Geospatial Sensors, Platforms and Data
| Code | School | Level | Credits | Semesters |
| ENGR4013 | Engineering Research | 4 | 10 | Autumn UK |
- Code
- ENGR4013
- School
- Engineering Research
- Level
- 4
- Credits
- 10
- Semesters
- Autumn UK
Summary
This module will introduce students to the technologies commonly used to capture and record geospatial data. It will cover sensor technology such as satellites, drones, social media, IoT and sensor networks, as well as multi-sensor platforms such as mobile mapping vehicles employing photography, video and laser scanning. The module will cover the different types of data generated by such sensors and platforms and investigate the key geospatial considerations around their use, such as spatial scale, observational density, and temporal velocity. The module will introduce students to the most commonly employed data formats and management software appropriate for different types of geospatial data.
Outline Syllabus
Characteristics of geospatial data
Spatial data types
Earth observation and remotely sensed data
Geospatial data acquired by airborne sensors and platforms
Geospatial sensor networks and internet of things
Location based social media and crowd sourced data
Location based services
Data formats and structures
Data standards
Target Students
The students will be the annual cohorts from the EPSRC Geospatial Systems CDT , from both UNiveristy of Nottingham and Newcastle University.
Classes
- One 4-hour practicum each week for 5 weeks
- One 1-hour lecture each week for 15 weeks
Assessment
- 20% Presentation: Presentation on a particular area of geospatial sensors and data.
- 40% Report: Lab reports of extended exercises relating to workshops.
- 40% Assignment: A essay giving a critical evaluation of the issues around particular geospatial data types. Word count: Up to 1,500.
Assessed by end of autumn semester
Educational Aims
This module will introduce students to the technologies commonly used to capture and record geospatial data. It will cover sensor technology such as satellites, drones, social media, IoT and sensor networks, as well as multi-sensor platforms such as mobile mapping vehicles employing photography, video and laser scanning. The module will cover the different types of data generated by such sensors and platforms and investigate the key geospatial considerations around their use, such as spatial scale, observational density, and temporal velocity. The module will introduce students to the most commonly employed data formats and management software appropriate for different types of geospatial data.Learning Outcomes
Understanding of the key characteristics of geospatial data.
Knowledge of the different sensor and platform technologies that acquire geospatial data.
Understanding of the different formats and standards employed in geospatial data handling
Knowledge of the most appropriate software tools for the management and manipulation of geospatial data
The ability to choose and source appropriate data for geospatial applications
Practical skills in handling different geospatial data types and formats
The ability to ingest, manage and manipulate geospatial data within software packages
Practical knowledge of how to capture and manage geospatial data streams and real-time data