1. NTTS 2011 Brussels February 22, 20111 Joint Research Centre (JRC) Sampling Very High Resolution Images for Area Estimation Javier.gallego@jrc.ec.europa.eu

2. 2 Spatial Statistics 2011 Univ. Twente 24 March 2011 Why sampling satellite images Very large areas Global studies Tropical deforestation Continents Small images Covering a medium-size country with Very High Resolution Images

3. 3 Spatial Statistics 2011 Univ. Twente 24 March 2011 Geoland2-SATCHMO Geoland2: large FP7-GMES project >50 partners Covers a wide range of topics in terrestrial monitoring, mainly in Europe The target is mainly building pre-operational tools SATCHMO: One of the Geoland2 “Core Mapping Services” More research-oriented than the rest of Geoland2 Aim of SATCHMO-AFS (Area Frame Sample): One of the components of SATCHMO assessing the use of a sample of Very High Resolution (1- 4 m) images for land cover (or change) area estimation Sampling units 10 x 10 km to 50 x 50 were assessed, but at the end 10 x 10 km units were imposed by image availability.

4. 4 Spatial Statistics 2011 Univ. Twente 24 March 2011 SATCHMO-AFS Stratification Strata 1: Cyprus and Malta. N=94 2: above 1200 m (>50%). N=1376 3: Euroland “transects”. N=1165 4: coastal areas (buffer 10km). N=3954 5: Urban atlas. N=4676 0: all the rest. N=31613 Most strata are determined by commitments with Euroland and LUCAS. Not a proper statistical criterion (priorities insufficiently clear)

5. 5 Spatial Statistics 2011 Univ. Twente 24 March 2011 SATCHMO-AFS Sample Systematic on blocks of 200x200 km Replicates selected with distance constraints To avoid that two replicates are too close to each other Number of replicates depends on the stratum

6. 6 Spatial Statistics 2011 Univ. Twente 24 March 2011 Land cover map vs sample CORINE Land Cover (no sampling) LUCAS: sample of points (field survey) Sample of VHR images Sampling error Non-sampling error NoneMediumHigh HighMediumLow Expected errors (to be checked…) ?

7. 7 Spatial Statistics 2011 Univ. Twente 24 March 2011 Comparing sampling errors Usual criterion: comparing variances of two different sampling schemes for the same cost. But the cost of samples of VHR images has a too wide variability. Alternative indicator: “equivalent number of points”: Example: if a sample of 4000 unclustered points gives the same variance as 200 sites (clusters) of 10x10 km we say that a site is equivalent to 20 points.

8. 8 Spatial Statistics 2011 Univ. Twente 24 March 2011 Using CORINE Land Cover as pseudo-truth % area cv 200 points (%) cv 200 sites 10 km (%) equivalent number of points/site artificial4.6532.012.36.8 arable28.6411.26.92.6 perm crops2.9240.821.93.5 pastures12.3118.99.73.8 heterogeneous11.9719.27.66.4 total agriculture43.538.14.82.8 forest and woodland26.6411.76.53.2 bare1.2962.033.83.4 other vegetation3.4637.418.14.3

9. 9 Spatial Statistics 2011 Univ. Twente 24 March 2011 Using a land cover map as pseudo-truth Is the comparison fair when we use a (coarse resolution) land cover map as pseudo-truth? Coarse resolution Lower within-site variance Points in the site appear more redundant than they are Smaller equivalent number of points than using fine scale information

10. 10 Spatial Statistics 2011 Univ. Twente 24 March 2011 Variance in single-stage cluster sampling For a sample of n clusters out of N, with M elementary units in each cluster. intra-cluster correlation if n is large and n/N is small if M (cluster size) is also large True in our case

11. 11 Spatial Statistics 2011 Univ. Twente 24 March 2011 Equivalent number of points The “equivalent number of points” can be approximated from the intra-cluster correlation that quantifies the link between nearby points (in the same cluster) Also the correlogram measures the link between nearby points Any link?

12. 12 Spatial Statistics 2011 Univ. Twente 24 March 2011 Correlogram and Intra-cluster correlation The correlogram at distance d is estimated by: The intra-cluster correlation is a weighted average of the correlogram: Thus we can approximately compute the “equivalent number of points” from the correlogram.

13. 13 Spatial Statistics 2011 Univ. Twente 24 March 2011 Correlogram Arable land

14. 14 Spatial Statistics 2011 Univ. Twente 24 March 2011 Correlogram interpolation An exponential model gives a good adjustment to the behaviour of most correlograms (other models might be better) The adjusted correlogram is used to estimate the Intra-cluster correlation and the “equivalent number of points”

15. 15 Spatial Statistics 2011 Univ. Twente 24 March 2011 Wheat and Sunflower

16. 16 Spatial Statistics 2011 Univ. Twente 24 March 2011 Intracluster correlations Intracluster correlation Site sizeArable CLCArable LUCASWheatSunflower 5km0.540.420.200.14 10km0.460.360.170.12 20km0.390.300.130.09 30km0.350.270.120.08 equivalent number of points 5km1.92.45.07.0 10km2.22.76.08.6 20km2.63.37.511.1 30km2.83.88.613.0

17. 17 Spatial Statistics 2011 Univ. Twente 24 March 2011 Some cost considerations The average field survey cost per point in LUCAS ranges between 20 € and 25 €. The equivalent number of points per site of 10x10 km ranges between 2 and 10 for major land cover types.  The cost per VHR image (including processing) should be at most 250 € to be cost-efficient in the EU from the point of view of sampling error.  Bad news for the use of VHR images in the for area estimation in the EU, at least from a marketing perspective

18. 18 Spatial Statistics 2011 Univ. Twente 24 March 2011 Better news Land cover change is more scattered than land cover status Lower spatial correlation Higher equivalent number of points per site Better chances to be cost-efficient For sites of 10x10 km (coarse resolution) % area cv 200 points (%) cv 200 sites 10 km (%) equivalent number of points/site New artificial0.27136.721.839.6 New agriculture0.15183.534.728.3 Agricultural abandonment0.21154.625.238 Other changes1.6454.815.612.5

19. 19 Spatial Statistics 2011 Univ. Twente 24 March 2011 Remote areas Tropical rainforest Siberia Countries with restricted access (North Korea…) The cost of a point survey has nothing to do with the cost of LUCAS. Correlograms? The assessment can change a lot from case to case.

20. 20 Spatial Statistics 2011 Univ. Twente 24 March 2011 Stratification The equivalent number of points changes with stratification To which extent?

21. 21 Spatial Statistics 2011 Univ. Twente 24 March 2011 Stratification based on GLC2000

22. 22 Spatial Statistics 2011 Univ. Twente 24 March 2011 Stratification The correlogram in each stratum is lower than the non- stratified correlogram  Higher equivalent number of points

23. 23 Spatial Statistics 2011 Univ. Twente 24 March 2011 Stratification But not always uniformly lower than the correlogram in each stratum

24. 24 Spatial Statistics 2011 Univ. Twente 24 March 2011 Equivalent number of points stratum equiv n. points0123456 No strata Arable coarse5.74.03.63.34.33.42.92.0 Arable10.15.36.55.17.15.65.02.5 Forest coarse3.12.42.93.3 4.42.8 Forest2.92.63.13.53.73.95.72.7 Vineyard coarse194.012.63.12.72.86.42.32.5 Vineyard52.013.410.66.66.010.23.7 Wheat26.49.611.411.912.09.26.24.7 Sunflowe r>100 68.4>1009.616.410.15.8