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香港六合彩 Module Catalogue

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Geospatial Data Science (IRDR0047)

Key information

Faculty
Faculty of Mathematical and Physical Sciences
Teaching department
Institute for Risk and Disaster Reduction
Credit value
15
Restrictions
N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module is focused on quantitative disaster risk management with geospatial and data science, mainly using geographic information systems (GIS), remote sensing (e.g., satellite, drone, radar data) and machine learning or other relevant methods. Students will learn how to select appropriate geospatial data, prepare, process, and use them for decision-making for diverse disaster risk reduction applications. Students will be introduced to different geospatial and remote sensing data types to learn their properties and specific application areas in risk and disaster science and humanitarian crises. Students will also learn how to prepare and process GIS and remote sensing data using data science techniques to extract targeted information and evaluate the accuracy of the results. Applications will be in various topics, from monitoring natural hazard-induced disasters and conflicts to assessing their impact on urban and rural environments using an appropriate programming language and industry-standard software. In addition, emerging geospatial and data science topics will be introduced to familiarise students with future directions in the field.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
40% In-class activity
60% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
8
Module leader
Dr Saman Ghaffarian
Who to contact for more information
irdr-education@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

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