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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 34, Part XXX
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
All classes (except coniferous forest) have better result of
correct interpretation in the second cycle. For example Al
Annual agricultural plants has a correct interpretation of 97 %,
but still some classes has a low rate of correct interpretation.
A3 Pasture has a correct interpretation in 73 % of the cases. The
operator often interpret this areas as Al Full cultivated areas (10
%) and A4 Pasture and hay meadows apparently no longer in
use (6 %). The rest (9 %) are placed in several different classes.
The conclusion is that the time of the photo is extremely
important. The area need to be characterised by grazing and
photos from early spring and summer often miss this character.
A4 Pasture and hay meadows apparently no longer in use has a
correct interpretation of 56 %. The interpretation has increased
from 52 % in first cycle. The operator explains this improve-
ment with the possibility of looking at images from two
different dates which makes it easier to understand the
development of the area.
F1 Semi-natural grassland is a class that is considerably
influenced by human activities, but which is not clearly grazed
or cut. The area is usually directly associated with agricultural
land and buildings. Investigation of the material shows that this
area is misinterpreted as A4 Pasture and hay meadows
apparently no longer in use (16 %) and A3 Pasture (11.5 %).
This reflects the difficulties with overgrown area in or out of
use.
F5 Outfield pasture is the class the operators find most
difficulty to interpret. The grazing is not intensive and the
operator needs some signs like high proportion of grass and
herbs, pathways or animals in the terrain. A detailed review
shows that 30 % of the misinterpretation is into the classes A3
Pasture and A4 Pasture and hay meadows apparently no longer
in use, 25 % are misinterpreted as F2 Heats and ridges. As a
follow-up of the poor result the next field work area for
calibrating, the operators will have focus mainly on outfield
pasture.
3. ANALYSES
The monitoring program’s main aim is to ensure a sustainable
use and management of the agricultural landscape. We produce
statistics at both national and regional level. To show the
development of the agricultural landscape and the differences
between the regions in Norway, we use different indicators.
This is an example of visualizing regional differences with a
radar chart.
Lowland districts of Eastern Norway and Trendelag
Figure 1. Lowland districts of Eastern Norway and the county
Troendelag. The red line is the average of the country and the
blue is the condition in these districts. The chart shows that
these districts have more agricultural land than the average of
the country. It is also more built-up area than the country
average.
The Fjords of Nordland and Troms Counties
Agricultural land
Semi-natural grassland Arable field size
Scrub encroachme Number of arable fields
Farms without agriculture "Akerholmer"
Farms without residents Farm ponds
Registered buildings Streams & ditches
Within 100m from roads Grass strips
Figure 2. Fjord districts of the counties Nordland and Troms.
The red line is the average of the country and the blue is the
condition in these districts. The northern district of Norway has
a climate that makes the agricultural land very small. This chart
also shows that there are a lot of farms without agriculture and
without residents. The depopulation is high in these district.
4. CONCLUSIONS
The opportunity to see two images from different dates
covering the same area gives the operator a greater under-
standing of what he / she sees and an better ability to interpret
the land use. The quality of the photos, information of where in
the country the photo is taken and the photo-date is crucial in
order to interpretate the areas correctly.
Field control of photo interpretation is very important to be able
to highlight the uncertainty of the data. The analysis can then
merge classes or pay attention to misinterpretation in a more
correct manner.
References from Other Literature.
Strand, G-H. , Dramstad, W., Engan, G., 2002. The effect of
field experience on the accuracy of identifying
land cover types in aerial photographs. /nternational journal of
Applied Earth Observation and Geoinformation 4 (2002), pp.
137-146.
Engan, G., 2012. 3Q — feltkontroll av flybildetolking for ârene
2004-2008. Skog og landskap, 2012.
Dramstad, W., Fjellstad, W., Puschmann, O., 2003. 3Q -
Tilstandsoverváking og resultatkontroll i jordbrukets
kulturlandskap. NIJOS, Report, 11/03.
http://www.skogoglandskap.no/publikasjon/nj rapport 11 03
