AndreaBozzo/ceres-open-data-index huggingface dataset:
2021 NI Coastal Survey

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
Priority Habitats - Grassland

<div style='text-align:Left;'><div><div><p style='margin:0 0 14 0;'><span>About this layer</span></p><p style='margin:0 0 14 0;'><span>The Grassland Inventory incorporates evidence collected from a series of research contracts let to identify and survey areas of grassland of high nature conservation value. </span></p><p style='margin:0 0 14 0;'><span>This data represents NIEA surveys and may not represent the entire extent of habitat or species across Northern Ireland</span></p><p style='margin:0 0 14 0;'><span /><span><span>The research focused on identifying grassland habitats that are a priority within the Northern Ireland biodiversity strategy and also those identified as being of particular importance within Annex 1 of the Habitats Directive. The research methodology used well established survey techniques to identify high nature conservation value grasslands from high incidence study areas throughout Northern Ireland.</span></span></p><p style='margin:0 0 14 0;'><span><span>Data Sources:</span></span></p><p style='margin:0 0 14 0;'><span><span>Habitat Survey Team, Conservation Science:  1985 - 2014</span></span></p><p style='margin:0 0 14 0;'><span><span>University of Ulster:  1999</span></span></p><p style='margin:0 0 14 0;'><span><span>ADAS:  2000 - 2005</span></span></p><p style='margin:0 0 14 0;'><span><span>Allen &amp; Mellon Environmental:  2005 - 2007</span></span></p><p style='margin:0 0 14 0;'><span><span>What can you do with the layer?</span></span></p><p style='margin:0 0 14 0;'><span><span>Visualisation: This layer can be used for visualisation online in web maps.</span></span></p><p style='margin:0 0 14 0;'><span><span>Analysis: This layer can be used in dashboards.</span></span></p><p style='margin:0 0 14 0;'><span><span>Download: The data is downloadable.</span></span></p></div></div></div>

Tags: Calcareous Grassland, Lowland Acid Grassland, Lowland Meadow, NI, Natural Environment Division, Northern Ireland, Northern Ireland Environment Agency, Priority Habitats, Purple Moor-Grass and Rush Pastures, UK, United Kingdom
Organization: OpenDataNI
Modelled fluvial flood depth and climate change depth difference data created 2004: 0.1  percent annual chance for grid reference SX

The depth difference dataset (2004) is a depth grid showing the difference between modelled fluvial flood depths and modelled fluvial flood depths under climate change conditions (an increase in peak flows of 20%). 
Modelled fluvial flood depth and climate change depth difference data* was created for both the 0.1% annual chance of flooding situations and was produced as a by-product from the 2004 generalised modelling project. The purpose of the generalised modelling project was to fill the gaps where there was no detailed local modelled data in 2004, in order to define the extents of Flood Zones for spatial planning.
A two-dimensional hydrodynamic model called JFlow was used to produce both the modelled fluvial flood depth and modelled fluvial flood depth with climate change data. This depth difference data, using these 2 datasets, is provided on a 5x5m grid.
Since 2004, some local detailed modelling projects have included scenarios for climate change however this depth difference dataset has not been updated.
INFORMATION WARNING: This data is not suitable for identifying whether an individual property will flood due to climate change, for detailed decision making or for use in site specific Flood Risk or Strategic Flood Risk Assessments. Where this data is used further evidence, verification and studies should be undertaken. Climate change allowances have changed since this work was completed in 2004.
More recent, accurate and local detailed modelling depth data with climate change is available for some places. Please contact your local Environment Agency office to see if detailed modelling is available for your area of interest. 
This metadata record is for Approval for Access product AfA480 2004 1 in 1000 Fluvial Depth Grid Climate Change Difference
Modelled fluvial flood depth data with climate change are available for the whole of England, however this data is for the 100x100km squared Ordnance Survey National Grid reference SX. If you are interested in data for another grid reference refer to this Ordnance Survey National Grid document to find the relevant referencing code and search on Data.gov.uk again to download the data. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved. Some features of this information are based on digital spatial data licensed from the Centre for Ecology & Hydrology © NERC (CEH). Defra, Met Office and DARD Rivers Agency © Crown Copyright. © Cranfield University. © James Hutton Institute.  Contains OS data © Crown copyright and database right 2015. Land & Property Services © Crown copyright and database right.

Tags: environment, flood, flooding, risk assessment
Organization: Environment Agency
Modelled fluvial flood depth and climate change depth difference data created 2004: 0.1  percent annual chance for grid reference SY

The depth difference dataset (2004) is a depth grid showing the difference between modelled fluvial flood depths and modelled fluvial flood depths under climate change conditions (an increase in peak flows of 20%). 
Modelled fluvial flood depth and climate change depth difference data* was created for both the 0.1% annual chance of flooding situations and was produced as a by-product from the 2004 generalised modelling project. The purpose of the generalised modelling project was to fill the gaps where there was no detailed local modelled data in 2004, in order to define the extents of Flood Zones for spatial planning.
A two-dimensional hydrodynamic model called JFlow was used to produce both the modelled fluvial flood depth and modelled fluvial flood depth with climate change data. This depth difference data, using these 2 datasets, is provided on a 5x5m grid.
Since 2004, some local detailed modelling projects have included scenarios for climate change however this depth difference dataset has not been updated.
INFORMATION WARNING: This data is not suitable for identifying whether an individual property will flood due to climate change, for detailed decision making or for use in site specific Flood Risk or Strategic Flood Risk Assessments. Where this data is used further evidence, verification and studies should be undertaken. Climate change allowances have changed since this work was completed in 2004.
More recent, accurate and local detailed modelling depth data with climate change is available for some places. Please contact your local Environment Agency office to see if detailed modelling is available for your area of interest. 
This metadata record is for Approval for Access product AfA480 2004 1 in 1000 Fluvial Depth Grid Climate Change Difference
Modelled fluvial flood depth data with climate change are available for the whole of England, however this data is for the 100x100km squared Ordnance Survey National Grid reference SY. If you are interested in data for another grid reference refer to this Ordnance Survey National Grid document to find the relevant referencing code and search on Data.gov.uk again to download the data. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved. Some features of this information are based on digital spatial data licensed from the Centre for Ecology & Hydrology © NERC (CEH). Defra, Met Office and DARD Rivers Agency © Crown Copyright. © Cranfield University. © James Hutton Institute.  Contains OS data © Crown copyright and database right 2015. Land & Property Services © Crown copyright and database right.

Tags: environment, flood, flooding, risk assessment
Organization: Environment Agency
1990 AP

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
Roe Network Contribution

<div style='text-align:Left;'><div><div><p style='font-weight:bold;'><span><span>About this layer</span></span></p><p><span>Network contribution area scores were exported from the SciMAP application outputs within SAGA GIS. The scores were based on inputs from CEH Land cover 2007, Met Office average rainfall and 5 meter DTM. The High contribution category boundary was determined by selecting +1 standard deviation of the distribution of the scores.</span></p><p style='font-weight:bold;'><span>What can you do with the layer?</span></p><p style='margin:1 1 1 20;'><span style='font-weight:bold;'>Visualisation: </span><span><span>This layer can be used for visualisation online in web maps.</span></span></p><p style='margin:1 1 1 20;'><span style='font-weight:bold;'><span>Analysis: </span></span><span><span>This layer can be used in dashboards.</span></span></p><p style='margin:1 1 1 20;'><span style='font-weight:bold;'><span>Download:</span></span><span> The data is downloadable.</span></p></div></div></div>

Tags: High Network Contribution, NI, Northern Ireland, Rivers, Surface Flow, Surface Water Connectivity, UK, United Kingdom
Organization: OpenDataNI
Rivers Strahler Ranking

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The first segment of a stream is a 1st order stream. When two 1st order streams merge the next segment becomes a 2nd order stream. When two 2nd order streams merge it becomes a 3rd order stream and so on. However lower order streams joining a higher order stream do not change its order classification.</SPAN></P></DIV></DIV></DIV>

Tags: Northern Ireland, River Network, Rivers, Strahler
Organization: OpenDataNI
1976 OS 27 10K

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
Linear Regression Rate

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
Boundary

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022. This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>Later in the year Fugro were commissioned to undertake a second LiDAR survey of the north coast from White Rocks to Magilligan in September 2022. The aim of this repeat survey was to ascertain the levels of recovery along the soft sediment coastlines since March 2022.</p><div style='text-align:Left; font-size:12pt;'><p>As with the initial survey undertaken by Fugro this topographic LiDAR survey collected data from the intertidal area to 10m inland for the same soft sediment areas along the north coast, with data being acquired at 0.5m resolution. The survey was quite restrictive when it could be flown: it had to be 2 hours either side of Low Water, during clear conditions below 6000ft, sun had to be at a suitable angle to capture imagery and as photography was being captured the survey could only be flown during day light hours. <div style='text-align:Left; font-size:12pt;'><p>All data collected was to be directly comparable with the data collected in the initial post storm Survey undertaken, as this would help us to understand and accurately quantify how our soft, sedimentary coastlines respond and recover from extreme storm events.</p><div style='text-align:Left; font-size:12pt;'><p>This is the orthophotography that was collected as part of the post-storm recovery survey. <br /></p></div></div></div></div></div></div></div></p>

Tags: 3D, Coastal, DTM, Digital Terrain Model, Ireland, Marine, Northern, Observatory, Ortho, Orthophotography, Post Storm, Recovery, Survey
Organization: OpenDataNI