Natural Resource Sampling and Modelling

Course content

The main objective of the course is to provide students with tools for sampling, modelling and interpreting information on structure and diversity of vegetation cover, land use and production of various products in terrestrial environments. Furthermore, the course aims to enable students to plan and implement minor inventories and field experiments and critically analyse and reflect on the reliability of empirical results. Finally, the course aims to provide students with the basis required for preparing guidelines for sustainable use. Hence, the course contributes to competences needed when doing empirical work within the MSc programmes in Forest and Nature Management, SUFONAMA, SUTROFOR and EnvEuro. The course would also be relevant for students within other programmes, e.g. Agricultural Development, who emphasise management of forest and nature in their curriculum or plan to prepare their MSc thesis within this realm.


Course contents in detail

  • Measurements in terrestrial environments (forest and nature); for individuals and populations of trees, shrubs, herbs and rare species; for fauna and geophysical site characteristics. The emphasis is on direct measurements but an introduction to applications of remote sensing techniques is given.
  • Sampling methods and design, inventory planning and implementation, introduction to experimental design and practice.
  • Practical application of statistical methods for analysis of data from inventories and experiments, data management, model choice and model validation.
  • Relationships between physical environment (climate, soil, topography) and growth, competition and succession of ecological systems in forest and nature.
  • Modelling states and developments of - and relationships between - individuals, populations and systems in forest and nature.
  • Models describing volume, biomass and carbon, growth and yield, size distributions, relationships between various measures on individuals (allometric models) and populations.
  • Growth models working at various levels of detail: stand growth models, size-class models and individual-tree models.
  • Introduction to systems models, including process models, CO2 models, gap models and landscape/ecosystem models.
  • Use of quantitative methods, inventory results and models as the basis of sustainable management decisions and natural resource planning.

MSc Programme in Agriculture
MSc Programme in Forest and Nature Management
MSc Prgramme in Agricultural Development
MSc Programme in Forest Ecosystems, Nature and Society (SUFONAMA)
MSc Programme in Forests and Livelihoods (SUTROFOR)

Learning outcome


  • Describe principles and procedures applied for measuring typical variables in forest and nature.
  • Classify and reflect on sampling strategies typically used in natural resource inventories.
  • Describe basic relationships between the biophysical environment, growth of individual organisms and populations, competition between organisms, and succession of ecosystems.
  • Show overview of model types used to describe relationships and to model growth and development of individual plants, populations and ecosystems.


  • Compare sampling strategies, assess their suitability, and select appropriate strategies for given natural resource contexts.
  • Apply principles and methods from basic statistics in typical sampling and modelling situations in terrestrial environments.
  • Select suitable model formulations for modelling particular relationships and assess the quality of predictions.


  • Apply principles used for measuring and modelling typical variables in forest and nature to new situations.
  • Discuss the relevance, reliability, validity and interpretation of empirical data and results obtained in particular contexts.
  • Evaluate empirical evidence, put results into perspective and discuss consequences in relation to sustainable management.

Theoretical considerations, models and methods are presented in lectures along with relevant examples. Implications of the theory are illustrated in exercises. Some of the exercises are intended for individual work; others are intended for group work. Some exercises are based on small datasets; others are based on larger extracts from real datasets. During the course students will choose an empirical case, formulate a research question and conduct a small survey in groups of 3-5 persons. This work includes planning of the sampling procedure and the subsequent analysis, sampling of data in the field (during an excursion), data analysis, interpretation of results and, finally, discussion of the results in plenum.

The distribution of the 12 weekly hours of instruction is: lectures 4 hours, classroom exercises 4 hours, computer exercises 4 hours. The course includes one excursion (approx. 6 hours) in the middle of the course period.

Part of the course is based on scientific papers, lecture notes and exercise materials. Moreover, selected chapters of the following textbooks are included:

  • Avery, T. E. & H. E. Burkhart, 2001. Forest Measurements. 5th Edition. McGraw-Hill Inc, New York. ISBN 0071130055.
  • Bonham, C. D. 1989. Measurements for Terrestrial Vegetation. John Wiley & Sons, New York. ISBN 0471048801.
  • Buckland, S. T.; D. R. Anderson; K. P. Burnham; J. L. Laake; D. L. Borchers & L. Thomas 2001. Introduction to Distance Sampling. Estimating Abundance of Biological Populations. Oxford University Press, Oxford. ISBN 0198509278.
  • Franklin, Steven E. 2001. Remote Sensing for Sustainable Forest Management. Lewis Publishers, CRC Press, Boca Raton. ISBN 1566703948.
  • Vanclay, J. K., 1994. Modelling Forest Growth and Yield. Applications to Mixed Tropical Forests. CAB International, Wallingford. ISBN 0851989136.
  • Van Laar, A. & A. Akça, 2007. Forest Mensuration, Managing Forest Systems, Vol. 13. Springer, Dordrecht. ISBN 978-1-4020-5990-2.


The final course literature will be announced through Absalon. Similarly, all lecture notes, exercise materials and slides will be made available through Absalon.

Basic BSc courses of mathematics and statistics. Throughout the course we will use a range of methods from basic statistics. Students who are not familiar with basic statistics must expect an increased workload.

The day and time of the excursion will be decided jointly by course participants and course responsible teacher and may include hours outside standard module hours (e.g. Friday afternoon).

7,5 ECTS
Type of assessment
Written assignment, 12 hours
12 hour written assignment. On the day of the examination questions and data are available from 8:00 am. It is the personal responsibility of each student to make sure that the examination questions and all associated datasets have been received. 12 hours later, at 8:00 pm, all students must appear personally at the department, Rolighedsvej 23, to hand in their written assignment. No material can be handed in after 8:30 pm.
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Two internal examiners
Criteria for exam assessment

See description of learning outcomes

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 32
  • Excursions
  • 6
  • Theory exercises
  • 64
  • Exam
  • 12
  • Project work
  • 6
  • Preparation
  • 86
  • English
  • 206