European Organization for Experimental ... - Host Ireland

2.4.6 Tracks.
The alignment of tracks was very easy to capture, but problems arose when trying to differentiate
between tracks and small metalled roads.
2.4.7 Vegetation.
General vegetation was easy to depict although the actual nature of the vegetation is not
easy to identify. This imagery would be suitable for mapping at scales ranging from 1:2500
to 1:50,000.
2.4.8 Forestry limits.
These were very easy to capture. Species and type of tree were a little more difficult to
determine. However, it is possible to distinguish between wholly coniferous or wholly nonconiferous
areas, indicating that this imagery would be suitable for 1:10,000 scales mapping
and smaller.
2.4.9 Electricity poles / pylons.
Actual poles are difficult to identify, but the identification is greatly helped by shadows
caused by the shallow sun angle. Pylons are a bit easier to identify. However, in both types
the actual electricity lines cannot be seen, thus making the alignment of the whole line
through the image quite difficult to follow.
Pylons and alignment could be captured for 1:10,000 mapping and smaller, while electricity
poles would require field completion/verification
2.4.10 Water detail.
Lakes and ponds were easily identified and captured. Lakes would be acceptable for
1:10,000 mapping and smaller. Small ponds would require confirmation on the ground.
The capture process would be helped using multispectral or pan-sharpened imagery.
2.4.11 Rivers and streams.
Rivers are quite easy to detect, but smaller streams are difficult to differentiate from paths.
Multispectral, or pan-sharpened, imagery would make this task easier. It is also difficult to
determine the width of a stream; and it is thought that stereo imagery would help in this
process. The capture of rivers from this imagery would be acceptable for 1:10,000 mapping
and smaller, but streams would require field completion to get a true picture of the topographic
feature.
2.5 Comment on results
The identification of all of the features considered in this research would be improved
greatly if stereo imagery was used. Previous studies at the Ordnance Survey (Ridley et al.
1997), analysing sub-sampled 1m aerial imagery, concluded that stereo imagery would
increase identification by 20%. Although stereo data was not available for this project,
stereo IKONOS imagery was viewed by kind permission of Professor Dowman at UCL, and
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