Pilot Project National Forest Inventory (NFI)

in Suriname

Cayenne, 28 – 29 April 2014

2009: • COP15; • Meetings

between Suriname and Austria.

2010: • Technical meetings between

SBB and Austria; • Austrian fact finding mission

to Suriname; • Introduction and technical

NFI workshop in Suriname.

2012: • Introduction pilot NFI; • MOU signing; • 1st collection aerial images; • Workshop NFI; • 2nd collection aerial images pilot NFI; • Aerial image interpretation in

Austria; • Preparations pilot NFI.

2013 - 2014: • Training of field teams; • Collecting field data for the

30 SU’s (finished in April 2014);

• Data processing, analysis, reporting and evaluation of pilot NFI;

• Planning and implementation of the NFI.

SU Sampling Unit

Timeline

Approach to the NFI Situation in Suriname:

• Remoteness of most of the forests (especially south of Suriname);

• Difficult access and high costs of field sampling; • Limited number of personnel; • Little is known about the variability of forest

stocking conditions across the country’s forest types.

Approach to the NFI

Approach Multisource Sampling Design:

Aerial and Terrestrial Inventory.

• Systematic sampling design (grid) of 20x20km covering the entire country;

• Every grid intersection is a Sampling Unit (SU);

• Pilot NFI: 6 flight lines (North – South);

• Flight lines overlay the GRID lines;

• Aerial images collected with ADAMC;

• Pilot NFI: Field data collection in 30 SU‘s.

Collection of aerial images

• Period: September 2012

• Amount: ± 22000 ortho images (9TB data)

• ADAMC : Special camera georeferenced aerial images

Accuracy ~ 15 cm on elevation of 1000m

Mounted on any cessna

No ground control points needed for georeference

Aerial images can be processed to:

4 band NIR/RGB ortho-photo’s

Ortho-photo mosaics

3D landcover models and Digital Surface

Models (RSG/ 3D GIS software)

Problems during aerial images collection

• Cloudcover.

Aerial image interpretation

• Flight elevation => ± 750m;

• Interpretation is done in Aerial Sampling Units (SUa) of 750x750m;

• SUa is fully covered by aerial images.

750m

75

0m

750m

75

0m

Aerial image interpretation Sources of information:

• CBL (topographic) maps;

• Reconnaissance soil map of Northern Suriname (DBK, 1977);

• Ecosystems of the coastal plain (P.A. Teunissen, 1978);

• Forest cover map of Suriname (Ministry RGB, 2010);

• SRTM data;

• Inventory data (if available);

• Field experience.

Aerial image interpretation

Aerial image interpretation

Mutual criteria for image interpretation (related to determination of forest definition):

• Minimum Mapping Unit (MMU) of 1 ha;

• Minimum crown coverage to classify an area as forest is 30%;

• Minimum vegetation height to classify an area as forest 5m.

Interpretation is being done:

• By using the 2D ortho-photo’s;

• In some cases by using 3D ortho-photo’s (useful to see elevation differences between classes of forest and non-forest);

• Or DSM’s (can be used to help determine the delineation between the several forest types).

• Result => SUa is classified according to forest/ non-forest, forest type and stocking class.

Aerial image interpretation

Collection of Field data • Field data is collected during ground truthing in Field Sampling Units (SUf);

• Field data will be used to try and establish a relationship between aerial photo

parameters and timber stocks, AGB etc.

Design of the SUf:

8 Principal Sample Plots (PSP’s) =>100mx20m = 0,2ha p/PSP

Each PSP is divided in 20 Main Assessment Plots (MAP’s) => 10mx10m

Within 2 standard MAP’s per PSP are 2 subplots => 5mx5m

SUa

SUf

PSP

18

Field parameters collected

• Finding the exact location of the center point of the SUf;

• The time lapse between the moment of aerial image acquisition and field data collection sometimes resulted in a changed crown cover due to natural causes (windbreak) or other activities (new roads, forestry activities, mining, etc.) in the area;

• Strengthen community consultation and awareness;

• Physical establishment of outer border of the plots is necessary;

• Tree height estimations- estimation of 1 or 2 tree heights;

• More standardization for tree species determination is needed.

Lessons learnt during pilot NFI project

• GPS

• Maps

• Ortho photos

Determination of exact location in the field

• Finalization and evaluation of the Pilot project (data processing, analysis and reporting)

• Preparations towards the complete NFI: • Formulate project proposal (Country support within ONF REDD+ project) • Fundraising activities • Evaluation of methodology

• Stratification • Plot design • Use of multisource data

• Necessary preparations before complete NFI • Standardization of tree species recognition; • Forest type classification system (with interpretation key for RS and field) • Allometric equations • Awareness and communication program especially for forest based communities • Evaluation of registered field parameters after consultation with stakeholders (towards a multipurpose

NFI)

• Implementation of the NFI

Next steps

• Establishment and/ or evaluation of allometric equations: • Creation of a regional database

• Exchange of methods implemented in the various countries (incl. capacity building component)

• Joint publications or scientific research

• Exchange on tree species determination • Photo database

• Protocol for collection of plant material

• Field guide and protocol for tree species determination

• Exchange between the approaches within the region

• Regional platform for botanists and tree spotters

Ideas for regional collaboration