The document summarizes a ground truth survey conducted in the Spanish provinces of Córdoba and Málaga. 56 survey points were visited and 58 were surveyed. Photos and recordings were taken at each point. Challenges included steep slopes, dense vegetation, and restricted access. The points were classified according to the ArcFuel system. While 60% were well classified, some points were misclassified due to difficult vegetation to differentiate or outdated data. Improved shrub classification and use of LiDAR data were recommended.

1. Ground truth survey in Spain
D. Caballero
ArcFuel Workshop
Thessaloniki 2013

2. Spanish study area
• Provinces of Córdoba and Málaga,
Andalucía, Spain
• Córdoba is one of the largest provinces in
Spain.
• Both hold forestlands in a rough terrain,
shrublands and agricultural lands

3. Spanish study area

4. Survey points
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LUCAS points (P)
Alternative points (ALT)
Complementary points (PC)
Other review activity (Fotos)

5. Survey points

6. Method
• Geo-tagged pictures
• Recordings and annotations for every
photo set
• GPS antenna linked (BT) to tablet with
OruxMaps and Google Earth (cached)
• Taken 8 pics (N, NE, E, SE, S, SW, W, NW),
Upslope, Dwnslope, Canopy, Ground
• Extra pictures showing the environment

7. Navigation to survey points
Geo-One GPS receiver attached to a Nikon D7000 camera

8. Navigation to survey points

9. Difficulties
• Private properties! Almost no access,
everything with fences!
• Topography, very steep slopes
• Vegetation: dense vegetation with thorns
(Ulex sp)
• Hunting activty (specially at dusk), bullfighting
bulls
• Winter time, short daylight hours
• Look for alternative points, jump fences and a
lot of walking -> reduced performance

11. Survey - Spain
• Poor accessbility -> alternative points of the
same structure
• A total of 56 points, 58 surveyed, one
outside study area (Seville), one missing
information

12. Survey - Spain
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1 EG Broad Scrub
2 EG Broad Open
3 EG Broad Dense
7 EG Conif Scrub
15 EG Mix Dense
19 Shrubs
20 Grasses
24 No fuel
1
5
4
1
2
30
5
4

13. ArcFuel Classification
• Classification of points according ArcFuel
Map: depends on precision and resolution
• Complicated in highly fragmented fuels
• Suggestion: adaptative resolution
(according fuel fragmentation)
• Suggestion: use of LiDAR

15. Classification results
• Good for urban areas, it should be tested in
dense intermix areas (i.e. North of Cordoba
city)
• EG Broad Scrub vs. Open: no so clear the
difference sometimes. Required data on
height (LiDAR)
• In general good classifying dense forests

17. Classification results
• Missing EG Broad Dense for EG Conif Scrub
(PC03A)
• Missing EG Conif Scrub for Shrub! (P4)
• Missing Shrub for EG Broad Dense (PC05A)
• Missing EG Conif Dense for Agrofor (P27)
• Missing EG Mix Dense for EG Broad Dense
(PC38A, PC04A)

18. Classification results
• Good classifying shrubs (80%), but many
different formations and structures
included as shrubs (see comments) Missing
Shrubs for Grasses, Shrubs for Agrofor ->
abandoned lands PC10A, P35ALT, PC35A,
P52ALT
• Missing Grasses for Shrubs, difficult to
differenciate (shrub density) P45, P47ALT

19. Conclusions
• 34 points well classified (60%)
• 3 points very badly classified, wrong or
inconsistent data sources
• 8 points badly classified, difficult to
differentate heights, densities, species
• 11 with reasonable classification,
particularly abandoned agro lands,
outdated data sources (19%)

20. Conclusions
• Need for more information on shrubs
• Design and apply a robust method to
classify shrubs in the understory
• Use of temporal and thematically
consistent data sources
• Use of LiDAR (where available) may help in
future classifications