pilot project national forest inventory (nfi) in suriname · pilot project national forest...
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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