EMODNet Confidence

EMODNet Confidence Assessment

• Aims– To produce an easy, yet meaningful visual

assessment of confidence for the EMODNet substrate map

– Employ a simple, transferable methodology– Ability to integrate confidence maps from all

partners into a single output

EMODnet Confidence v1• Data gap analysis – confidence level based on the

amount/type of data available. • A high density of data infers a greater confidence• Numerical score. Low to high confidence 1-8• Created in ESRI ArcMap Grid format. Easy to combine

all partners map outputs. Need Spatial Analyst extension

• Easy if you hold all samples/survey tracks in a digital format (ESRI). Issues for legacy mapping

EMODnet Confidence v1

• Scoring System

An unique grid is created for each of the following:– Sample Density. Point density function in Spatial Analyst used to

assign a score– Geophysical Survey Tracks. Convert track line to grid and assign

score based on equipment type– Multibeam. Convert extent to grid and assign a score.– Legacy data/Expert Interpretation

Final confidence map = sum of all grids

EnglandEngland

NiedersachsenNiedersachsen

PomorskiePomorskie

ZachodniopomorskieZachodniopomorskie

BrandenburgBrandenburg

Mecklenburg-VorpommernMecklenburg-Vorpommern

Schleswig-HolsteinSchleswig-Holstein

WielkopolskieWielkopolskie

Kujawsko-PomorskieKujawsko-Pomorskie

Vármlands LänVármlands Län

Sachsen-AnhaltSachsen-Anhalt

ScotlandScotland

Warminsko-MarzurskieWarminsko-Marzurskie

Sweden

PolandGermany

Norway

Denmark

United Kingdom Netherlands

Poland

Germany

Sweden

Norway

United Kingdom

Ireland

France

Latvia

Lithuania

Ukraine

Estonia

Belarus

Finland

Czech Republic

Belgium

Slovakia

Russia

Denmark

Netherlands

Poland

Germany

Sweden

Norway

United Kingdom

Ireland

France

Latvia

Lithuania

Ukraine

Estonia

Belarus

Finland

Czech Republic

Belgium

Slovakia

Russia

Denmark

Netherlands

Poland

Germany

Sweden

Norway

United Kingdom

Ireland

France

Latvia

Lithuania

Ukraine

Estonia

Belarus

Finland

Czech Republic

Belgium

Slovakia

Russia

Denmark

Netherlands

Re-Iterative Process

V1

V2

Final Version

JNCC – 3 step confidence assessment for habitat mappingSimplify MESH 15 classes into only 3 criteria. Remote sensing coverage, Amount of Sampling, Distinctness of Class boundaries.

BMBR_Grabs

EUNIS_subs

coarse sediment

mud and sandy mud

BMBR_20130712_BroadscaleHabitatTypes_v1

BSH_EUNIS

A4.2 Moderate Energy Circalittoral Rock

A5.1 Subtidal Coarse Sediment

A5.2 Subtidal Sand

A5.3 Subtidal Mud

A5.4 Subtidal Mixed Sediment

A5.5 Subtidal Macrophyte Dominated Sediment

A5.6 Subtidal Biogenic Reef

What method to use

• EMODNet V1 – Data gap analysis• JNCC – 3 step approach• OR a combination of the 2 – to be developed.