GV2EDNU: Analysing Environmental Data and Information Systems

Module code: GV2EDNU

Module provider: Geography and Environmental Science; School of Archaeology, Geography and Environmental Science

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 1

Module convenor: Dr Jess Neumann, email: j.l.neumann@reading.ac.uk

NUIST module lead: Jianbing Jin, email: hqhaixia@163.com

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: No

Last updated: 20 May 2024

Overview

Module aims and purpose

This module aims to develop skills in the management and analysis of environmental data. Using Microsoft Excel and other statistical software, students will have the opportunity to analyse their own independently collected data, as well as analyse data sets provided from published environmental research studies. The module will also develop the students’ skills in the creation, management and use of Environmental Information Systems in environmental decision making.  

Outputs from a variety of practical investigations will be interpreted through the application of a range of standard and modern statistical methods, as well as the application of GIS, remote sensing and environmental mapping. 

Raphinos Murava (bapaul@nuist.edu.cn) will also be teaching on this module.

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Understand the rudiments of environmental information, databases and the importance of statistics and Environmental Information Systems (EIS) in environmental decision making and protection. 
2. Execute research design and sample collection protocols that are suitable for a given statistical test. 
3. Apply a range of statistical skills to condense, summarise, analyse and interpret current environmental data. 

4. Explain the structures and processes in developing environmental databases and EIS and design EISs conceptually towards resolving an actual environmental problem. 

Module content

• Introduction to databases, statistics and EIS: Why do we need them? 
• Types of data: discrete or continuous, dependent or independent? 
• Frequency distributions (percentiles, polygons and curves) 
• How to graphically display data: scatterplots, boxplots, stem and leaf plots, etc. 
• Describing distributions and uncertainties (IQR, variance, standard deviation, skewness, kurtosis) 
• Probability models (special discrete distributions and normal distribution) 
• Sampling distributions, estimation, confidence intervals 
• Testing for differences and relationships: t-test, ANOVA, correlation and regression. 
• What is an Environmental Information System? 
• An overview of databases 
• Meta-data: ‘data on data’ 
• How to acquire and standardise environmental information in GIS 
• Spatial data models and geodatabases in GIS 
• Spatial data processing and analysis in GIS 
• The development and application of an EIS in resolving an environmental challenge 

Structure

Teaching and learning methods

The theory sections of the module are taught through interactive lectures that introduce the students to the principles and methods covered. Seminars allow students to research and discuss topics in greater depth whilst case studies, problem solving sessions, intensive open-ended assignments and videos may also be used to enhance understanding. 

Methods will be applied during the computer laboratory practical sessions; the students will consolidate their knowledge by collecting and analysing their own data, working in groups and delivering presentations.  

Study hours

At least 96 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Monthly homework assignments are designed to develop the student's understanding and to provide feedback on written work. Regular surgery tutorials provide an opportunity for students to seek additional help, if required. 

Reassessment

Additional costs