GV2MESNU-Monitoring the Earth from Space

Module Provider: Geography and Environmental Science
Number of credits: 20 [10 ECTS credits]
Level:5
Semesters in which taught: Semester 1 module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2023/4

Module Convenor: Dr Jonathan Dale
Email: j.j.dale@reading.ac.uk

NUIST Module Lead: Simon Measho Yhdego
Email: 100101@nuist.edu.cn

Type of module:

Summary module description:

This module will introduce students to a variety of remotely sensed data and teach them how to turn this into useful information for a range of geographical applications. This module will also develop skills in extracting useful information about the environment from a wide range of Earth Observation data, using industry-standard software tools.

Aims:

The aim of this module is to furnish students with sufficient understanding and skills to enable them to employ remote sensing techniques as part of their geographical studies, and more specifically for their research projects and dissertations.

Assessable learning outcomes:

On completion of this module it is expected that a student will be able to:

• Describe and explain the physical basis of optical and radar remote sensing


• Distinguish between and evaluate the main types of remote sensing system


• Name the most important remote sensing missions, and discuss their utility for environmental monitoring


• Understand and explain the physical controls over what we can and cannot interpret from different types of remote sensing data


• Identify appropriate data from specific remote sensing missions for a range of environmental applications


• Describe and explain the form and structure of digital image data


• Compare and contrast a range of image processing algorithms


• Select appropriate techniques to analyze and interpret a range of remotely sensed data


• Adopt a systematic approach to accuracy, precision and uncertainty


• Use IT effectively and appropriately to select, analyze, present, and communicate spatial data Apply basic and more advanced numerical skills effectively and appropriately to spatial data

Additional outcomes:

The module will cover development of remote sensing, aerial photography and stereopsis, the structure of digital image data, electromagnetic radiation and the electromagnetic spectrum, energy-matter interactions, spectral characteristics of vegetation, soils, rocks and water, remote sensing systems, remote sensing platforms, applications in geology, geomorphology, soil science, vegetation monitoring, meteorology and climatology, coastal zone and oceanography. The practicals will cover the nature and structure of digital image data, acquiring and importing remote sensing data, contrast stretching and density slicing, false colour composites, vegetation ratios, spatial filtering, image preprocessing, image enhancement, classification, time series analysis, processing of synthetic aperture radar data.

Outline content:

Brief description of teaching and learning methods:

A one hour lecture and two hour practical over nine weeks, with an additional surgery session for completion of coursework