Senior Phhotogrammetry Technologist
Kampsax India Pvt. Ltd., Gurgaon, India
In recent years, the use of computer-based techniques for spatial data analysis has grown into an important scientific area, combining techniques from geographical information systems and emerging areas such as neurocomputing, heuristic search and cellular automata. In order to distinguish this new interdisciplinary area from the simple extension of statistical techniques for spatial data, some authors (Openshaw and Abrahart, 1996) have coined the term “geocomputation” to describe the use of computer-intensive methods for knowledge discovery in physical and human geography, especially those that employ non-conventional data clustering and analysis techniques. Lately, the term has been applied in a broader sense, to include spatial data analysis, dynamic modelling, visualisation and space-time dynamics (Longley, 1998). The first international conference on ‘GeoComputation’, hosted by the School of Geography at the University of Leeds in 1996, heralded the launch of a new research agenda in geographical analysis and modelling.
What is GeoComputation?
Simply defined, geocomputation “is the process of applying computing technology to geographical problems”. Rees and Turton (1998) define ‘geocomputation as the process of applying computing technology to geographical problems. Couclelis (1998) notes that ‘geocomputation just means the universe of computational techniques applicable to spatial problem’.
However, GeoComputation is concerned with new computational technique, algorithms and paradigms that are dependent upon and can take advantage of high performance computing. it involves combination of four leading edge technologies:
- GIS, which creates the data;
- Artificial intelligence (AI) and computational intelligence (CI), which provide smart tools;
- High performance computing, which provides the power;
- Science, which provides the philosophy.
GeoComputation is linked by name to what is broadly termed as computational science with which it is clearly related and shares many of its aims. In broad terms, computational science involves using computer to study scientific problems and it seeks to complement the use of theory and experimentation in scientific investigation.
It seeks to gain understanding principally through the use and analysis of mathematical models and computer simulation of processes performed using the availability of high performance computing. It is largely or wholly the computational approach to scientific investigation in which computer power is used to supplement and perhaps in some areas supplant more traditional scientific tools.
GeoComputation V/s GIS
GeoComputation is not GIS and embraces a different perspective and set of tools. There is a relationship between GeoComputation and GIS. GeoComputation has other relationships also which may be just as important e.g., with computer science or numerical methods or statistics. From a geographical perspective, GeoComputation is what you do after GIS in that it seeks to make use of the data richness created by GIS and other developments in information technology. If GIS is mainly about digital map information then GeoComputation is about using it in many different application areas within which the focus is not any longer particularly on the original GIS component.
Nor is GeoComputation about evolving new or better data structure for use within GIS or about any of the GIS research agenda. GIS is merely a database infrastructure, which is nice to have, but which is lacking in science or theory other than the measurement science the one on which it is based on. GeoComputation is not just an add on to GIS in fact it is not really a part of it at all.
What makes GeoComputation Special?
GeoComputation can be regarded as the application of the computational science paradigm to study a wide range of problems in geographical and earth science context. GeoComputation is not just the application of computer in geography or earth science. It is meant to imply the adaptation of a large scale computationally intensive scientific paradigm as a tool for doing all forms of geographical research. There are three aspects, which make GeoComputation special:
- There is an emphasis on the ‘geo’ subject. This is partly disciplinary focus on the area of interest but it is more than geography. GeoComputation is concerned with geographical or spatial information of all types but until recently the distinctiveness of geographical data had been lost.
- The computational sub phrase in GeoComputation is also special. It is the intensity of the computation that is especially distinctive. As computer becomes faster the very concept of a solution changes. GeoComputation is about finding new or better solutions to existing problems via a computational route. It also involves thinking about tackling new classes of problems that previously were unthinkable and insoluble.
- Computation implies a very particular paradigm based on numerical approximation rather than analytical precision. It can be based on data driven high performance computer powered inductive tools rather than data force, analytically based, deductive methods. It involves trying to compute solution to problem that could not previously be solved at all. It is based on substituting vast amount of computation as a substitute for missing knowledge or theory to augment knowledge. It could be data driven in a data mining sense, or it could be entirely data free with large scale computer experimentation being used as a purely theoretical tool for understanding how complex systems work via modelling and simulation of their dynamics and behavior.
Future of GeoComputation
In essence GeoComputation is concerned with the application of a computational science paradigm to study all manner of geo-phenomena. GeoComputation is all about the use of relatively massive computation to tackle grand challenge problems of immense complexity.
The driving factors in GeoComputation are three folds:
- Developments in high performance computing are simulating the adaptation of a computational paradigm to problem solving analysis and modelling.
- The need to create new ways of handling and using the increasingly large amount of information about the world, much of which is spatially addressed.
- The increased availability of artificial intelligence and computational intelligence methods that exist and are readily applicable to many areas of geography and earth sciences.
The opportunity for researchers and academicians in GeoComputation are essentially four folds:
- To speed up existing computer bound activities so that more extensive experiments can be performed;
- To improve the quality of results by using computational intensive methods to reduce the number of assumptions and remove shortcuts and simplifications formed by computational restraints that are no longer relevant;
- To permit larger databases to be analyzed and/or to obtain better results by being able to process finer resolution data;
- Develop new approaches and new methods based on computational technologies developed by other disciplines, particularly Artificial Intelligence and Computational Intelligence.
Problems for GeoComputation
A few problems need to be resolved before this new technology is effectively harnessed. Many of these are methodological; sophisticated tools require sophisticated set-up and operation. Although there are many reported examples of the use of these tools in the earth sciences literature, their use often necessitates considerable investment in terms of customization, set-up, experimentation and testing before useful results are obtained. Therefore, GeoComputation must overcome some significant challenges if the techniques are to become established in the toolbox of the geographer.
These challenges include:
- the inclusion of geographical ‘domain knowledge’ within the tools to improve performance and reliability
- the design of suitable geographic operators for data mining and knowledge discovery
- the development of robust clustering algorithms able to operate across a range of spatio-temporal scales
- obtaining computability on geographical analysis problems too complex for current hardware and software
- visualization and virtual reality paradigms that support a visual approach to exploring, understanding and communicating geographical phenomena.
In short, there is a gap in knowledge between the abstract functioning of these tools (which is usually well understood in the computer science community) and their successful deployment to the complex applications and datasets that are commonplace in geography. It is precisely this gap in knowledge that GeoComputation aims to address.
GeoComputation represents a conscious attempt to move the research agenda back to geographical analysis and modelling, with or without GIS in tow. Its concern is to enrich geography with a toolbox of methods to model and analyze a range of highly complex, often non-deterministic problems. It is about neither compromising the geography, nor enforcing the use of unhelpful or simplistic representations. It is a conscious effort to explore the middle ground from the doubly informed perspective of geography and computer science. It is a true enabling technology for the quantitative geographer and a rich source of computational and representational challenges for the computer scientist. To summarize GeoComputation is
- not another name for GIS
- not quantitative geography
- not extreme intuitivism
- not devoid of theory
- not lacking of philosophy
- not a grab bag of tools sets
The challenge for GeoComputation lies in developing the ideas, the methods, the models and the paradigms able to use the increasing computer speeds to do ‘useful’, ‘worth while’, ‘innovative’ and ‘new’ science in a variety of geo-context.
- Couclelis, H. 1998. Geocomputation in context, In: P.A. Longley, et al. (eds) Geocomputation: A Primer, pp. 17-30, Chichester, Wiley.
- Longley, P.A. 1998. Foundations. In: P.A. Longley et al., (eds) Geocomputation: A Primer, pp. 1-16, Chichester, Wiley.
- Rees, P. and Turton, I. 1998. Geocomputation: solving geographical problems with computing power, Environment and Planning A, 30: 1835-1838.
- Openshaw, S. and Abrahart, R.J. 1996. Geocomputation, In: Proceedings 1st International Conference on Geocomputation, Leeds: University of Leeds, 2, pp. 665-666,