GIS, Geostatistics, and Machine Learning in Medical Geology

Geographical information system (GIS) is gaining its popularity beyond geography and information technology (IT) with its strong power in managing and analysing spatial data. In medical geology, GIS provides two main useful functions: (a) mapping and (b) spatial analysis. It contains specialised computer software and hardware designed to process data with locational information. Besides geology and medical information, data in medical geology usually contain locational information which is suitable for mapping and spatial analysis using GIS. Regarding mapping, one of the main techniques linked with GIS is geostatistics which is widely applied for the production of spatial distribution maps based on sampling. Environmental samples in medical geology are generally collected at points, which need to be converted to spatial distribution maps for practical uses in management as well as for scientific interpretation. Geostatistics provides an effective way to estimate the values at un-sampled locations, so that the estimated values can be used for production of spatial distribution maps in medical geology. As for spatial analysis, machine learning begins to receive attention in medical geology in the big data era. It contains advanced statistical techniques which can be used to “learn” from the data, and then be applied for classification, clustering, and prediction in medial geology. This chapter explains the basic concepts of GIS, geostatistics, and machine learning and demonstrates how they are used for mapping and analysing data in medical geology. 1. GIS and its links with medical geology. 2. Geostatistics and its links with medical geology. 3. Big data and machine learning and their links with medical geology. 4. Case studies.