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JRC Place on dd Month YYYY – Event Name 1 Land cover change Objective: estimate land cover changes, in particular between agriculture and non-agriculture.

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Presentation on theme: "JRC Place on dd Month YYYY – Event Name 1 Land cover change Objective: estimate land cover changes, in particular between agriculture and non-agriculture."— Presentation transcript:

1 JRC Place on dd Month YYYY – Event Name 1 Land cover change Objective: estimate land cover changes, in particular between agriculture and non-agriculture classes The best data source at the moment is probably CORINE Land Cover: changes from photo-interpretation but bias of direct estimates from CLC-change is insufficiently known Scale effect (minimum mapping unit) Identification inaccuracy in photo-interpretation. When comparing loss of UAA in France between CLC and TERUTI: difference of 1 to 5 !! Ideal data source: point survey (LUCAS) Two years needed with the same sample (2006 and 2009?) Critical issue: avoiding “pseudo-changes” from location errors or nomenclature interpretation LUCAS 2001-2003 failed producing reasonable land cover change matrices because surveyors in 2003 did not have the information on the 2001 observations. LUCAS 2006 changed sampling plan; it is better than LUCAS 2001-2003 for land cover area estimation, but not for changes.

2 JRC Place on dd Month YYYY – Event Name 2 Land cover change and CLC LUCAS can be used to calibrate the changes derived from CORINE Land Cover (change layer) (used as co-variable) Problems to be tackled: –How to integrate National Statistics in change matrix estimation from LUCAS? –Which grouping of classes is meaningful (ex: soil sealing, abandonment, aforestation, etc.

3 JRC Place on dd Month YYYY – Event Name 3 Land cover change from a sample of images GEOLAND2 Photo-interpretation by point would eliminate the bias generated by the scale First analysis by simulation using CLC-change (1990-2000) as pseudo-truth Sampling errors for units with different size 10 km20 km30 km40 km50 km60 km n350328309292276263 new artificial16.412.711.210.09.6 new agriculture26.118.015.113.512.912.8 Agric. Abandonment19.013.210.99.78.8 other changes11.79.88.98.47.9 Large sites (~50 km) would be more efficient than small sites (~10 km) But this means lower resolution  non sampling errors (photo-interpretation) still to be assessed Sampling errors at equal cost (CV %) Person to contact: javier.gallego@jrc.it


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