Advanced GIS and Remote Sensing MSc

Program Overview

This MSc program in Remote Sensing and GIS equips graduates with advanced skills in geospatial data management, remote sensing, and GIS analysis. The program's industry-focused curriculum and experienced faculty prepare students for careers in environmental management, urban planning, and other geospatial fields. Graduates benefit from strong industry connections and international recognition, enhancing their career prospects globally.

Program Outline

Outline:

Modules:

• GIS and Spatial Data Management: This module introduces the functional components of a GIS, projections, data and modelling processes for managing spatial data.
Students will learn to organize and integrate spatial and aspatial data within a GIS, analyze and prepare data within appropriate spatial databases, and examine the role of the INSPIRE Directive and FAIR data principles for enabling interoperability between spatial data infrastructures.
• Scientific Python: This module develops students' skills and confidence in writing Python code and accessing a broad ecosystem of packages and tools that comprise the foundations of Data Science.
Students will learn about fundamental programming concepts, explore Python scientific packages for data analysis and visualization, and apply geospatial data analysis and visualization with Python.
• Aerial Photography and Digital Photogrammetry: This module introduces the techniques for extracting topographic information from remotely sensed data using digital photogrammetry techniques.
Students will also learn image interpretation principles and practices.
• Applied Earth Observation: This module explores the physical principles and imaging technology behind the appropriate application of remote sensing to the monitoring of Earth resources.
Students will learn to define primary physical quantities related to measured radiance, compare the nature of surface and atmospheric interactions with electromagnetic radiation between passive and active satellite sensors, evaluate appropriate data for surface monitoring applications, and analyze the complete remote sensing process from data reception to information extraction.
• Image Processing and Analysis: This module teaches students various image processing techniques for extracting and analyzing information from satellite, aerial, and drone image data.
Students will evaluate a wide range of image processing techniques and their underlying mathematical principles, select appropriate image processing sequences to achieve predetermined objectives, operate and manage an image processing system, and integrate image processing techniques into applications of remote sensing.
• Advanced GIS Methods: This module introduces advanced GIS analysis methods used in environmental modeling and applications.
Students will learn to assess the quality of geographic data, apply advanced spatial analyses, design and conduct field surveys for data collection and verification, and select and perform appropriate modeling and statistical analyses.
• Environmental Resource Survey: This module covers the fundamentals of environmental resource surveys, including why, when, where, and how to conduct them.
Students will learn about R software for manipulating and visualizing survey data, survey strategies for environmental resources, development of classification schemes, sampling and rapid estimates for plant communities, water and soil quality, assessment of existing data quality and use in survey design, statistical design and analysis for environmental resource surveys, and quality assessment of environmental data.
• Web Mapping: This module introduces web mapping technologies and applications relevant to the management and dissemination of geographical data on the Internet.

Teaching:

Teaching Team:

The course features a diverse team of research and academic staff, along with industry representatives, with expertise in various areas of remote sensing, GIS, and environmental studies.

Teaching Methods:

The course utilizes a variety of teaching methods, including lectures, tutorials, real-world case studies, practical sessions, consultancy-led projects, and independent research.

Faculty:

The program boasts a highly qualified and experienced faculty with research backgrounds and industry connections.

Careers:

Career Opportunities:

The program equips graduates for diverse and rewarding careers in the geospatial sector, including:

• Environmental management
• Natural resource management
• Urban planning
• Transportation planning
• Emergency management
• Science
• Government and Business intelligence
• Data Analyst
• Academic Researcher
• GIS Technician
• Geospatial Analyst
• GIS officer
• Project Development Officer
• Remote Sensing Scientist
• Airbus
• Cambridgeshire Acre

Other:

• The program is designed in close collaboration with industry to ensure graduates possess the necessary skills and knowledge to meet current industry demands.
• The program is internationally recognized by employers across scientific, industrial, and educational communities.
• The program offers a unique and innovative curriculum that blends theoretical knowledge with practical skills training.
• The program boasts a strong international outlook with career opportunities not limited to the UK.
• The program provides support for international students to work in the UK after graduation.
• The program offers practical, industry-led education, making graduates highly desirable to global employers.
• Cranfield's strong reputation and links with potential employers provide outstanding opportunities for graduates to secure exciting jobs and develop successful careers.
• Cranfield Careers and Employability Service offers career coaching and advice, CV development, interview practice, job opportunities, and access to hundreds of available jobs via their platform.
• Cranfield alumni have access to lifelong career resources for education and career advancement.

Note:

This response combines information extracted from the provided context and is not an exhaustive list of all potential details related to the program.