Surface melt driven summer diurnal and winter multi-day stick-slip motion and till sedimentology.

Fluctuations in glacier motion are very common and are thought to be controlled by subglacial hydrology and till deformation. There are few instrumented studies that have monitored seasonal changes. We use the innovative Glacsweb subglacial in situ wireless probes, combined with dGPS and custom geophone data from an Icelandic soft-bedded temperate glacier, to show that there are two distinct seasonal styles of speed-up events. Relatively small diurnal events occur during the melt season, whilst during winter there are larger multi-day events related to positive degree days. These events are accompanied by a distinct pattern of till deformation and basal icequakes. We argue these reflect stick-slip motion which occurs when the glacier hydrological system is unable to accommodate the melt water flux generated by surface melt episodes. We show a rare fully instrumented coupled glacier/till record of contrasting summer and winter stick-slip motion and discuss its implication for till sedimentology.

A semantic sensor web for environmental decision support applications.

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

An integrated content and metadata based retrieval system for art.

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.