Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The mapping dataset was created specifically for static mapping purposes in order to visually emphasize asset locations and symbology. This dataset represents the point feature type of the mapping dataset.
Service Item Id: 72933f447e6f476783b60507ef504b04
Copyright Text: Cummins Cederberg, Inc., Halff Associates, Inc.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The analysis dataset joined critical asset point data that fell completely within 2020 parcel data (Source: FGDL) utilizing a spatial join. This step was necessary in order to better reflect potential impact when intersecting with flood scenario vector data. This dataset represents the point feature type of the analysis dataset.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The mapping dataset was created specifically for static mapping purposes in order to visually emphasize asset locations and symbology. This dataset represents the polyline feature type of the mapping dataset.
Service Item Id: 72933f447e6f476783b60507ef504b04
Copyright Text: Cummins Cederberg, Inc., Halff Associates, Inc.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The analysis dataset joined critical asset point data that fell completely within 2020 parcel data (Source: FGDL) utilizing a spatial join. This step was necessary in order to better reflect potential impact when intersecting with flood scenario vector data. This dataset represents the polyline feature type of the analysis dataset.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicVisual_A = Visual analysis to determine if critical asset infrastructure intersects the FEMA Floodplain; If so, the storm event is recorded.Due to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The analysis dataset joined critical asset point data that fell completely within 2020 parcel data (Source: FGDL) utilizing a spatial join. This step was necessary in order to better reflect potential impact when intersecting with flood scenario vector data. This dataset represents the polygon feature type of the analysis dataset.A visual analysis was performed on critical assets for all nine counties to determine their vulnerability. The parcels intersecting the FEMA Special Flood Hazard Areas were identified for further review. The critical assets were then manually inspected to determine the proximity of the FEMA floodplain to buildings and other infrastructure on the site, including parking lots, and entry roads. The resulting vulnerable assets were identified and the related storm event was recorded. This process filtered out instances where the intersecting SFHA was not adjacent to the infrastructure.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The mapping dataset was created specifically for static mapping purposes in order to visually emphasize asset locations and symbology. This dataset represents the polygon feature type of the mapping dataset.
Service Item Id: 72933f447e6f476783b60507ef504b04
Copyright Text: Cummins Cederberg, Inc., Halff Associates, Inc.
Description: GIS datasets were obtained from local, statewide, and nationwide data sources to identify critical and regionally significant assets located throughout the Apalachee Regional Planning Council (ARPC) region. These available datasets were reviewed by a team of coastal engineers, water resource professionals, GIS analysts, and local government staff to verify potential data overlap and potential data gaps prior to analysis. All critical asset data were first organized by asset type and source within each of the four Statute required critical asset categories (Transportation, Critical Community and Emergency Facilities, Critical Infrastructure, and Natural Cultural and Historic Resources). Critical asset types that had multiple, qualifying datasets were analyzed spatially to determine areas of overlap, in order to identify and produce final primary and secondary source data layers that eliminated duplicate data. The final critical asset data were merged by GIS feature type (point, polyline, and polygon) to reduce the number of layers used as inputs in following geoprocessing tasks. The original attribute tables for the final, merged critical asset layers were simplified to retain only complete, pertinent fields and new attribute fields were added to enable more efficient querying, sorting, and analysis of the data. The newly added fields, specifically LYR_Name and LYR_Source, can also be used to link back to their original dataset source information that can be found in tables 2, 3, 4, and 5 of the report, Apalachee Regional Vulnerability Assessment: An Evaluation of Current and Future Flood Risks Across the Nine-County Region. These new attribute fields include:Asset_Cate = Critical Asset CategoryCrit_Asset = Critical Asset TypeLYR_Name = Critical Asset GIS Layer NameLYR_Source = Critical Asset GIS Layer SourceCounty_New = Florida County where Critical Asset ResidesOwnership = Critical Asset Ownership Type; Private or PublicDue to significant amounts of data and the mapping extents required to show the full County limits for statics maps in the Apalachee Regional Vulnerability Assessment report, two separate datasets were created, one for mapping and one for analysis. The analysis dataset joined critical asset point data that fell completely within 2020 parcel data (Source: FGDL) utilizing a spatial join. This step was necessary in order to better reflect potential impact when intersecting with flood scenario vector data. This dataset represents the polygon feature type of the analysis dataset.