The creation of the dedicated

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1 Enabling decision making with the SPOT 5 Building Count by Adri de la Rey, Eskom ESI-GIS An overview of the development and perceived benefits of the Eskom SPOT 5 Building Count (SBC) datasets and possible future developments of the datasets with regards to providing physical infrastructure services for the development of rural and less developed areas. The creation of the dedicated remote sensing dataset, SPOT Building Count (SBC), was undertaken to enhance the master planning process for the Integrated National Electrification Programme (INEP) and electricity master planning. The Department of Minerals and Energy (DME) is the custodian of the electrification process and the various distributors are the executioners. The distributors are the metros, licensed municipalities and Eskom through its Distribution Division. The DME allocates funding to the distributors based on various criteria; one of these criterions is the electricity backlog or people that don t have electricity for lighting in a specific local authority area e.g. local municipality and/or metro. The demographic datasets from Statistics South Africa (Stats SA) are used to determine the backlog, but the data is only reliable up to local municipalities, district municipalities and provinces level. However, the lower classifications, place names and sub places don t have enough detailed geographical data to pin-point the specific areas that should be electrified. ESI-GIS, a section in the divisional technology department of the Eskom Corporate Services Division, was tasked with providing the whole of Eskom with up-to-date and applicable geographical information datasets. As part of the service a decision was made to use satellite imagery to determine Table 1: Number of homes electrified. the geographical position of physical structures, and to maintain and enhance these data points. Background One of the challenges that South Africa is facing currently is meeting the electricity demand for its inhabitants. In the State of the Nation Address in February 2004, the president stated that the Integrated National Provinces Households March 2007 All connection by distributors 2006/7 Backlog March 2007 without growth Backlog March 2007 growth 2% metros, 1% municipalities Percentage backlog March 2007 Eastern Cape ,03% Free State ,09% Gauteng ,49% KwaZulu Natal ,05% Mpumalanga ,93% Northern Cape ,13% Limpopo ,71% North West ,23% Western Cape ,29% South Africa ,40% Table 2: Unpublished working figure (DME, DBSA and Eskom). PositionIT - July/August

2 Electrification Plan must be completed by 2012, to enable everyone to have access to electricity by this time. Table 1 indicates the number of electrification connections that Eskom has done so far. The 177 local distributors as the executers, together with the national treasury as the provider of funds, and DME as the custodian, are sharing the challenge with Eskom to ensure that everyone has access to electricity by DME has various criteria to allocate the funding to the distributors. One of these criterions is the accumulation of data regarding households without electricity for lighting (backlog). Eskom uses the following three sources as their reference for this backlog: Statistics South Africa Gaffney s Local Government in South Africa , official year book South Africa Survey 2006 / 2007 South African Institute of Race Relations. In January 2008, Eskom, the Development Bank of South Africa (DBSA) and DME accepted the following backlog figures for South Africa (see Table 2). The backlog figures are only reflected per municipality and don t reflect the lower levels, small areas, or the geographical spread. The challenge was for ESI-GIS to get recent and relatively accurate dwelling data showing the small geographical areas with the greatest electricity backlog for the country so that the whole planning process could be improved. This improved dataset would enable the following: A better understanding by the national treasury of the challenges and monetary requirements of future electrification programmes. Enhance the capabilities of the distributors to do master plans that include the electrification growth at an acceptable level. The performing of proper macro and micro planning with the detailed designs of specific electrification areas. The creation of change maps to monitor the movement of people on the ground and identify the latest growth points and other areas. The physical geographical area is basically categorised as: Proclaimed: townships areas that are registered in the deeds office as part of the national land register. Tribal authority land: the land is not part of the national land register. Farm and agriculture land: major regions identified by the Surveyor General and on those areas where people are establishing informal housing. Remote sensing South Africa doesn t have a geographical conventional map depicting these attributes with regards to demographic data. Eskom has accepted remote sensing as the technology that could help to improve this kind of data. Remote sensing is seen as a tool box of technologies that could be applied for every specific need. The three major technologies are briefly described below: Satellite imagery with various resolutions, age and technologies. The resolution can range from a metre to 10 to 20 m and up to kilometres. It could be black and white and/or colour with or without infrared. It is relatively cheap and the imagery tiles can cover large areas 60 x 60 km SPOT 5 and 180 x 180 km Landsat. 1: and larger scale aerial photography are referred to as large Fig. 1: Eskom field service area in South Africa. scale photography while small scale aerial photography encompasses aerial photography of less than 1: Large scale aerial photography is normally undertaken per project and within two years of the actual construction. The Chief Directorate of Surveys and Mapping is producing 10% to 15% of small scale aerial photography per annum, however this is not sufficient to cover the country and to enable master or macro planning. Lidar (light detection and ranging) is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant target. It is a very expensive and accurate application which has its place in delivering applicable products. Eskom s vision in the early 2000s with regard to the electrification challenge was to create a maintained change detection master map with the right attributes for the country to enable the best possible electrification and electricity master planning. This map should have the applicable man-made and natural attributes and it should be enhanced and maintained through the adding of meaningful small, large scale and or lidar images. Remote sensing can deliver the right imagery from this mixture of the applicable technologies to satisfy the different needs for geographical data. 34 PositionIT - July/August 2008

3 Field Name FID Shape SOURCE SOURCE_IMG CLASS CLASS_NAME PROV MUNIC ESKOM_FSA TRIBAL_AUT PROCLAIMED* INT_ERVEN INT_FARM INT_FARMPN INT_AGRHLD INT_PARK INT_TA SUB_HV_DES SUB_MV_DES TRNFM_NAME Description Feature ID, Automatically created in ArcGIS Point/polygon Name of the company/contractor Imagery used The classification Class name Province Municipality The FSA (field services area) that it falls inside Tribal authority Does point or polygon intersect with any cadastral boundary or tribal land? Does point or polygon intersect with urban cadastral boundary? Does point or polygon intersect with farm cadastral boundary? Does point or polygon intersect with farm portion cadastral boundary? Does point polygon intersect with agricultural holding cadastral boundary? Does point/polygon intersect with park cadastral boundary Does point/polygon intersect with tribal authority cadastral boundary Name of high voltage substation, 450 m buffer area, that it falls inside Name of medium voltage substation, 450 m buffer area, that it falls inside Name of the transformer, 450 m buffer area, that it falls inside informal housing structures were too dense to be mapped individually. To maintain mapping consistency the following general rules were followed: One point per possible rural housing structure One point per main farm house worker s house One point per grouping of housing structures as found in KwaZulu Natal and Eastern Cape One point per formal and informal cadastre polygon One point per school building in mines and quarries building in resorts building in industrial and commercial areas One point per one or group of silos One point per one or group of reservoirs A polygon is mapped around informal dense areas Where there is any uncertainty the 50/50 mapping rule will be followed and the structure will be mapped. Table 3: Common fields in the attribute table. (*Points/polygons were declared proclaimed if they intersect or were completely contained in urban, farm, farm portion, agricultural holding, park or tribal land layers.) Core geographical data used in the process Imagery The Council for Scientific and Industrial Research (CSIR) created this opportunity to extend remote sensing for the country by negotiating a national contract (via a consortium of interested parties) to purchase the SPOT 5 imagery for the geographical industry in the three tiers of government. Eskom entered into this partnership and also initiated the SPOT 5 Building Count on this core geographical satellite imagery. The partners involved in creating this dataset are: GeoTerraImage CSIR - Satellite Applications Centre Eskom Divisional Technology ESI-GIS SPOT 5 Building Count (SBC) The overall objective of the SBC product was to map the location of dwelling units and any building structures or density polygons in dense areas for each field service area (FSA) (see Fig.1). A field service area is an Eskom Distribution area of interest in the engineering field used in the management of the electricity distribution industry. Once the point and density polygon data has been captured, it will be analysed against proclaimed land, which is essentially land that is electrifiable and includes areas with existing SG cadastral coverage, as well as tribal lands and non-proclaimed land, which is essentially areas outside of tribal lands and those without SG cadastral minor coverage. The geo-referenced dwelling frame also has benefits for other organs of state, such as providing addresses for postal delivery by the South African Post Office, developing an authoritative address register that can be utilised by departments such as Home Affairs, meeting the requirements for FICA, and assisting with the improvement of service delivery at local municipality level. Methodology The structure or dwelling count was done using the 2005/6 SPOT 2,5 m natural colour satellite imagery at 1:5000 mapping scale. All structures/dwelling units were manually captured by placing a point (digitising) on each one of them and a polygon was created where the 2005/6 SPOT 2,5 m natural colour imagery. Ancillary data Schools, 1: map sheets; cadastral data; roads; and existing dwelling points. Existing dwelling points Where possible, the existing dwelling point layer was incorporated into the methodology. This also included the existing growth indicator and Stats SA dwelling frame points. Stats SA dwelling frame work points were captured from Quickbird images and aerial photographs. Growth indicator points were captured from the 2005 Quickbird images and the 2007 SPOT5 2,5 m natural colour imagery. These points were overlaid onto the 2005/6 SPOT 2,5 m image and where new dwellings exist post their capture in these projects, they are captured as such. The attribute field from all original source information was retained in the attribute of the newly PositionIT - July/August

4 FSA Dwellings Schools Complexes/ hostels Resort Mines/ quarries Total no. of structures Informal dense polygons Bellville Benoni Bethlehem Bloemfontein East London Empangeni George Groblersdal Hazyview Kimberly Klerksdorp Margate Mmabatho Mthata Nelspruit Newcastle Nigel Pietermaritzburg Pietersburg Port Elizabeth Pretoria Queenstown Randfontein Rustenburg Sandton Secunda Soweto Thohoyandou Tzaneen Vereeniging Vryburg Warmbad Welkom West Coast Witbank Worcester Total Table 4: Statistical breakdown per FSA created data layer. Classes for the SBC dataset School building or group of buildings used as an institution for study, teaching, and learning. Only clearly identifiable primary/secondary schools are classified as schools. This class doesn t include colleges and universities. Complex/hostel this class includes a group of houses with the same structure occupying a specific piece of land. Mine/quarry mine is a site where ores and minerals are extracted, and a quarry is defined as a site where stone, rock and construction materials are extracted. Resort a place used for relaxation or recreation, attracting visitors for holidays or vacations. Dense informal these dense informal settlements are typically unauthorised areas and are invariably located upon land that has not been proclaimed for residential use. Dwelling building or portion thereof used exclusively for residential purposes. This class includes any other building structures that do not belong to any of the above mentioned classes. Results Deliverables The product is packaged per field service 36 PositionIT - July/August 2008

5 Sample Number of points Area per point Total area sample Total urban SA % sampled Urban sample 323 1,5 484, , Rural sample , , Peri-urban sample , , Total sample , , , Table 5: Area stratification Sample % Error of commission % Error of omission Urban sample 0,06 0,16 Rural sample 0,47 1,95 Peri-urban sample 0,08 0,2 Total error 0,61 2,31 Table 6: Sampled errors area (FSA). A field service area is an Eskom Distribution area of interest in the engineering field used in the management of the electricity distribution industry. Each FSA will have a point layer and a polygon layer for informal settlements if they exist. All layers are projected to geographic projection, WGS 84 spheroid and datum. Due to the large number of points for some provinces, it is impossible at the moment to package the product per province. Deliverable column descriptions All the points or polygons mapped are linked to an attribute table which contains the following common fields (see Table 3). Statistics analysis The total number of dwelling units/ structures and informal dense polygons mapped totalled and respectively (see Table 4). About 98,97% of dwelling structures mapped are proclaimed i.e. the points intersect with either the cadastral or tribal land boundaries provided by ESKOM. The unverified Stats SA number of households per dwelling is 1,1 with an average number of 3,9 people per dwelling. If we multiply the total number of Eskom dwelling points by 1,1 and 3,9 respectively to determine a dwelling point derived population for 2006, a figure of is derived. This figure compares extremely well with the Stats SA census estimate of and the Central Intelligence Agency fact book estimate of Quality assurance methodology An independent remote sensing specialist was appointed to run a quality assurance analysis on the dwelling inventory product. This activity was conducted to provide evidence needed to establish confidence among all concerned, that quality-related activities were performed effectively. The area mapped was stratified into urban, peri-urban and rural. These areas were defined according to Stats SA definitions and conformed to these boundaries. A random selection method was utilised to identify representative samples to be independently evaluated and the results of this are shown in Table 5. A grid of 1,5 km 2 was created around each of the random points. The number of missed dwellings/structures inside each grid was recorded as an omission error and the number of points mapped where there are no dwellings was recorded as a commission error. Results The total error of commission and omission is 0,61% and 2,31% respectively. This analysis was done per FSA. Conclusion The location of dwelling units/building structures or dense informal areas was successfully mapped using SPOT 2,5 m natural colour satellite imagery. This is the first truly geographical enabled dataset in South Africa and can be used as a sample frame for household surveys and for conducting population and housing censuses in South Africa, similar to the use of business frames to support economic surveys and censuses. The data was captured at its lowest unit of measure and the user can summarise it to any arbitrary areas such as wards, sub-places or areas identified at identified needs basis. This will allow for the monitoring of people movements and trends within any area as needed. Possible future studies Some follow-on exercises could include quantifying the existing electrification backlog per area of interest. Areas suitable for renewable energy sources can be identified. Where the informal housing structures are too dense to be mapped individually, the density polygons can be selected and prioritised for surveying by some other more applicable technology. Disaster management departments will for the first time be able to determine the location of structures with the applicable number of people that may be affected by a devastating fire or flood. Currently it is only possible to assume the number of people within a high-risk area based on generalised statistics. With the SBC and other core datasets such as roads and contour-plans, a precise picture can be created for every situation. Clearly with further development and applications, remote sensing satellite imagery can contribute to better electrification planning. Author Adri de la Rey is a professional land surveyor and professional geographical science practitioner in Eskom. He has worked in the Distribution Division where he was involved in undertaking surveys, obtaining authentic legal rights and undertaking environmental impact assessments and management plans. He has spent the last ten years working in various capacities at Eskom dealing with geographical data. He is currently the GIS manager for the Eskom Corporate Services Division. References [1] CSIR: Eskom Dwelling Inventory Report, 2008 [2] GTI: ESKOM ESI-GIS SPOT Building Count Report, 2008 Contact Adri de la Rey, Eskom, Tel , dlreya@eskom.co.za 38 PositionIT - July/August 2008