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1. Bangladesh Climate-Resilient Ecosystem
Curriculum (BACUM)
Module 3: Forest Carbon Measurement and Monitoring

2. Module 3: Forest Carbon Measurement and Monitoring
SECTION III: FOREST CARBON MEASUREMENT AND MONITORING METHODS
3.3. Field Sampling Design Methods

3. Forest
Carbon
Measurement
and
Monitoring
(FCMM)
I. FUNDAMENTALS OF FOREST CARBON IN REDD+ CONTEXT
1.1. Forests, the Global Carbon Cycle and Climate Change
1.2. The Roles of Forests and Forest Carbon in Global Climate Negotiations
1.3. Challenges for Forest-based Climate Change Mitigation
II. FOREST CARBON STOCKS AND IPCC GUIDELINES
2.1. Overview of Forest Carbon Pools (Stocks)
2.2. Land Use, Land Use Change, and Forestry (LULUCF)
2.3. IPCC Guidelines for Forest Carbon Measurement and Monitoring
2.4. Reference Levels – Monitoring against a Baseline
III. FOREST CARBON MEASUREMENT AND MONITORING METHODS
3.1. Overview of Forest Carbon Measurement and Monitoring
3.2. Quality Assurance and Quality Control (QA/QC)
3.3. Field Sampling Design Methods
3.4. Forest Carbon Field Measurement Methods
3.5. Carbon Stock Calculation and Available Tools
3.6. Creating Activity Data and Emissions Factors
3.7. Considerations in Developing a Monitoring System

4. Acknowledgements
UNIVERSITIES
Bangladesh Agricultural University
University of Chittagong
Dhaka University
Independent University, Bangladesh
Khulna University
Noakhali University of Science and Technology
Shahjalal University of Science and Technology
Sher-e-Bangla Agriculture University
North South University
EXPERT CONTRIBUTORS SPECIFIC INPUTS
Prof. (Dr.) Manzoor Rashid Curriculum Development for all
topics
Prof. (Dr.) Md. Danesh Miah REDD+, Forest Carbon
Prof. (Dr.) Md. Jakariya Community NR Management,
Climate Change, Natural Resources
Management
DESIGN, LAYOUT AND CONTENT DEVELOPMENT: Ms. Chi Pham, Curriculum Development Expert, Bangkok, Thailand
CREL STAFF CREL STAFF
John A Dorr Utpal Dutta
Abu Mostafa Kamal Uddin Ruhul Mohaiman Chowdhury
Kevin T. Kamp Rahima Khatun
Paul Thompson Sultana Razia Zummi
Abdul Wahab Shams Uddin
Shahzia Mohsin Khan

5. At the end of this session, students will be able to:
• Explain why sampling is necessary
• Distinguish among random, stratified, and systematic
sampling, and know where each is appropriate
• Identify the advantages and drawbacks of different sampling
schemes
Learning Objectives

6. Class Exercise

7. Class Exercise

8. • Often it is impractical to examine an entire population
• Instead, we select a sample from our population of interest
and, on the basis of this sample, information about the
entire population will be inferred
What is Sampling?

9. Reasons for Sampling
It is extremely unlikely that we would have the
time and resources needed to measure the entire
carbon stock in a forest or landscape

10. • Instead we select a sample from an area of interest, on the
basis of this sample, we can infer information about the
entire area
• Conclusions about an entire population will be drawn based
on the sample information through statistical inference
Value of Sampling

11. 1. Measure carbon stocks in sampled
areas
2. Assume sampled carbon stocks
represent a reasonable estimate of
population carbon stocks,
3. Multiply measured carbon per unit
area by entire area of interest to
calculate the carbon stocks
4. Use the variation among your plot
values to estimate uncertainty
Carbon Sampling Example

12. • The sample must provide an
accurate picture of the population
from which it is drawn
• The sample should be random;
each individual in the population
should have an equal chance of
being selected
Sampling Theory

13. Different sampling schemes can be used:
1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Cluster sampling
Sampling Theory

14. 1. Simple Random Sampling

15. 2. Systematic Sampling

16. 3. Stratified Sampling

17. 4. Cluster Sampling

18. • Sampling units are independently
selected one at a time until the
desired sample size is achieved
• Each study unit in the finite population
has an equal chance of being included
in sample without any bias
Simple Random Sampling
http://www.youtube.com/watch?v=yx5KZi5QArQ

19. Simple Random Sampling
A random sample
Advantages:
 Representativeness and
freedom from bias
 Ease of sampling and analysis
Disadvantages:
 Errors in sampling
 Time and labor requirements

20. • Distributes the sample evenly over
the entire population
• Bias may arise if there is some
type of periodic variation in
carbon stocks, but such patterns
are rare
Systematic Sampling
http://www.youtube.com/watch?v=QFoisfSZs8I

21. Advantages:
 Spatially well distributed
 Small standard errors
 Long history of use
Disadvantages:
 Bias in overestimating the
actual standard error
 Less flexible to increase or
decrease the sampling size
 Not applicable for fragmented
strata
Systematic Sampling

22. • Involves grouping the population
of interest into strata to estimate
characteristics of each stratum
and to improve the precision of an
estimate for entire population
Stratified Sampling
http://www.youtube.com/watch?v=sYRUYJYOpG0

23. Stratified Sampling
Advantages:
 Allows specifying the sample
size within each stratum
 Allows for different sampling
design for each stratum
Disadvantages:
 Yields large standard error if
the sample size selected is not
appropriate
 Not effective if all variables
are equally important

24. • Involves a grouping of the
spatial units or objects
sampled
• All observations in the
selected clusters are included
in the sample
Cluster Sampling
http://www.youtube.com/watch?v=QOxXy-I6ogs

25. Cluster Sampling
Primary Sampling
Unit (PSU)
Secondary Sampling
Unit (SSU) - cluster
Advantages
 Can reduce the time and
expense of sampling by reducing
travel distance
Disadvantages
 Can yield higher sampling error
 Can be difficult to select
representative clusters

26. 1. Divide class in 4 groups (pick students randomly or systematically)
2. Randomly assign each group one of the sampling techniques and a map of
land cover either national or regional
3. Each group should meet outside of class and decide on how to locate sampling
plots to estimate per cent of each major land cover class based on the
technique they were assigned. Next class they should be prepared to present
their maps with sampling plots marked on them
Homework

27. Forest Carbon Stratification Techniques

28. • Allows for measuring and monitoring areas where changes
are likely to occur
• Reduces sampling effort while maintaining accuracy and
precision in carbon stocks estimates
• Allows for wise spending of the resources
Why Stratify for Carbon Inventory?

29. By threat of deforestation
• Use historical evidence to identify critical factors of deforestation
• Create potential for deforestation map
• Identify areas with high probability of deforestation
By forest type
• Use existing maps of vegetation types
• Use existing forest inventory
By accessibility
• Define accessibility criteria (e.g. 5 km accessibility to main roads)
• Use spatial analysis to model accessibility
Types of Stratification

30. • Stratifying by carbon stock reduces the sampling effort
required to achieve targeted precision level
Stratification by Carbon Stocks

31.  Develop initial stratification plan
• Land use
• Vegetation
• Slope
• Drainage
• Proximity to settlement
 Collect preliminary data (~10
plots per stratum)
Stratification by Carbon Stocks & Forest Type

32. Not All Forests are Equally Threatened

33. Stratification by Threat
1. Use spatially explicit land
use change model
2. Identify key factors impacting
historical deforestation patterns
3. Identify areas with high suitability
for deforestation
4. Create deforestation threat
map

34. Sampling Design

35. Background: Existing forest inventories in Bangladesh
E Carbon Inventory (PA) 2014 (CREL)
D Carbon Inventroy 2010 (CREL)
! FD-97-coastal
! FD-97-hill
! FD-97-sund
) FD-NFA
! FD-SAL
! MKNP
! Sund RF
In total 17,371 plots
have already been
measured in
Bangladesh since 1958.
9 930 sample plots are
still available, out of
them
368 510 trees have
been inventoried

36. Example of previous plot designs in Bangladesh
NFA
- Rectangle
- 4 sub plots
- Large area
- Less intensity
- 298 plots
- Circular
- Nested
- 17.84m: > 50cm
- 10m: > 20
- 4m: > 5
- 2m: saplings
Protected Area Carbon Inventory
Sal
- Circular
- Cluster
- 3x volume plots
(17.84m)
- 4x area plots
(5.64 – 7.98)
Plot size different
depending on
location
Sundarban Carbon Assessment
- Circular
- Cluster
- 10m: > 10cm
- 4m: Non-tree veg
- 3m: >10cm
- 2m: Herbs

37. • Sampling is very important in forest inventory in order to
estimate information about an entire population
• There are a number of sampling techniques but stratified
sampling is most commonly used in forest carbon inventory
• Forest types (or Carbon stocks) and threat of deforestation/
degradation are two main factors that are used to stratify
the study area.
Take Home Message

38. • USAID. 2015. USAID LEAF‘s Climate Change Curriculum. USAID Lowering Emissions in Asia Forests
Program (USAID LEAF). Winrock International and US Forest Service. Bangkok, Thailand.
• Asner, G.P. 2009. Tropical forest carbon assessment: Integrating satellite and airborne mapping
Approaches. Environ. Res. Lett. 4 034009
• Czaplewski, R., R. McRoberts and E. Tomppo. 2004. Sample designs. FAO-IUFRO National Forest
Assessments Knowledge reference. http://www.fao.org/forestry/7367/en/
• Maniatis, D. and D. Mollicone. 2010. Options for sampling and stratification for national forest
inventories to implement REDD+ under the UNFCCC Carbon Balance and Management,
5:9 doi:10.1186/1750-0680-5-9
References

39. The curriculum of USAID’s Climate-Resilient Ecosystems and Livelihoods (CREL) in Bangladesh is a free
resource of teaching materials for university professors, teachers and climate change training experts.
Reproduction of CREL’s curriculum materials for educational or other non-commercial purposes is
authorized without prior written permission from the copyright holder, provided the source is fully
acknowledged.
Suggested citation: Winrock International. 2016. USAID‘s Climate-Resilient Ecosystems and Livelihoods
(CREL). Winrock International. Dhaka, Bangladesh.
Disclaimer: The CREL’s curriculum is made possible by the support of the American People through the
United States Agency for International Development (USAID). The contents of the curriculum do not
necessarily reflect the views of USAID or the US Government.
References and Resources

40. USAID's Climate-Resilient Ecosystems and Livelihoods (CREL) Project
Winrock International Headquarters
2101 Riverfront Drive, Little Rock
Arkansas 72202-1748 USA
Tel: 1-501-280-3000
Web: www.winrock.org