Centre for GIS and Remote Sensing
Key staff: Mr Fakar Khalid, Dr Mike McGibbon and Dr Tim Acott
The geographical information system (GIS) and remote sensing system analytically portray spatial data to reveal relationships, patterns and trends that cannot be visualised any other way. Any data with a spatial element (e.g. census data, demographics, roads, water resources, soil type, crop productivity, air quality, elevation, etc.) can be input and manipulated with GIS. These data, with the help of GIS analyses, are used to solve a range of problems as diverse as environmental modelling, urban planning, precision agriculture, transport planning, mineral and hydrocarbon exploration, landscape evaluation, crime mapping and hazard management – the variations are endless.
Remote sensing provides up-to-date aerial and satellite images of Earth as well as extraterrestrial objects. These images can be enhanced and analysed by image-processing techniques to reveal natural patterns of variation and monitor changes in areas. Applications of remote sensing range from monitoring meteorological systems to the detection of hidden archaeological remains. With the rapid advances in technology these images are improving in quality day by day. Aircraft-borne and satellitemounted sensors can pick up details as small as a few centimetres in the target area.
Recent projects
Development of an algorithm to automatically detect cyclones from meteorological satellite imagery
Cyclones are one of the most deadly natural disasters known to mankind. Software was developed, as part of a PhD, which uses artificial intelligence (fuzzy logic) to automatically detect cyclones from real-time satellite imagery. Use of fuzzy logic gives a more accurate understanding of the development stages of a cyclone.
Use of GIS in hazard and risk management of hurricane-struck areas
GIS was used to highlight and identify hazardous areas in the case of a hurricane making land contact in the island of Barbados. The hazard maps generated were then assessed to calculate the risk to the population and the environment.
Risk assessment of flood plains in Medway Towns using high-resolution satellite and aerial data
Highly precise elevation data gathered using LiDAR (light detection and ranging) and RADAR was used to assess the risk of flooding in Medway towns in the case of a predicted sea-level rise.
Other projects
- Spatiotemporal crime analysis of motor-vehicle theft in the Borough of Hillingdon using GIS.
- Use of GIS in crime mapping and analysis in Southend-on-Sea.
- Environmental impact assessment of wind turbines off the southern coast of England.
- Environmental impact assessment of oil spillage in the Niger delta.
- Assessment of positional accuracy improvement (PAI) algorithms.
- Use of GIS in the determination of new roost-site locations for the brown log-eared bat, Plecotus auritus, in Kent.
- Implementation and evaluation of a government-proposed road-pricing scheme using GIS.
- Investigation into the identification of precursors of traffic accidents on motorways in the south-east of England using GIS.
- Use of historic maps and aerial photographs to assess land-use change in the Thames Gateway.
- Feasibility study of solar-panel installation in a densely populated city using LiDAR.
- Evaluation of the effects of salinisation on vegetation change by using temporal Landsat imagery of the Sukkur and Faisalabad regions of the Indus basin in Pakistan.
Publications
Babb, R. and Khalid, F. Risk assessment and hazard management of hurricane Ivan using GIS. Journal of Maps. (In press.)
Khalid, F., Power, C. and Shehab, E. (2003). Designing a fuzzy logic pattern recognition system for tropical cyclones. Proc. Remote Sensing and Photogrammetric Society Conference.
Khalid, F., Power, C. and Shehab, E. (2005). Evaluation of a fuzzy pattern recognition algorithm for tropical cyclones monitoring and assessment. Proc. Annual Conference of the Remote Sensing and Photogrammetric Society with the NERC Earth Observation Conference.
Khalid, F., Power, C. and Shehab, E. An automated fuzzy pattern recognition system to detect cyclones using meteorological satellite imagery. International Journal of Remote Sensing. (In press.)