time series – spatial information espon workshop, 6 th may 2010 oscar gomez, eea
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Time series – spatial information
ESPON workshop, 6th May 2010Oscar Gomez, EEA
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My understanding of time series and GIS
• Traditional GIS does not consider time dimension miss dynamics of some phenomena
• Time dimension is important in:– Administrative boundaries– Land cover/land use– Population– Hydrology– Vegetation/crops– Wildlife
• On the EEA side, this is secured in land cover with land cover changes layers
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Example: hydro systems• Our context:
ECRINS hydro database
• Drainage doesn’t change with our time scale (*)
• Continental water dynamics
(*) except in the case of canals
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Spatial information and time• Our context: CORINE Land Cover• 1:100.000, EEA MSs + collaborating countries geographic
extents, with exceptions• Homogeneous across participating countries• 1990, 2000, 2006, with exceptions• 39 countries CLC2000-2006• LC snapshots + LC changes• Many datasets derived spatial disaggregation generally
depends on CLC + something else• PHARE 1975 – 1990 LC Bulgaria, Hungary, Romania,
Slovakia, Czech Republic• LACOAST 1975 – 1990 coastal LC: EU15 (except UK, LU)
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Exchange of data
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CORINE Land Cover• Co-ownership EEA/Communities and Member States,
data flow control• They are modified only to harmonize borders• Problem: time span in 2010 we have 2006 data• GLOBCorine (ESA): from GLOBCover (medium
resolution), trained with CORINE GlobCorine– Better geographic coverage– Nowcasting– Less classes– Less certainty about individual changes– 2006 done, 2009 before summer (ESA)
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GlobCORINE
•Urban and associated areas•Rainfed cropland•Irrigated cropland•Forest•Heathland and sclerophyllous vegetation•Grassland•Sparsely vegetated area•Vegetated low-lying areas on regularly flooded soil•Bare areas•Complex cropland•Mosaic cropland / natural vegetation•Mosaic of natural (herbaceous, shrub, tree) vegetation•Water bodies•Permanent snow and ice•No data (burnt areas, clouds,…)
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Land cover and HANTS(EVI 2006)Salting (Bosplaat, Terschelling)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Urban (Amsterdam)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Grassland (Friesland)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Deciduous forest (Harderbos, Flevopolder)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Drifting sand (Veluwe)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Pine forest (Veluwe)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Agriculture (Flevoland)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Grain cultivation (Dollard, Groningen)
0
0.2
0.4
0.6
0.8
1
1 7 13 19
16-days-NDVI-composites
ND
VI
original
HANTS fitted
Red; medium, Green; medium, Blue; high
Red; medium, Green; high, Blue; medium
Red; high, Green; low, Blue; low
Red; low, Green; low, Blue; lowRed; high, Green; high, Blue; low
Red; medium, Green; high, Blue; low
Red; high, Green; low, Blue; medium
Red; low, Green; medium, Blue; low
Red = average NDVIGreen = Annual AmplitudeBlue = Six months Amplitude
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Water quantity
• Run-off data• No data flow established• Based on the good willingness of MSs• The data flow is being defined
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Spatial dimension
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Land cover – and derived
• Neighbourhood: yes, on analysis; for example, green landscape outside cities
• Spatial disaggregation: Not directly us (by now), mainly the JRC:– Population density– Agro-land use: AFOLU crops, livestock
• Spatial aggregation: used constantly; OLAP cubes
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Livestock density EU27
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Water drainage (ECRINS)
• Interpolation of climate data (rainfall, temperature) “spatial disaggregation”
• Spatial aggregation: to the catchment level
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Time dimension
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Time dimension
• Water: climate data is always spatially interpolated data; extrapolation: IPCC scenarios, forecast
• Land cover: no interpolation; extrapolation: land use modelling (JRC: MOLAND, LUMOCAP)
• Need for time-dimensioned GIS layers: i.e. transport networks, protected areas, ... start_date, end_date fields!
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Trends in the coast: 1975 to 2006 (30 years of changes)
•Artificialisation has a constant growth rate: 0.5% relative increase each year
•Water bodies were created in 1975-2000
•Agriculture shows a constant decline•Wetlands and forest and semi-natural decreased heavily (around 10%) in 1975-1990; it has slowed down
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Trends 1990 – 2000 – 2006 (*)
(*) 100% = status in 1990; the lines show the relative increase (trend) for the 2 periods, 1990-2000, 2000-2006
• Urbanisation: same trend, above 0.5% yearly increase• Forest and semi-natural are stable• Wetlands don’t disappear as quickly as in the previous period; strong trend change (from 0.22% yearly loss to 0.06% yearly loss)• Water bodies are created at a slower pace (0.19% yearly increase to 0.08%)