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Large-scale geomorphological maps of mountainous areas are traditionally made using complex symbol-based legends. They can serve as excellent “geomorphological databases”, from which an experienced geomorphologist can extract a large amount of information for hazard mapping. However, these maps are not designed to be used in combination with a GIS, due to their complex cartographic structure. In this paper, two methods are presented for digital geomorphological mapping at large scales using GIS and digital cartographic software. The methods are applied to an area with a complex geomorphological setting on the Borsoia catchment, located in the Alpago region, near Belluno in the Italian Alps. The GIS database set-up is presented with an overview of the data layers that have been generated and how they are interrelated. The GIS database was also converted into a paper map, using a digital cartographic package. The resulting largescale geomorphological hazard map is attached. The resulting GIS database and cartographic product can be used to analyse the hazard type and hazard degree for each polygon, and to find the reasons for the hazard classification.

Road Traffic Accidents (RTA) are known to be one of the main causes of fatalities worldwide. One usef ul approach to improve road safety is through the identification of RT A hotspots along a road, so they can be prioritised and treated. This paper introduces an approach based on Geographical Information System (GI S) to identify and prioritise RTA hotspots along a road network using historical RTA data. One particular urban road in Brunei with a historically high rate of RT As, Jalan Gadong, was selected as a case study. Five years of historical RTA data were acquired from the relevant authorities and input into a GIS database. GI S analysis was then used to identify the spatial extension of the RT A hotspots. The RT A hotspots were ranked according to three different schemes: frequency, severity and socio-economic impact of RTAs. A composite ranking scheme was also developed to combine these schemes; this enabled the prioritisation and development of intervention and maintenance programmes of the identified RTA hotspots. A visualisation method of the RTA spatial distribution within each identified RTA hotspot was also developed to determine the most risky road stretches within each hotspot, which is important for treatment prioritisation when limited resources are available.

A geographic information system (GIS) was used to evaluate the area in logging trails categorized by number of machine passes. Preharvest logging trail surveys and observations of machine movements during harvesting were transferred to a GIS to determine areas. Detailed procedures and time required to build the GIS database are presented. There was excellent agreement between the trail area estimates based on the GIS database and those from an independent, line-transect method. However, the line-transect method gives no information on the number of machine passes.