A Web App by The Crown Estate for displaying Title and Ownership data for The Crown Estate Coastal Portfolio.

This map represents all current live offshore agreements in English, Welsh and Northern Irish waters. The boundaries are a true reflection of what has been signed in the Agreements for Lease and Lease documents. Much of the agreements data shown in this map is available from the The Crown Estate Open Data portal.

This dataset represents all current offshore minerals mining site agreements in English, Welsh and Northern Irish waters. The boundaries are a true reflection of what has been signed in the Agreements for Lease and Lease documents.

A series of maps describing geological factors relevant to offshore seabed activities. Produced in collaboration with The Crown Estate in 2014. The Bedrock Summary Lithologies dataset is a digital geological map across the bulk of the UK Continental Shelf (UKCS), for areas up to a water depth of 200m, which groups the bedrock lithologies (rock types) into classes based on similar engineering geology characteristics. The map is derived from the 1:250,000 scale digital bedrock map of the UKCS, called DiGRock250k, which is available separately from the BGS. The map was produced in 2014 in collaboration with The Crown Estate as part of a project to assess seabed development opportunities across the UKCS. This map has been released for viewing on the Offshore GeoIndex alongside a series of other offshore geological maps from the BGS.

This layer includes all Crown Land and Properties managed by LINZ which have been identified spatially and can include properties managed by LINZ on behalf of other agencies. The attributes in this dataset are derived from the National Property and Land Information System (NaPALIS), which is a centralised database for all Land Information New Zealand (LINZ) and Department of Conservation (DOC) administered land.

The boundaries of many properties are linked to the applicable Landonline Primary Parcel(s), but in some cases the boundaries may have been drawn in as unsurveyed parcels to varying degrees of accuracy. As such please note that the boundaries are indicative only. The layer excludes any LINZ managed properties which do not have an identified location or extent.

More information on Crown Property can be found under the Crown Property section on the LINZ Website. A subset of Crown Property can be found in the South Island Pastoral Leases layer. A table of Property associations to Primary Parcels is published in the LDS here.

APIs and web services This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services ArcGIS Online map services

A series of maps describing geological factors relevant to offshore seabed activities. Produced in collaboration with The Crown Estate in 2014. The Quaternary Deposits Summary Lithologies dataset is an offshore digital geological map across the bulk of the UK Continental Shelf (UKCS), for areas up to a water depth of 200 m, which groups the deposits into classes based on similar engineering geology characteristics. The map is derived from (unpublished) BGS 1:1,000,000 scale Quaternary digital geological mapping. The map was produced in 2014 in collaboration with The Crown Estate as part of a project to assess seabed development opportunities across the UKCS. This map has been released for viewing on the Offshore GeoIndex alongside a series of other offshore geological maps from the BGS.

This dataset represents all current wave agreements in English, Welsh and Northern Irish waters. The boundaries are a true reflection of what has been signed in the Agreements for Lease and Lease documents.

This dataset represents all current offshore wind farm agreements in pre-planning, planning, construction and operational phases in English, Welsh and Northern Irish waters. The boundaries are a true reflection of what has been signed in the Agreements for Lease and Lease documents.

Pan-European water depth suitability map, derived from EMODnet (European Marine Observation and Data Network) Bathymetry data, showing the relative suitability for offshore wind pile foundations. The relative scoring system is from 0 (null) and 1 to 5 (i.e., high to low suitability, respectively), resulting in regional water depth suitability map for pile foundations. Null values represent hexagons that extended too far inland (e.g. estuaries) and thus don’t overlay the bathymetry map, however are kept in for information. A score of 5 (low suitability) is given to values >=0 and over 80 m. A score of 3 is given to 60-80 m. A score of 2 (higher suitability) is given to 10-50 m. The scoring system is a relative suitability scale, defined by BGS (2014), a commercial project undertaken with The Crown Estate. The original water depth (EMODnet Bathymetry) data has been translated into Hex maps due to the various data resolutions of the bathymetry datasets. Hex maps permit spatial screening of suitable license areas over vast areas and provides the end-user with an understanding to the level of uncertainty regarding the final maps. This pan-European digital GIS product is produced by the British Geological Survey (BGS) and forms part of a series of maps that define domain parameters related to marine geotechnical conditions, focusing on water depth and suitability for foundation installation. Water depth is a critical parameter influencing the selection and design of foundation systems for offshore infrastructure. Water Depth is a domain-type to support early-stage site assessment, engineering design constraints and risk evaluation processes in offshore development projects. The data is useful for marine spatial planners, wind farm developers, and research institutions who would like to understand the suitability of different foundation types for various water depths at a regional scale.

PDF map showing the interaction of OGA licences with those issued by The Crown Estate (TCE)

In support of The Crown Estate’s Offshore Leasing Round 5, this data describes a final scenario of Project Development Areas (PDAs) for the leasing round. This data is published in the British National Grid projection.

An indicative map for White Gum Moist Forest (WGMF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. The determination of WGMF was reviewed by the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel), and a set of diagnostic parameters for identifying the WGMF TEC was agreed. Our mapping process relied upon the occurrence of E.dunnii to diagnose the presence of WGMF.

We reviewed existing vegetation maps, predictive models and observation records of E.dunnii to identify State Forests that are known or likely to include stands of the species. We then attempted several different approaches to sampling and mapping E.dunnii using ground based surveys, predictive modelling and aerial photograph interpretation (API). We used API assessment of known E.dunnii stands to identify image patterns and signatures that indicated the presence of E.dunnii. We used our findings to examine un-surveyed areas of relevant state forests via API, and then we mapped any areas which appeared to be dominated or co-dominated by E.dunnii. We also developed a Random Forest presence-absence model and used it to predict the distribution of WGMF across its range. We constructed an indicative map of WGMF using the combined results of our API mapping and our predictive model. In total, we mapped approximately 980 hectares of forest likely to be dominated or co-dominated by E.dunnii across 16 State Forests. Two thirds of the mapped area is associated with the northern populations of E.dunnii – the largest areas were in Beaury, Donaldson and Yabbra State Forests. In the southern area, Kangaroo River State Forest includes the largest representation of E.dunnii in State Forest. Our conclusions from this exercise is that our API interpretation is capable of separating E.dunnii from other related eucalypts but only where it is supported by field reconnaissance. Therefore, further work is required to increase API confidence throughout its range before our maps are suitable for operational applications. Nonetheless, our indicative map is still useful for providing a list of State Forests that include mapped areas of E.dunnii and identifying the areas that have corroborating field based evidence of E.dunnii. As our indicative map stands at present, we consider that it overestimates the extent of E.dunnii and its dominance, however, it is unlikely that extensive stands exist outside our mapped areas. We also conclude that existing mapping (including both forest type mapping and OEH (2012) mapping) significantly underestimates the likely true extent).

Indicative TEC Mapping have been generated from best available composite environmental data layers - standardised to 30 m pixels.

The operational map for Montane Peatlands and Swamps was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. The project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) reviewed the determination for Montane Peatlands and Swamps and agreed upon a set of diagnostic parameters for its identification through aerial photograph interpretation (API). These parameters included an elevation of greater than 400m and, broadly, the presence of treeless native vegetation on poorly drained soils. Using API, we then assessed whether Montane Peatlands and Swamps is present within more than 828,000 hectares of state forests within the coastal, tableland and montane regions of eastern NSW. A number of State Forests were excluded from the assessment because they fell below the elevation threshold or were underlain by Triassic sandstone sediments, which are explicitly excluded in the determination for Montane Peatlands and Swamps. In total we identified 1729.5 hectares of candidate Montane Peatlands and Swamps across State Forests in eastern NSW. From this we constructed several operational maps showing the extent of the Montane Peatlands and Swamps TEC within the relevant State Forests. More than 60% of the total mapped areas were located in the southern tablelands. The largest areas of the candidate TEC were mapped in Bago, Glenbog and Badja State Forests in the south, and in Boonoo and Girard State Forests in the north. Patch size varied, with more than 200 patches being smaller than 0.1 hectare and around 50 patches being larger than 30 hectares. It is noted that the broad mapping criteria will have captured a wide range of floristic assemblages including swamps, bogs, marshes, fens, meadows, grasslands and herb fields. Not all of these assemblage will be Montane Peatlands and Swamps, and it is highly likely that the mapping has captured two related TECs due to their overlapping environmental gradients and similar vegetation structure. These two TECs (Upland Wetlands of the Drainage Divide of the New England Bioregion and Carex Sedgeland of the New England Tableland, Nandewar, Brigalow Belt South and NSW North Coast Bioregions) are both candidate TECs within State Forests in their own right.

Operational TEC Mapping have been derived by API at a viewing scale between 1-4000 using ADS40 50 cm pixel imagery and 1 m derived LIDAR DEM grids for floodplain EECs.

This is the final report on sublittoral mapping of Milford Haven, Pembrokeshire and south Cardigan Bay which formed part of the Broadscale Mapping Project: a project funded by the Crown Estate, the Countryside Council for Wales, English Nature, Scottish Natural Heritage and the Newcastle University (SeaMap). It is supported by the European Commission under the Life programme. The survey of the Milford Haven, Pembrokeshire and south Cardigan Bay has contributed to the development of a methodology for broad scale survey and mapping of large areas of sea floor using acoustic remote sensing techniques. The methodology relies on the relatively inexpensive acoustic ground discrimination system (AGDS) based on a single beam echo sounder. Image processing requires ground truth samples of the biota and habitats from the sea floor and the sampling techniques range from the traditional grab, trawl and dredge to the deployment of remote video.

These maps are master copies which were created for a cadastre, a public register recording the boundaries, roads, waterways, identifiers and names for a parcel of land. The maps were adapted to chart the changes of subdivisional patterns and land status changes created by the registration of deposited plans. The maps contain contemporary and historical subdivision information.

Other notations may include strata plans, Crown grant boundaries and grant information if the land is Torrens, Old System or Crown land title. Also included are Primary Applications (PA) and Conversion Actions (CA), historical subdivision plans, road plans, acquisitions, resumption dedications and other land status changes recorded in government gazettes. Parish, county, locality and local government authority are also shown.

The maps charted subdivisional, status and boundary changes. These maps use the Central Mapping Authority (CMA) index maps drawn at a range of scales. They do not show land use or ownership changes.

Each map title is prefaced by MC; for Master Copy;, for example, MC/Q0162-06. The numbering runs across quadrants of the original topographic map which provides the first number. Some quadrants are divided again, resulting in a more complex number.

In September 2002 the manual updating of all Land and Property Information paper maps was discontinued. All notations, status and subdivisional changes are made in the Integrated Titling System (ITS) and the Digital Cadastral Database (DCDB). All charting information regarding subdivision and status changes since September 2002 is provided to the public through the Cadastral Records Enquiry (CRE) also known as the Property Location Map. (1)

Endnotes

1.NSW Government, NSW Land & Property Information, Searching the Registrar General's Maps and Plans, March 2013, p. 21. http://www.lpi.nsw.gov.au/_data/assets/pdf_file/0019/150706/Searching_RG_Maps_Plans.pdf (accessed 2 March 2015).

This dataset represents all current meteorological equipment agreements in English, Welsh and Northern Irish waters. The boundaries are a true reflection of what has been signed in the Agreements for Lease and Lease documents.

Operational map for River-flat Eucalypt Forest:

The operational map for River-flat Eucalypt Forest (RFEF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the coastal Integrated Forestry Operation Agreements. The map was constructed in two parts, with State Forests to the north of Sydney being mapped in a separate process to those to the south of Sydney. We did this to minimise the risk that relationships between regional vegetation communities and the TEC would be confounded or masked by geographical variation or other major ecological gradients, which might otherwise be a significant risk if we had treated the full latitudinal range of the TEC as a single study area. In total, we assessed 1,218,000 hectares of State Forest across coastal NSW. This consisted of 868,000 hectares of State Forest on the north coast and more than 350,000 hectares of State Forest on the south coast. In both study areas, the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) preceded the assessment process by reviewing the determination for RFEF and agreeing upon a set of diagnostic parameters for its identification. The Panel found that RFEF is primarily defined by floristic plot data and that it is mostly located on coastal floodplains and associated alluvial landforms. Following on from these conclusions, we started the mapping process by mapping the distribution of floodplains and alluvial soils and thus identifying possible areas of RFEF. For both the north and the south coast we used an existing map of coastal landforms and geology in combination with several fine-scale models of alluvial landform features to determine the likely extent of floodplains and alluvial soils within our study areas. We used aerial photograph interpretation (API) to assess the floristic and structural attributes of the vegetation cover found on our modelled alluvial environments, and thus delineated polygons likely to contain RFEF. We also used API to modify the boundaries of the modelled alluvial areas using a prescribed list of eucalypt, casuarina and melaleuca species in combination with the interpretation of landform elements relevant to alluvial and floodplain environments. We then compiled floristic plot data for all State Forest areas within our modelled alluvial landforms and API polygons. For both the north and the south coast the floristic plot data was sourced from both existing flora surveys held in the OEH VIS database and from targeted flora surveys conducted specifically for this project. We compared these plots with those previously assigned to flora communities listed in the determination of RFEF. Both dissimilarity-based methods and multivariate regression methods were used for the comparison. The results of the comparison were then used to assess the likelihood that the plots in State forests belonged to one or more of the communities listed in the RFEF determination. Following this, we developed a predictive statistical model of the probability of occurrence of RFEF using plot data and a selection of environmental and remote-sensing variables. For the north coast, we used a Random Forest model, while for the south coast we used a Boosted Regression Tree model. To create the operational map, we assigned every mapped API polygon to RFEF if appropriate based on the plot data, over-storey and understorey attributes, landform features and modelled probabilities underlying each API polygon. We mapped 3819 hectares of RFEF on the south coast and 198 hectares of RFEF on the north coast.

Operational map for Swamp Oak Floodplain Forest:

The operational map for Swamp Oak Floodplain Forest (SOFF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the coastal Integrated Forestry Operation Agreements. The map was constructed in two parts, with State Forests to the north of Sydney being mapped in a separate process to those to the south of Sydney. We did this to minimise the risk that relationships between regional vegetation communities and the TEC would be confounded or masked by geographical variation or other major ecological gradients, which might otherwise be a significant risk if we had treated the full latitudinal range of the TEC as a single study area. In total, we assessed 1,218,000 hectares of State Forest across coastal NSW. This consisted of 868,000 hectares of State Forest on the north coast and more than 350,000 hectares of State Forest on the south coast. In both study areas, the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) preceded the assessment process by reviewing the determination for SOFF and agreeing upon a set of diagnostic parameters for its identification. The Panel found that SOFF is primarily defined by floristic plot data and that it is mostly located on coastal floodplains and associated alluvial landforms. Following on from these conclusions, we started the mapping process by mapping the distribution of floodplains and alluvial soils and thus identifying possible areas of SOFF. For both the north and the south coast we used an existing map of coastal landforms and geology in combination with several fine-scale models of alluvial landform features to determine the likely extent of floodplains and alluvial soils within our study areas. We used aerial photograph interpretation (API) to assess floristic and structural attributes of the vegetation cover on our modelled alluvial environments, and thus delineated polygons likely to contain SOFF. We also used API to modify the boundaries of the modelled alluvial areas using a prescribed list of casuarina and melaleuca species in combination with the interpretation of landform elements relevant to alluvial and floodplain environments. We then compiled floristic plot data for all State Forest areas within our modelled alluvial landforms and API polygons. For both the north and the south coast the floristic plot data was sourced from both existing flora surveys held in the OEH VIS database and from targeted flora surveys conducted specifically for this project. We compared these plots with those previously assigned to flora communities listed in the determination of SOFF. Both dissimilarity-based methods and multivariate regression methods were used for the comparison. The results of the comparison were then used to assess the likelihood that the plots in State forests belonged to one or more of the communities listed in the SOFF determination. To create the operational map, we assigned every mapped API polygon to SOFF based on the plot data, over-storey and understorey attributes, landform features and model output underlying each API polygon. In total, we mapped approximately 272 hectares of SOFF across our full study area.

Operational map for Swamp Sclerophyll Forest:

The operational map for Swamp Sclerophyll Forest (SSF) was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the coastal Integrated Forestry Operation Agreements. The map was constructed in two parts, with State Forests to the north of Sydney being mapped in a separate process to those to the south of Sydney. We did this to minimise the risk that relationships between regional vegetation communities and the TEC would be confounded or masked by geographical variation or other major ecological gradients, which might otherwise be a significant risk if we had treated the full latitudinal range of the TEC as a single study area. In total, we assessed 1,218,000 hectares of State Forest across coastal NSW. This consisted of 868,000 hectares of State Forest on the north coast and more than 350,000 hectares of State Forest on the south coast. In both study areas, the project’s Threatened Ecological Community (TEC) Reference Panel (the Panel) preceded the assessment process by reviewing the determination for SSF and agreeing upon a set of diagnostic parameters for its identification. The Panel found that SSF is primarily defined by floristic plot data and that it is mostly located on coastal floodplains and associated alluvial landforms. Following on from these conclusions, we started the mapping process by mapping the distribution of floodplains and alluvial soils and thus identifying possible areas of SSF. For both the north and the south coast we used an existing map of coastal landforms and geology in combination with several fine-scale models of alluvial landform features to determine the likely extent of floodplains and alluvial soils within our study areas. We used aerial photograph interpretation (API) to assess the floristic and structural attributes of the vegetation cover on our modelled alluvial environments, and thus delineated polygons likely to contain SSF. We also used API to modify the boundaries of the modelled alluvial areas using a prescribed list of eucalypt, casuarina and melaleuca species in combination with the interpretation of landform elements relevant to alluvial and floodplain environments. We then compiled floristic plot data for all State Forest areas within our modelled alluvial landforms and API polygons. For both the north and the south coast the floristic plot data was sourced from both existing flora surveys held in the OEH VIS database and from targeted flora surveys conducted specifically for this project. We compared these plots with those previously assigned to flora communities listed in the determination of SSF. Both dissimilarity-based methods and multivariate regression methods were used for the comparison. The results of the comparison were then used to assess the likelihood that the plots in State forests belonged to one or more of the communities listed in the SSF

The Broadscale Mapping Project has been devised and funded by a consortium consisting of the Crown Estate, the Countryside Council for Wales, English Nature, Scottish Natural Heritage and the SeaMap research group based at Newcastle University and undertaken by SeaMap. Three trial areas were selected, around Milford Haven, Pembrokeshire and South Cardigan Bay, for developing and testing the methodology, although experience from many other surveys conducted by SeaMap have also contributed to the development of the methodology. The aim of this data collection was to map the seafloor sediments and biota, for habitats and biotope mapping. This was supplemented by maps and supporting data showing the location of ground truth samples and the positions of the acoustic tracks.

Methodologies for broad scale mapping of sublittoral habitats and biota based on acoustic remote sensing was developed as the Broadscale Mapping Project (BMP), a three year project funded by a consortium consisting of the Crown Estate, the Countryside Council for Wales, English Nature, Scottish Natural Heritage and Newcastle University through the SeaMap Research Group. The project was also supported by the European Commissionâ s Life programme. The Firth of Lorn study area was selected by Scottish Natural Heritage (SNH) because it encompassed a wide range of physical environmental conditions and had considerable existing conservation value. Part of the BMP study area was recently put forward as a possible Special Area of Conservation in recognition of the significant marine biological interest of both intertidal and subtidal rocky reefs. A nested survey strategy was developed for the Firth of Lorn which involved careful pre-planning and iterative field survey. By adopting this nested and iterative approach, the overall summary maps comprise a jigsaw of small maps where the underlying data vary in their level of detail. The main features and biota were mapped using acoustic remote sensing techniques combined with biological sampling. Linking the biological data with the acoustic data was completed using classification techniques developed for processing satellite images.

Additional information source:

Davies, J., 1999. Broad scale remote survey and mapping of sublittoral habitats and their associated biota in the Firth of Lorn. Report for SNH

The operational map for Coastal Saltmarsh was constructed to resolve long-standing issues surrounding its identification, location and extent within the NSW State Forest estate covered by the eastern Regional Forest Agreements. The project’s Threatened Ecological Community Reference Panel (the Panel) reviewed the determination for Coastal Saltmarsh and agreed upon a set of diagnostic parameters for its identification. We identified that any treeless saline and sub saline native vegetation found in the intertidal zone had the potential to be Coastal Saltmarsh. We estimated the extent of the intertidal zone by using a fine scale digital elevation model to determine the highest astronomical tideline (HAT). We then mapped potential Coastal Saltmarsh by analysing recent fine scale three dimensional aerial imagery to identify any native vegetation that comprised of low-growing treeless communities and was located within the HAT and on the landward side of mangroves. Mapping criteria used a tree cover tolerance of up to 30% to include areas that had a mixed cover of mangrove, paperbark or casuarina species with a saltmarsh understorey. Exposed mudflats and banks were also mapped when they were visible. Our mapping covered 1.4 million hectares of State Forest within the south, central and north coast regions of NSW. We identified a total of 111.9 hectares of Coastal Saltmarsh within 14 State Forests along the east coast. The most extensive areas are located in Bermagui and Mogo State Forests on the south coast and in Wallaroo State Forests on the north coast. We validated our map of coastal saltmarsh using an existing independent map of estuarine habitats (Creese et al 2009). Our mapping consistently identified almost twice as much coastal saltmarsh as Creese et al (2009), but this was attributable to differences in the mapping criteria rather than any error.

Operational TEC Mapping have been derived by API at a viewing scale between 1-4000 using ADS40 50 cm pixel imagery and 1 m derived LIDAR DEM grids for floodplain EECs.