# load dependencies
## geospatial data handling
library(rgdal)
library(raster)
library(sp)
library(mapdata)
library(maptools)
library(ncdf4)
## general data handling
library(XML)
library(dplyr)
library(tidyr)
library(reshape2)
library(downloader)
## plotting
library(directlabels)
library(rasterVis)
library(ggplot2)
## for display reasons
library(knitr)
library(IRdisplay)
library(repr)
options(repr.plot.wdith=6, repr.plot.height=8)
Loading required package: sp rgdal: version: 1.4-4, (SVN revision 833) Geospatial Data Abstraction Library extensions to R successfully loaded Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20 Path to GDAL shared files: /usr/share/gdal/2.2 GDAL binary built with GEOS: TRUE Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493] Path to PROJ.4 shared files: (autodetected) Linking to sp version: 1.3-1 Loading required package: maps Checking rgeos availability: FALSE Note: when rgeos is not available, polygon geometry computations in maptools depend on gpclib, which has a restricted licence. It is disabled by default; to enable gpclib, type gpclibPermit() Registered S3 methods overwritten by 'tibble': method from format.tbl pillar print.tbl pillar Attaching package: ‘dplyr’ The following objects are masked from ‘package:raster’: intersect, select, union The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union Attaching package: ‘tidyr’ The following object is masked from ‘package:raster’: extract Attaching package: ‘reshape2’ The following object is masked from ‘package:tidyr’: smiths Loading required package: lattice Loading required package: latticeExtra Loading required package: RColorBrewer Attaching package: ‘ggplot2’ The following object is masked from ‘package:latticeExtra’: layer
During the second part of the tutorial, we focus on the "Estuaires picards et mer d'Opale" Marine Protected Area (MPA) in France. We download the outline of this MPA in GeoJSON format from the EMODnet Human Activities Nationally Designated Areas dataset, using the Web Feature Service (WFS), and filtering on the MPA's ID number (555559631) which we get from the link above. Below the WFS will be explained in more detail.
# construct the WFS request
con <- paste("https://ows.emodnet-humanactivities.eu/wfs?service=WFS",
"request=GetFeature",
"typeNames=emodnet:cddaareas",
"SRSName=EPSG:4326",
"outputFormat=json",
"cql_filter=cddaid=555559631",
sep = "&")
# read it into R
mpa <-readOGR(dsn=con,layer = 'OGRGeoJSON')
# get the spatial extent of the MPA
xmin <- extent(mpa)@xmin
ymin <- extent(mpa)@ymin
xmax <- extent(mpa)@xmax
ymax <- extent(mpa)@ymax
OGR data source with driver: GeoJSON Source: "https://ows.emodnet-humanactivities.eu/wfs?service=WFS&request=GetFeature&typeNames=emodnet:cddaareas&SRSName=EPSG:4326&outputFormat=json&cql_filter=cddaid=555559631", layer: "OGRGeoJSON" with 1 features It has 35 fields
We make some maps to show the location of the MPA.
# Localisation at global scale
map("worldHires",col="light grey",fill=T)
points(coordinates(mpa),cex=2,col="blue",pch="+")
title(paste("Region of interest ",
"( W-Lon",round(xmin,2),
"S-Lat",round(ymin,2),
"E-Lon",round(xmax,2),
"N-Lat",round(ymax,2),")"),cex=.5)
# Localisation at local scale
plot(mpa,xlim=c(xmin-1,xmax+1),ylim=c(ymin-1,ymax+1),axes=T,col="red")
map("worldHires",add=T,col="light grey",fill=T)
plot(mpa,add=T,col="blue")
title(paste("MPA",mpa$ORIG_NAME),cex=.5)
We again extract the bathymetry using the function defined in part 1 of this tutorial.
# Define a function to read in raster data from the EMODnet bathymetry WCS
getbathymetry<-function (name = "emodnet:mean", xmin = 15, xmax = 20.5, ymin = 30, ymax = 32.5){
bbox <- paste(xmin, ymin, xmax, ymax, sep = ",")
con <- paste("https://ows.emodnet-bathymetry.eu/wcs?service=wcs&version=1.0.0&request=getcoverage&coverage=",
name,"&crs=EPSG:4326&BBOX=", bbox,
"&format=image/tiff&interpolation=nearest&resx=0.00208333&resy=0.00208333", sep = "")
print(con)
stop
nomfich <- paste(name, "img.tiff", sep = "_")
nomfich <- tempfile(nomfich)
download(con, nomfich, quiet = TRUE, mode = "wb")
img <- raster(nomfich)
img <- -1*img # reverse the scale (below sea level = positive)
img[img == 0] <- NA
img[img < 0] <- 0
names(img) <- paste(name)
return(img)
}
# get the bathymetry data for the MPA
bathy_img <- getbathymetry(name = "emodnet:mean", xmin, xmax, ymin, ymax)
bathy <- as.data.frame(as(bathy_img, "SpatialPixelsDataFrame"))
[1] "https://ows.emodnet-bathymetry.eu/wcs?service=wcs&version=1.0.0&request=getcoverage&coverage=emodnet:mean&crs=EPSG:4326&BBOX=0.78521945,50.05172857,1.688691,50.81768059&format=image/tiff&interpolation=nearest&resx=0.00208333&resy=0.00208333"
Using the EMODnet biology WFS we can get the zooplankton abundances for different grid cells within the MPA (bbox). To calculate statistics of the abundance data over a particular period and a particular season, we can download it as a geoJSON file.
# set the request parameters
reg.name = 36317
spec.name = 'Acartia_spp'
trend_start = 2004
trend_end = 2013
season.code = 1
bbox <- paste(xmin, ymin, xmax, ymax, sep = ",")
type.name='Emodnetbio:OOPS_products_vliz'
# build the WFS URL
url<-"http://geo.vliz.be/geoserver/Emodnetbio/ows?service=WFS&version=1.0.0&request=GetFeature&outputFormat=json"
full_url<-paste(url,"&viewParams=;startYearCollection:",trend_start,";mrgid:",reg.name,";scientificName:",spec.name,";season:",season.code,"&typeName=",type.name,"&BBOX=",bbox,sep="")
# get the data as a geoJSON file
library("rjson")
json_data <- fromJSON(file=full_url)
# to display the file
# str(json_data)
# to save
# geojson_write(json_data, file = 'MyJson.geojson') #bogue ?
test<-json_data[['features']]
mean=0
l<- length(test)
for (i in 1:l){
tests<-test[[l]]
mean<-mean+tests$properties$measurementValue
}
mean_value_season1<-mean/l
mean_value_season1
We can also visualise the extent of the zooplankton abundance grid cell by downloading the data as a zipped shapefile and plotting it on a map.
# build the WFS URL
url<-"http://geo.vliz.be/geoserver/Emodnetbio/ows?service=WFS&version=1.0.0&request=GetFeature&outputFormat=shape-zip"
full_url<-paste(url,"&viewParams=;startYearCollection:",trend_start,";mrgid:",reg.name,";scientificName:",spec.name,";season:",season.code,"&typeName=",type.name,"&BBOX=",bbox,sep="")
# get the data as a zipped shapefile
download(full_url, dest="shapefile.zip", mode="wb")
unzip("shapefile.zip", overwrite = TRUE)
OOPS_products <- readOGR(dsn = ".", layer = "OOPS_products_vlizPolygon")
# plot on a map
map<-ggplot()+
theme_bw()+
theme(panel.grid.minor.y= element_blank(), panel.grid.minor.x = element_blank())+
geom_raster(data=bathy,aes(x=x,y=y,fill=emodnet.mean),alpha=.75)+
scale_fill_gradient(low = "white", high = "darkblue",name="Depth (m)")+
geom_polygon(data=OOPS_products,aes(x=long,y=lat,group=group, fill="OOPS_products"),colour="green",fill="blue",alpha=.1)+
coord_quickmap(xlim=range(xmin,xmax),ylim=range(ymin,ymax))+
ggtitle("OOPS_products polygons")+xlab("Longitude")+ylab("Latitude")
plot(map)
# export to a shapefile which can then be visualised in e.g. QGIS
writeOGR(OOPS_products,"OOPS_products","OOPS_products_bbox",driver="ESRI Shapefile",overwrite_layer = TRUE)
OGR data source with driver: ESRI Shapefile Source: "/home/jovyan/R-tutorial", layer: "OOPS_products_vlizPolygon" with 62 features It has 10 fields
Regions defined for each Polygons
Alternatively, we can also download the zooplankton abundance grid cell as geoJSON.
# function to read GeoJSON
getgeojson<-function(name="Emodnetbio:OOPS_products_vliz",xmin=-1,xmax=1,ymin=49,ymax=50){
reg.name = 36317 #label="Greater North Sea"
trend_start = 1958 #startDate
trend_end = 2013 #endDate
spec.name = 'Acartia_spp'
trend_start = 2004
trend_end = 2013
season.code = 1
bbox<-paste(xmin,ymin,xmax,ymax,sep=",")
url<-"http://geo.vliz.be/geoserver/Emodnetbio/ows?service=WFS&version=1.0.0&request=GetFeature&outputFormat=json"
con<-paste(url,"&viewParams=;startYearCollection:",trend_start,";mrgid:",reg.name,";scientificName:",spec.name,";season:",season.code,"&typeName=",name,"&BBOX=",bbox,sep="")
print(con)
temp <- tempfile()
download(con,temp)
ogrInfo(dsn=temp)
layer<-readOGR(dsn=temp)
return(layer)
}
OOPS_products<-getgeojson(name="Emodnetbio:OOPS_products_vliz",xmin,xmax,ymin,ymax)
map <- ggplot()+
theme_bw()+
theme(panel.grid.minor.y= element_blank(), panel.grid.minor.x = element_blank()) +
geom_raster(data=bathy,aes(x=x,y=y,fill=emodnet.mean),alpha=.75) +
scale_fill_gradient(low = "white", high = "darkblue",name="Depth (m)") +
geom_polygon(data=OOPS_products,aes(x=long,y=lat,group=group,fill="OOPS_products"),colour="green",fill="blue",alpha=.1) +
coord_quickmap(xlim=range(xmin,xmax),ylim=range(ymin,ymax)) +
ggtitle("OOPS_products polygons")+xlab("Longitude")+ylab("Latitude")
plot(map)
[1] "http://geo.vliz.be/geoserver/Emodnetbio/ows?service=WFS&version=1.0.0&request=GetFeature&outputFormat=json&viewParams=;startYearCollection:2004;mrgid:36317;scientificName:Acartia_spp;season:1&typeName=Emodnetbio:OOPS_products_vliz&BBOX=0.78521945,50.05172857,1.688691,50.81768059" OGR data source with driver: GeoJSON Source: "/tmp/RtmpcBHPv7/file14a39871eb5", layer: "file14a39871eb5" with 62 features It has 12 fields, of which 1 list fields
Regions defined for each Polygons
Using WFS, we can also access the zooplankton abundance time series as a csv file.
# determine parameters
reg.name = 36317 #label="Greater North Sea"
spec.name = 'Acartia_spp' #species
trend_start = 1958 #startDate
trend_end = 2013 #endDate
# construct WFS url
mainurl<-"http://geo.vliz.be/geoserver/Emodnetbio/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=Emodnetbio:OOPS_summaries&outputFormat=csv&SQL_FILTER=startYearCollection-endYearCollection=0"
fullurl<-paste(mainurl,"ANDscientificName='",spec.name,"'ANDmrgid=",reg.name,sep="")
# get the data
datans <- read.csv(file= fullurl, header=TRUE)
We now analyse the time series seasonality and trends using the stl()
loess seasonal decomposition function.
levels(datans$scientificName)[levels(datans$scientificName)=="RatioLS copepods"] <- "Large/Small copepod ratio"
seldata<-datans[with(datans, order(datans$startYearCollection,datans$season)),]
# convert to a time series object
tscf<-ts(data=seldata$avg_ab, start=trend_start, end=trend_end, frequency=4)
# decompose the time series
fitstl<-stl(tscf,s.window="periodic",t.window=15)
plot(fitstl)
Using the EMODnet Catalogue Service for the Web (CSW), we can query and search collections of metadata for data, services and information objects related to the EMODnet Marine Data. In the example below, we use the XML
package to send a request to the CSW endpoint, parse the XML response and store it in a dataframe. We use the OGC filter property to select only records whose type is 'dataset'.
# CSW request
con = paste("https://emodnet.ec.europa.eu/geonetwork/emodnet/eng/csw?SERVICE=CSW",
"REQUEST=GetRecords",
"VERSION=2.0.2",
"ELEMENTSETNAME=summary",
"OUTPUTSCHEMA=http://www.opengis.net/cat/csw/2.0.2",
"CONSTRAINTLANGUAGE=FILTER",
"CONSTRAINT_LANGUAGE_VERSION=1.1.0",
"RESULTTYPE=results",
"TYPENAMES=csw:Record",
"maxRecords=300", #limit the output
paste0("CONSTRAINT=", #following xml snippet described the filter to be applied, i.e. type=dataset
URLencode('<ogc:Filter xmlns:ogc="http://www.opengis.net/ogc">
<ogc:PropertyIsEqualTo>
<ogc:PropertyName>dc:type</ogc:PropertyName>
<ogc:Literal>dataset</ogc:Literal>
</ogc:PropertyIsEqualTo>
</ogc:Filter>')),
sep="&")
download(con,"cswrequest.xml", mode = "wb")
# get and parse response to a dataframe
response = xmlParse("cswrequest.xml")
response = xmlToList(response)
results = data.frame()
for(record in response$SearchResults[names(response$SearchResults) == "SummaryRecord"]){
# cast to datafame, negating empty fields
df = as.data.frame(Filter(Negate(is.null),record), stringsAsFactors = FALSE)
# combine multiple subjects into 1 column
if(sum(grepl("subject",names(df))) > 1){
df = unite(df,"subject",contains("subject"), sep = ", ", remove = TRUE)
}
# combine multiple formats into 1 column
if(sum(grepl("format",names(df))) > 1){
df = unite(df,"format",contains("format"), sep = ", ", remove = TRUE)
}
results = bind_rows(results,df)
}
Now that we have all the records stored in a dataframe, we can perform detailed queries.
# look for Records with keyword 'Habitat'
results %>% filter(grepl("Habitat",results$subject))
identifier | title | type | subject | format | abstract | modified | relation |
---|---|---|---|---|---|---|---|
<chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
8f8a9aa2-528b-4494-ab88-74633dfcf446 | EMODnet Human Activities: Protected Areas | dataset | Area management/restriction/regulation zones and reporting units, Land cover, Protected sites, Habitats and biotopes, protected area, natural area, natural areas protection, environment | unknown | The dataset on marine and coastal protected areas in the EU was created in 2014 by Cogea for the European Marine Observation and Data Network. The dataset is entirely based on the European Environmental Agency's (EEA) datasets "Natura 2000" and "Nationally designated areas (CDDA)". Natura 2000 is an ecological network composed of sites designated under the Birds Directive (Special Protection Areas, SPAs) and the Habitats Directive (Sites of Community Importance, SCIs, and Special Areas of Conservation, SACs). The Common Database on Designated Areas (CDDA) is more commonly known as Nationally designated areas. The inventory began in 1995 under the CORINE programme of the European Commission. It is now one of the agreed Eionet priority data flows maintained by EEA with support from the European Topic Centre on Biological Diversity. It is a result of an annual data flow through Eionet countries. The EEA publishes the dataset and makes it available to the World Database of Protected Areas (WDPA). The CDDA data can also be queried online in the European Nature Information System (EUNIS). Both EEA's datasets have been filtered by Cogea to show only maritime areas and sites (i.e. areas entirely at sea), and coastal areas and sites(internal areas that intersect and/or are tangent, using 1 km buffer, to the marine regions and subregions geographic boundaries shapefile, available at https://www.eea.europa.eu/data-and-maps/data/msfd-regions-and-subregions). The CDDA dataset cover the whole EU in the case of Natura 2000 data. In the case of CDDA, geographical coverage of GIS vector boundary data is: Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Kosovo under UNSC Resolution 1244/99, Latvia, Liechtenstein, Lithuania, Luxembourg, the former Yugoslav Republic of Macedonia, Malta, Montenegro, the Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland and United Kingdom. For further information please visit EEA's website. Compared with the previous version, this version of includes: update to 'CDDA v14' and 'Natura 2000 End 2016', both published by the EEA in 2017; new fields have been added to CDDA, reporting the lowest possible level code of the Nomenclature of Territorial Units for Statistics (NUTS1, NUTS2 or NUTS3) in which the geographical entity is located, the percentage of the total area of marine ecosystems in the site, the major ecosystem type, additional notes about sites; new fields have beed added to Natura 2000 with area of site (ha), and the percentage of the site considered marine. | 2016-04-13 | NA |
47489848-e54d-4bfa-bbec-c5516273b9f7 | Caratterizzazione bio-ecologica e bionomica del Parco Marino Sommerso di Gaiola | dataset | Habitats and biotopes, Map Files, biota, environment | Shapefile | The research work had the aim to obtain a first quantitative information for the characterization of the macrobenthic communities living in the submarine archaeological park, including necto-benthic fishes, and to perform a bionomic map by GIS methods. | NA | NA |
bcd93384-72f8-4a7e-a1db-903b59247492 | Seabed Habitat (EUNIS) - FR9301998 'Baie de la Ciotat' (Cartham) - FR003034 | dataset | Habitats and biotopes, Natura 2000, Parc naturel marin, Intertidal, Subtidal, Circalittoral, Biocénoses, Observation terrain, Transects plongeur audio, Plongées ponctuelles, Sonar, Bathymétrie, Habitat, Cartographie, France, Méditerranée, Bouches-du-Rhône, Ciotat, benthos, oceans | NA | Seabed habitat map (EUNIS classification system) performed by Andromede Oceanologie within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources : Side scan sonar (2010), bathymetrics (2007), orthophotos (2008), historical maps (2003). Ground truth data sources (2009-2011) : Divers with underwater cameras, direct human observations. Map confidence rated by Ifremer : 87% (Areas with doubtful outlines are mentioned in the "VAL_COMM" field ). | NA | NA |
7edf2f11-b203-4eb5-92e8-e92478e3dc7c | DK003046_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The substrate and nature type mapping was carried out for the Danish Nature Agency in the summer 2012. The survey included habitat classification of Limfjorden, Kattegat and The Belt Sea. This study area is a part of Limfjorden | NA | NA |
7bdbf389-3bf7-46db-97c7-f2ee0093995f | A74-Littoral Biotope Survey and Condition Assessment of the Tamar Tavy & St John's Lake SSSIs 2010 | NA | Eastern Channel, Marine habitat mapping, EUNIS, Habitats and biotopes, Oceanographic geographical features, environment | ESRI Shapefile | A Natural England commissioned verification survey. Littoral biotope survey and condition assessment of the Tamar, Tavy & St John's Lake SSSI. The purpose of the study was to establish a physical and biological baseline dataset to facilitate an assessment of favourable condition status of littoral sediment habitats of the SSSI site, as well as identifying species and biotopes that are representative and/or notable within the Tamar, Tavy & St John's Lake. The study comprised of Phase I and Phase II surveys. Phase I comprised of groundtruthing aerial photography to establish the distribution and extent of intertidal biotopes, interest features and species. Followed by Phase II; detailed descriptions of biotopes present , flora and fauna species list and abundance, as well as sediment characteristics by means of box-core sampling. The data was used to produce a detailed biotope map of the Tamar, Tavy & St John's Lake. | NA | NA |
0d6bfc21-a567-428f-850b-ea8237c4c484 | LongBank_HD_DEF | dataset | Habitats and biotopes, Downloadable Data, biota, environment | Shapefile | This file shows the distribution of the Annex 1 sandwaves in the Long Bank SAC. Habitat mapping is used to help define the area and range parameters for conservation objectives. Site-specific conservation objectives aim to define favourable conservation condition for Habitats Directive Annex I habitats at a site level. | NA | NA |
6804f273-2fb1-409d-832d-049d1bdac152 | Littoral and infralittoral biogenic reefs associated to Crassostrea angulata along the southatlantic spanish coast | NA | Marine Strategy Framework Directive, Marine habitat mapping, Habitats and biotopes, environment | Shapefile | Spatial distribution along the southatlantic spanish coast of the habitat: Littoral and infralittoral biogenic reefs associated to Crassostrea angulata. Study of the spatial distribution of the species by marine demarcations attending the area covered by the species within the Marine Strategy Framework Directive. The cartographic representation of the species is interpreted as one of the indicators proposed by the Commission for the study of the biodiversity of species, habitats and ecosystems. This information is from the Spanish Marine Strategy, belongs to the good environmental condition and initial evaluation of the Marine Southatlantic Demarcation. | NA | NA |
6f78f452-8aa2-4e3f-933b-781b9f88533b | Caratterizzazione bio-ecologica e bionomica del Parco Marino Sommerso di Baia (Fanerogame) | dataset | Habitats and biotopes, Habitats and biotopes, biota, environment | Shapefile | The research work had the aim to obtain a first quantitative information for the characterization of the macrobenthic communities of submarine archaeological park, including those living in the seagrass, and to perform a bionomic map by GIS methods. | NA | NA |
42ac3bd5-9135-4b07-9423-09f485624f5b | Marine habitat mapping within the GR1270010 Natura site (Akrotirio Pyrgos - Ormos Kypsas - Malamo) | NA | Marine habitat mapping, Habitats and biotopes, Protected sites, environment | Shapefile | The description and mapping of marine habitat types according to Annex I of Directive 92/43/EOK (EEC, 1992) and / or the European Nature Information System (EUNIS) in 66 of approximately 300 Greek NATURA 2000 network sites, were the subject of Research Work for the Ministry of Environment Planning and Public Works of Greece. This research project, under the name "Identification and description of habitat types at sites of interest for conservation", lasted from 1999 to 2002 and was carried out by the National Centre for Marine Research (NCMR, renamed as Hellenic Centre for Marine Research - HCMR since 2003) in association with the Institute of Marine Biology of Crete (IBCM, joined to HCMR since 2003), the Aristotle University of Thessaloniki and the Fisheries Research Institute (FRI). The recognition and imprinting of marine habitat types was based on the combined use of aerial photos of scale 1:5000 acquired during the second half of 1999 for the needs of the project, data from the scientific echo sounder Sea-Bed discrimination system "RoxAnn", phytobenthos samples and in situ observations by scuba diving and underwater cameras. Regarding the sampling, hard bottom samplings were carried out using SCUBA diving. The samples were collected on hard substrates mainly in the upper infralittoral zone (30 to 50 cm below the lowest sea level). For the study of the soft bottom habitats, oceanographic cruses were carried out with the IMBC R/V “Filia”, using a Smith McIntyre sediment sampler. | NA | NA |
7d86e10b-104e-4af7-b6c6-87e77784b3af | DK003002_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The Ministry of the Environment requested in 2011 the Consortium GEUS and Orbicon to carry out mapping tasks in the Danish part of the Kattegat and Western Baltic, partly as part of the government's raw material mapping and partly in connection with the implementation of the Marine Strategy Directive. | NA | NA |
ceccf1da-891f-44ec-85a7-b0e76c142e0a | DeepwaterMorphologicalFeatures | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, geoscientificInformation, biota, oceans | Shapefile | Mound features traced from high resolution bathymetric data of the seabed in Ireland's offshore sea area. | NA | NA |
5e247290-6076-48d4-9fe3-93a097f4ae83 | Krieged BroadScale Substrate Map of Fulmar rMCZ | dataset | Habitats and biotopes, Eunis, biota, oceans | ESRI Shapefile | A geostatistical analysis of the data is reported leading to the selection of a linear model of corregionalization for the composition of the sediment, based on the additive log-ratio transformation of data on mud, sand and gravel content. This model is then used for spatial prediction on a 250-m grid. At each grid node a prediction distribution is obtained, conditional on neighbouring data and the selected model. By sampling from this distribution, and backtransforming onto the original compositional simplex of the data, we obtain a conditional expectation for the proportions of sand, gravel and mud at each location, a 95% confidence interval for the value at each node, and the probability that each of the four sediment texture classes that underlie the EUNIS habitat classification is found at the node. | NA | NA |
2e227bc1-2b88-4e89-a0e2-65dac5698f7d | Beachy Head East rMCZ EUNIS habitat map | dataset | Habitats and biotopes, Eunis, biota, oceans | ESRI Shapefile | Updated habitat map resulting from an integrated analysis of the 2012 dedicated survey data for Beachy Head East recommended Marine Conservation Zone (rMCZ). | NA | NA |
d884f4af-6099-4707-a4f3-c63002221264 | North Sea Natura2000 habitats | dataset | Habitats and biotopes, Downloadable Data, biota, environment | Shapefile | Mapping of marine Natura2000 habitats. The mapping campaign was carried out in 2017. | NA | NA |
2b36f66c-449c-41a4-acb0-fc1764c6a042 | DK003056_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The substrate and nature type mapping was carried out for the Danish Nature Agency in the summer 2012. The survey included habitat classification of Limfjorden, Kattegat and The Belts. This study area is a part of Northren Kattegat. | NA | NA |
206fa656-b9eb-4121-b136-31d1444fe8a4 | Solan Bank Annex I habitat map (translated to EUNIS) | NA | Solan Bank, North Sea/Atlantic, Marine habitat mapping, EUNIS, Habitats and biotopes, Oceanographic geographical features, environment | ESRI Shapefile | Annex I habitat map created from data collected on the CEND 11/08 survey to Solan Bank - subsequently translated to EUNIS. Sublittoral sediments defined using acoustic and groundtruth data. Survey Techniques: Kongsberg EM3000D multi beam echosounder; Benthos SIS 1624 towed sidescan sonar; 0.1m2 Hamon grab; Rock dredge; Camera sledge; Drop frame video camera. See JNCC report 430, 2010 for more information. Orthorectified aerial photography used was flown to a scale of 1:5000. Photography was flown at low tide on a spring tide between the months of April and September to ensure maximum vegetation coverage. As a result of this and due to adverse weather conditions over some of the key tidal windows the whole project area was not captured in one block, but flown in stages between 2006 and 2009. Although ground-truthing was undertaken to support and validate the habitat map, not all areas were ground-truthed. | NA | NA |
aa789b9b-35a4-401d-aa78-7c2a59b539d9 | Number of satellite images for each pixel of PAR - Europe-wide | NA | Light, Earth observation, Marine habitat mapping, Habitats and biotopes, environment | GeoTIFF | Raster showing the number of MERIS images that were used to derive PAR values for each pixel. Data was collected by the MERIS satellite between 2005 and 2009 and this layer was created for use in the 2019 EUSeaMap and updated in 2018 in order to cover Iceland and the Barents Sea. Datasets spatial extent covers European Seas including the Azores and Canary Islands, but excluding the eastern Baltic. Created by the EMODnet Seabed Habitats consortium using data from the European Space Agency MERIS instrument. | NA | NA |
13dcc5ca-9463-45c3-83cd-5abda0ea381e | DK003050_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The substrate and nature type mapping was carried out for the Danish Nature Agency in the summer 2012. The survey included habitat classification of Limfjorden, Kattegat and The Belts This study area is a part of Limfjorden | NA | NA |
23e45078-ca1b-457a-b2e1-de2ebc128395 | Marine habitat mapping for the Vatika Bay, Peloponnese, Greece | dataset | Marine habitat mapping, Habitats and biotopes, boundaries | ESRI Shapefile | Mapping of the Vatika Bay seafloor has been conducted in two different periods: in June 2010 and May 2015.The shallow, northern part of the Bay has been mapped in 2010 during the research project "PAVLOPETRI" by means of swath bathymetry (RESON SeaBat 7125 200/400 kHz), side scan sonar (Geoacoustics 100/400 kHz) and pinger (3.5 kHz) subbottom profiler. The deeper seafloor of the Bay has been surveyed in 2015 by means of side scan sonar and chirp subbottom profiling for the purposes of the research project "Environmental Study of Vatika Bay", funded by the Prefecture of Peloponnese. The research vessel "ALKYON" has been used in both cruises. The description of the nature of the seafloor and the habitat mapping has been based mostly on the interpretation of the acoustic-geophysical data and Sentinel-2 satellite imagery, as well as secondarily on the limited sampling performed in the area. | 2015-05-01 | NA |
b4456a6a-ccd7-4a34-90a8-153bd26854ad | Biotope map of Greater Thames Estuary | NA | Southern North Sea, Marine habitat mapping, EUNIS, Habitats and biotopes, environment | ESRI Shapefile | This map was produced as part of the site selection process for the Greater Thames Estuary AoS. It aimed to characterise the habitat features of the AoS, and to identify the areas of Annex I habitat present. | NA | NA |
948455bb-22d3-481a-aeb6-25e7e48a1d62 | EUSeaMap (2019) Broad-Scale Predictive Habitat Map - Oxygen regime (a habitat descriptor) | dataset | Habitats and biotopes, Marine Strategy Framework Directive, Predominant habitats, biota, environment, oceans | Web Mapping Service | Oxygen regime class layer in the Black Sea produced by EMODnet Seabed Habitats as an input layer for the 2019 EUSeaMap broad-scale habitat model. The map of oxygen regime classes was produced using underlying potential density anomaly at the seabed and thresholds derived from statistical analyses or expert judgement on known conditions. Detailed information on the modelling process for the 2016 is found in the EMODnet Seabed Habitats technical report and its appendices (Populus et al, 2017, link in Resources). We are working on an updated report for the 2019 version. | NA | NA |
6ed3bb3855a3a1a652d357f3183cda78 | Haig Fras habitat map - EUNIS and Annex I Reef | dataset | Marine Environmental Data and Information Network, Habitats and biotopes, Habitats and biotopes, Geology, Habitat extent, Habitat characterisation, biota | NA | The result of a multidisciplinary field survey of the Haig Fras SAC which was initiated in January and completed during March/April 2011. The current study was initiated to investigate the extent of Annex I reef habitat at Haig Fras. Cefas and JNCC collected full-coverage multibeam bathymetric and backscatter data and associated ground-truthing data. This data has been analysed to update the extent of the Annex I reef and produce a broadscale habitat map. Seven biotopes were identified from drop camera transects with the predominant biotope characterised by Devonshire cup corals, sponges and crustose communities on wave-exposed circalittoral rock. The broadscale habitat map indicates the presence of four main biotopes; high energy circalittoral rock, moderate energy circalittoral rock, deep circalittoral coarse sediment and deep circalittoral sand. | NA | NA |
c44c9c48-b92c-4a1f-a25e-d6bbfdbc23d0 | 2013 Natural England Verification Survey of Intertidal Sediments within the Stour & Orwell Estuaries rMCZ | NA | Marine habitat mapping, EUNIS, Habitats and biotopes, Oceanographic geographical features, environment | ESRI Shapefile | Aerial imagery and OS mapping was digitised to produce baseline maps of biotope boundaries. The maps were annotated in the field to identify biotopes and boundaries as well as significant features. In addition, intertidal sediment cores were taken at 16 stations (0.01m2 cores 3 replicates at each station) distributed throughout the Cumbria Coast rMCZ at the low, mid and high shore, in order to assess the benthic species present, along with an additional sample for Particle Size Analysis. Samples were sieved over a 0.5mm sieve. Sediment scrape samples were also taken at 4 stations at the midshore for Tributyl tin, heavy metal and organic contaminant analysis. The Phase II quantitative survey of intertidal rocky reefs comprised of 9 quadrat sites per transect with 3 replicate quadrats at each low, mid and upper shore zone or the main biotope present. Percentage cover of species present within each 0.25m2 quadrat was recorded. The methods used for data collection and processing followed protocols and standards for biotope mapping and sampling. MEDIN Data Guideline for sediment sampling by grab or core for benthos. | NA | NA |
FFD58436-7F1E-4E6C-94F0-7D39E041E04F | Zostera marina distribution model - Finland | dataset | Marine habitat mapping, Habitats and biotopes, Downloadable Data, environment | Raster Dataset | Model describes the potential distribution range of Zostera marina in the Finnish coast. Model was produced using extensive data (~140,000 samples) on the Finnish Inventory Programme for Underwater Marine Environment (VELMU). Model was built using Boosted regression trees (BRT), and resulting models describe the probability of detecting a habitat-forming species in a cell. Environmental predictors include for instance (and are not only restricted to): bathymetry, euphotic depth, salinity, substrate, and wave exposure. As more accurate information is gained by diving than from video methods, dive data was used as the primary source for modelling with 75–90% for model training and 10–25% for validation. The secondary source, video data, was used only for species clearly identifiable from videos with additional subsets (25%) from targeted inventories. Dive and video data are limited to rather shallow depths (typically 20–30 m), leading to a situation where there are not enough samples from deep areas (below 50 m). To avoid artefacts in the models, a randomized absence dataset for areas deeper than 50 m was used during the modelling process. These points were used only as absences in macrophytes models, based on the knowledge that macrophytes do not live at such depths in the Baltic Sea due to habitat constraints and lack of light. | NA | NA |
86c5273c-6bf0-4535-8acd-817781503211 | Confidence in below halocline probability values | dataset | Habitats and biotopes, Marine Strategy Framework Directive, Predominant habitats, biota, environment, oceans | Web Mapping Service | Confidence in the below halocline probability layer, produced by DHI, for the EUSeaMap 2019 broad-scale habitat model. Values are on a range from 1 (Low confidence) to 3 (High confidence). Salinity data acquired from DHI hydrographic Model MIKE III (3D baroclinic model for free surface flow), with a resolution of a 5.5 km. Detailed information is found in the EMODnet Seabed Habitats technical report: Populus J. et al 2017. EUSeaMap, a European broad-scale seabed habitat map. Ifremer. http://doi.org/10.13155/49975 | NA | 02a444c8-bd2d-4e15-8e69-806059103760 |
eb12d2e2-9c57-4a27-8985-f3c43f11f174 | Seabed Habitat (EUNIS) - Lot 06 'Pertuis Charentais et Estuaire de la Gironde' (Cartham) - FR003013 | dataset | Habitats and biotopes, Natura 2000, Parc naturel marin, Subtidal, Circalittoral, Infralittoral, Intertidal, France, Atlantique, Golfe de Gascogne, Estuaire de la Gironde, Pertuis charentais, oceans | NA | Seabed habitat map (EUNIS classification system) performed by CREOCEAN, LIENSs, EPOC, GEOTRANSFERT, RE NATURE ENVIRONNEMENT & IODDE within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources: sonar (2011), orthos (2000), historical data (Hamdi et al., 2010; Hily, 1976; Chassé, 1974) Ground truth data sources (2010-2012): hamon grab, sediment dredges, direct human observations Map confidence rated by Ifremer : 88% | NA | NA |
dab8ef30-c604-4117-b8a6-83af617f1fad | Morlaix habitat map - Rebent subtidal | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | This map covers the inshore subtidal zone of the Baie de Morlaix. Several surveys surveys were carried out between 2008-2013: (i) optical remote sensing with bathymetric lidar (operated by Bloom Ltd.) and aerial photography (“Ortholittorale 2000”) in very shallow water, (ii) acoustic tools such as multibeam echosounder, side scan sonar and Roxann acoustic ground detection system. Ground truth data was obtained with underwater video, sediment and fauna grab samples interpreted in the lab for particle size analysis and benthos identification. The habitat classification is EUNIS 2007. Map scale is around 1:20000, with local improvements to1:10000 | NA | NA |
f2f75ee3-4f65-4907-a568-2e7f6076e3b9 | Marine habitat mapping within the GR4340001 Natura site (Imeri kai Agria Gramvoussa - Tigani kai Falasarna - Pontikonisi, Ormos Livadi - Viglia) | NA | Marine habitat mapping, Habitats and biotopes, Protected sites, environment | Shapefile | The description and mapping of marine habitat types according to Annex I of Directive 92/43/EOK (EEC, 1992) and / or the European Nature Information System (EUNIS) in 66 of approximately 300 Greek NATURA 2000 network sites, were the subject of Research Work for the Ministry of Environment Planning and Public Works of Greece. This research project, under the name "Identification and description of habitat types at sites of interest for conservation", lasted from 1999 to 2002 and was carried out by the National Centre for Marine Research (NCMR, renamed as Hellenic Centre for Marine Research - HCMR since 2003) in association with the Institute of Marine Biology of Crete (IBCM, joined to HCMR since 2003), the Aristotle University of Thessaloniki and the Fisheries Research Institute (FRI). The recognition and imprinting of marine habitat types was based on the combined use of aerial photos of scale 1:5000 acquired during the second half of 1999 for the needs of the project, data from the scientific echo sounder Sea-Bed discrimination system "RoxAnn", phytobenthos samples and in situ observations by scuba diving and underwater cameras. Regarding the sampling, hard bottom samplings were carried out using SCUBA diving. The samples were collected on hard substrates mainly in the upper infralittoral zone (30 to 50 cm below the lowest sea level). For the study of the soft bottom habitats, oceanographic cruses were carried out with the IMBC R/V “Filia”, using a Smith McIntyre sediment sampler. | NA | NA |
1D8074FE-49FB-4A60-9A9C-A54EBCF7CB53 | Mytilus trossulus x edulis distribution model - Finland | dataset | Marine habitat mapping, Habitats and biotopes, Downloadable Data, environment | Raster Dataset | Model describes the potential distribution range of Mytilus trossulus x edulisin the Finnish coast. Model was produced using extensive data (~140,000 samples) on the Finnish Inventory Programme for Underwater Marine Environment (VELMU). Model was built using Boosted regression trees (BRT), and resulting models describe the probability of detecting a habitat-forming species in a cell. Environmental predictors include for instance (and are not only restricted to): bathymetry, euphotic depth, salinity, substrate, and wave exposure. As more accurate information is gained by diving than from video methods, dive data was used as the primary source for modelling with 75–90% for model training and 10–25% for validation. The secondary source, video data, was used only for species clearly identifiable from videos with additional subsets (25%) from targeted inventories. Dive and video data are limited to rather shallow depths (typically 20–30 m), leading to a situation where there are not enough samples from deep areas (below 50 m). To avoid artefacts in the models, a randomized absence dataset for areas deeper than 50 m was used during the modelling process. These points were used only as absences in macrophytes models, based on the knowledge that macrophytes do not live at such depths in the Baltic Sea due to habitat constraints and lack of light. | NA | NA |
150e3cd4-3b24-4440-8179-7d48e0283d3f | DK003008_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The Ministry of the Environment requested in 2011 the Consortium GEUS and Orbicon to carry out mapping tasks in the Danish part of the Kattegat and Western Baltic, partly as part of the government's raw material mapping and partly in connection with the implementation of the Marine Strategy Directive. This studyarea covers part of Kattegat | NA | NA |
9292db07-0532-4141-b88b-4570cc11140b | Seabed Habitat (Habitat Directive) - FR9301996 'Cap Ferrat' (Cartham) - FR003049 | dataset | Habitats and biotopes, Natura 2000, Intertidal, Subtidal, Circalittoral, Biocenoses, Observation terrain, Transects plongeur audio, Plongees ponctuelles, Sonar, Bathymetrie, Habitat, Cartographie, France, Mediterranee, Alpes-Maritimes, Cap Ferrat, oceans | NA | Seabed habitat map (Habitat Directiveclassification system) performed by Andromede Oceanologie within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources : Sonar (2012, 2010, 2007), bathymetric datas (2007-2010), orthophotos (2009), historical data (2007), GPS (04/2012, 06/2010). Ground truth data sources (2010-2012) : Diving, sea-viewer. Map confidence rated by Ifremer : 81%. | NA | NA |
ef3966c9-187b-416a-8a74-e0a853f6fcfa | EMODnet Seabed Habitats collated habitat point data | dataset | Habitats and biotopes, Oceanographic geographical features, Eunis, Habitats Directive, Marine Strategy Framework Directive, Groundtruthing, biota, oceans | ESRI Shapefile | Composite data holdings of habitat point data from groundtruthing data in European waters. Data are collated by EMODnet Seabed Habitats partners from a variety of source datasets and conformed and standardised into the portal's Darwin-core compliant schema. Habitats are described in a variety of classification systems, including EUNIS (European Nature Information System), Habitats Directive Annex I, Marine Strategy Framework Directive Benthic Broad Habitats, Regional sea conventions (HELCOM HUB, OSPAR) and local classifcation systems. Sampling methods are standardised to NERC vocabulary server P01 parameters or ICES vocabulary concepts where possible. | NA | NA |
5c41038a-331a-4c5a-b700-f323dee2cbf2 | Marine habitat mapping within the GR1270002 Natura site (Oros Itamos - Sithonia) | NA | Marine habitat mapping, Habitats and biotopes, Protected sites, environment | Shapefile | The description and mapping of marine habitat types according to Annex I of Directive 92/43/EOK (EEC, 1992) and / or the European Nature Information System (EUNIS) in 66 of approximately 300 Greek NATURA 2000 network sites, were the subject of Research Work for the Ministry of Environment Planning and Public Works of Greece. This research project, under the name "Identification and description of habitat types at sites of interest for conservation", lasted from 1999 to 2002 and was carried out by the National Centre for Marine Research (NCMR, renamed as Hellenic Centre for Marine Research - HCMR since 2003) in association with the Institute of Marine Biology of Crete (IBCM, joined to HCMR since 2003), the Aristotle University of Thessaloniki and the Fisheries Research Institute (FRI). The recognition and imprinting of marine habitat types was based on the combined use of aerial photos of scale 1:5000 acquired during the second half of 1999 for the needs of the project, data from the scientific echo sounder Sea-Bed discrimination system "RoxAnn", phytobenthos samples and in situ observations by scuba diving and underwater cameras. Regarding the sampling, hard bottom samplings were carried out using SCUBA diving. The samples were collected on hard substrates mainly in the upper infralittoral zone (30 to 50 cm below the lowest sea level). For the study of the soft bottom habitats, oceanographic cruses were carried out with the IMBC R/V “Filia”, using a Smith McIntyre sediment sampler. | NA | NA |
b9d2e7ea-fd29-4049-a1ce-af4f24018899 | Broadscale habitat (EUNIS level 3) for South Rigg recommended Marine Conservation Zone (rMCZ) | dataset | Habitats and biotopes, Eunis, biota, oceans | ESRI Shapefile | A broadscale habitat map was produced by analysising and interpreting the acoustic and ground truth data collected at South Rigg rMCZ. Acoustic data was used to identify areas of Rock and sediment and groundtruthing data was used to divide the sediment areas into one of the four sediment classes, namely coarse sediment, sand, mud and mixed sediment. These areas were then divided into littoral and subtidal zones and different energy areas (Low, Moderate or High). These classes could then be classified using EUNIS. | 2015-03-09 | NA |
0616f79c-6d64-4365-b704-6b09deb25ad0 | Caratterizzazione bionomica dell’AMP Punta Campanella (Fanerogame) | dataset | Habitats and biotopes, Map Files, biota, environment | Shapefile | Starting from complete surveys by acoustic methods, the research work had the aim to obtain a first quantitative information on the density and distribution of the seagrass beds in the AMP and to perform a bionomic map by GIS methods. | NA | NA |
2cf1e2b1-fa8a-4bcb-9ce6-4c88c929c071 | EUSeaMap (2019) Broad-Scale Predictive Habitat Map - Confidence in classification of substrate type | dataset | Habitats and biotopes, biota, environment, oceans | Web Mapping Service | Confidence in the classification of substrate type in the 2019 EUSeaMap broad-scale predictive habitat map. Values are on a range from 1 (Low confidence) to 3 (High confidence). Substrate type is one of the layers of information used to categorise physical habitat types in EUSeaMap; these layers of information are collectively known as 'habitat descriptors'. The substrate layer confidence was obtained from reclassification and standardisation of the confidence scores associated with each primary layer used to create the Substrate types layer. Detailed information on the modelling process for the 2016 is found in section 2.7.2 of the EMODnet Seabed Habitats technical report and its appendices (Populus et al, 2017, link in Resources). We are working on an updated report for the 2019 version. Created by the EMODnet Seabed Habitats project consortium. | 2017-06-12 | f7d5a168-0097-4437-944e-cc63111d15c6 |
da029dbc-a4de-45c7-9666-ae7e35d93af4 | Celtic Sea Nearshore Habitats | dataset | habitat, biotope, sea, sea bed, sediment, rock, classification, Habitats and biotopes, substrate, oceans, geoscientificInformation, environment | Esri shapefile | Multibeam echosounder data and seabed sampling data acquired during the INFOMAR national seabed mapping programme were the primary sources of data used in the generation of this marine habitat map. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project. | 2013-07-02 | NA |
35bef350-f84b-4be8-b423-7c81b22fe9c9 | Eastern Channel Broadscale Habitat Mapping Project: Aggregate Levy Sustainability Fund (ALSF) | NA | Eunis, Marine habitat mapping, Habitats and biotopes, environment | EMODnet Seabed Habitats | This aim of the project was to provide integrated broadscale habitat maps for an extensive area within the central part of the Eastern English Channel in order to support the sustainable management of offshore resources. The maps integrated geological, geophysical and biological data and interpretations, including new surveys using high resolution geophysical systems, ground truthed with sampling and video. The immediate driver was the discovery of substantial aggregate resources in this area and the requirement to manage the sustainable development of this resource and minimise potential impacts. The results are available in GIS format and may be used by Government, Nature Conservation bodies and the aggregate industry to inform the planning process. It may also be a valuable tool for fisheries management. BGS, CEFAS and JNCC are partners in the project, and MES a sub-contractor. | NA | NA |
f000be57-1eb3-4998-ba2a-d7ea3413d103 | North West Irish Sea Mounds Survey | dataset | Marine, Seabed Habitat Maps, EUNIS, Confidence assessment required, Nature Conservation, Drop camera, Grabs, Multibeam echo sounder, Towed video, biota | Geospatial (vector polygon) | Collaborative survey between JNCC and AFBI to investigate potential Annex I reef areas in the North Channel Peaks. Four survey cruises completed in total to obtain multibeam coverage and biological ground truthing data. Geophysical data was worked up through an MOA between JNCC and AFBI. Biological intepretation and habitat map production created through contracted awarded to AFBI. Final report received June 2007. | NA | NA |
51665c96-4673-489d-9246-e6f74d78c504 | Habitat LIC Sistema de Cañones Submarinos de Avilés | NA | Marine habitat mapping, INDEMARES, LIFE, LIFE+, Instituto Español de Oceanografía, FUNDACIÓN BIODIVERSIDAD, EMODNET, EUSeaMap, Bay of Biscay, Benthos, Bentos, Habitat, Hábitat, Seabed, Fondo marino, Golfo de Vizcaya, Mar Cantábrico, Cantabrian Sea, Habitats and biotopes, Hábitats y biotopos, Protected sites, Lugares protegidos, Species distribution, Distribución de las especies, Rasgos oceanográficos, Geology, Geología, Biology, Biología, environment | Shapefile | This dataset contains the habitats map from the SCI (Site of Community Importance) “Sistema de cañones submarinos de Avilés” (Avilés Canyon System). The Avilés Canyon system is located in the eastern sector of the North Atlantic Ocean, on the continental margin to the north of the Iberian Peninsula. It is structurally a highly complex area, where the continental shelf in the Bay of Biscay is deeply affected by the action of tectonic compression, containing important geomorphological elements; these include: three great submarine canyons, a marginal platform and a tall structural rocky mass. This study was supported by the INDEMARES-LIFE+ Project, EC contract INDEMARES-LIFE+ (07/NAT/E/000732): Inventory and Designation of the Natura 2000 network in marine areas of the Spanish State (www.indemares.es/en). This work was coordinated by the Spanish Institute of Oceanography (IEO, www.ieo.es) and the Biodiversity Foundation (www.fundacion-biodiversidad.es). The interpretation has been made possible thanks to direct and indirect samplings and geophysical data from campaigns INDEMARES (AVILES_0710, AVILES_0410, AVILES_0412-0912). Habitats are classified according to EUNIS nomenclature and the List of Marine Habitats in Spain (LPRE, that it’s classified hierarchically and was completed and published in March 2013). | NA | NA |
c04c0bf4-4bb1-43f2-9854-8748fc46e8e8 | Sublittoral and infralittoral Seagrass beds along the southatlantic spanish coast | NA | Marine Strategy Framework Directive, Marine habitat mapping, Habitats and biotopes, environment | Shapefile | Spatial distribution along the southatlantic spanish coast of the habitat: Sublittoral and infralittoral Seagrass beds. Study of the spatial distribution of the species by marine demarcations attending the area covered by the species within the Marine Strategy Framework Directive. The cartographic representation of the species is interpreted as one of the indicators proposed by the Commission for the study of the biodiversity of species, habitats and ecosystems. This information is from the Spanish Marine Strategy, belongs to the good environmental condition and initial evaluation of the Marine Southatlantic Demarcation. | NA | NA |
f54a299c-697d-429b-ae12-626771296546 | Marine habitat mapping within the GR4210004 Natura site (Kastellorizo kai Nisides Ro kai Strongyli kai Paraktia Thalassia Zoni) | NA | Marine habitat mapping, Habitats and biotopes, Protected sites, environment | Shapefile | The description and mapping of marine habitat types according to Annex I of Directive 92/43/EOK (EEC, 1992) and / or the European Nature Information System (EUNIS) in 66 of approximately 300 Greek NATURA 2000 network sites, were the subject of Research Work for the Ministry of Environment Planning and Public Works of Greece. This research project, under the name "Identification and description of habitat types at sites of interest for conservation", lasted from 1999 to 2002 and was carried out by the National Centre for Marine Research (NCMR, renamed as Hellenic Centre for Marine Research - HCMR since 2003) in association with the Institute of Marine Biology of Crete (IBCM, joined to HCMR since 2003), the Aristotle University of Thessaloniki and the Fisheries Research Institute (FRI). The recognition and imprinting of marine habitat types was based on the combined use of aerial photos of scale 1:5000 acquired during the second half of 1999 for the needs of the project, data from the scientific echo sounder Sea-Bed discrimination system "RoxAnn", phytobenthos samples and in situ observations by scuba diving and underwater cameras. Regarding the sampling, hard bottom samplings were carried out using SCUBA diving. The samples were collected on hard substrates mainly in the upper infralittoral zone (30 to 50 cm below the lowest sea level). For the study of the soft bottom habitats, oceanographic cruses were carried out with the IMBC R/V “Filia”, using a Smith McIntyre sediment sampler. | NA | NA |
3a215926-a7d1-4495-b05d-21cae776ab44 | Seabed Habitat (EUNIS) - FR9400574 'Porto, Scandola, Revellata, Calvi, Calanches de Piana' (Cartham) - FR003057 | dataset | Habitats and biotopes, Natura 2000, Parc naturel marin, Intertidal, Subtidal, Circalittoral, Biocénoses, Observation terrain, Transects plongeur audio, Plongées ponctuelles, Sonar, Bathymétrie, Habitat, Cartographie, France, Méditerranée, Corse, Porto, Scandola, Revellata, Calvi, Calanches de Piana, oceans | NA | Seabed habitat map (EUNIS classification system) performed by Andromede Oceanologie & Stareso within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources: sonar (2010), bathymetry (2010), orthos (2007), historical data (2011, 2001, 1997) Ground truth data sources: none Map confidence rated by Ifremer : 61% | NA | NA |
9e5ebfb6-69ce-4307-8bbd-9d10cb7f686a | DK003047_HabitatsDirective_DEF | dataset | Habitats and biotopes, Downloadable Data, Downloadable Data, biota, geoscientificInformation, oceans | Shapefile | The substrate and nature type mapping was carried out for the Danish Nature Agency in the summer 2012. The survey included habitat classification of Limfjorden, Kattegat and The Belts This studyarea is a part of Limfjorden | NA | NA |
c4a72a72-c3f9-486b-b458-2404922d0a39 | IE003095_OH_DEF | dataset | Habitats and biotopes, Downloadable Data, biota, environment | Shapefile | This file shows the distribution of seabed substrate classes in Dundalk Bay on the northeast coast of Ireland. The map was generated from the interpretation of MBES data and groundtruthed using sediment samples. | NA | NA |
5787a922-a8a5-4dce-b322-de6b0e5c0b21 | Seabed Habitat (EUNIS) - FR9400591 'Plateau de Pertusato, Bonifacio et Iles Lavezzi' (Cartham) - FR003073 | dataset | Habitats and biotopes, Natura 2000, Parc naturel marin, Intertidal, Subtidal, Circalittoral, Biocénoses, Carthographie, France, Méditerranée, Corse, Corse du Sud, oceans | NA | Seabed habitat map (EUNIS classification system) performed by Stareso, Evemar and Sintinelle within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources: sonar (2010-2011), orthos (2010-2011), historical data (Guennoc et al., 2001; Pasqualini, 1997) Ground truth data sources (2002-2012): diving, sea-viewer, direct human observations, ROV Map confidence rated by Ifremer : 87% | NA | NA |
6f1309f0-980b-486a-8d6c-4aab2ed6f5a6 | Seabed Habitat (Typologie des biocenoses de Mediterranee) - FR9402018 'Cap Rossu, Scandola, Pointe de la Revellata, Canyon de Calvi' (Cartham) - FR003063 | dataset | Habitats and biotopes, Natura 2000, Parc naturel marin, Intertidal, Subtidal, Circalittoral, Biocénoses, Observation terrain, Transects plongeur audio, Plongées ponctuelles, Sonar, Bathymétrie, Habitat, Cartographie, France, Méditerranée, Corse, Cap Rossu, Scandola, Pointe de la Revellata, Canyon de Calvi, oceans | NA | Seabed habitat map (Typologie des biocenoses de Mediterranee classification system) performed by Andromede Oceanologie & Stareso within the framework of CARTHAM ("cartographie des habitats marins") project coordinated by the French Biodiversity Agency (Agence française pour la biodiversité, AFB). Digital data sources: sonar (2010), bathymetry (2007), orthos (2009), historical data (2001, 1997) Ground truth data sources: direct human observations (06/2011) Map confidence rated by Ifremer : 87% | NA | NA |
# look for Records with keyword 'substrate'
results %>% filter(grepl("substrate",results$subject))
identifier | title | type | subject | format | abstract | modified | relation |
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<chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> |
da029dbc-a4de-45c7-9666-ae7e35d93af4 | Celtic Sea Nearshore Habitats | dataset | habitat, biotope, sea, sea bed, sediment, rock, classification, Habitats and biotopes, substrate, oceans, geoscientificInformation, environment | Esri shapefile | Multibeam echosounder data and seabed sampling data acquired during the INFOMAR national seabed mapping programme were the primary sources of data used in the generation of this marine habitat map. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project. | 2013-07-02 | NA |