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Introduction to WG5 onCwRS imagery use and alternatives and
QE5 on claimed rate inside the RPPeter Viskum Jørgensen, FERV and
Birger Faurholt Pedersen, University of Aarhus, DK
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CwRS Imagery use and alternatives• In Denmark DJF at Århus University is responsible for the CwRS and FERV
is responsible for the LPIS updating and LPQA• In 2010 8 zones were selected for CwRS (4 Ikonos, 4 GeoEye)• It was decided to supply some of the VHR imagery with so-called Snapfotos• Furthermore all reference parcels were screened for potential errors by DJF
before June 1, 2010 and the reference parcels were updated by FERV using the 2010 imagery before the CwRS began
• Danish LPIS build on Physical blocks: approx 300.000 RP of 9 ha in avg. • National ortophoto coverage from spring/summer 2010 were also available
via Quick-access, when processed at the contractor from August 2010 and will fully be available late October
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Wiki Cap requirements for LPIS-QAArt. 10.2.5 in the frozen version 19/9 2010 on LPIS-QA
• Quickbird, GeoEye-1 and Worldview-2.
– These sensors are suitable by default for all conditions and are labelled as "prime LPIS QA" sensors.
• IKONOS and Kompsat-2.
– These sensors can be used under certain conditions and are labelled as "secondary LPIS QA" sensors.
• At least with Ikonos alternative solutions might be useful!
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Snapfotos
• Rectified aerial photos • Acquired 7 April 2010• Covering 4 whole CwRS zones + part of two other zones or approx. 3000
km2 in total• 40 cm resolution• Both RGB and CIR• Price “ready to use” approx. 70.000 EUR: 23 EUR/km2• Delivered 23 April 2010 to DJF and FERV • No adjustment of colors and seam lines
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SNAPFOTOS missing adjustments
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”Snap-foto” overall conformanceDQ Sub elements Conformance Quality Level & Tolerance Limits OK
Spatial resolution <= 1m x
Radiometric resolution =>8 bits/channel x
Spectral Resolution Color (natural or color infrared) x
General Image Quality
Lack of defects and artifacts, which could prevent the visual interpretation of the image x
Cloud cover <5-10% x
Overall clipping <0.5% at each tail x
Histogram Peak +/-15% of middle value x
Color balance <2% between min and max value of triplet (x)
Noise Signal to Noise Ratio > 12 for each channel x
ContrastThe coefficient of variation of the image DN values
should be in the range of 10-20% (x)
Geometric accuracy RMSEx <= 2.5 m; RMSEy <= 2.5 m x
Mosaicking
DN valies variation on similar area type not to exceed 10% in average (or 4% between each of the 3
channels) (x)
Mosaicking Geometric mismatches along seam lines (d) <3 pixels x
CompressionLossless (TIF, LZW-TIF) Visually lossless (JPEG2000,
ECW, MrSID) at last stage (storage) x
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SNAPFOTO 7. April 2010
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IKONOS 15. April 2010
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ORTO DDO2008
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Geoeye 15 APRIL 2010
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SNAPPHOTO 7 APRIL 2010
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ORTHO DDO 2008
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Conclusion on use of Snapfotos
• Better than Ikonos• Similar to GeoEye• The missing adjustments of colors, contrast and
seamlines a minor problem• But archive orthophotos are of much better quality
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Other findings on this topic
• Limited information from other MS!• For setting up and updating LPIS Orthophotos are used
in most MS’s. For the ETS Satellite images are used. These 2 sources have a different quality and will lead to different digitized area
• Image quality is not always adequate to perform the ETS
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ETS inspection, example 1
inspection is obstructed due to
oblique image (off nadir)
and/or large tree canopys,
shadows...
LPIS,Copenhagen 2010
Satellite image 2010
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ETS inspection, example from Sweden
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2010-09-23
ETS inspection, example from Sweden
Ortophoto 2008
LPIS,Copenhagen 2010
inspection not obstructed
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What to discuss and clarify on the use of CwRS imagery and alternatives
• In some cases the inspected area is more incorrect than the recorded area. In some cases RP boundaries is delineated better from older images (1-3 years old)
– Solution could be to allow alignment in such cases to be done from older images
• Off-nadir image causes problems. Distortions noticed on several images– Solution could be: Increase quality control of CwRS imagery regarding geo-referencing and
ortho-rectification
• Sometimes it is necessary to use orthopotos form previous years, because trees cover up the border of RP, specially in case of image, which is acquired with low angle. These orthophotos form previous years allow to digitize RP border in the places where it is not well visible in satellite imagery. In some cases the 2010 satellite imagery fit well with other orthophotos, they are not shifted or rotated.
– Solution use older Orthophotos, when 2010 satellite imagery fails to deliver quality?
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QE 5: Claimed rate inside the RP• Values and expectations:
– At least 95 percent of the claimed parcels shall be completely claimed taking into account the last sentence of point 3.5.3 in the discussion paper on “LPIS quality inspection EU requirements and methodology”
• Problems and comments from MS– The threshold is too strict– “Declared area” needs to be clarified– Is it “declared area” or “determined area” (area determined by administrative and on-the-spot
controls)? The problem is that declared area can be bigger than recorded area of RP (this is overdeclaration/overclaim). If we use declared area, we can get result that “ratio of declared area to the maximum eligible area” >100%
– Is the purpose of this quality measure to find the amount of irregular declarations made by farmers (in this case we should use declared area) or the amount on land actually used in RP (in this case we should use determined area)
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Problems with ”Declared vs. Determined area”
• Examples on not applied, but eligible areas within reference parcels. How do we handle these in terms of QE5?
• Farmers might be inaccurate in delineation of the applications. What areas should be compared. The area of the polygon of the single parcels or the area that the farmer has applied in the alpha numeric data?
• How do we handle exceeding areas? – delimitation of the reference parcel or establishing a layer of not applied areas within the reference parcel
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Example from Sweden
Problems with intrepretation
Reference parcel is 3,11 ha and was controlled in OTSCIn 2008
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What should be digitised? 2,14 of 3,11 ha (cereal), whichIs comparable with the southern part1. Grass or ?2. Perm. Grass ”betesmark”?3. Arable land!
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Example from Sweden