30 datasets found
  1. Data from: FCE Redlands Flood Zones, Miami-Dade County, South Florida

    • search.dataone.org
    • portal.edirepository.org
    Updated Feb 16, 2024
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    Jeff Onsted (2024). FCE Redlands Flood Zones, Miami-Dade County, South Florida [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-fce%2F1182%2F3
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    Dataset updated
    Feb 16, 2024
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Jeff Onsted
    Area covered
    Variables measured
    FID, AREA, ELEV, ZONE, Shape, PERIMETER, PFLOODZN_, ZONE_ELEV, PFLOODZN_I
    Description

    Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.

  2. a

    MDC FEMA Flood Zones Vector - Tile Layer

    • mdc.hub.arcgis.com
    Updated Jun 19, 2018
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    Miami-Dade County, Florida (2018). MDC FEMA Flood Zones Vector - Tile Layer [Dataset]. https://mdc.hub.arcgis.com/maps/ae7c7340ac6b43a28007db2442356177
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    Dataset updated
    Jun 19, 2018
    Dataset authored and provided by
    Miami-Dade County, Florida
    Area covered
    Description

    A polygon feature class that depicts the inundation limits representing flood risk information and supporting data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards, " Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP. The FIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The FIRM Database serves to archive the information collected during the Flood Risk Project.

  3. w

    Flood Zones - MDC_FEMAFloodZone

    • data.wu.ac.at
    • datadiscoverystudio.org
    xml
    Updated Sep 21, 2017
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    NSGIC Local Govt | GIS Inventory (2017). Flood Zones - MDC_FEMAFloodZone [Dataset]. https://data.wu.ac.at/schema/data_gov/MTI2ZDU1M2EtMGM4Yy00ZTM0LWExNzktZGEwMTcyYTNmYWUy
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    xmlAvailable download formats
    Dataset updated
    Sep 21, 2017
    Dataset provided by
    NSGIC Local Govt | GIS Inventory
    Area covered
    38f9a457bdf73733fe136288470c7984c1e20677
    Description

    Polygon feature class of Federal Emergency Management Agency (FEMA) Flood Hazard Zones for Miami-Dade County.

  4. w

    Flood Zones, Identify the boundaries of the Flood Zone area, Published in...

    • data.wu.ac.at
    html
    Updated Aug 19, 2017
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    NSGIC Local Govt | GIS Inventory (2017). Flood Zones, Identify the boundaries of the Flood Zone area, Published in 2012, 1:2400 (1in=200ft) scale, Miami-Dade County Government. [Dataset]. https://data.wu.ac.at/schema/data_gov/NGU2N2EwZGItODExYy00YWE3LTg0YzItYzgwNDg4MWMzZGRl
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    htmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Local Govt | GIS Inventory
    Area covered
    0b1e89cc9d39ec1f3546066574693bebfc66d3a8
    Description

    Flood Zones dataset current as of 2012. Identify the boundaries of the Flood Zone area.

  5. a

    Flood Zone

    • hub.arcgis.com
    • gis-mdc.opendata.arcgis.com
    Updated Feb 11, 2019
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    Miami-Dade County, Florida (2019). Flood Zone [Dataset]. https://hub.arcgis.com/maps/MDC::flood-zone
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    Dataset updated
    Feb 11, 2019
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    A table of the Flood Zones.Updated: Every 10 yrs

  6. a

    FEMA Flood Zone

    • hub.arcgis.com
    • gis-mdc.opendata.arcgis.com
    Updated Dec 26, 2021
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    Miami-Dade County, Florida (2021). FEMA Flood Zone [Dataset]. https://hub.arcgis.com/datasets/MDC::fema-flood-zone/about
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    Dataset updated
    Dec 26, 2021
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    A polygon feature class of Federal Emergency Management Agency (FEMA) flood hazard zones within Miami-Dade County. The data depicts the inundation limits representing flood risk information and supporting data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

  7. a

    FEMA Flood Zone 1994

    • hub.arcgis.com
    • gis-mdc.opendata.arcgis.com
    Updated Jun 5, 2018
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    Miami-Dade County, Florida (2018). FEMA Flood Zone 1994 [Dataset]. https://hub.arcgis.com/datasets/MDC::fema-flood-zone-1994
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    Dataset updated
    Jun 5, 2018
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    A polygon feature class of the Federal Emergency Management Agency (FEMA) Flood Zones for Miami-Dade County (1994).Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

  8. Building damage costs due to flood risk in the U.S. 2022, by metro area

    • statista.com
    Updated Aug 8, 2023
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    Statista (2023). Building damage costs due to flood risk in the U.S. 2022, by metro area [Dataset]. https://www.statista.com/statistics/1291811/structural-damage-costs-due-to-flood-in-buildings-by-metro-area-us/
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    Dataset updated
    Aug 8, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In 2022, Miami, FL was the U.S. metropolitan area with the highest structural damage costs due to flood risk across office, retail, and multi-residential buildings. At the time, costs to repair damages or replace buildings at flood risk at this metro area were estimated at over one billion U.S. dollars. Trailing second was New York's metro area, with an estimated expense of 582 million dollars. New York was also the U.S. metropolitan area with the highest number of buildings at flood risk, with a over 30 thousand retail, office, and multi-residential buildings.

  9. u

    50-year mean elevation

    • marine.usgs.gov
    Updated Jun 4, 2025
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    (2025). 50-year mean elevation [Dataset]. https://marine.usgs.gov/coastalchangehazardsportal/ui/info/item/K5dTw4co
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    Dataset updated
    Jun 4, 2025
    Area covered
    Description

    The flooding extent polygons are based on wave-driven total water levels for the coral reef-lined coast of Florida. The wave and sea level conditions were propagated using the XBeach open-source model (available at https://oss.deltares.nl/web/xbeach) over 100-m spaced shore-normal transects modified to account for base, mean elevation, and mean erosion scenarios. The impact of future coral reef degradation on coastal protection was examined for two different seafloor elevation-change scenarios based on DEM projections of the study area out 100 years from 2001 using either 1) historical rates of mean elevation-change as a conservative change model, or 2) historical rates of mean erosion. Methods describing the generation of the 'mean elevation' and 'mean erosion' scenarios are described in detail in Yates and others (2018, 2019a, and 2019b). The greater colonization results in higher rugosity and thus hydrodynamic roughness via friction and was parameterized per van Dongeren and others (2013) and Quataert and others (2015). Where the locations along each transect were coincident with one of the damage-assessment locations, a reduction in roughness, and/or an increase in profile depth were applied. The changes to bathymetry and roughness were then carried on to each XBeach model run to ascertain the change in flooding during large storm events due to the projected reef degradation. These flood extents can be combined with economic, ecological, and engineering tools to provide a rigorous financial valuation of the projected future coastal protection benefits of Florida’s coral reefs.

  10. K

    Miami Valley Regional Planning Commission Floodplain

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Jan 10, 2023
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    State of Ohio (2023). Miami Valley Regional Planning Commission Floodplain [Dataset]. https://koordinates.com/layer/112020-miami-valley-regional-planning-commission-floodplain/
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    shapefile, mapinfo tab, kml, geopackage / sqlite, mapinfo mif, csv, geodatabase, dwg, pdfAvailable download formats
    Dataset updated
    Jan 10, 2023
    Dataset authored and provided by
    State of Ohio
    Area covered
    Description

    Geospatial data about Miami Valley Regional Planning Commission Floodplain. Export to CAD, GIS, PDF, CSV and access via API.

  11. a

    County Flood Criteria 2022

    • gis-mdc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Dec 31, 2022
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    Miami-Dade County, Florida (2022). County Flood Criteria 2022 [Dataset]. https://gis-mdc.opendata.arcgis.com/datasets/MDC::county-flood-criteria-2022/about
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    Dataset updated
    Dec 31, 2022
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    A polygon feature class of the county flood criteria boundaries within Miami-Dade County. The purpose of the Miami-Dade County Flood Criteria Map is to determine the minimum ground surface elevation of developed properties, crown/grade of roads, and secondary canal banks based on a 10-year, 24-hour storm event, 2060 scenario with SLR, and the minimum top elevation of seawalls, unless higher elevations are required by other regulatory applicable standards.Available for review and comment October 22, 2021 through December 22, 2021.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

  12. NOAA Office for Coastal Management Coastal Inundation Digital Elevation...

    • catalog.data.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Florida, Keys [Dataset]. https://catalog.data.gov/dataset/noaa-office-for-coastal-management-coastal-inundation-digital-elevation-model-florida-keys1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Florida, Florida Keys
    Description

    These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Florida Keys digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Miami-Dade and Monroe Counties. The DEM was produced from the following lidar data sets: 1. 2015 Miami-Dade County, Florida Lidar 2. 2015 NOAA NGS Topobathy Lidar: Dry Tortugas 3. 2018 - 2019 NOAA NGS Topobathy Lidar Hurricane Irma: Miami to Marquesas Key, FL The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

  13. a

    FEMA 100 Year Flood Zones

    • geospark-mvrpc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jul 25, 2013
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    Miami Valley Regional Planning Commission (2013). FEMA 100 Year Flood Zones [Dataset]. https://geospark-mvrpc.opendata.arcgis.com/maps/58b828218d724cf99bbf1d3572c44d8d
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    Dataset updated
    Jul 25, 2013
    Dataset authored and provided by
    Miami Valley Regional Planning Commission
    Area covered
    Description

    This map represents Flood Insurance Rate Map (FIRM) data important for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). The 100-year flood is referred to as the 1% annual exceedance probability flood, since it is a flood that has a 1% chance of being equaled or exceeded in any single year.

  14. m

    Data from: Comparing first street foundation and PRIMo flood hazard data...

    • scholarship.miami.edu
    Updated Jul 8, 2024
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    Jochen Schubert; Brett Sanders; Katharine Mach (2024). Comparing first street foundation and PRIMo flood hazard data across the Los Angeles metropolitan region [Dataset]. https://scholarship.miami.edu/esploro/outputs/dataset/Comparing-first-street-foundation-and-PRIMo/991032075183802976
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    Dataset updated
    Jul 8, 2024
    Dataset provided by
    Dryad
    Authors
    Jochen Schubert; Brett Sanders; Katharine Mach
    Time period covered
    Jul 8, 2024
    Area covered
    Greater Los Angeles, Los Angeles
    Description

    Extreme flooding events are becoming more frequent and costly, and impacts have been concentrated in cities where exposure and vulnerability are both heightened. To manage risks, governments, the private sector, and households now rely on flood hazard data from national-scale models that lack accuracy in urban areas due to unresolved drainage processes and infrastructure. The data in this repository supports an assessment of the uncertainties of First Street Foundation (FSF) flood hazard data, available across the U.S.. For the analysis, FSF data was compared to PRIMo-Drain, a flood hazard model that resolves drainage infrastructure and fine resolution drainage dynamics. In the linked journal manuscript, using the case of Los Angeles, California, we find that FSF and PRIMo-Drain estimates of population and property value exposed to 1%- and 5%-annual-chance hazards diverge at finer scales of governance, for example by 4- to 18-fold at the municipal scale. FSF and PRIMo-Drain data often predict opposite patterns of exposure inequality across social groups (e.g., Black, White, Disadvantaged). Further, at the county scale, we compute a Model Agreement Index of only 24%—a ~1 in 4 chance of models agreeing upon which properties are at risk. Collectively, these differences point to limited capacity of FSF data to confidently assess which municipalities, social groups, and individual properties are at risk of flooding within urban areas. These results caution that national-scale model data at present may misinform urban flood risk strategies and lead to maladaptation, underscoring the importance of refined and validated urban models.

  15. a

    County Flood Criteria 2022 - Raster

    • gis-mdc.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Dec 28, 2023
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    Miami-Dade County, Florida (2023). County Flood Criteria 2022 - Raster [Dataset]. https://gis-mdc.opendata.arcgis.com/documents/68ee47dfc3af4b8daa7d63ebdbb0d165
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    Dataset updated
    Dec 28, 2023
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    A raster dataset of the county flood criteria boundaries within Miami-Dade County. The purpose of the Miami-Dade County Flood Criteria Map is to determine the minimum ground surface elevation of developed properties, crown/grade of roads, and secondary canal banks based on a 10-year, 24-hour storm event, 2060 scenario with SLR, and the minimum top elevation of seawalls, unless higher elevations are required by other regulatory applicable standards. Available for review and comment October 22, 2021 through December 22, 2021.Download County Flood Criteria Raster

  16. a

    Coastal A Zone

    • gis-mdc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jun 5, 2018
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    Miami-Dade County, Florida (2018). Coastal A Zone [Dataset]. https://gis-mdc.opendata.arcgis.com/datasets/coastal-a-zone
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    Dataset updated
    Jun 5, 2018
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    A polygon feature class of the Coastal A Zone boundaries. Developed to aid the spatial location of the Coastal A Zones in Miami-Dade County for permitting purposes. Based on the Miami-Dade County Digital Flood Insurance Rate Map (DFIRM), effective September 11, 2009 published by FEMA and the ASCE 24 guidelines. 'Coastal A� Zone according to FEMA, is the area landward of a V Zone or landward of an open coast without mapped V Zones. In a coastal A Zone, the principal source of flooding will be astronomical tides, storm surges, seiches or tsunamis and not riverine flooding. During base flood conditions, the potential for breaking wave heights between 1.5 feet and 3.0 ft, will exist.Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

  17. g

    NOAA Office for Coastal Management Coastal Inundation Digital Elevation...

    • gimi9.com
    Updated Apr 28, 2018
    + more versions
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    (2018). NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Florida, SW [Dataset]. https://gimi9.com/dataset/data-gov_noaa-office-for-coastal-management-coastal-inundation-digital-elevation-model-florida-sw1/
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    Dataset updated
    Apr 28, 2018
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Florida
    Description

    These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Florida, SW digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Charlotte, Collier, Glades, Hendry, Miami-Dade, Monroe, and Palm Beach Counties. The DEM was produced from the following lidar data sets: 1. 2018 Florida Peninsular FDEM - Charlotte 2. 2018 Florida Peninsular - Collier 3. 2017 Everglades FL Lidar 4. 2018 West Everglades Topobathy NP FL Lidar 5. 2018 Southeast FL Lidar (B1, B2, TL) 6. 2018 Southwest FL Lidar (A, B, B TL) 7. 2018 Florida Peninsular FDEM - Glades 8. 2018 Florida Peninsular FDEM - Hendry 9. 2015 Miami-Dade County, Florida Lidar 10. 2017 Palm Beach County, Florida Lidar 11. 2014 Seminole Tribe Big Cypress Reservation Lidar The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

  18. a

    Property Card

    • hub.arcgis.com
    Updated Apr 5, 2021
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    CityMiamiFL (2021). Property Card [Dataset]. https://hub.arcgis.com/datasets/f12e4de69f2a474a8c29c8e8664f75c2
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    Dataset updated
    Apr 5, 2021
    Dataset authored and provided by
    CityMiamiFL
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This point geographic dataset contains general information about the properties located within the City of Miami. This feature layer detailed information about zoning, flood zones, code enforcement, city commissioners and other relevant information for each of the properties found within the City of Miami limits.

  19. a

    FEMA Panel 1994

    • hub.arcgis.com
    Updated Jun 5, 2018
    + more versions
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    Miami-Dade County, Florida (2018). FEMA Panel 1994 [Dataset]. https://hub.arcgis.com/maps/MDC::fema-panel-1994
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    Dataset updated
    Jun 5, 2018
    Dataset authored and provided by
    Miami-Dade County, Florida
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    A polygon feature class of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Map (FIRM) map panels for Miami-Dade County (1994).Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

  20. a

    Flood Hazard

    • hub.arcgis.com
    • geospark-mvrpc.opendata.arcgis.com
    Updated Jan 7, 2025
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    Miami Valley Regional Planning Commission (2025). Flood Hazard [Dataset]. https://hub.arcgis.com/maps/MVRPC::flood-hazard-2
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    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Miami Valley Regional Planning Commission
    Area covered
    Description

    This layer represents Flood Insurance Rate Map (FIRM) data important for
    floodplain management, mitigation, and insurance activities for the
    National Flood Insurance Program (NFIP). The 100-year flood is referred to as the 1% annual exceedence probability flood, since it is a flood that has a 1% chance of being equaled or
    exceeded in any single year.

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Jeff Onsted (2024). FCE Redlands Flood Zones, Miami-Dade County, South Florida [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-fce%2F1182%2F3
Organization logo

Data from: FCE Redlands Flood Zones, Miami-Dade County, South Florida

Related Article
Explore at:
Dataset updated
Feb 16, 2024
Dataset provided by
Long Term Ecological Research Networkhttp://www.lternet.edu/
Authors
Jeff Onsted
Area covered
Variables measured
FID, AREA, ELEV, ZONE, Shape, PERIMETER, PFLOODZN_, ZONE_ELEV, PFLOODZN_I
Description

Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.

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