Geographic Information Systems explained

Colin Mumfordin Consultancy

Geographic information systems and electromagnetic induction scanning as a

maintenance tool for sports surfaces

By Colin Mumford


Managers of sporting facilities (e.g. golf courses) need to be able to produce satisfactory playing surfaces that fulfil the performance characteristics required for the sport played. To achieve this requires the manager to have information on many factors pertaining to the site including topography, orientation, soil physical properties such as soil texture, vegetation variability, and drainage and irrigation systems; all of which are likely to vary from location to location. These factors influence the way in which the manager maintains the facility. Each factor will be location specific (spatial) and can be placed on a map of the facility.

Larger facilities, especially multi-surface facilities, will have a large amount of information that would be difficult to present in an easy to understand format. However, technologies have been developed to combine data from maps with computer processes to generate maps to aid land management, and have evolved into Geographic Information Systems (GIS). This report gives an explanation of GIS and how its use can be incorporated into the management of a sports surface, with particular emphasis on the integration of data from electromagnetic induction (EMI) scanning sensors.

What Is GIS?

GIS is the integration of three constituent parts, which Davis (1996) describes as:

Geographic: Of the real world, the spatial realities, the geography

Information: Data and information; their meaning and use

Systems: The computer technology and support infrastructure

A true definition of GIS is difficult to establish. Some authors refer to GIS as a set of tools (Burrough, 1986; Clarke, 1995), whilst others (Duecker, 1970; Star and Estes, 1990) refer to GIS as an information system. However ESRI (2004) define GIS as "a method to visualize, manipulate, analyse, and display spatial data" creating smart maps that link a database to a map.

How does GIS work?

Information on a site is collated and arranged as tables, numbers, lists, maps, pictures or indexes. A database of this information is then created and stored as a file in a computer. Attributes (e.g. labels, categories, numbers) are stored as column headers within the database, and the rows are identified as records. A value, either numerical or text, is stored within an attribute for one record (Clarke, 1999). A geographic reference to a map - for example latitude and longitude - must be included in the data to allow GIS to cross-reference map data with the attribute data. By cross-referencing data, searches can be based on either the attribute data or the map data.

The data can be generated as layers of information over a corresponding map to compile a graphic representation. Figure one illustrates five different layers of information (rivers, roads, lakes, capitals and states) for the United States of America (USA). Figure two (overleaf) shows the layers overlaid onto a map of the USA.

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Rivers Roads Lakes

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Capitals States

Figure 1: Five layers of a GIS map representing the rivers, roads, lakes, capitals and states of the United States of America (ESRI, 2004)


Figure 2: Map of United States of America with five layers of information on rivers, roads, lakes, capitals and states overlaid on top (ESRI, 2004)

Dimension, volume and continuity are the characteristics of the geographic information, and complex features can be represented by building-up simple geographic features. The collective properties of which are size, shape, scale, orientation, distribution, pattern, neighbourhood and continuity (Clarke, 1999). The majority of analysis and characterization of GIS involves investigating geographic feature properties, and determining the relationships between them.

Soil Mapping for Sports Surfaces

Traditional soil analysis methods usually require soil samples to be removed from the playing surface, which can affect the performance characteristics of the surface (e.g. ball roll on a golf putting green). The samples are then sent to specialist laboratories for analysis. This can be expensive and time consuming, and may not give an accurate account of the soil characteristics within the soil profile.

However, developments in remote sensing for precision farming has led to more efficient, economic and effective management practices, and has driven advancements in soil mapping techniques, including non-intrusive rapid scanning sensors that can measure soil apparent electrical conductivity (ECa) by electromagnetic induction (EMI). Research by Frogbrook et al. (2003) and Gale (2003) showed that EMI soil scanning can quickly identify general soil characteristics, and highlight areas that require further study using traditional soil analysis techniques. Gale (2003) also showed the potential of EMI scanning on sports surfaces.

Conducting an EMI scan

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The above images (From L-R) show the EMI scanner, the aerial photo with the site soil variability map, and the soil analysis data.

A site survey to plot and reference topographic levels, orientation and known landmarks of the area is carried out using Global Positioning System (GPS) surveying technology simultaneously to the EMI scan. The EMI scanner can record and position soil measurements at speeds between 10-15 km/h, when towed behind an appropriate vehicle, if ground weather conditions are suitable.

To pin point the exact locations of EMI readings in relation to longitude and latitude reference points located by the GPS satellites, differential GPS (DGPS) and radio transmitters and receivers are positioned at a ground base station and on the vehicle towing the EMI scanner. Data is logged at five points per second into a data logger during the scanning process. The data is then transferred to a computer to configure it into GIS files. Included in the data are a topographic plan of the area scanned - taken from the GPS component of the scan - and vertical and horizontal dipole results.

GIS maps produced from EMI data

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Figure 3: Clustered vertical ECa (mS/m) soil map

(TurfTrax Ground Management Systems Limited, Gale 2003)

Figure 4: Vertical 20 classification contoured ECa (mS/m) soil map

(TurfTrax Ground Management Systems Limited, Gale 2003)

Gale (2003) described two methods for transforming ECa data into images of the data. The first method - to explore the data set and see if the resultant ECa map showed any similar ECa variations - involved a clustering technique, using GIS Arcmap, to transform the ECa data into six classifications (Figure 3). The second method involved using 20 classifications for the original ECa data, which are then interpolated to produce contoured images (Figure 4).

Using the GIS map as a surface maintenance tool

The EMI soil maps in Figure Three and Figure Four show two layers of a sports surface GIS map (a football pitch in this case). Their importance to the manager of the facility extends from the ability of the soil to conduct an electrical current. EMI reveals variability in soil conductance properties that predominantly relate to differences in salinity of the soil solution (for most inland UK soils this is negligible) and differences in volumetric moisture content. Clearly moisture content is influenced by the amount a water an area receives so variability as shown by EMI scanning can reveal areas of a sports field that are significantly wetter than other areas (perhaps as a result of seepage from a cut slope, a collapsed drain or a leaking irrigation pipe. Differences in soil texture can also create effective differences in volumetric moisture content, therefore in areas where the sports field has received the same amounts of rainfall and there are no other sources of water to affect one area of the ground in contrast to another, EMI scanning can provide an approximate soil texture map. Finally, because changes in bulk density affect volumetric moisture content, EMI scanning can differentiate areas that might be compacted within a sports field, particularly if the sports field has been constructed from the soil of the same texture.

Should there be any buried infrastructure within the sports field that has a significantly different conductance to the surrounding soil, then EMI scanning can be very effective in locating such features, these might include metal water pipes, electricity cables or dry permeable fill around a drain in an otherwise wet soil. In addition, if a sports ground has been developed on a land-filled site or on made ground, differences in conductivity between materials used as fill will be clearly seen on an EMI scan. This can be useful in identifying problematic subsoil below sports grounds that might be subject to settlement or might pose a pollution risk, depending on the nature of any fill material in them.

It is important to recognise that EMI scanning will only create soil variability maps, on its own it cannot identify the cause of any recorded variability. This requires subsequent, targeted soil sampling. The great benefit, however, is the information a sports turf manager gains in knowing where to carry out the soil sampling to determine the cause of variability in the most time and cost efficient manner. Frogbrook et al. (2003) and Gale (2003) conclude that an EMI ECa map is not a substitute for soil sampling, but is a good method to identify areas for in-depth analysis. However an EMI ECa map does form a useful layer in a GIS database, enabling the manager quick access to site specific information that can be cross-referenced and, where necessary, analysed with other information (layers) within the GIS database.


Geographic Information Systems (GIS) have been developed over many years, but is a relatively new field in the sports surface sector. The adoption of the technology is beginning to become widely accepted, especially with the advent of Electromagnetic Induction (EMI) soil mapping. Such acceptance may see the introduction of other developing technologies that are applicable to GIS, such as yield mapping which is already present in the agriculture industry. Technology of this type, coupled with GIS, will potentially enable more accurate fertilizer and spray applications to be made in a sports surface environment, which has environmental and economic benefits.

For further information please contact Colin Hood at TurfTrax on 01722 434000 or e-mail


The author would like to thank TurfTrax Ground Management Systems Limited for the use of their EMI scan images.

TurfTrax Ground Management Systems Limited, Unit 1, Highfield Parc, Highfield Road, Oakley, Bedfordshire. MK43 7TA


Burrough, P.A. (1986) Principles of Geographic Information Systems for land Resources Assessment. Oxford: Clarendon Press.

Clarke, K.C. (1995) Analytical and Computer Cartography (2nd edition). New Jersey: Prentice Hall.

Clarke, K.C. (1999) Getting Started with Geographic Information Systems (2nd edition). New Jersey: Prentice Hall.

Davis, B. (1996) GIS: A Visual Approach. Santa Fe: OnWord Press.

Duecker, K.J. (1979) 'Land Resource Information Systems: A Review of Fifteen Years of Experience', Geo-Processing, 1 (2), 105-128.

ESRI (2004) Geographic Information Systems "GIS" [www document]. (accessed 26th July 2004).

Frogbrook, Z.L., Oliver, M.A. and Derricourt, K.E. (2003) 'Exploring the Spatial Relations between Soil Properties and Electro-Magnetic Induction (EMI) and the Implications for Management', in J. Stafford and A. Werner (eds.) Precision Agriculture: Proceedings of the 4th European Conference on Precision Agriculture, Berlin, 15-18 June 2003. The Netherlands: Wageningen Academic, 217-222..

Gale, L.W. (2003) A Preliminary Investigation into the Relationship between Electromagnetic Induction Data and Soil Chemical and Physical Properties of a Low Maintenance Natural Turf Football Pitch. Unpublished MSc thesis. Silsoe: Cranfield University at Silsoe.

Star, J. and Estes, J.E. (1990) Geographic Information Systems: An Introduction. New Jersey: Prentice Hall.

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