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Module DDL-4205:
Forest Inventory, Assessment and Monitoring

Forest Inventory, Assessment and Monitoring 2022-23
DDL-4205
2022-23
School Of Natural Sciences
Module - PGT
20 credits
Module Organiser: John Healey
Overview

Forest mensuration: terminology and units; measurement of single trees, forest stands and forest products; assessment of current/potential yield. Forest inventory planning. Sampling techniques: types and application with respect to forest trees, forest-dwelling organisms and forest products; the effects of variation on sampling systems. Forest inventory and statistics, forest resource monitoring, recurrent forest inventory and their roles in forest and forest products certification.

The use of remote sensing (Earth observation) technologies will have a predominant role across all the other subtopics, as it has implications in the design and statistics of modern forest inventories.

Course material will be supplied as a series of course booklets, plus text book(s). In addition to the course material, there will be a guided reading handbook which contains supplementary course material, self-assessment, a timetable for carrying out the work and details of assessments. The student's work will be evaluated with summative assessments gradually submitted during the three months over which the module runs, which will be marked and commented for the students to keep improving as the module progresses. All these will be used to monitor student progress and provide feedback, toward a final summative assessment submitted at the end of the module and marked. Students will be able to contact the module organiser to seek guidance. There will also be a web-based information resource that students can use to find information or request information, and which will include a student mutual help facility.

Assessment Strategy

-threshold -Grades C- to C+:Limited understanding of forest measurement, inventory and monitoring techniques. Limited ability to use techniques for calculating / estimating forest parameters e.g. height, basal area, stocking density, level of error in sampling.Limited evidence of wider reading.

-good -Grades B- to B+:Good understanding of forest measurement, inventory and monitoring techniques. Clear ability to use techniques for calculating / estimating forest parameters e.g. height, basal area, stocking density, level of error in sampling.Clear evidence of wider reading.

-excellent -Grades A- to A**:Excellent understanding of forest measurement, inventory and monitoring techniques. Advanced ability to use techniques for calculating / estimating forest parameters e.g. height, basal area, stocking density, level of error in sampling.Extensive evidence of wider reading and understanding.

Learning Outcomes

  • Appreciate how variation in the forest resource impacts on the process of forest inventory.

  • Appreciate the fundamental importance of assessment, inventory and monitoring with respect to forest resource management.

  • Appreciate the implications of using modern remote sensing technologies in forest inventories, and develop the skills necessary to implement them in practice.

  • Appreciate the importance of monitoring forest resources.

  • Be able to use these techniques to perform a range of calculations relating to forest resources.

  • Learn how communicate topics related to forest inventory and provide the results of an inventory work following professional standards.

  • Understand and be able to apply the sampling systems commonly used in forest inventory.

  • Understand how the state of a forest resource may be reliably monitored over time to meet a range of objectives.

  • Understand how to plan a forest inventory.

  • Understand techniques, terminology and conventions used in forest mensuration and how these are applied in modern forest management.

Assessment method

Coursework

Assessment type

Crynodol

Description

Traditional Inventory based on field plot sampling

Weighting

20%

Due date

19/02/2023

Assessment method

Coursework

Assessment type

Crynodol

Description

Forest classification using aerial photography

Weighting

20%

Due date

19/03/2023

Assessment method

Coursework

Assessment type

Crynodol

Description

Estimation of forest variables using airborne laser scanners

Weighting

20%

Due date

02/04/2023

Assessment method

Coursework

Assessment type

Crynodol

Description

The value of forest information

Weighting

40%

Due date

21/05/2023

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