Through MISCADA’s Earth & Environment specialisation, we seek to provide the advanced knowledge of how to use the datasets and tools to tackle cutting-edge and societally-relevant problems relating to the Earth’s environment and management of its scarce resources. The specialisation introduces a variety of Earth and Environmental datasets, and to the specialist mathematical and software tools required for their quantitative and computational analysis.
In Term 1, The first portion of the module will focus on equipping students with the necessary specialist mathematical and software tools to handle, manipulate, visualise and analyse environmental datasets. This term will start with the use of spatial information systems, including GIS, and remotely sensed data. The second topic will be the use of forward and inverse modelling to interpret environmental data not only to understand the fundamental structure of the Earth, but also understand risks and hazards and the exploitation of natural resources. Finally, the use of statistical modelling approaches to understand environmental management for controlling pollution.
The second term of the module is structured around four topics; each addressing a key broad data-stream in the Earth Sciences. Each topic will first feature a brief introduction to the Earth Sciences context, background, and key concepts relevant to each data-stream. This brief introduction will be followed by a deep-dive into the relevant datasets themselves, including collecting or obtaining the data, handling and processing, and unique considerations/limitations/strengths of the different datasets. Finally, each topic will highlight a variety of diverse real-world problems the data can be used to address, e.g. for satellite radar: ship tracking, landslide detection, atmospheric tomography and volcano early-warning systems. For the end of the second term there will be a Data Camp, a short field course focussed on acquisition of data from a range of sources from individual sensors, through drones and on to satellite data, followed by processing of these datasets, integration and joint analysis with supplementary datasets across a diverse range of scales (e.g. satellite data, national, international sensor networks).