Geodataset Name:       SENSHR_2013
Geodataset Type:       SHAPEFILE
Geodataset Feature:    Polyline
Feature Count:         59204

DATA SOURCE(S):                    Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research Institute
SCALE OF ORIGINAL SOURCE MAPS:     Unknown
GEODATASET EXTENT:                 State of Florida

PUBLICATION DATE:                  2013
TIME PERIOD OF CONTENT:            Begin Date: 2003    End Date: 2013
DOWNLOAD LINK:                     http://www.fgdl.org/metadataexplorer/explorer.jsp

FEATURE ATTRIBUTE TABLES:

Datafile Name: SENSHR_2013.DBF

FEATURE ATTRIBUTE TABLES CODES AND VALUES:

Item	Item Description
OBJECTID	Internal feature number.
Shape	Feature geometry.
ESI	The 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. 1A = Exposed Rocky Shores 1B = Exposed, Solid Man-made Structures 2A = Exposed Wave-cut Platforms in Bedrock, Mud, or Clay 2B = Exposed Scarps and Steep Slopes in Clay 3A = Fine- to Medium-grained Sand Beaches 3B = Scarps and Steep Slopes in Sand 4 = Coarse-grained Sand Beaches 5 = Mixed Sand and Gravel Beaches 6A = Gravel beaches, bars, and gently sloping banks 6B = Riprap 7 = Exposed Tidal Flats 8A = Sheltered Rocky Shores and Sheltered Scarps in Bedrock, Mud, or Clay 8B = Sheltered, Solid Man-made Structures 8C = Sheltered Riprap 9A = Sheltered Tidal Flats 9B = Vegetated Low Banks 9C = Hypersaline Tidal Flats 10A = Salt- and Brackish-water Marshes 10B = Freshwater Marshes 10C = Swamps 10D = Scrub-shrub Wetlands U = Unranked
LINE	Type of geographic feature. H = Hydrography S = Shoreline B = Breakwater
ENVIR	Type of regional environment. E = Estuarine R = Riverine
VER_NEED	Refers to whether field verification is needed (2003 data)
VER_DATE	Date of field verification (2003 data)
G_SOURCE	Geographic source integer identifier that links to records in the SOURCES data table.
A_SOURCE	Attribute source integer identifier that links to records in the SOURCES data table.
DESC_	Description of all ESI codes present for a line segment.
CASE_	ESI numerical/alpha value of the most oil spill sensitive shoreline type for any given arc regardless of landward or seaward orientation.
FREQUENCY	Verbal short description of most oil spill sensitive shoreline type
SHRT_DESC	Short description of all ESI codes present for a line segment.
MOST_SENS	Most sensitive ESI code present for a line segment.
MSTSENDES	Description of most sensitive ESI code present for a line segment.
DESCRIPT	FGDL added field based on SHRT_DESC
FGDLAQDATE	FGDL added field based on date downloaded from source
AUTOID	Unique ID added by GeoPlan
SHAPE.LEN	Length in meters

USER NOTES:

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 (such as dangles, unnecessary node, etc.), and SQL SERVER(R) to ARC/INFO(R) consistencies. A final review is made by the GIS manager. See process step for additional logical consistency checks performed by FWRI to reconcile the multiple data sources used to create the composite data set.

These data represent coastal shorelines and habitats classified according to the Environmental Sensitivity Index (ESI) classification system. See also the ESIP and HYDRO data layers, part of the larger South Florida ESI database, for additional ESI information.

GeoPlan relied on the integrity of the attribute information within the original data.

Prior to July 1, 2004, the Fish and Wildlife Research Institute (FWRI) was known as the Florida Marine Research Institute (FMRI). The institute name has not been changed in historical data sets or references to work completed by the Florida Marine Research Institute. The institute name has been changed in references to ongoing research, new research, and contact information.

To visually represent the most recent Environmental Sensitivity Index data available for each area within the state of Florida.

The spatial location of the ESI shoreline was developed from pre-existing digital sources and reflects the positional accuracy of these original data.

This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan

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 may be inaccurate due to inconsistencies resulting from changes in mapping conventions, data collection techniques, and computer processes over time. FWC shall not be liable for improper or incorrect use of these 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. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html

REFERENCES:

FWRI For more information contact the Florida Fish and Wildlife Research Institute (FWRI), GIS data librarian at gislibrarian@myfwc.com Online ESI atlas's and metadata by region: http://ocean.floridamarine.org/esimaps/

DATA LINEAGE SUMMARY:

PROCESS STEPS IN MAPJOINING NEW AND OLD ESI INTO A COMPOSITE STATEWIDE ESI DATASET: Tools Used: ArcGIS for Desktop Advanced License: ArcMap v. 10.0, Service Pack 5, XTools Pro Version 9.1.956 1. Data gathering and QA/QC: ESI Statewide 2003, ESI Birds from 2000, Panhandle ESI from 2012, South Florida ESI from 2013. All original data as COVERAGES were converted to File Geodatabase (fGDB) feature classes. Biological data sets as region polygon data within coverages were exported to file geodatabase Feature Classes. Info tables were exported to fGDB tables. 2. Schema validation: Differences across 2000, 2003, 2012, and 2013 datasets were noted. The overall schema from 2013 ESI (for South Florida) was used to create the final composite ESI file geodatabase schema design, though some modifications were made to this schema to accommodate concatenation and longer field character limits as mentioned below. 3. Align RARNUMS to be unique to each dataset by year produced (2000, 2003, 2012, 2013). This required schema change to increase RARNUM field length to accommodate a larger integer field. 4. Align G_SOURCE, A_SOURCE, S_SOURCE, and SOURCEID to be unique to each dataset by year produced (2000, 2003, 2012, 2013). This required schema change to increase source id fields lengths to accommodate a larger integer field. 5. Compare SPECIES tables across datasets, eliminate duplicates, merge into composite SPECIES table. Validate species scientific name is current across all species. Several were noted to be using "older" species scientific name. These were corrected in the final composite SPECIES table. 6. Compare STATUS table across datasets, eliminate duplicates, merge into composite STATUS table in 2012/2013 STATUS table schema, establish relate to SPECIES table and then validate T/E/C status across all of the T/E/C species as compared to T/E species list prepared by FWC in 2012. It should be noted that there are significant differences between the STATUS table used in 2003 and prior ESI data versus later editions of the STATUS table. These differences have been reconciled. 7. File Geodatabases were created and prepared, one for each source edition of ESI geodata, and one for the final composite ESI. Beginning with the statewide 2003 ESI Biology layers and the RARNUM field for each layer, the RARNUM was recalculated to append "2003" onto the front of the original RARNUM. With RARNUM being a "double" field, this was done by using the field calculator in an edit session like this; RARNUM = RARNUM + 20030000, as no RARNUM was longer than 4 digits in any of the biology feature classes. This same edit was then performed on the RARNUM field within the BIORES table and relationships were validated for intactness. Within the BIORES table, there were four fields for source identification; G_SOURCE (geographic source), S_SOURCE (seasonality source), GEO_SRC (geographic source), and SEASON_SRC (seasonality source) depending on the year of the data. These fields were reconciled in the final composite data file. Each of these fields needed to be recalculated in the same manner as for RARNUM to key them into the edition of the dataset so that each would remain unique once merged into the composite ESI geodata statewide. Additionally in the BIORES table there is an important key field named ELE_SPE_SEA which is a composite code generated from the ELEMENT, SPECIES, and SEASONAL identifiers. This field needed to be modified by extending the field length from 8 to 16 characters (Text/String values). In order to retain the EL_SPE_SEA values as unique to each atlas edition, the original values of each ELE_SPE_SEA had the year of the atlas concatenated onto the END of it. In example, ELE_SPE_SEA of R0000501 became R00005012003, indicating ELEMENT = Reptile, SPECIES ID = 00005 (Leatherback Sea Turtle), SEASON_ID = 01 (listed as March-July) for the 2003 ESI Atlas (Statewide ESI 2003). The same attribute table schema modifications were performed on the 2012 geodata (Panhandle Florida), 2013 geodata (South Florida), and on the BIRDS (region.bio) geodata and tables for 2000. IMPORTANT NOTE: BIRDS (region.bio) and NESTS (points) from 2000 were used instead of the 2003 geodata because the updates to each of these layers and associated tables performed in 2003 only included a subset of the species that were included in 2000, so thus it was deemed that the 2000 data was superior and would be used instead. 8. Using the "Erase Features" tool in XTools Pro and the "Study Area" polygons of the 2012 Panhandle Florida ESI and 2013 South Florida ESI geodata, the areas of the statewide 2003 ESI geodata were systematically erased to prepare that data for merging with the newer geodata. The result was a fGDB of ESI geodata for the areas of Florida NOT updated in either the Panhandle or South Florida updates performed from 2010 to 2013 that additionally had the table and attribute modifications needed in order for the data to be smoothly mapjoined with all of the newer ESI data. 9. Using ArcCatalog and a copy of the South Florida ESI geodata and tables in a fGDB as a start, each of the layers within the Panhandle ESI were systematically imported, including tables, into the template "Composite Statewide" ESI file geodatabase. Once complete, each layer was viewed in comparison with its counterpart layer in the "erased 2003" geodata to ensure that no temporal overlap would occur in the data merge. 10. Using ArcCatalog, the "erased 2003" geodata were imported systematically into the merged Panhandle and South Florida ESI geodata (except for BIRDS and NESTS which were prepared separately using the geodata from 2000) to produce an "almost complete" Statewide Composite ESI" file geodatabase. Finally the appropriately and similarly prepared BIRDS and NESTS geodata and table records from 2000 were imported. In certain circumstances, some "cross-field mapping" was performed as needed to ensure that appropriate values were carried over into the final data schemas. This was largely done in the STATUS table because the schemas are radically different between 2003 data and the current (final) STATUS table schema used in the "Composite Statewide" 2013 geodata. QA and QC were then performed extensively using as series of Joins, Relates, and Queries, validating the soundness and completeness of the overall dataset. Process Date: Data have been sorted so that the draw order is from Upper left to lower right. Process Date: GeoPlan downloaded this data in shapefile format from the Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research Institute FTP site on July 1, 2014. The data was received as a shapefile in projection: Albers NAD 83. The dataset was then projected from Albers NAD 83 to FGDL Albers HPGN. - Added a FGDLAQDATE field based on date received from source - Renamed shapefile from ESI_Classification_ARC to senshr_2013 - Deleted fields SHAPE.LEN - Upcased all records in the attribute table - Added DESCRIPT field based on SHRT_DESC Process Date: 20140707

MAP PROJECTION PARAMETERS:

Projection                          ALBERS
Datum                               HPGN
Units                               METERS
Spheroid                            GRS1980
1st Standard Parallel               24  0  0.000
2nd Standard Parallel               31 30  0.000
Central Meridian                   -84 00  0.000
Latitude of Projection's Origin     24  0  0.000
False Easting (meters)              400000.00000
False Northing (meters)             0.00000

DATA SOURCE CONTACT (S):

Name:
Abbr. Name:
Address:


Phone:

Web site:
E-mail:
Contact Person:
         Phone:
        E-mail:

Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research Institute
FFWCC-FWRI
Fish and Wildlife Research Institute, 100 Eighth Avenue Southeast
St. Petersburg, Florida
33701
727-896-8626


http://myfwc.com/research
GISLibrarian@MyFWC.com
Andrew Hayslip

Name:                   FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name:             FGDL
Address:                Florida Geographic Data Library
                        431 Architecture Building
                        PO Box 115706
                        Gainesville, FL  32611-5706
Web site:               http://www.fgdl.org

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