20250623141741001.0ISO 19139 Metadata Implementation SpecificationFALSESENSHR_2023ArcSDE Connection61939.273700793991.86220059488.270700754095.549300176.262002ProjectedGCS_North_American_1983_HARNLinear Unit: Meter (1.000000)NAD_1983_HARN_Florida_GDL_Albers<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.4.0'><WKT>PROJCS["NAD_1983_HARN_Florida_GDL_Albers",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-84.0],PARAMETER["Standard_Parallel_1",24.0],PARAMETER["Standard_Parallel_2",31.5],PARAMETER["Latitude_Of_Origin",24.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3087]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3087</WKID><LatestWKID>3087</LatestWKID></ProjectedCoordinateSystem>202508051347500020250805134750001500000005000FGDCdatasetGISLibrarianFlorida Fish and Wildlife Conservation Commission-Fish and Wildlife Research InstituteGIS Data Librarian(727) 896-8626(727) 893-1679Fish and Wildlife Research Institute 100 Eighth Avenue SoutheastSt. PetersburgFlorida33701GISLibrarian@MyFWC.com2025061276.262Florida Geographic Data Library (FGDL)Jonathan and Melanie Antevy Hall1480 Inner Road, Room 431PO Box 115706GainesvilleFL32611-5706UShttps://fgdl.org/info/contact/NoneDOWNLOADABLE DATAhttps://www.fgdl.org/Enterprise Geodatabase Feature ClassFlorida's Environmentally Sensitive Shorelines - 20232020-03-01T00:00:00SecondFlorida Wildlife Research Institute (FWRI), Florida Fish and Wildlife Conservation Commission (FWCC)St. Petersburg, FloridaFlorida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute and Research Planning, Inc.vector digital dataNoneEast FloridaState of FloridaThis data set contains vector lines representing the ESI classified shoreline of Florida classified according to the Environmental Sensitivity Index (ESI) classification system. This data set comprises the ESI data for Florida. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the ESIP data layer, part of the larger Florida ESI database, for additional ESI information. Environmental Sensitivity Index (ESI) is more properly known as 'Sensitivity of Coastal Habitats and Wildlife to Spilled Oil' Atlases. The term 'ESI' is often used in reference to the whole dataset, but the term 'ESI' is really a reference to the classification system of shoreline types known as Environmental Sensitivity Index, that classifies a shoreline on a scale from 1 to 10 based upon overall sensitivity to spilled oil. These datasets were delivered as feature classes in overlapping-polygon format following the NOAA ESI Data Standard. The Florida ESI data format is consistent with the V4 ESI Guidelines.The ESI data provide sensitive areas data for oil spill planning and response and other environmental management and natural resource purposes. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive areas. These data also support other related state and federal regulatory requirements for oil spill prevention, planning, response, and restoration.
This statewide ESI dataset includes five merged datasets, each representing a different region of Florida. The primary use for this database is for use in the Florida Marine Spill Analysis System (FMSAS) application. The remainder of this metadata document represents only one of the three ESI databases that were used in the compilation. For full metadata for other regions please download the source ESI geodatabase for that region from https://geodata.myfwc.com/. This project was supported by the Florida Wildlife Research Institute (FWRI), Florida Fish and Wildlife Conservation Commission (FWC). Timyn Rice with FWRI served as contract and technical manager for the project. Steven Nicholl, Timyn Rice, Christi Santi, Ryan Druyor, Latosha Thompson, Chris Boland, Ryan Druyor and other FWRI staff contributed significantly to the project, as did many other individuals from several state and federal agencies and other organizations. At Research Planning, Inc. in Columbia, South Carolina, numerous scientific and staff were involved with different phases of the project. Mark White, GIS Director, and Christine Boring, Biology Dept. Manager, were co-Project Managers. The ESI shoreline was classified by Jennifer Horsman, Lee Diveley, and Katy Beckham. The biological data were collected and compiled by Christine Boring, Lauren Szathmary, Jennifer Weaver, and Lincoln Smith. Katy Beckham, Lee Diveley, Jeff Dahlin, and Chris Locke produced the GIS data and final metadata documents.withheldDepicts the relationships between spatial data layers and attribute data tables for the East Florida ESI data.JPEGCoastal FloridaSouthwest FloridaOil spill planningNatural Resource Damage AssessmentG_WISShoreline habitatsESICoastal Zone ManagementCoastal resourcesWildlifeSensitivity mapsISO 19115 Topic CategoryenvironmentbiotaCoastal FloridaOil spill planningenvironmentNatural Resource Damage AssessmentSouthwest FloridaG_WISbiotaShoreline habitatsESICoastal Zone ManagementCoastal resourcesWildlifeSensitivity mapsThis data set is in the public domain, and the recipient may not assert any proprietary rights thereto nor represent it to anyone as other than a Florida Fish and Wildlife Conservation Commission produced data set; it is provided 'as-is' without warranty of any kind, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. The user assumes all responsibility for the accuracy and suitability of this data set for a specific application. In no event will the staff of the Florida Fish and Wildlife Conservation Commission be liable for any damages, including lost profits, lost savings, or other incidental or consequential damages arising from the use of or the inability to use this data set.These data are unrestricted. Where possible, always acquire this dataset directly from FWC as other sources may have altered the original data.The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation.DO NOT USE MAPS FOR NAVIGATIONAL PURPOSES. Management boundaries are not to be considered legal boundaries. Edges may have been altered for cartographic processes. Note that the ESI database should not be used to the exclusion of other pertinent data or information held by state or federal agencies or other organizations. Likewise, information contained in the database cannot be used in place of consultations with environmental, natural resource, and cultural resource agencies, or in place of field surveys. Recognize that the information contained in the ESI database represents known concentration areas or occurrences of natural, cultural, and human-use resources, but does not necessarily represent the full distribution or range of each species or resource. This is particularly important to recognize when considering potential impacts to protected resources, such as endangered species, wetlands, etc. The ESI databases were developed to provide summary information on sensitive natural and human-use resources for the purposes of oil spill planning, environmental planning, and natural resource management. Although the ESI data should be a valuable planning and resource management tool, they should not be used to the exclusion of other pertinent data or information held by state or federal agencies or other organizations. Likewise, these data cannot be used in place of consultations with environmental, natural resource, and cultural resource agencies, or in place of field surveys. Also, these data and any related map products should not be used for navigation. Recognize that the information contained in the ESI databases represents known concentration areas or occurrences of natural, cultural, and human-use resources, but does not necessarily represent the full distribution or range of each species or resource. This is particularly important to recognize when considering potential impacts to protected resources, such as endangered species, wetlands, archaeological sites, etc. For more information or guidance on proper and improper uses of these data, please contact the Fish and Wildlife Research Institute (FWRI) and Research Planning, Inc. Acknowledgement of the publishers, contributors, and sources listed in the Data_Set_Credit (below) and Lineage section of this document would be appreciated in products derived from or utilizing these data. Users are encouraged to read and fully comprehend the metadata record prior to using these data. Please acknowledge the Florida Fish and Wildlife Conservation Commission (FWC) as the data source for any products developed from these data. Users should be aware that comparison with other data sets for the same area from other time periods may be inaccurate due to inconsistencies resulting from changes in mapping conventions, data collection, and computer processes over time. FWC shall not be liable for improper or incorrect use of this data. These data are not legal documents and are not to be used as such. This is not a survey data set and should not be utilized as such. These data are not to be used for navigation. Besides the above warnings, there are no use constraints on these data. Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595The data were compiled during 2013-2024. The currentness dates for this data range from 2013 to 2024 and are documented in the Lineage section.2013-01-01T00:00:002025-01-01T00:00:00-81.91765-76.5931326.3643230.778051-81.877731-79.88209830.77757126.373577Shoreline Rankings:
Environmental Sensitivity Index (ESI) maps use shoreline rankings to rate how sensitive an area of shoreline would be to an oil spill. The ranking scale goes from 1 to 10.
A rank of 1 represents shorelines with the least susceptibility to damage by oiling. Examples include steep, exposed rocky cliffs and banks. The oil cannot penetrate into the rock and will be washed off quickly by the waves and tides.
A rank of 10 represents shorelines most likely to be damaged by oiling. Examples include protected, vegetated wetlands, such as mangrove swamps and saltwater marshes. Oil in these areas will remain for a long period of time, penetrate deeply into the substrate, and inflict damage to many kinds of plants and animals. The photo at right shows oil coating a significant portion of a mangrove swamp.Last metadata review date: 202506A multi-stage error checking process, described in the above Attribute_Accuracy_Report, is used to verify both attribute accuracy and logical consistency throughout data production. This process includes multiple automated logical consistency checks that test the files for missing or duplicate data, rules for proper coding, GIS topological consistencies, and SQL SERVER(R) to ArcGIS(R) consistencies. A final review is made by the ESI manager, where the data are written to CD-ROM and the metadata are written. RARNUM's are defined on an element basis, so 'resources at risk' groupings will contain only a single element.A multi-stage error checking process, described in the above Attribute_Accuracy_Report, is used to verify both attribute accuracy and logical consistency throughout data production. This process includes multiple automated logical consistency checks that test the files for missing or duplicate data, rules for proper coding, GIS topological consistencies, and SQL SERVER(R) to ArcGIS(R) consistencies. A final review is made by the ESI manager, where the data are written to CD-ROM and the metadata are written. RARNUM's are defined on an element basis, so 'resources at risk' groupings will contain only a single element.These data represent coastal shorelines classified according to the Environmental Sensitivity Index (ESI) classification system. See also the ESIP data layer, part of the larger East Florida ESI database, for additional ESI information.A multi-stage error checking process is used to verify both attribute accuracy and logical consistency throughout data production. The process includes a standardized data entry methodology, data review by in-house and external resource experts, a final Quality Assurance/Quality Control (QA/QC) process, and multiple automated logical consistency checks. Quantitative data (such as densities, counts, abundances, or concentrations) provided by resource experts for inclusion in the data set may vary widely in attribute accuracy, depending upon the methodology used to collect and compile such data. For a more detailed evaluation of source data attribute accuracy, contact the sources listed in the Lineage section. The attribute accuracy is estimated to be 'good' given the years of ESI experience, the data input methodology, the quality control review sessions, and the digital logical consistency checks.The spatial location of the ESI shoreline was developed from pre-existing digital sources and reflects the positional accuracy of these original data. The minimum mapping unit (MMU) of the actual shoreline classification segments is estimated at 50 meters where mapping is conducted using 1:24,000 hardcopy fieldmaps. Field verification has shown that the absolute positional accuracy of breaks between shoreline ESI types with a 95-percent error bound is approximately 58 meters. See the Lineage and Process_Description sections for more information on the original source data and how these data were integrated or manipulated to create the final data set.ESIL INFORMATION24000SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: SOUTH FLORIDA: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)NONE2013-01-01T00:00:00FLORIDA FISH AND WILDLIFE CONSERVATION COMMISSION (FWC), FLORIDA WILDLIFE RESEARCH INSTITUTE (FWRI)ST PETERSBURG, FLFLORIDA FISH AND WILDLIFE CONSERVATION COMMISSION (FFWCC), FLORIDA WILDLIFE RESEARCH INSTITUTE (FWRI)VECTOR DIGITAL DATAhttp://geodata.myfwc.com/datasets/2910418e885f4d69823021720e0156e3_24?page=5907DATE OF PUBLICATION2013-01-01T00:00:002024-01-01T00:00:00SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: East FLORIDA: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: East FLORIDA: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)2020-01-01T00:00:00SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Panhandle: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Panhandle: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)2024-01-01T00:00:00SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Northwest Peninsula Florida: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Northwest Peninsula Florida: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)2017-01-01T00:00:00SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Southwest Peninsula Florida: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)SENSITIVITY OF COASTAL ENVIRONMENTS AND WILDLIFE TO SPILLED OIL: Southwest Peninsula Florida: ESIL (ENVIRONMENTAL SENSITIVITY INDEX SHORELINE TYPES - LINES)2016-01-01T00:00:00Spatial and Attribute Information2023-01-01T00:00:00GISLibrarianFlorida Wildlife Research Institute (FWRI)(727) 896-8626(727) 893-1679100 Eighth Avenue, S.E.St. PetersburgFlorida33701GISLibrarian@MyFWC.govThis statewide ESI dataset includes five merged datasets, each representing a different region of Florida. The Panhandle data was created in 2024, followed by the South Florida dataset in 2013. The Southwest Peninsular dataset dates back to 2016, and the Northwest Peninsular data was created in 2017. The most recent update is the East Florida dataset, which was finalized in 2020. The most recent St Johns River ESI data were from 2003.
ESI LINE dataset: merged all regions data. Made descriptions for LANDWARD,SEAWARD1,SEAWARD2, and GENERALIZED_ESI_TYPE consistent using the ESI guidelines document for spelling/punctuation. Updated SOURCE fields to use numbers unique across atlases as was done in the SOURCES table.This dataset was downloaded on 6/13/2025 and was made available by Christi Santi (Elizabeth.Santi@MyFWC.com). The data was received as a shapefile and was in the following projection: WGS 1984 Web Mercator (auxiliary sphere). The data was projected to NAD 1983 HARN Florida GDL Albers using the WGS_1984_(ITRF00)_To_NAD_1983 + NAD_1983_To_HARN_Florida transformation.
- All records were uppercased
- A DESCRIPT field was added based on concatenation of fields
ESI, LANDWARD_S, SEAWARD_SH, and SEAWARD_1. VBscript = [ESI] & " - " & [LANDWARD_S] & "; " & [SEAWARD_SH] & "; " & [SEAWARD__1]
- A FGDLAQDATE field was added based on date of download
- Renamed file from Statewide_ESIL to senshr_2023
2025-06-24T00:00:00GeoPlanThis data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology.This data is provided 'as is' by GeoPlan and is complete to our knowledge.GeoPlan relied on the integrity of the attribute information within the original data.This data is provided 'as is' and its horizontal positional accuracy has not been verified by GeoPlan.This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan.0104082EPSG6.12(9.2.0)In addition to the geographic data layers, one relational attribute or data table, SOURCES, is used to store the source data information in the ESI data structure. The geographic data layer containing resource information (in this case, ESIL) is linked to the SOURCES table using the SOURCE_ID. The entity-relationship diagram describes relationships between attribute tables in the ESI data structure.A complete description of entity types, attributes, and attribute values for ESI atlases can be found in the NOAA ESI Guidelines (http://response.restoration.noaa.gov/esi_guidelines).SENSHR_2023Feature Class104082SENSHR_2023FWRIOBJECTIDOBJECTIDOID4100Internal feature number.EsriSequential unique whole numbers that are automatically generated.ShapeFeature geometry.EsriCoordinates defining the features.SHAPEGeometry800ESIESIString1200The item ESI contains values representing the ESI shoreline type. In many cases shorelines are ranked with multiple codes, such as "6B/3A" (listed landward to seaward from left to right). The first code, "6B", is the most landward shoreline type and the second code, "3A", is the shoreline type closest to the water. Singular shoreline types are listed below. No multiple codes are listed, but all multiple codes included in the data set can be assembled from the codes described. The ESI rankings progress from low to high susceptibility to oil spills. To determine the sensitivity of a particular intertidal shoreline habitat, the following factors are integrated: 1) Shoreline type (substrate, grain size, tidal elevation, origin); 2) Exposure to wave and tidal energy; 3) Biological productivity and sensitivity; 4) Ease of cleanup. Prediction of the behavior and persistence of oil in intertidal habitats is based on an understanding of the dynamics of the coastal environments, not just the substrate type and grain size. The intensity of energy expended upon a shoreline by wave action, tidal currents, and river currents directly affects the persistence of stranded oil. The need for shoreline cleanup activities is determined, in part, by the slowness of natural processes in removal of oil stranded on the shoreline. The potential for biological injury, and ease of cleanup of spilled oil are also important factors in the ESI ranking. Generally speaking, areas exposed to high levels of physical energy, such as wave action and tidal currents, and low biological activity rank low on the scale, whereas sheltered areas with associated high biological activity have the highest ranking. This value can be used for symbolization using the ESI LINE - CARTO layer file.NOAA ESI GuidelinesLINELINEString200Type of geographic feature.NOAA ESI GuidelinesBBreakwaterNOAA ESI GuidelinesDDockNOAA ESI GuidelinesFNFenderNOAA ESI GuidelinesGRGroinNOAA ESI GuidelinesHHydrographyNOAA ESI GuidelinesJJettyNOAA ESI GuidelinesPPierNOAA ESI GuidelinesSShorelineNOAA ESI GuidelinesENVIRENVIRString100Type of regional environment.NOAAEEstuarine: River-mouth; salt- or brackish-water.NOAALLacustrine: Related to lakes.NOAARRiverine: Related to rivers, particularly large rivers.NOAAMOST_SENSIMOST_SENSIString400If multiple shoreline types appear in ESI classification, this field represents the highest value (most sensitive type); otherwise it is the same value as the ESI field.NOAALANDWARD_SLANDWARD_SString6000The numeric representation and physical description of the first (or only) ESI type found in the ESI field. Shoreline type farthest from the shoreline.NOAA ESI GuidelinesSEAWARD_SHSEAWARD_SHString6000The numeric representation and physical description of the second ESI type in the ESI field (NULL if not applicable). Shoreline type closest to the waterNOAA ESI GuidelinesSEAWARD__1SEAWARD__1String6000The numeric representation and physical description of the third ESI type in the ESI field (NULL if not applicable). The middle value in between the shoreline and most-distant shoreline type.NOAA ESI GuidelinesGENERAL_SYGENERAL_SYInteger450The highest numeric representation (most sensitve type) found in the generalized ESI shoreline type. This value can be used for symbolization using the ESI LINE - GENERAL layer file.NOAA ESI Guidelines1ArmoredNOAA ESI Guidelines2Rocky and Steep Shorelines (Bedrock/Sand/Clay)NOAA ESI Guidelines3Beaches (Sand/Gravel)NOAA ESI Guidelines4Flats (Mud/Sand)NOAA ESI Guidelines5Vegetated (Grass/Marsh/Mangroves/Scrub-Shrub)NOAA ESI GuidelinesGENERALIZEGENERALIZEString18000The numeric representation and physical description of the generalized ESI shoreline type.NOAA ESI GuidelinesSOURCE_IDSOURCE_IDInteger4100Undefined by sourceGeoPlanESI_SOURCEESI_SOURCEInteger4100Undefined by sourceGeoPlanESI_DATEESI_DATEInteger450Undefined by sourceGeoPlanLINE_DATELINE_DATEInteger450Undefined by sourceGeoPlanDESCRIPTDESCRIPTString20000FGDL added field based on ESI, LANDWARD_S, SEAWARD_SH, and SEAWARD_1. VBscript = [ESI] & " - " & [LANDWARD_S] & "; " & [SEAWARD_SH] & "; " & [SEAWARD__1]GeoPlanFGDLAQDATEThe date GeoPlan acquired the data from the source.GeoPlanFGDLAQDATEDate800AUTOIDAUTOIDInteger410Unique ID added by GeoPlan. This field is for historic tracking of features.0SHAPE.LENSHAPE.LENDouble00Length of feature in internal units0/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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