European Organization for Experimental ... - Host Ireland

• To perform a cost benefit analysis of using High Resolution Sensor imagery versus conventional
methods.
• To investigate the maturity of software system products to exploit automatic land use
classification from High Resolution Sensor imagery.
Three submissions were received for Work Package 4 – one final report, one interim report
and one slide presentation. Each of these is reproduced as an annexe.
3.4.2 A summary of the Work Package 4 report by Peter Atkinson and Isabel Sargent,
University of Southampton (Annexe 5)
This report concentrated on the imagery of the Chandlers Ford area of the UK. It utilised
structured large-scale polygon data (the forerunner of OS MasterMap) supplied by the Ordnance
Survey. The objective was to classify the area to the CORINE specification. The
study found that the OS MasterMap data is already classified to some extent and that a large
proportion of CORINE classifications could be populated using the information already held
in the large-scale polygon data at attribute level. Notwithstanding this conclusion, a classification
of a small subset of the IKONOS imagery was performed, using a maximum likelihood
classifier. Four classes were identified (woodland, smooth grass, rough grass and bare
soil) and the image was classified on a per-pixel basis. The classified pixels were then analysed
on a per-parcel basis; in which each OS MasterMap polygon was assigned the modal
class of all the pixels it contained. In a separate experiment the mean spectral values within
each polygon were used to perform a direct per-parcel classification. Interestingly, these two
methods gave different results – especially when differentiating between rough and smooth
grassland.
The report concludes that a combination of OS MasterMap data and IKONOS imagery could
be used to identify most of the CORINE classes, with the possible exception of ‘mineral
extraction sites’, ‘vineyards’ and ‘pastures’.
3.4.3 A summary of the work package 4 report by Peter Lohmann et al, University of
Hannover - (Annexe 6)
This submission was in the form of a slide presentation, which is reproduced at Annexe 6.
The study concentrated on the multispectral image of the Chandlers Ford area, using ERDAS
Imagine and Definiens eCognition software. Use was made of the OS LandPlan 1:10 000
scale raster data and land use data provided by Hampshire County Council (although it was
noted that this was not based on a CORINE classification). The high resolution of the imagery
was found to introduce new aspects not normally found in multispectral satellite imagery.
One of these is the presence of shadows in the image, which can be used to identify
larger buildings and trees. A second aspect of the high resolution imagery is the heterogeneity
of the image - each land parcel may be made up of several different classes, which would
have been averaged out in lower resolution imagery. The use of the CORINE classification
itself was found to be problematic, in that it caters for usage types of natural objects (e.g.
“sport and leisure facilities”) rather than the land cover types (e.g. “grassland”) which can be
determined from the imagery. This was especially the case in urban areas (Annexe 6.2).
The resolution of the imagery was not sufficient to differentiate buildings and streets within
a housing area – it is suggested that the 1m panchromatic imagery would be useful for this.
The report concluded that, while high resolution imagery has the potential to permit detailed
classification, new techniques need to be developed to aid the classification process.
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