[GB001601] EUNIS habitats from the NatureScot "Points to polygon" project - extracted from GeMS

This dataset can be described as a collection of predictive habitat maps covering several different Scottish SAC's and MPA's, classified to EUNIS and extracted from the GeMS database (v24_1).

Alternate title: GB001601

Date (Creation): 2019-05-15

Citation identifier: 5877d808-3fd7-11eb-b378-0242ac130002

Point of contact

Organisation name	Individual name	Electronic mail address	Role
MyOrganisation		info@my-organisation.eu	Owner

GEMET - INSPIRE themes, version 1.0

GEMET - Concepts, version 4.1.3

Access constraints: Other restrictions

Other constraints: no limitations to public access

Use constraints: Other restrictions

Other constraints: Available under the Creative Commons Attribution (CC-BY) License v4.0

Spatial representation type: Vector

Denominator: 50000

Language: English

Topic category

Biota
Oceans

Begin date: 2019-04-29

Reference system identifier: http://www.opengis.net/def/crs/EPSG/0/3857

Distribution format

Name	Version
ESRI Shapefile	1.0
GML	3.2.1

OnLine resource

Protocol	Linkage	Name
OGC:WFS-1.0.0-http-get-capabilities	https://ows.emodnet-seabedhabitats.eu/geoserver/emodnet_open_maplibrary/wfs?service=wfs&version=1.0.0&request=GetFeature&typeNames=EU000000	WFS GetFeature request for downloading the data set related to Land Use
WWW:LINK-1.0-http--link	https://files.emodnet-seabedhabitats.eu/data/EMODnetSBHsurvey_GB001601.zip	EMODnet Seabed Habitats download

Hierarchy level: Dataset

Conformance result

Date (Publication): 2010-12-08

Explanation: This data set is conformant with the INSPIRE Implementing Rules for the interoperability of spatial data sets and services

Pass: Yes

Statement: Individual maps within the dataset were produced differently on a site-by-site basis, depending on:

1) The best available data, which include; sample point data, aerial imagery, acoustic data and physical parameter data layers

2) The predictive modelling technique applied, including; statistical modelling, imagery classification and rule-based modelling

Therefore, predictive mapping outputs produced GIS polygon data range for a range of features across the sites, at varying scales, and to different degrees of confidence

For further details, please read Report 980:

https://www.nature.scot/naturescot-commissioned-report-980-predictive-mapping-seabed-features-within-selected-special-areas

Metadata

File identifier: 67e212c1-bd02-42fb-a550-a6efd61513dd XML

Metadata language: English

Character set: UTF8

Hierarchy level: Dataset

Date stamp: 2021-11-29T16:54:14

Metadata author

Organisation name	Individual name	Electronic mail address	Role
MyOrganisation		info@my-organisation.eu	Point of contact

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