8/12/2015
1
¼ Century GIS
and RS in Fiji
Forestry
NOA VAKACEGU, MSD-FORESTRY
1991 Establishment of
GIS&RS in MSD Forestry
PC with 400 MB hard disk, the biggest
computer in Government !
Digitising table
Tape drive
GPS …… (did not work under canopy)
ERDAS software
ArcInfo software (not utilised at this time)
One laptop with 40 MB hard disk
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2
Forest Inventory Fiji
Tracking and Data Relay Satellite System TDRSS
High amount of scenes recorded and stitched within 2
years to cover Fiji, EOSAT provider (not all recovered !)
Supervised image classification with DTM involvement
Image classification carried out in Europe not in Fiji
Forest Function
Map 1991/92
Raster data GIS application
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Lessons Learned:
Supervised classification difficult in
Pacific volcanic islands due to
atmospheric conditions
Supervised classification must be
performed with field knowledge in
the country
DTM 1:10,000
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Logging Maps
scale 1:10,000
road network
creeks
contour lines
ridges
areas of slope > 32 degree
Field Data Capture
1996 Hardwood
Plantation Mapping
MSD Forestry 1996
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Lessons learned
DTM creation went very well, more DTMs at
1:10,000 scale than ever before in Fiji
Hardwood plantation survey was not
accepted as the legal system did not
recognise GPS
System could not be maintained as no funds
available for hardware maintenance
No funds available to train the second
photogrammetric specialist
No more DTM establishment at MSD ……
Chain of Custody ITTO
Project 1999
Define origin of timber when exporting to
other countries
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Spatial Display
Timber available in sawmills
Log Tagging for
Identification
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Chain of custody
Transport
Arrival at Sawmill
Into Saw Gate
Exported
Scaling
SQL Server
MSD
Application for Export
License
Felling
Sawn timber
One Central Database
at MSD Forestry
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Update of Database
Tables at MSD-Forestry
DFO-South
DFO-North
DFO-West
MSD-Forestry
SQL-Server 7.0
Lessons learned
ITTO used Fiji as an example in newsletter
and poster world wide
Project died
No acceptance by most sawmills
No funds for phone bills
No funds for tags
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National Forest Inventory
2006, GIZ funded
Automatic classification pre-condition
Landsat data from 2001 as Landsat 7 died
Reduction from 3 forest densities to 2
Best Fit of Classes,
Unsupervised Classification
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Haze
Different thresholds
Only Natural Forest
Plantation
Mangroves
None forest
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Lessons learned
Unsupervised classification has more
possibilities for interaction than supervised
Mask building helped
Atmospheric problems required visual
interpretation to create reasonable results
Rate of Deforestation
GIZ funded 2009
Overlay of
forest map created 1991,
forest map created 2006 with image data
2001
Forest map created with data recorded 2007
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Visual Interpretation
Forest layers created in 1991 and in 2006
had to be revised
Multi layer interpretation (i) normal colour,
(ii) false colour IR, (iii) vegetation index
Lessons learned
1991 forest layer and 2001 forest layer had
to be re-established
Geometric accuracy problems between
image data from different periods and Fiji
map basis
Unclear definition of plantations
Deforestation is low in Fiji most timber
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Forest Mapping 1:10,000
Start as visual interpretation with
atmospherically corrected image data
Visual interpretation at 1:10,000 too slow,
move back to semi automatic classification
Separation of semi dense and dense forest
possible by applying object based
classification software (eCognition)
Cooperation between Forestry and
Agriculture
Outlook: Mapping
Degradation of Forest
Investigation mapping secondary vegetation
as indicator for forest degradation
Investigation mapping logging tracks with
multiple free data sources (Landsat,
Sentinel)
Investigation mapping logging tracks with
high resolution radar data
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Thanks
