[Metadata] Tropical storms, hurricanes, and tsunamis create waves that flood low-lying coastal areas. The National Flood Insurance Program (NFIP) produces flood insurance rate maps (FIRMs) that depict flood risk zones referred to as Special Flood Hazard Areas (SFHA) based modeling 1%-annual-chance flood event also referred to as a 100-year flood. The purpose of the FIRM is twofold: (1) to provide the basis for application of regulatory standards and (2) to provide the basis for insurance rating.SFHAs identify areas at risk from infrequent but severe storm-induced wave events and riverine flood events that are based upon historical record. By law (44 Code of Federal Regulations [CFR] 60.3), FEMA can only map flood risk that will be utilized for land use regulation or insurance rating based on historical data, therefore, future conditions with sea level rise and other impacts of climate change are not considered in FIRMs. It is important to note that FEMA can produce Flood Insurance Rate Maps that include future condition floodplains, but these would be considered “awareness” zones and not to be used for regulatory of insurance rating purposes.The State of Hawai‘i 2018 Hazard Mitigation Plan incorporated the results of modeling and an assessment of vulnerability to coastal flooding from storm-induced wave events with sea level rise (Tetra Tech Inc., 2018). The 1% annual-chance-coastal flood zone with sea level rise (1%CFZ) was modeled to estimate coastal flood extents and wave heights for wave-generating events with sea level rise. Modeling was conducted by Sobis Inc. under State of Hawaiʻi Department of Land and Natural Resources Contract No: 64064. The 1%CFZ with 3.2 feet of sea level rise was utilized to assess vulnerability to coastal event-based flooding in mid to - late century.The 1%CFZ with sea level rise would greatly expand the impacts from a 100-year flood event meaning that more coastal land area will be exposed to damaging waves. For example, over 120 critical infrastructure facilities in the City and County of Honolulu, including water, waste, and wastewater systems and communication and energy facilities would be impacted in the 1%CFZ with 3.2 feet of sea level rise (Tetra Tech Inc., 2018). This is double the number of facilities in the SFHA which includes the impacts of riverine flooding.A simplified version of the Wave Height Analysis for Flood Insurance Studies (WHAFIS) extension (FEMA, 2019b) included in Hazus-MH, was used to create the 1% annual chance coastal floodplain. Hazus is a nationally applicable standardized methodology that contains models for estimating potential losses from earthquakes, floods, tsunamis, and hurricanes (FEMA, 2019a). The current 1%-annual-chance stillwater elevations were collected using the most current flood insurance studies (FIS) for each island conducted by FEMA (FEMA, 2004, 2010, 2014, 2015). The FIS calculates the 1%-annual-chance stillwater elevation, wave setup, and wave run-up (called maximum wave crest) at regularly-spaced transects around the islands based on historical data. Modeling for the 1%CFZ used the NOAA 3-meter digital elevation model (DEM) which incorporates LiDAR data sets collected between 2003 and 2007 from NOAA, FEMA, the State of Hawaiʻi Emergency Management Agency, and the USACE (NOAA National Centers for Environmental Information, 2017).Before Hazus was run for future conditions, it was run for the current conditions and compared to the FEMA regulatory floodplain to determine model accuracy. This also helped determine the stillwater elevation for the large gaps between some transects in the FIS. Hazus was run at 0.5-foot stillwater level intervals and the results were compared to the existing Flood Insurance Rate Map (FIRM). The interval of 0.5-feet was chosen as a small enough step to result in a near approximation of the FIRM while not being too impractically narrow to require the testing of dozens of input elevations. The elevation which matched up best was used as the current base flood elevation.Key steps in modeling the projected 1%CFZ with sea level rise include: (1) generating a contiguous (no gaps along the shoreline) and present-day 1%-annual-chance stillwater elevation based on the most recent FIS, (2) elevating the present-day 1%-annual-chance stillwater elevation by adding projected sea level rise heights, and (3) modeling the projected 1%-annual-chance coastal flood with sea level rise in HAZUS using the 1%-annual-chance wave setup and run-up from the FIS. The 1%CFZ extent and depth was generated using the HAZUS 3.2 coastal flood risk assessment model, 3-meter DEM, the FIS for each island, and the IPCC AR5 upper sea level projection for RCP 8.5 scenario for 0.6 feet, 1.0 feet, 2.0 feet, and 3.2 feet of sea level rise above MHHW (IPCC, 2014). The HAZUS output includes the estimated spatial extent of coastal flooding as well as an estimated flood depth map grid for the four sea level rise projections.Using the current floodplain generated with Hazus, the projected 1%-annual-chance stillwater elevation was generated using the four sea level rise projections. This stillwater elevation with sea level rise was used as a basis for modeling. The projected 1%-annual coastal flood with sea level rise was modeled in Hazus using the current 1%-annual-chance wave setup and run-up from the FIS and the projected 1%-annual-chance stillwater elevation with sea level rise. Statewide GIS Program staff extracted individual island layers for ease of downloading. A statewide layer is also available as a REST service, and is available for download from the Statewide GIS geoportal at https://geoportal.hawaii.gov/, or at the Program's legacy download site at https://planning.hawaii.gov/gis/download-gis-data-expanded/#009. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/coastal_flood_zones_summary.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

The Protected Areas Database of the United States (PAD-US) is a geodatabase, managed by USGS GAP, that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The State, Regional and LCC geodatabases contain two feature classes. The PADUS1_3_FeeEasement feature class and the national MPA feature class. Legitimate and other protected area overlaps exist in the full inventory, with Easements loaded on top of Fee. Parcel data within a protected area are dissolved in this file that powers the PAD-US Viewer. As overlaps exist, GAP creates separate analytical layers to summarize area statistics for "GAP Status Code" and "Owner Name". Contact the PAD-US Coordinator for more information. The lands included in PAD-US are assigned conservation measures that qualify their intent to manage lands for the preservation of biological diversity and to other natural, recreational and cultural uses; managed for these purposes through legal or other effective means. The geodatabase includes: 1) Geographic boundaries of public land ownership and voluntarily provided private conservation lands (e.g., Nature Conservancy Preserves); 2) The combination land owner, land manager, management designation or type, parcel name, GIS Acres and source of geographic information of each mapped land unit 3) GAP Status Code conservation measure of each parcel based on USGS National Gap Analysis Program (GAP) protection level categories which provide a measurement of management intent for long-term biodiversity conservation 4) IUCN category for a protected area's inclusion into UNEP-World Conservation Monitoring Centre's World Database for Protected Areas. IUCN protected areas are defined as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" and are categorized following a classification scheme available through USGS GAP; 5) World Database of Protected Areas (WDPA) Site Codes linking the multiple parcels of a single protected area in PAD-US and connecting them to the Global Community. As legitimate and other overlaps exist in the combined inventory GAP creates separate analytical layers to obtain area statistics for "GAP Status Code" and "Owner Name". PAD-US version 1.3 Combined updates include: 1) State, local government and private protected area updates delivered September 2011 from PAD-US State Data Stewards: CO (Colorado State University), FL (Florida Natural Areas Inventory), ID (Idaho Fish and Game), MA (The Commonwealth's Office of Geographic Information Systems, MassGIS), MO (University of Missouri, MoRAP), MT (Montana Natural Heritage Program), NM (Natural Heritage New Mexico), OR (Oregon Natural Heritage Program), VA (Department of Conservation and Recreation, Virginia Natural Heritage Program). 2) Select local government (i.e. county, city) protected areas (3,632) across the country (to complement the current PAD-US inventory) aggregated by the Trust for Public Land (TPL) for their Conservation Almanac that tracks the conservation finance movement across the country. 3) A new Date of Establishment field that identifies the year an area was designated or otherwise protected, attributed for 86% of GAP Status Code 1 and 2 protected areas. Additional dates will be provided in future updates. 4) A national wilderness area update from wilderness.net 5) The Access field that describes public access to protected areas as defined by data stewards or categorical assignment by Primary Designation Type. . The new Access Source field documents local vs. categorical assignments. See the PAD-US Standard Manual for more information: gapanalysis.usgs.gov/padus 6) The transfer of conservation measures (i.e. GAP Status Codes, IUCN Categories) and documentation (i.e. GAP Code Source, GAP Code Date) from PAD-US version 1.2 or categorical assignments (see PAD-US Standard) when not provided by data stewards 7) Integration of non-sensitive National Conservation Easement Database (NCED) easements from August 2011, July 2012 with PAD-US version 1.2 easements. Duplicates were removed, unless 'Stacked' = Y and multiple easements exist. 8) Unique ID's transferred from NCED or requested for new easements. NCED and PAD-US are linked via Source UID in the PAD-US version 1.3 Easement feature class. 9) Official (member and eligible) MPAs from the NOAA MPA Inventory (March 2011, www.mpa.gov) translated into the PAD-US schema with conservation measures transferred from PAD-US version 1.2 or categorically assigned to new protected areas. Contact the PAD-US Coordinator for documentation of categorical GAP Status Code assignments for MPAs. 10) Identified MPA records that overlap existing protected areas in the PAD-US Fee feature class (i.e. PADUS Overlap field in MPA feature class). For example, many National Wildlife Refuges and National Parks are also MPAs and are represented in the PAD-US MPA and Fee feature classes.

[Metadata] Mean Annual Rainfall Isohyets in Millimeters for the Islands of Hawai‘i, Kaho‘olawe, Kaua‘i, Lāna‘i, Maui, Moloka‘i and O‘ahu. Source: 2011 Rainfall Atlas of Hawaii, https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Note that Moloka‘I data/maps were updated in 2014. Please see Rainfall Atlas final report appendix for full method details: https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Statewide GIS program staff downloaded data from UH Geography Department, Rainfall Atlas of Hawaii, February, 2019. Annual and monthly isohyets of mean rainfall were available for download. The statewide GIS program makes available only the annual layer. Both the monthly layers and the original annual layer are available from the Rainfall Atlas of Hawaii website, referenced above. Note: Contour attribute value represents the amount of annual rainfall, in millimeters, for that line/isohyet. For additional information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/isohyets.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] Underground Injection Control Line - POLYGONS (UIC Polys). NOTE: If you need to determine whether your parcel/project is above or below the UIC line, please contact the DOH Safe Drinking Water Branch (SDWB) at (808) 586-4258. This layer should be used ONLY as a low resolution/rough cut approximation of where the UIC lines are located. May, 2023 - Data is still current, per DOH SDWB. Upon request by the State DOH SDWB, the GIS Program made several modifications to this layer. 1. Changed the UIC_Code attributes from a numeric code field to a text field in order to add clarity to the meaning of the attribute values (whether the area was above or below the UIC line). 2. Created a uic_line layer from the uic_poly layer to reduce confusion when using the layer to depict and refer to the UIC "LINE" and to enable more straightforward symbolization of the layer. The uic_poly layer is being kept in place to allow for easier analysis. For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/uic_poly.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San Miguel-Ayanz, J., 2013. Toward open science at the European scale: Geospatial Semantic Array Programming for integrated environmental modelling. Geophysical Research Abstracts 15, 13245+. ISSN 1607-7962, European Geosciences Union (EGU).

This is the authors’ version of the work. The definitive version is published in the Vol. 15 of Geophysical Research Abstracts (ISSN 1607-7962) and presented at the European Geosciences Union (EGU) General Assembly 2013, Vienna, Austria, 07-12 April 2013http://www.egu2013.eu/

Toward open science at the European scale: Geospatial Semantic Array Programming for integrated environmental modelling

Daniele de Rigo ¹ ², Paolo Corti ¹ ³, Giovanni Caudullo ¹, Daniel McInerney ¹, Margherita Di Leo ¹, Jesús San-Miguel-Ayanz ¹ ¹ European Commission, Joint Research Centre, Institute for Environment and Sustainability,Via E. Fermi 2749, I-21027 Ispra (VA), Italy ² Politecnico di Milano, Dipartimento di Elettronica e Informazione,Via Ponzio 34/5, I-20133 Milano, Italy ³ United Nations World Food Programme,Via C.G.Viola 68 Parco dei Medici, I-00148 Rome, Italy

Excerpt: Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental, global) environmental problems need transdisciplinary integration within a context of modelling complexity and multiple sources of uncertainty. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. Approaches (either of computational science or of policy-making) suitable at a given domain-specific scale may not be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and corresponding policy-making. In WSTMe, the characteristic heterogeneity of available spatial information and complexity of the required data-transformation modelling (D-TM) appeal for a paradigm shift in how computational science supports such peculiarly extensive integration processes. In particular, emerging wide-scale integration requirements of typical currently available domain-specific modelling strategies may include increased robustness and scalability along with enhanced transparency and reproducibility. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP exploits the joint semantics provided by SemAP and geospatial tools to split a complex D-TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...]

This is not the most current data source. This service contains NPS fuels treatments documented in NFPORS and does NOT contain data after FY23. (September 30, 2023) To access fuels treatments occurring since then please use the IFPRS service or the Integrated Interagency Fuels Treatment (IIFT) service. IFPRSIIFTDocumenting, managing and protecting our lands in the National Park Service, remains fundamental to our understanding of the nationally significant landscapes we steward. The ability to use geographic information systems (GIS) to help manage all aspects of park operations, including wildland fire history and fuel treatments, provides the National Park Service with a powerful tool. In order to take advantage of this tool to adequately plan and maintain wildland fires among other daily activities, we must maintain accurate spatial information for wildland fire history and fuel treatments. This service displays our wildland fire history. It will assist in program direction, reporting and information requests. Purpose and BenefitsThe purpose of creating and utilizing such wildland fire history and fuel treatment spatial data services is to consolidate our wildland fire history and fuel treatment spatial data and integrate the existing feature attribute information into a national database for budgeting, reporting and planning purposes. Visualizing trends in wildland fire history data geographically through a GIS and accessing all available descriptive information at the same time, without needing to physically combine databases creates a powerful management tool. In this way, planners, resource managers, and superintendents can bring all of the various perspectives which may relate to a single wildland fire together via GIS, enabling them to visualize trends and explore how resources of different types may relate to each other and their contexts. Ultimately, use of the wildland fire history service will lead to more comprehensive access to all of our available wildland fire history and fuel treatment data and provide a more integrated approach to wildland fire data management across the NPS and at all levels: park, region and program. As resource specialists and managers continue to move their legacy data into the service and collect new data in the service, it will allow the NPS Fire Program to effectively budget, plan and manage future wildland fires and fuel treatments. LayersThis service is a combination of two feature classes the NPS Fire GIS program uses to store NPS fire program data agency wide. Each polygon feature displayed includes attributes from the shape's corresponding NFPORS Treatment record. Data is updated nightly to reflect any edits from NFPORS, NPS Treatment Inspector and edits made by Regional Fire GIS Specialists. TreatmentA point feature class representing past and future fuel treatments. This feature class is updated on a regular basis from the National Fire Plan Operations and Reporting System (NFPORS). Treatment records can be created for non-NFPORS treatments or for treatments before NFPORS began in 2003. The Treatment feature class has a many to many relationship to the Event feature class - meaning many treatments can have many events and vice versa. Event A polygon feature class representing completed events. This feature class will represent any complete treatments.

Table from the American Community Survey (ACS) 5-year series on disabilities and health insurance related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes C21007 Age by Veteran Status by Poverty Status in the Past 12 Months by Disability Status, B27010 Types of Health Insurance Coverage by Age, B22010 Receipt of Food Stamps/SNAP by Disability Status for Households. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

The Digital Geologic-GIS Map of Everglades National Park and Vicinity, Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (ever_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (ever_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (ever_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (ever_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (ever_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (ever_geology_metadata_faq.pdf). Please read the ever_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Florida Geological Survey and U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (ever_geology_metadata.txt or ever_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:675,000 and United States National Map Accuracy Standards features are within (horizontally) 342.9 meters or 1125 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

[Metadata] Mental Health Professional Shortage Areas as of April 2024. Source - Hawaii State Department of Health. Description: Designation of Health Professional Shortage Areas for Mental Health. See also Health Professional Shortage Areas for Dental Health and Primary Care. A Health Professional Shortage Area (HPSA) means any of the following which has a shortage of health professionals: (a) an urban or rural area which is a rational service area for the delivery of health services, (b) a population group, or (c) a public or nonprofit private medical facility. HPSAs are divided into three major categories according to the type of health professional shortage: primary care, dental or mental health HPSAs. For more information about HPSA’s, visit the Hawaii State Department of Health HPSA website at https://health.hawaii.gov/opcrh/home/health-professional-shortage-area-hpsa/. Hawaii Statewide GIS Program staff downloaded data from https://data.hrsa.gov/data/download?hmpgtitle=hmpg-hrsa-data April 2024. Projected to UTM Zone 4 NAD 83 HARN, and clipped to coastline. For additional information, please refer to summary metadata at https://files.hawaii.gov/dbedt/op/gis/data/hpsa.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

This database consists of a series of maps that depict the spatial distribution of nearshore topo-bathymetric transects perpendicular to the road and accompanying profiles that present elevation and depth values along these transects on the islands of Maui and Molokai.

Transects are identified by Francis et al. (2024a). State of Hawaii Department of Transportation (HDOT) state routes and Maui County Roads are acquired from HDOT (2023) and MC (2022). Shoreline datasets are provided by NGS (2017). Elevation and depth values along the transects are referenced to local mean sea level (LMSL) and are sampled from a digital elevation model (DEM) prepared by Francis et al. (2019).

References 1) Francis, O., Yang, L., & Togia, H. (2024a). Ocean Hazards Database (OHD) for the State of Hawaii Maui County Coastal Roads Report [Data set]. https://doi.org/10.17632/ndyy8nz77x.

2) Francis, O., Yang, L., Togia, H., & Tumino Di Costanzo, G. (2019). Ocean Hazards Database (OHD) for the State of Hawaii Statewide Coastal Highway Program Report [Data set]. https://doi.org/10.17632/7p3hyypmjm.

3) Francis, O., Zhang, G., Ma, D., Robertson, I., Togia, H., Yang, L., Eyre, K., Rossi, C., Martinez, B.A., Han, R., Hataishi, M., Hunter, N., Takahashi, C., Wang, Y., Yang, H., Zhou, S., & Yuan. R. (2024b). State of Hawaii Maui County coastal roads report. Prepared for the Maui County and State of Hawaii Department of Transportation, Project number HWY-L 2.3089, February 26, 2024.

4) HDOT (State of Hawaii Department of Transportation). (2023). “hpms” [shapefile]. Scale Not Given. HPMS (Highway Performance Monitoring System Roads for Hawaii - 2021). Hawaii Statewide GIS Program. Retrieved from https://files.hawaii.gov/dbedt/op/gis/data/hpms.shp.zip (September 2023).

5) MC (Maui County) (2022). “roads_mau” [shapefile]. Scale Not Given. Maui County Roads (2022). Hawaii Statewide GIS Program. Retrieved from https://files.hawaii.gov/dbedt/op/gis/data/roads_mau.shp.zip (September 2023).

6) NGS (National Geodetic Survey) (2017). National Oceanic and Atmospheric Administration (NOAA) Continually Updated Shoreline Product (CUSP). Retrieved from https://www.ngs.noaa.gov/CUSP/ (October 2017).

This dataset consists of summer temperature metrics for Boston, MA. These heat metrics summarize six CAPA Urban Heat Watch program temperature and heat index datasets using geographical boundaries from the Census Tract (CT) layer. Heat datasets were created by Museum of Science, Boston, and the Helmuth Lab at Northeastern University. Heat metrics are presented in the attribute table as mean values of each Heat Watch program dataset for all hexagon features. The six heat values included in this table are July 2019 temperature and heat index in degrees Fahrenheit for each of 3 1-hour periods -- 6 a.m., 3 p.m., and 7 p.m. EDT. The geographic boundaries used to summarize the heat metrics are current as of 2019.

[Metadata] Mean Annual Rainfall Isohyets in Inches for the Islands of Hawai‘i, Kaho‘olawe, Kaua‘i, Lāna‘i, Maui, Moloka‘i and O‘ahu. Source: 2011 Rainfall Atlas of Hawaii, https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Note that Moloka‘I data/maps were updated in 2014. Please see Rainfall Atlas final report appendix for full method details: https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Statewide GIS program staff downloaded data from UH Geography Department, Rainfall Atlas of Hawaii, February, 2019. Annual and monthly isohyets of mean rainfall were available for download. The statewide GIS program makes available only the annual layer. Both the monthly layers and the original annual layer are available from the Rainfall Atlas of Hawaii website, referenced above. For additional information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/isohyets.pdf or contact Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Table from the American Community Survey (ACS) 5-year series on education enrollment and attainment related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B14007/B14002 School Enrollment, B15003 Educational Attainment. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

Table from the American Community Survey (ACS) 5-year series on languages spoken and English ability related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B16004 Age by Language Spoken at Home by Ability to Speak English, C16002 Household Language by Household Limited English-Speaking Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

[Metadata] Underground Injection Control Line (UIC Line). NOTE: If you need to determine whether your parcel/project is above or below the UIC line, please contact the DOH Safe Drinking Water Branch (SDWB) at (808) 586-4258. This layer should be used ONLY as a low resolution/rough cut approximation of where the UIC lines are located. May, 2023 - Data is still current, per DOH SDWB. Upon request by the State DOH SDWB, the GIS Program made several modifications to this layer. 1. Created a uic_line layer from the uic_poly layer to reduce confusion when using the layer to depict and refer to the UIC "LINE" and to enable more straightforward symbolization of the layer. 2. Changed the UIC_Code attributes in the uic_poly layer from a numeric code field to a text field in order to add clarity to the meaning of the attribute values (whether the area was above or below the UIC line). For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/uic line.pdf or https://files.hawaii.gov/dbedt/op/gis/data/uic_poly.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] Medically Underserved Areas/Populations (MUA/P) for the State of Hawaii as of March 2025. Source: US Health Resources and Services Administration (HRSA). Downloaded by the Hawaii State GIS Program from the Federal Health Resources and Services Administrations (HRSA) website, 3/10/25 (https://data.hrsa.gov/data/download). These data describe geographic areas and populations with a lack of access to primary care health services. Medically Underserved Areas (MUAs) may be a whole county or a group of contiguous counties, a group of county or civil divisions or a group of urban census tracts in which residents have a shortage of personal health services. Medically Underserved Populations (MUPs) may include groups of persons who face economic, cultural or linguistic barriers to health care. HRSA's Bureau of Health Workforce develops shortage designation criteria and uses them to decide whether or not a geographic area or population group is a MUA or MUP.For more information about this layer and attribute values and meanings please see https://files.hawaii.gov/dbedt/op/gis/data/mua_medically_underserved_areas.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] Locations of community care foster family homes in the State of Hawaii as of November 2021. Source: Created by Hawaii Statewide GIS Program from data downloaded from Hawaii State Department of Health Office of Health Care Assurance (OHCA), November 2021. As defined in Hawaii Administrative Rules, (HAR 11-800), a community care foster family home is defined as any facility providing twenty four hour living accommodations, including personal care and homemaker services, for not more than two adults at any one time, at least one of whom shall be a Medicaid recipient, who are at the nursing facility level of care, who are unrelated to the foster family, and who are receiving the services of a licensed home and community-based case management agency. (See also §321-481, HRS).For more information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/Comm_Care_Foster_Family_Homes.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.