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Improved National Forest Inventory Sampling Design Bac Kan Case Study Tani Höyhtyä, 28 Aug 2012

Improved National Forest Inventory Map sampling design

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Forestry and Forest Industry in Green Economy An effort is under way worldwide to better manage our planet’s forest resources and better enhance their role in mitigating climate change. Forest loss and degradation in developing countries account for nearly 20% of global greenhouse gas emissions. Monitoring and reducing these emissions has been the key goal for the international community in climate change negotiations and is important for the upcoming Rio+20 conference on sustainable development. Viet Nam is one example of a country that’s taking important steps to manage and expand its forest resources. Previous loss of forested areas has been reversed and the country is now increasing forest area by about 1% every year

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Page 1: Improved National Forest Inventory Map sampling design

Improved National Forest Inventory Sampling Design Bac Kan Case Study

Tani Höyhtyä, 28 Aug 2012

Page 2: Improved National Forest Inventory Map sampling design

NATIONAL FOREST ASSESSMENT (NFA)

PROJECT

• NFA project is designing improved national forest inventory system to be implemented in Vietnam during the next national forest inventory round between 2016 and 2020.

• NFA project is not carrying out any large scale national forest inventory excluding some pilot tests

• NFA project is developing tools for next NFI round • Data collection, input, verification, calculation, analyses and

dissemination tools

• Hardware and software solutions

• Strengthening of institutional and human resources through training of all personnel involved

14.11.2011 2

Page 3: Improved National Forest Inventory Map sampling design

THE PURPOSE OF NATIONAL FOREST

INVENTORIES

3

To produce statistical data on national and province level: forest area, growing stock, forest types, quality of forests...

Needed to plan policy actions, estimating cutting possibilities, promoting sustainable

forest management, protection of forests. monitor the success/failures of policies plan future investments: production capacity of timber, pulp wood,

bioenergy... international reporting processes: FAO Global FRA, UNFCCC

Not for operative planning, not for management planning at local level

When only statistical data is needed, it is possible to use sampling techniques => costs are much lower than in management planning inventories

When combined with satellite images => forest maps can be produced, but not at very detailed level

Page 4: Improved National Forest Inventory Map sampling design

NFI & MULTI-SOURCE NFI

Field data

High resolution satellite imagery

Digital maps and other data sources

Statistics] Thematic maps]

Processing

Page 5: Improved National Forest Inventory Map sampling design

TYPICAL INFORMATION CONTENT OF NFI

• Area of land • by land use classes and forest categories (e.g. forestry, agriculture...)

• by land cover classes (forest, other wooded land, other land)

• Area of forest land • by forest types, by tree species dominancy and by age classes

• Volume of growing stock • by tree species, by forest types

• Growth by tree species or tree species groups (permanent sample plots)

• Volume of the total drain (=harvest plus natural losses) (permanent plots)

• Carbon pool and carbon pool changes of the five pools given in IPCC GPG LULUCF 2007 (above ground biomass, below ground biomass, dead wood, litter, soil)

• The areas of accomplished and needed operations on forest land

• Quality: damages and disturbances

• Biodiversity elements

• Changes

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Page 6: Improved National Forest Inventory Map sampling design

NFI-4 SAMPLING DESIGN

6

Line for forest stand boundary definition

1000 m

1 2 3 4 5 6 7 8 9

8 – NN

13.8

9 – IIIB

7.9

4 – IIA

9.5

2 – IIB

6.4 I – IIIA3

14.8

3 –

IC 5.8

7 – IVB

8.6 6 – IIIA2

20.4

5 – IIIB

13.8

Longitude

1000

m

Latitude

N

40 sub-plots in

L-shape line

Page 7: Improved National Forest Inventory Map sampling design

WHY IMPROVED DESIGN?

• NFI-4 sampling design is scientifically valid, but very

laborious

• Mapping of forest types in the field

• Measurement of large number of sub-plots and trees

• New information needs arise => costs would increase

• Development of remote sensing, measurement, GIS & ICT

tools

=> Costs of data collection can be reduced to cover the

costs caused by new information needs

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Page 8: Improved National Forest Inventory Map sampling design

ROAD MAP FOR THE IMPROVED NFIMAP

SAMPLING DESIGN

A. Plot size evaluation with NFI-4 data

B. Correlogram / Semivariogram analyses with NFI-4 data to compare efficiency of different designs

C. Accessibility analysis; tests with Google Earth

D. Improved sampling design and field tests in Bac Kan province

E. Information need analyses

F. Compilation of improved NFIMAP design and methodology for whole country

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Page 9: Improved National Forest Inventory Map sampling design

A. PLOT SIZE EVALUATION WITH NFI-4 DATA

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Page 10: Improved National Forest Inventory Map sampling design

PLOT SIZE EVALUATION

10

• Usually there are more small trees than big trees

• For efficiency, the plot should be larger for big

trees than for small trees

• The same volume estimates by DBH classes

can be get through reducing the number of

measured trees for smaller DBH classes

Nested circular plot

= different radius

according to DBH

Page 11: Improved National Forest Inventory Map sampling design

PLOT SIZE ADJUSTMENT HOW CAN WE DO THIS?

11

7 654 trees

Rectangular plot Subplot size: 20 m x 25 m

Nested circular plot Diameter, cm Plot radius, m 6 .0 – 19.9 6 20.0 – 49.9 12 50.0 – 15

22 481 trees (NFI-4 data)

Tree expansion factor 6.25 1.5625 1

Page 12: Improved National Forest Inventory Map sampling design

B. CORRELOGRAM / SEMIVARIOGRAM

ANALYSES WITH NFI-4 DATA TO COMPARE

EFFICIENCY OF DESIGNS

12

Page 13: Improved National Forest Inventory Map sampling design

ABOUT CLUSTER FORMS

• line, square, triangle, L-shape...

Page 14: Improved National Forest Inventory Map sampling design

Line would be optimal in that sense that the distance between

plots increases plot by plot => the correlation within cluster is

small

However, walking distance from the last plot back to the

vehicle is long

Page 15: Improved National Forest Inventory Map sampling design

SQUARE CLUSTER

Advantage: • If you measure the whole cluster during a day, it is usually easy to move

from the last plot to the vehicle. Disadvantage: • Plots are more correlated than in the line cluster design

Page 16: Improved National Forest Inventory Map sampling design

TRIANGLE CLUSTER

Advantages: • If you measure the whole cluster during the day , it is usually easy

to move from the last plot to the vehicle • Plots are not too correlated • Suitable if you can assume to measure 3 plots per day

Page 17: Improved National Forest Inventory Map sampling design

CORRELOGRAM / SEMIVARIOGRAMS

• General challenges in planning inventory

sampling design

• Avoiding unnecessary walking by locating plots near to

each other => clustering

• Plots close to each other are very similar (same forest

type, almost same volume etc.)

=> Balance between unnecessary walking between

plots and high correlation between plots must be found

=> Correlogram analyses with existing data

17

Page 18: Improved National Forest Inventory Map sampling design

CORRELOGRAMS FOR

BAC KAN AND HA TINH PROVINCES

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Page 19: Improved National Forest Inventory Map sampling design

USE OF CORRELOGRAMS: ESTIMATE SAMPLING

VARIANCES OF DIFFERENT CLUSTER DESIGNS

• estimator of sampling error in random sampling:

• not valid for cluster sampling because plots in a cluster are

correlated, estimator:

• where n = number of plots in a cluster, m=number of clusters

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Page 20: Improved National Forest Inventory Map sampling design

RESULTS FOR DIFFERENT CLUSTER

TYPES IN BAC KAN

Plots

in a

cluster

Cluster

type

Distance

between

plots

Number of

clusters

Sampling error

mean volume,

(m3/ha)

Sampling error

forest area

(%)

4 square 100 meters 100 5.4 9.6

150 meters 100 5.0 8.8

200 meters 100 4.8 8.2

3 triangle 173 (d=100) 100 5.6 9.3

260 (d=150) 100 5.5 8.8

346 (d=200) 100 5.5 8.2

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Page 21: Improved National Forest Inventory Map sampling design

C. ACCESSIBILITY ANALYSES - GOOGLE

EARTH STUDY

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Page 22: Improved National Forest Inventory Map sampling design

ACCESSIBILITY ANALYSIS

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Questionaire for analysis of accessibility of clusters and plot

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D. IMPROVED SAMPLING DESIGN AND FIELD

TESTS IN BAC KAN PROVINCE

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Page 24: Improved National Forest Inventory Map sampling design

NFI-4 INVENTORY DESIGN AND BAC KAN

PILOT INVENTORY DESIGN

Bac Kan pilot inventory design

• 77 plots (clusters), 907 sub-plots of which 720

are accessible according to GoogleEarth study

NFI-4 inventory design

• 48 plots, 1920 sub-plots

Page 25: Improved National Forest Inventory Map sampling design

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Advantages:

• Team can use the same base camp

for several days

• Less time for travelling

• Less time for administrative

procedures

• Some of the plots can be located in

the same location as the NFI-4 plots

CAMP UNIT DESIGN TO BE TESTED: CLUSTER OF 4 PLOTS AND 12 SUB-PLOTS

1 km

150 m

Cluster of 4 plots and

12 sub-plots

Sub-plot Plot

Page 26: Improved National Forest Inventory Map sampling design

BAC KAN PILOT INVENTORY CLUSTERS

8 km 1 km

150 m

Some plots overlay with NFI-4 plots

Page 27: Improved National Forest Inventory Map sampling design

NEW EQUIPMENT TO BE TESTED

• Simple to use, quicker and easier measurements

• More accurate and reliable measurements

Garmin GPS with topographic maps

TruPulse

Vertex

Page 28: Improved National Forest Inventory Map sampling design

NEW EQUIPMENT TO BE TESTED

TruPulse, laser rangefinder measure:

- distance

- height

- inclination

- calculate horizontal and vertical

distances

Vertex + transponder (ultrasound).

- distance

- height

- slope

- horizontal and vertical distances - some problems have been reported with

environmental sounds (e.g. crickets in

Tasmania) interfering with the sonic pulses.

Aim and shoot!

Page 29: Improved National Forest Inventory Map sampling design

CHALLENGES

• Field manuals and instructions must be clear and simple,

no room for (mis)interpretation

DBH measurement?

Stump diameter? Bamboo’s?

Page 30: Improved National Forest Inventory Map sampling design

E. INFORMATION NEED ANALYSES

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Page 31: Improved National Forest Inventory Map sampling design

INFORMATION NEEDS ANALYSES

• New national and international data requirements emerge

• Reliable, internationally accepted estimates are needed for forested area, land uses and their time-wise changes / trends, volume and growing stock, sequestered carbon (UN REDD+) etc.

• Variables to be measured in improved NFIMAP

• Bio-physical data (quite well known, further analyses needed)

• Socio-economic data (on-going development work)

• Some FG related data (on-going development work)

• National INA Expert (Information Needs Assessment) to be recruited and supporting VNFOREST working group to be established

• To study and analyze information needs of all identified stakeholders

• To summarize, evaluate and prioritize information needs to be included for nationwide NFIMAP proposal by December 2012

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Page 32: Improved National Forest Inventory Map sampling design

F. COMPILATION OF IMPROVED NFIMAP

DESIGN AND METHODOLOGY FOR THE

WHOLE COUNTRY

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Page 33: Improved National Forest Inventory Map sampling design

MAIN DIFFERENCES BETWEEN NFI-4

AND IMPROVED NFI SAMPLING DESIGN

Item NFI-4 Improved NFI

Coverage of sample Forested area only All land uses

Plot (cluster) 40 sub-plots in L-shape Camp unit design, 4 plots

and 12 sub-plots in a cluster

Plot shape Rectangular 20 x 25 m Nested circular with 6,12,15

meter radiuses

Distance between plots 0 (zero) meters 150 meters

Correlation between plots High Low

Ratio of trees measured 100 % 34 %

Sub-plot demarcation in

the field

Concrete pole and GPS-

coordinates for L-shape corner

only

GPS coordinates for each

sub-plot

PSP (Permanent Sample

Plot) demarcation in the

field

Concrete pole and GPS-

coordinates for L-shape corner

only

Metal stick inside ground and

3 reference points for each

PSP-plot

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Page 34: Improved National Forest Inventory Map sampling design

MAIN DIFFERENCES BETWEEN NFI-4

AND IMPROVED NFI SAMPLING DESIGN

Item NFI-4 Improved NFI

Trees outside forest

measured?

No Yes, based on systematic

sampling over all land uses

Dead wood measurement

carried out?

No Yes

Carbon calculations exist? No Yes, using models (litter and soil

excluded from current plan)

Data input, verification and

validation

• Custom made VB 6

tools, standalone

computers only

• Data delivery by mail on

CD-ROM

• OpenFORIS Collect tool

• Remote access via Internet

• Data storage directly on FIPI

server

Result calculations for

national and provincial

levels

• Based on measured

ground sample plots

only

• Manual calculations

• Based on combined use of

ground sample plots and

satellite image interpretation

• OpenFORIS tools

Thematic mapping using

satellite images

No Yes 34

Page 35: Improved National Forest Inventory Map sampling design

NEXT STEPS

• Implementation of pilot inventory in Bac Kan province (Sep - Oct 2012)

• Review or alignment of some variables and attributes (with Vietnamese practices)

• Field manual, attributes to be measured, time study, equipment, materials, human resources, field forms, planning of data entry

• Collected data is utilized in further analysis and improvement of sampling design (autumn 2012)

• Measurement cost: time study is part of Bac kan pilot

• Stratification: measurement costs + land use map

• Sampling simulation with multisource forest map

• Develop data input, validation and processing tools for the test data set using FAO and METLA Open Source Tools

• Final proposal for nationwide improved NFIMAP design by the end of 2012

Page 36: Improved National Forest Inventory Map sampling design

THANK YOU!

14.11.2011 36