Geographic Information System (GIS): Meaning, Problems and Prospects

After reading this article you will learn about:- 1. Meaning of Geographic Information System (GIS) 2. Strategies for Implementation of GIS 3. Problems 4. Cartographic Modelling 5. Problems for Implementation 6. Prospects.

Meaning of Geographic Information System (GIS):

Geographic information system is a computer system that can hold and use data describing places on the earth’s surface. In other words, GIS is a system of capturing, storing, checking, integrating, manipulating, analysing and displaying data which are spatially referenced to the earth.

However, GIS has three components namely:

(i) A computer system,

(ii) Uses spatially referenced or geographical data and

(iii) Management and data analysis.

In short, GIS can be used to add value to spatial data. By allowing data to be organised and viewed efficiently, by integrating them with other data, by analysis and by the creation of the new data that can be operated on in turn, GIS creates useful information to help decision making.

(i) Computer Systems and Software:

GIS runs on the whole spectrum of computer systems ranging from portable personal computers (PCs) to multi-user super computers, and are programmed in a wide variety of software languages.

There are a number of elements that are essential for effective operation of GIS which are as follows:

(a) Process or with adequate power to run the software.

(b) Sufficient memory for data storage.

(c) A good quality with high resolution colour graphics screen.

(d) Input and output devices for data e.g. scanners, keyboard, printer etc.

(ii) Spatial Data:

Spatial data are characterised by information about position, connections with other features and details of non-spatial characteristics. The spatial referencing of spatial data is important and should be considered at the outset of any GIS project. Spatial data representing layers or objects must be simplified before they can be stored in the computer.

(iii) Management and Analysis of Data:

A GIS should be able to perform include data input, storage, management, transformation, analysis and output. Data input is the process of converting data from its existing form to one that can be used by the GIS. GIS need to handle two types of data—graphical data and non-spatial attribute data. The graphical data describe the spatial characteristics of the real world feature be modelled.

Non-spatial attribute data describe what the features represent. Transformation and the procedure for analysis can also be classified based on the amount of data analysed. The technology of GIS is now well established and so it has been in use since the 1960s.

The growth in application areas and products through the later years of the 20th century has helped GIS to become an accepted tool for the management and analysis of spatial data.

Strategies for Implementation of GIS:

The implementation methods of GIS fall into four main categories as follows:

(i) Direct conversion from the old system to the new,

(ii) Parallel conversion, where both old and new systems run alongside one another for a short time period,

(iii) Phased conversion, where some of the functions of the old system are implemented first, then others follow, and

(iv) Trial and dissemination i.e. conversion to a new system.

The method of implementation is one of the factors that can affect the success or failure of a GIS programme.

Problems of GIS:

Before developing a GIS application, the problem of GIS must be identified.

However, there are two techniques to be used for the identification of the GIS problem:

(i) Creating a rich picture, and

(ii) Developing a root definition.

Both these techniques are obtained from the soft systems approach to system design.

(i) Rich Picture:

It is a schematic view of the problem a project will address. It presents the main components of the problem, as well as any interactions that exist. The rich pictures are particularly useful when considering the design of computer systems within organisations.

The development of a rich picture should not be rushed, particularly if it is trying to reflect an unstructured problem. A poorly defined rich picture may translate into a poor GIS application. An additional check to ensure that the problem is well-understood is to develop a root definition.

(ii) Root Definition:

The term root definition also comes from the soft systems approach. The root definition is a view of a problem from a specific perspective. Different users have different views of a problem. Establishing a common root definition for a problem will help others to evaluate and understand why a GIS has been constructed in a particular way.

If a single root definition can be agreed upon then there is a greater chance the GIS will meet the requirements of all concerned. Once rich picture and root definition exist the main aims and objectives for a project can be identified and a GIS data model can be created.

Cartographic Modelling in GIS:

Cartographic modelling is derived from a collection of old ideas that have been organised, augmented and expressed in terms amenable to digital processing. According to Tomlin, it is termed as “Map Algebra” and Berry as “Mapematics” that established cartographic modelling as an accepted methodology for the processing of spatial information.

It is a generic way of expressing and organising the methods by which spatial variables, and spatial operations, are selected and used to develop a GIS data model. Cartographic modelling is a geographic data processing methodology that views maps as variables in algebraic equations.

In algebra, real values are represented by symbols such as y and z. In map algebra these symbols may represent numeric attributes of map elements e.g. pH values related to soil properties.

There are four stages in the development of a cartographic model which are as follows:

(i) Identify the map layers or spatial data sets required.

(ii) Use natural language to explain the process of moving from the data available to a solution.

(iii) Draw a flow chart to represent graphically the process in step (ii), representing a series of equations providing queries of the spatial data.

Example: a—b = c, where a = land use map; b = urban land use map; c = country side.

(iv) Annotate this flow chart with the commands necessary to perform these operations within the GIS used.

Problems for Implementation of GIS:

There are usually three problems which are most common:

(i) Data in the wrong format for the GIS software,

(ii) A lack of GIS knowledge imposing technical and conceptual constraints on a project and

(iii) Users of the GIS frequently changing their mind about what they want the GIS to do.

The dynamic nature of the GIS design process is such that the information needs of users are often in a constant state of flux. By the time a GIS data model is implemented the needs of the users and the scope of the problem may have moved away from the original defined by the rich picture.

Prospects of GIS:

Making predictions for a field changing and developing as rapidly as GIS is very difficult. In the early 1990s GIS were general purpose software packages. Widespread use of manual digitizing techniques made the data conversion process slow. Large volumes of data were generated, but storage devices were still relatively limited.

The GIS of the early 1990s was not windows-based-most packages were command line driven. A high level of skill was required and generally GIS expertise was at a premium. Training and awareness of GIS are important. Rhind (1992) offered two contrasting views of the future of the GIS—it might be fragmented and disappeared.

More positively and accurately, convergence in GIS that would result in:

(i) Better tools for the handling and exchange of information,

(ii) A better served GIS community (with conference, text books, magazines etc.),

(iii) New players in the GIS industry,

(iv) The development of standards for data issues, and

(v) The development of a core set of ideas to inform teaching and training in GIS.

After review of the GIS about its success and limitations the following points may be considered for the GIS,

(i) Two-dimensional with limited abilities to handle the third dimension,

(ii) Static, with limited abilities to cope with temporal data,

(iii) Good at capturing the physical positions of objects, their attributes and their spatial relationships, but with very limited capabilities for representing other forms of interaction between objects,

(iv) Offerings a diverse and confusing set of data models and

(v) Still dominated by the idea of a map, or the view of a spatial database as a collection of digital maps.

However, GIS can be effectively used to study soil survey, soil classification, land use planning, crop forecasting, weather forecasting, water resources study, integrated nutrient and pest management etc. which are associated with the sustained agricultural production.