spatial sampling strategy

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Spatial sampling strategy MODIRISK

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Spatial sampling strategy. MODIRISK. Basis for sampling strategy. Grid of 10X10 km = 326 cells Three samples per grid cell = 978 samples Take into consideration: Major biotopes Seasonal variation Import risk. Proposed procedure. - PowerPoint PPT Presentation

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Page 1: Spatial sampling strategy

Spatial sampling strategyMODIRISK

Page 2: Spatial sampling strategy

MODIRISK Kick-off-meeting

Basis for sampling strategyBasis for sampling strategy

Grid of 10X10 km = 326 cells

Three samples per grid cell = 978 samples

Take into consideration:→ Major biotopes→ Seasonal variation→ Import risk

Grid of 10X10 km = 326 cells

Three samples per grid cell = 978 samples

Take into consideration:→ Major biotopes→ Seasonal variation→ Import risk

Page 3: Spatial sampling strategy

MODIRISK Kick-off-meeting

Proposed procedureProposed procedure

Identify key habitats based on Corine LC classes by aggregating urban, agriculture, natural and import risk classes.

Calculate total surface per aggregated class

Assign proportional number of sample points to aggregated class.

Generate appropriate number of random sampling points within each class.

Randomly assign sampling points within each class to two sampling seasons.

Geocode and assign sample sites per team.

Identify key habitats based on Corine LC classes by aggregating urban, agriculture, natural and import risk classes.

Calculate total surface per aggregated class

Assign proportional number of sample points to aggregated class.

Generate appropriate number of random sampling points within each class.

Randomly assign sampling points within each class to two sampling seasons.

Geocode and assign sample sites per team.

Page 4: Spatial sampling strategy

MODIRISK Kick-off-meeting

Aggregation of CORINE LC dataAggregation of CORINE LC data

CORINE includes 50 classes divided in five groups:→ Artificial surfaces including

urban and industrial→ Agriculture areas→ Forest and semi natural

areas→ Wetlands→ Water bodies

CORINE includes 50 classes divided in five groups:→ Artificial surfaces including

urban and industrial→ Agriculture areas→ Forest and semi natural

areas→ Wetlands→ Water bodies

Page 5: Spatial sampling strategy

MODIRISK Kick-off-meeting

Corine data – 50 classesCorine data – 50 classes

Page 6: Spatial sampling strategy

MODIRISK Kick-off-meeting

Class aggregationClass aggregation

(1) Urban biotopes

(2) Land in the agriculture cycle

(3) Natural terrestrial habitats

(4) Risk of introduction areas: ports, airports, dump sites, moors and heat land, inland marshes, salt marshes

(5) Areas excluded from sample: industrial and commercial units, roads, mines and mineral extraction sites, construction sites, sparsely vegetated areas

(6) Water bodies

(1) Urban biotopes

(2) Land in the agriculture cycle

(3) Natural terrestrial habitats

(4) Risk of introduction areas: ports, airports, dump sites, moors and heat land, inland marshes, salt marshes

(5) Areas excluded from sample: industrial and commercial units, roads, mines and mineral extraction sites, construction sites, sparsely vegetated areas

(6) Water bodies

Page 7: Spatial sampling strategy

MODIRISK Kick-off-meeting

Corine - 6 aggregated classesCorine - 6 aggregated classes

Page 8: Spatial sampling strategy

MODIRISK Kick-off-meeting

Sample size per aggregated class

Sample size per aggregated class

Class Pixels Percentage Samples

Urban 769,723 17.7% 173

Agriculture 2,514,104 57.7% 564

Natural 888,272 20.4% 199

Specific 56,479 1.3% 13

Secondary 103,411 2.4% 23

Water bodies 28,285 0.6% 6

TOTAL 4,360,274 100.0% 978

In blue = automated random assignment

In red = manual attribution in selected areas

In blue = automated random assignment

In red = manual attribution in selected areas

Page 9: Spatial sampling strategy

MODIRISK Kick-off-meeting

173 random urban sampling points173 random urban sampling points

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Page 10: Spatial sampling strategy

MODIRISK Kick-off-meeting

564 random agri sampling points564 random agri sampling points

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Page 11: Spatial sampling strategy

MODIRISK Kick-off-meeting

199 random natural sampling points199 random natural sampling points

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Page 12: Spatial sampling strategy

MODIRISK Kick-off-meeting

Non-random sampling pointsNon-random sampling points

Not yet included in map

42 sampling points to be allocated in areas representing a particular risk of introduction: ports, airports, dump sites, moors and heat land, inland marshes, salt marshes.

Additional samplings should also be conducted in other selected areas:→ Zoos and safari parks (list available)→ Second hand tire import/storage (list to

be established)→ Protected areas involving presence of

large numbers of migratory birds (list available)

Not yet included in map

42 sampling points to be allocated in areas representing a particular risk of introduction: ports, airports, dump sites, moors and heat land, inland marshes, salt marshes.

Additional samplings should also be conducted in other selected areas:→ Zoos and safari parks (list available)→ Second hand tire import/storage (list to

be established)→ Protected areas involving presence of

large numbers of migratory birds (list available)

Page 13: Spatial sampling strategy

MODIRISK Kick-off-meeting

Sample: institute / year / seasonSample: institute / year / season

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Page 14: Spatial sampling strategy

MODIRISK Kick-off-meeting

Sample per instituteSample per institute

Rough division by province:→ ITG (274 + 42): Antwerp,

Limburg, Brabant→ KBIN (293): Oost

Vlaanderen, West Vlaanderen, Brabant

→ UCL (365): Hainaut, Namur, Luxembourg

Needs reassessment !!!

Rough division by province:→ ITG (274 + 42): Antwerp,

Limburg, Brabant→ KBIN (293): Oost

Vlaanderen, West Vlaanderen, Brabant

→ UCL (365): Hainaut, Namur, Luxembourg

Needs reassessment !!!

Page 15: Spatial sampling strategy

MODIRISK Kick-off-meeting

Data baseData base

Flexibility to re-allocate sampling areas

Geocode random sampling points to nearest relevant feature to ease sampling: road access, street names, house numbers, …

UTM numbering grid cells according to standard

Flexibility to re-allocate sampling areas

Geocode random sampling points to nearest relevant feature to ease sampling: road access, street names, house numbers, …

UTM numbering grid cells according to standard

Page 16: Spatial sampling strategy

MODIRISK Kick-off-meeting

Web based MODIRISK survey map

Web based MODIRISK survey map

Online map (Google map) with status of field survey per team

Public access: important dissemination purpose because most urban samples will be conducted in house gardens

Link to entomological data base future link with biodiversity data base

Password protected centralized data entry using Palmtop:→ Field forms→ Entomology forms→ Cross check forms

Generate addresses in urban areas to contact prior to sampling

Online map (Google map) with status of field survey per team

Public access: important dissemination purpose because most urban samples will be conducted in house gardens

Link to entomological data base future link with biodiversity data base

Password protected centralized data entry using Palmtop:→ Field forms→ Entomology forms→ Cross check forms

Generate addresses in urban areas to contact prior to sampling