1. Technical guidance for grid based provision of data for MSFD reporting
Dr. Lidija Globevnik
Dunja Vrenko Zupan
Institute for Water of the Republic of Slovenia
TC VODE - Thematic center for Water
(ETC ICM Water)
Event/ date:
Copenhagen, MFSD - WG DIKE; 1

2. Purpose of the document
Guidance document to support reporting of MFSD spatial data
Presentation of basic concepts and definitions of grid based spatial data as developed and used in Europe
Description of methods for data manipulation

3. MSFD reporting in 2012 Reporting under Articles 8,9,10
Data related to MarineUnitID/Region/SubRegion/SubDivision/AssessmentArea
Data connected to geographical Assessment Area - different feature classes:
Point, Line, Polygon (irregular, regular: grid cells)
Most used grid cells are square cells

4. Example of national data - Land use
1 KM GRID_ETRS89-LAEA

5. Data handling methodology
Aggregation is the process of grouping spatial data at a level of detail or resolution that is coarser than the level at which the data were collected.
Disaggregation is the breakdown of observations, usually within a common branch of a hierarchy, to a more detailed level to that at which detailed observations are taken.
Spatial disaggregation or downscaling is the process by which information at a coarse spatial scale is translated to finer scales while maintaining consistency with the original dataset.

6. Reporting based on grid system
Advantages
Easy use in spatial analysis
Usage of square grid cells
Grid-based “statistics” is independent of administrative borders
Disadvantages
Problems with harmonization and integration of national and European grid systems – direct transformation not possible
Re-projecting national grids into an European projection system may distort the formerly square grid cells
MSs as a data producer should have the source data (original data) in a format different from grid. For grid-based purposes the developed methodology for creating grid based data should be prepared. When Member States use grid system in national coordinate system and prepare data for European level in European grid system the pre-prepared system for both types of coordinate systems will manage to do the appropriate output.

7. Aggregation methods for polygon and point data
For transformation from small cells to large cells in a different grid system or to polygons (geographic units), simple methods, such as adding small cells with the centre inside the new cell or polygon, or simple areal weighting (allocation proportional to area) are acceptable.
POLYGON DATA
MAXIMUM AREA CRITERIA (uncountable variables)
PROPORTIONAL CALCULATION
PROPORTIONAL AND WEIGHTED CALCULATION (countable variables)
POINT DATA
AVERAGE OF ORIGINAL VALUE
MEDIAN ORIGINAL VALUE

8. Disaggregation methods for polygon data
Whenever it is possible PROPORTIONAL AND WEIGHTED CALCULATION should be used to disaggregate the data, as it gives an added value to the source data, providing more interesting results when different data are put together on a cell-by-cell basis.
Other methods:
SIMPLE AREA WEIGHTING (should be avoided)
MASK AREA WEIGHTING
DASYMETRIC DISAGGREGATION
STOCHASTIC ALLOCATION

9. PROPORTIONAL AND WEIGHTED CALCULATION
Cell value = Wc Σ ( Vi * Sharei )
Where: Vi = Value of unit i
Sharei = Share of unit i within the cell
Wc = weight assigned to cell c
In the example: Wc * (V1 * V2 * 0.15)
the cell takes also a proportionally calculated value, but this value is weighted for each cell, according to an external variable (e.g. population)
Proposed for countable variables

10. MAXIMUM AREA CRITERIA
Cell takes the value of the unit which covers most of the cell area
Proposed for uncountable variables

11. Examples of national data & considerations
1 km grid_ETRS89-LAEA
Examples of national data & considerations

12. Grid design from polygon and point data (number of inhabitants)
count
intersect V1 V2 V3

13. Protected areas – points/polygons

14. Habitat status – midlittoral and infralittoral (5 classes)

15. Aggregation methods for point data:
Three types of distribution of point features: random, uniform and clustered.
Median of original value is the middle occuring value of all points selected to be aggregated.
Average of original value is the average value of all the points selected to be aggregated. In case of grid cells means all values of points on the selected grid cell.

16. Status in regard to Chlorophyll a (5 classes)