user or a vendor must report any deficiency in the quality of spatial information to the data custodian or data vendor who supplied the information within the period prescribed after discovering that deficiency.

It further states that if the data custodian or data vendor does not respond within the prescribed time, the user or data vendor may refer the matter to the Committee of Spatial Information, and the committee may take remedial action. Quality as defined in the act means the degree to which spatial information has been captured or collected satisfies stated or implied needs and it includes geographic information about lineage, completeness, currency, logical consistency and accuracy of spatial information. ISO 19139 schema defines the technical encoding specifications of metadata as attested by Metadata and Catalogue Services [8]. ISO 19115 further provides a comprehensive vocabulary and structure of metadata.

In cognisance of data requirements for informal settlement growth together with land ownership and non-ownership growth analysis, there is no doubt that imagery datasets would play a major role in that regard. Remote sensing techniques are indispensable when dealing with phenomena that are highly dynamic through time and space [9]. SANSA, working on a collaborative project with the NDHS, used SPOT5 satellite images captured between eight and ten months, and the pixels were sharpened to 2,5 m resolution for the identification of structures. This is adequate data and it is relevant enough to analyse structural change. SANSA further updated their cadastral data for 2011, Rivers, Roads, Wetlands as captured from 1:50 000 maps. The objectives of the project included mapping the spatial location of informal settlements in 2006 and 2011, assessing the development status of informal settlements between 2006 and 2011, conduct analysis on environmental status of the 2011 informal settlements and conduct analysis on road infrastructure.

 

The Housing Development Agency said that the NDHS Atlas of 2009, Statistics South Africa enumerated data, and their own enumerated data were used as datasets for their project analysis. In their datasets, there is no image data mentioned to reflect on structural change analysis (see Fig. 2) Statistics South Africa data is mainly for counting households whilst reflecting on the social and economic status. Eighty20 was collecting enumerated data for a different time period than Statistics South Africa.

NDHS Atlas 2009 shows the layers: informal settlements status, village, municipal boundary, railway line, highway, secondary roads and URP notes as it appears in Fig. 3. The results on the Limpopo research report show that land tenure arrangements were mapped without reference to any previously captured images [5]. Taking into consideration the objective of the project, it becomes clear that there is no image dataset used at macro scale to determine uncertainty and reliability of end results reflected.

Conclusions and recommendations

Based on the discussions above, critical issues in line with data collection, data quality and relevancy became apparent but were not addressed as per the Spatial Data Infrastructure Act [10]. At the same time it was pointed out how data was used by state entities under the human settlement sector in South Africa. It is noted in the introduction that the research was initiated with a view to understand how state entities as end-users of spatial data will be in a good position to furnish how end results in the project were accomplished, and the quality of data collected was addressed before the end process. Instead, based on data gathered, the research came to the following findings:

• Data identification was not done appropriately in line with the project’s scope of work, leading to insufficient data collected as per the project’s requirements (i.e. no previously captured images to help in change detection assessment to determine growth).
• Data used for mapping was not adequately referenced nor verified in any way to determine quality and strengthen the project analysis.
• Non-compliance with statutory regulatory requirements for the determination of survey coordinates as per the PLATO Act of 1984.
• Metadata was not sufficiently communicated to the end-user in terms of the Spatial Data Infrastructure Act.
• GIS methodologies to study growth in informal settlements and tenure status were not clear in some instances.

Based on the findings, the following recommendations were put forward for similar future projects:

• The user requirements analysis must be done appropriately to determine spatial datasets required in line with the project’s scope of work.
• Data quality issues like data verification before use or having reference for datasets, temporal consistency, compliance with the Copy Right Act and the Confidentiality Act should be considered when doing analysis.
• The GIS processing methodology must be clear and should be tested to see if it gives correct end results with respect to the user requirements output specifications.
• Skilled GIS personnel must be involved when dealing with GIS projects.
• Adhere to regulatory laws related to data collection and the use of data as augmented to by certain statutory bodies in the country.

References

[1] South Africa: Department of Human Settlement: The National Housing Code 2009, Part A1, 2
[2] South Africa: Department of Human Settlement: South African Yearbook 2012/13, pp. 338
[3] City Press: “Uncontrollable increase of informal settlements”, 19 March 2013, pp. 1
[4] Housing Development Agency: Informal Settlement Status, South Africa, 2012, pp. 4
[5] Housing Development Agency: Informal Settlement Status, Limpopo, 2012, pp. 17
[6] MR Ramotlou: “The use of spatial data to study informal settlement growth in Limpopo urban towns”, Department of Geoinformatics-Z_GIS, University of Salzburg, pp. 85-87, 90
[7] Spatial Data Infrastructure Act 2003, South Africa, S, 10, 12, 17
[8] Q Haywood: “Investigating changes in Land Cover Patterns in the Richards Bay area”, PositionIT, pp. 36
[9] M Belgiu: “Metadata and Catalogue Services”, Department of Geoinformatics- Z_GIS, University of Salzburg: OpenGIS and Distributed GI Infrastructures, pp. 9
[10] South African Council for Professional and Technical Surveyors Act 40 (South Africa) S.27

Contact Rufus Ramotlou, University of Salzburg, Tel 073 262-2742, rufus.ramotlou@gmail.com

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