Jeremy Giles

Elevation Models for Geoscience

Elevation data are a critical element in most geoscience applications. From geological mapping to modelling Earth systems and processes geologists need to understand the shape of the Earths surface. Vast amounts of digital elevation data exist, from large-scale global to smaller scale regional datasets, and many datasets have been merged to improve scale and accuracy. For each application, decisions are made on which elevation data to use driven by cost, resolution and accuracy. This publication shows the current status of available digital elevation data and illustrates the key applications. The types of data assessed include: ASTER stereo satellite imagery, Shuttle Radar Topographic Mapping data, airborne laser and radar such as NEXTMap, and Multibeam Bathymetry. Applications covered include: glacial deposits, landslides, coastal erosion and other geological hazards. Technical issues discussed include: accuracy analysis, derived product creation, software comparisons and copyright considerations. This volume is a comprehensive look at elevation models for geoscience.

Future of technology in NERC data models and informatics: outputs from InformaTEC

Abstract The ‘Big Data’ paradigm will revolutionize understanding of the natural environment. New technologies are revolutionizing our ability to measure, model, understand and make robust, evidence-based predictions at increasingly spatial and temporal resolutions. Realising this potential will require reengineering of environmental sciences in the observation infrastructure, in data management and processing, and in the culture of environmental sciences. Collectively these will deliver vibrant, integrated research communities. Manipulating such enormous data streams requires a new data infrastructure underpinned by four technologies. Pervasive environmental sensor networks will continuously measure suites of environmental parameters and transmit these wirelessly to scientists, regulators and modellers in real time. Integrated environmental modelling will process data, streamed from sensor networks, using components synthesizing natural systems developed by domain experts, each of which will be linked at runtime to other expert developed components. Semantic interoperability will facilitate cross-disciplinary working, as has already happened within the biosciences so that data items can be exchanged with unambiguous, shared meaning. Cloud computing will revolutionize data processing allowing scalable computing close to observations on an as-needed basis. Leveraging the full potential of these technologies requires a major culture change in the environmental sciences where national and continental scale observatories of sensors networks become basic scientific tools.

Model fusion at the British Geological Survey: experiences and future trends

Abstract The British Geological Survey (BGS) is developing integrated environmental models to address the grand challenges that face society. Here we describe the BGS vision for an Environmental Modelling Platform (BGS 2009) that will allow integrated models to be built, and describe case studies of emerging models in the United Kingdom. This Environmental Modelling Platform will be founded on the data and information that the BGS holds. This will have to be made as accessible and interoperable as possible to both the academic and stakeholder decision-making community. The geological models that have been built in an ad hoc way over the last 5–10 years will be encompassed in a National Geological Model that will be multi-scaled, beginning with onshore UK and eventually including the offshore continental shelf. The future will be characterized by the routine delivery of 3D model products from a multi-scaled and scalable 3D geological model of the UK that can be dynamically updated. The deployment of this model will generate further significant requirements across the Information and Knowledge Exchange spectrum, from applications development (database, GIS, web and mobile device), data management, information product development, to delivery to a growing number of publics and stakeholders.

Introducing elevation models for geoscience

Elevation data are a critical element in any geoscience application. From the fundamentals of geological mapping to more advanced three-dimensional (3D) modelling of Earth systems there must be an understanding of the shape of the Earths surface. Vast amounts of digital elevation data exist, from large-scale global datasets to smaller-scale regional datasets, and in many cases datasets have been merged to improve scale and accuracy. For each application decisions must be made on which elevation data are appropriate. This will depend on many factors including the cost, resolution and accuracy of the data. The types of data discussed in this special publication include: ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), LiDAR (Light Detection And Ranging) – terrestrial and airborne, NEXTMap, SRTM (Shuttle Radar Topography Mission) and multibeam bathymetry. Applications covered include: landslide mapping, coastal erosion, glacial deposits and hazard mapping, and some of the issues discussed include: accuracy analysis, derived product creation, software comparisons and copyright considerations (Table 1 ). Since some of the papers were written for the Special Publication certain datasets have evolved and been created; for example, the GDEM global elevation dataset derived from ASTER data. This illustrates the fast moving nature of this field. View this table:In this windowIn a new windowTable 1. Summary of applications and sensors discussed in this Special Publication With the proliferation in data available for the production of digital elevation models (DEMs) it is increasingly important to understand how to use the raw data correctly and effectively. Giglierano discusses the use of LiDAR for natural resource mapping applications, and states how a ‘black box’ approach is dangerous and that knowledge of the data being used is essential, especially as more non-specialists begin to use the data. Many users reduce the resolution of the DEM to shorten processing time and also decrease the amount of space required to store the data. …

Dataset Acquisition to Support Geoscience

Abstract Environmental scientists are both producers and consumers of data. Numerous studies have shown that significant amounts of scientists’ time can be consumed in acquiring, managing and transforming data prior to their use. To facilitate the work of its scientists, the British Geological Survey (BGS) has identified a series of national datasets that are required by scientists across the organization. The BGS then seeks to acquire and manage these centrally, and to supply them to the scientists in formats that they normally use. Making these datasets readily available helps to: enhance the quality of the science; promote interdisciplinary working; reduce costs.

The what, why, when, how, where and who of geological data management

Abstract The variety, form and volume of data available to geologists have increased significantly over the past few decades. It has become essential to use databases (either analogue or digital) to turn this avalanche of data into usable information. A significant percentage of databases that are created do not repay the cost and effort of their creation and can therefore be considered to be failures. The probability of creating a successful database can be increased by careful consideration of a few simple questions. What is the objective that the database will meet? Why is a digital database being considered? When, if ever, will the cost and effort of creating the database be repaid? How will the database be designed and created? Where are the users? And finally, who will be responsible for maintaining the integrity of the database?

Integrated Environmental Modelling to Solve Real World Problems: Methods, Vision and Challenges

The discipline of Integrated Environmental Modelling (IEM) has developed in order to solve complex environmental problems, for example understanding the impacts of climate change on the physical environment. IEM provides methods to fuse or link models together, this in turn requires facilities to make models discoverable and also to make the outputs of modelling easily visualized. The vision and challenges for IEM going forward are summarized by leading proponents. Several case studies describe the application of model fusion to a range of real-world problems including integrating groundwater and recharge models within the UK Environment Agency, and the development of ‘catastrophe’ models to predict better the impact of natural hazards. Communicating modelling results to end users who are often not specialist modellers is also an emerging area of research addressed within the volume. Also included are papers that highlight current developments of the technology platforms underpinning model fusion.

Introduction to integrated environmental modelling to solve real world problems: methods, vision and challenges

Across the world, stakeholders are asking questions of their governments and decision makers to quantify the risks of environmental threats to their well-being. These questions manifest themselves as ‘deceptively simple questions’, which are easy to articulate but difficult to solve. An example of which is: ‘how much will the eruption of an Icelandic volcano cost the UK economy’. Answering these questions requires predictions of the interaction of multiple environmental processes, this requires the development and maintenance of systems that allow these processes to be simulated, and that is the nascent science of integrated environmental modelling (IEM). Such processes may be long-term (e.g. those that are impacted by climate change) or short-term threats, such as the impact of drought on UK agriculture or the impact of space weather on energy supply systems.