The Maine Silver Jackets team developed a set of coastal flood risk data layers to support local resilience planning. The USACE New England District modeled three different storm intensities (10-yr, 25-yr, and 100-yr) based on historic analogues (Patriot's Day Storm of April 15-17, 2007; Bomb Cyclone of Jan 4-6, 2018; and the Blizzard of Feb 4-10, 1978), and four different sea level heights (0, 1.5, 3.0, 3.9, and 8.8 feet above current mean higher-high water, NTDE 1983-2001). Tides, sea level rise scenarios, and riverine discharges were added as boundary conditions to the Coastal Modeling System framework (CMS-Flow), a hydrodynamic model solving for depth-averaged circulation. This was coupled with a spectral wave transformation model, CMS-Wave, to compute wave statistics and account for wave setup within the model domain. The resulting model information was provided as sets of nodes, or points, representing grid cell centroids (easting and northing) and maximum water level values referenced to NAVD88. These sets of model nodes were post-processed by NOAA to generate a single set of clean, consistent, merged, and spatially-referenced points. The points were used to interpolate raster-based water surface elevation data which became the basis for inundation mapping. High resolution lidar-derived elevation data were compiled with breaklines representing shorelines and waterfront infrastructure to generate a physical representation against which the storm-generated water surface elevation data were compared. Inundation depth grids and flood extent polygons were produced as final data layers.

Street centerline network for the City of Portland, Multnomah County, Clackamas County and Washington County developed for geocoding purposes. This dataset has a character (textual) street number field to better allow for locating addresses that have leading zeros (e.g., 0680 SW Bancroft St.). This dataset does not yet include the data fields and structure necessary for performing routing operations.--Additional Information: Category: Transportation - Streets Purpose: Provides a dataset including all address segments to be used for geocoding (locating) addresses in the Portland Region. Includes the capability to search those addresses whose street number begins with a zero.-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=52067

Council_Districts

Tile Download Link 2005 6" pixel resolution orthoimagery of South Portland from May 6, 2005. Provided by the Maine Office of GIS and the Maine GeoLibrary Board. As the prime contractor, Bradstreet Consultants, Inc. used the aerial photography flown in one session on May 6, 2005, by Richard Crouse & Associates, Inc. of Frederick, MD who acquired approximately 1335 photos @ 1"=600' with airborne GPS using a Wild RC-30 (#13261) aerial camera. Bradstreet Consultants, Inc. painted and repainted ground targets for photo survey control points (~200) to support full analytical aerotriangulation. The aerotriangulation solution was used to set up each stereopair of photos for orthorectification and DTM compilation. The ortho imagery was created by scanning (14 microns (um) per pixel or 1815 dpi) the original 1"=600' scale film and employing a digital terrain model (DTM) from updating some town's original DTM and some town's from scratch using the 1"=600' scale negatives or diapositives using both analytical and softcopy (digital) stereoplotter in the Kork KDMS format.

Maine Statewide Orthoimagery Project - During the spring of 2020 new 4-band (R, G, B, and NIR) aerial imagery was acquired covering the entire project area using Leica ADS digital camera systems. All imagery was collected during the 2022 spring flying season during leaf-off conditions for deciduous vegetation in the State of Maine. The sun angle shall be 25-degrees or greater, and streams should be within their normal banks, unless otherwise negotiated. During flight planning and acquisition, a significant effort is made to limit clouds, snow (please note: small amounts of snow such as piles in parking lots, extreme shaded areas, within dense evergreens or unpopulated northern facing slopes may be acceptable), fog, haze, smoke, or other ground obscuring conditions in the imagery. In no case will the maximum cloud cover exceed 5% per image. Within the immediate areas of power plants, factories, or controlled agricultural burns some steam or smoke and/or shadows may be visible on imagery. Woolpert produced new 8-bit, 4-band stacked color digital orthoimagery files in GeoTIFF format with TFW “world file” at a 45cm (18-inch), 30cm (12-inch), 15cm (6-inch) and 7.5cm (3-inch).The Maine GeoLibrary Board has developed a statewide, 5-year, rotating orthoimagery acquisition program for Maine to facilitate state, regional and local government GIS base mapping in an efficient and cost-effective program. The State of Maine will use digital orthoimagery for the development of various base map products in a computerized GIS that will support the needs of the state and multiple stakeholders through applications, such as, multi-jurisdictional homeland security mapping applications, state and county emergency management applications, regional and local planning, state and local public safety applications, economic development and other GIS business objectives.

This dataset shows sidewalks in the PACTS member communities. There are attributes for sidewalk material, width, condition, curbing, etc. but these attributes may not be available for all features due to differences in data collection in different municipalities. This layer is based on the MaineDOT sidewalk layer. Local sidewalk data have been added from South Portland, Scarborough, Windham, Falmouth, and Yarmouth. This dataset was compiled on April 26, 2022. The MaineDOT data are current as of 4/26/2022, but some of the local data sources may be 5-10 years out of date. The location of the sidewalk is still accurate, but the condition, materials, etc. may have changed and there may be new sidewalks.

These data were automated to provide an accurate high-resolution historical shoreline of Columbia River - Portland, Oregon suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

description: Abstract: Monthly and annual average solar resource potential for the lower 48 states of the United States of America. Purpose: Provide information on the solar resource potential for the United States of America lower 48 states. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location. Supplemental Information: This data provides monthly average and annual average daily total solar resource averaged over surface cells of approximatley 40 km by 40 km in size. This data was developed from the Climatological Solar Radiation (CSR) Model. The CSR model was developed by the National Renewable Energy Laboratory for the U.S. Department of Energy. Specific information about this model can be found in Maxwell, George and Wilcox (1998) and George and Maxwell (1999). This model uses information on cloud cover, atmostpheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 7-year histogram (1985-1991) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data are obtained from the National Climatic Data Center in Ashville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalible at a 40km resolution. As a result, it is believed that the modeled values are accurate to approximately 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Units are in kilowatt hours per meter squared per day. OtherCitation Details: George, R, and E. Maxwell, 1999: "High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model", Proceedings of the 1999 Annual Conference, American Solar Energy Society, Portland, ME. Maxwell, E, R. George and S. Wilcox, "A Climatological Solar Radiation Model", Proceedings of the 1998 Annual Conference, American Solar Energy Society, Albuquerque NM. Marion, William and Stephen Wilcox, 1994: "Solar Radiation Data Manual for Flat-plate and Concentrating Collectors". NREL/TP-463-5607, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401. ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data. Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data. THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA. The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.; abstract: Abstract: Monthly and annual average solar resource potential for the lower 48 states of the United States of America. Purpose: Provide information on the solar resource potential for the United States of America lower 48 states. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, oriented due south at an angle from horizontal equal to the latitude of the collector location. Supplemental Information: This data provides monthly average and annual average daily total solar resource averaged over surface cells of approximatley 40 km by 40 km in size. This data was developed from the Climatological Solar Radiation (CSR) Model. The CSR model was developed by the National Renewable Energy Laboratory for the U.S. Department of Energy. Specific information about this model can be found in Maxwell, George and Wilcox (1998) and George and Maxwell (1999). This model uses information on cloud cover, atmostpheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 7-year histogram (1985-1991) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data are obtained from the National Climatic Data Center in Ashville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalible at a 40km resolution. As a result, it is believed that the modeled values are accurate to approximately 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. Units are in kilowatt hours per meter squared per day. OtherCitation Details: George, R, and E. Maxwell, 1999: "High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model", Proceedings of the 1999 Annual Conference, American Solar Energy Society, Portland, ME. Maxwell, E, R. George and S. Wilcox, "A Climatological Solar Radiation Model", Proceedings of the 1998 Annual Conference, American Solar Energy Society, Albuquerque NM. Marion, William and Stephen Wilcox, 1994: "Solar Radiation Data Manual for Flat-plate and Concentrating Collectors". NREL/TP-463-5607, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401. ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data. Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data. THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN

Points representing the locations of verified active addresses in the Portland Metro Region. Addresses been culled from the City of Portland Master Address Repository, Multnomah County Assessor Records and the RLIS Master Address Points dataset.--Additional Information: Category: Address Purpose: For mapping, geocoding, mailing, and analysis of addresses in the Portland Metro Region. Update Frequency: Twice Weekly-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=54157

The Maine Silver Jackets team developed a set of coastal flood risk data layers to support local resilience planning. The USACE New England District modeled three different storm intensities (10-yr, 25-yr, and 100-yr) based on historic analogues (Patriot's Day Storm of April 15-17, 2007; Bomb Cyclone of Jan 4-6, 2018; and the Blizzard of Feb 4-10, 1978), and four different sea level heights (0, 1.5, 3.0, 3.9, and 8.8 feet above current mean higher-high water, NTDE 1983-2001). Tides, sea level rise scenarios, and riverine discharges were added as boundary conditions to the Coastal Modeling System framework (CMS-Flow), a hydrodynamic model solving for depth-averaged circulation. This was coupled with a spectral wave transformation model, CMS-Wave, to compute wave statistics and account for wave setup within the model domain. The resulting model information was provided as sets of nodes, or points, representing grid cell centroids (easting and northing) and maximum water level values referenced to NAVD88. These sets of model nodes were post-processed by NOAA to generate a single set of clean, consistent, merged, and spatially-referenced points. The points were used to interpolate raster-based water surface elevation data which became the basis for inundation mapping. High resolution lidar-derived elevation data were compiled with breaklines representing shorelines and waterfront infrastructure to generate a physical representation against which the storm-generated water surface elevation data were compared. Inundation depth grids and flood extent polygons were produced as final data layers.

Lines representing the top of the South Waterfront riverbank (Willamette River). https://www.portlandoregon.gov/bps/article/53363-- Additional Information: Category: Zoning Code Purpose: Use for applying zoning restrictions and development requirements in the South Waterfront area of Portland. Update Frequency: As Needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=52755

Feature class that compare the elevations between seawall crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland). The dataset included the development of an inventory of coastal armor structures from a range of different datasets. Feature classes include the following:

Defines the boundary of the Columbia South Shore Protection Zone-- Additional Information: Category: Boundary Purpose: To allow Bureau staff to design, construct, utilize, analyze and manage the Bureau's water supply and distribution system. Update Frequency: As needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=53757

Polygon representing an area of the River General (g) greenway overlay zone for South Waterfront development. https://www.portlandoregon.gov/bps/article/53363-- Additional Information: Category: Zoning Code Purpose: For mapping the General (g) overlay zone in South Waterfront. Update Frequency: As Needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=52732

Feature class that compares the elevations between sand dune crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland).

Archaeological evidence has confirmed that American Indians used the area prior to the entry of Euro-Americans to the Portland area. Archaeological resources have historic, cultural, and scientific value to the general public and heritage value to the associated tribes, whose ancestors lived in the plan district area and harvested local natural resources for subsistence and spiritual/ceremonial uses. https://www.portlandoregon.gov/bps/article/53364-- Additional Information: Category: Zoning Code Purpose: Protect inventoried significant archaeological resources and their functional values in the Columbia South Shore Plan District and South Reach River Overlay in a way that increases certainty of development potential. Update Frequency: As Needed-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=53428

This layer was developed by GPCOG based on information available in each transit agency's route maps, as well as the Southern Maine Transit Tracker website. The following transit agencies are included:METROSouth Portland Bus ServiceShuttlebus-ZOOMRTP's Lakes Region ExplorerCasco Bay LinesChebeague Transportation CompanyNNEPRA's Amtrak DowneasterThe routes in this layer are up to date as of 7/11/24 and to the best of our knowledge.

Set of all the USGS 24k Quadrangle maps that intersect Eaton County, Michigan.The quadrangles included are Aurelius, Bellevue, Charlotte, Chester, Dimondale, Duck Lake, Eagle, Eaton Rapids, Hoytville, Lansing North, Lansing South, Nashville, Needmore, Olivet, Onondaga, Portland South, Saubee Lake, Springport, Wacousta, and Woodbury. They are all the 2019 versions of the maps except Needmore, which is 2017. These maps were acquired by download from the National Map Viewer.https://www.usgs.gov/core-science-systems/ngp/tnm-delivery/ on 1/9/2020.

Willamette River Study Boundary by reach (North, Central, South Waterfront, South) for Planning purposes.-- Additional Information: Category: Boundary Purpose: Map river reach boundaries defined for River Environmental Planning. Update Frequency: Infrequent-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60873