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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Purpose: This is an ArcGIS Pro template that GIS Specialists can use to identify vulnerable populations and special needs infrastructure most at risk to flooding events.How does it work?Determine and understand the Place Vulnerability (based on Cutter et al. 1997) and the Special Needs Infrastructure for an area of interest based on Special Flood Hazard Zones, Social Vulnerability Index, and the distribution of its Population and Housing units. The final product will be charts of the data distribution and a Hosted Feature Layer. See this Story Map example for a more detailed explanation.This uses the FEMA National Flood Hazard Layer as an input (although you can substitute your own flood hazard data), check availability for your County before beginning the Task: FEMA NFHL ViewerThe solution consists of several tasks that allow you to:Select an area of interest for your Place Vulnerability Analysis. Select a Hazard that may occur within your area of interest.Select the Social Vulnerability Index (SVI) features contained within your area of interest using the CDC’s Social Vulnerability Index (SVI) – 2016 overall SVI layer at the census tract level in the map.Determine and understand the Social Vulnerability Index for the hazard zones identified within you area of interest.Identify the Special Needs Infrastructure features located within the hazard zones identified within you area of interest.Share your data to ArcGIS Online as a Hosted Feature Layer.FIRST STEPS:Create a folder C:\GIS\ if you do not already have this folder created. (This is a suggested step as the ArcGIS Pro Tasks does not appear to keep relative paths)Download the ZIP file.Extract the ZIP file and save it to the C:\GIS\ location on your computer. Open the PlaceVulnerabilityAnalysis.aprx file.Once the Project file (.aprx) opens, we suggest the following setup to easily view the Tasks instructions, the Map and its Contents, and the Databases (.gdb) from the Catalog pane.The following public web map is included as a Template in the ArcGIS Pro solution file: Place Vulnerability Template Web MapNote 1:As this is a beta version, please take note of some pain points:Data input and output locations may need to be manually populated from the related workspaces (.gdb) or the tools may fail to run. Make sure to unzip/extract the file to the C:\GIS\ location on your computer to avoid issues.Switching from one step to the next may not be totally seamless yet.If you are experiencing any issues with the Flood Hazard Zones service provided, or if the data is not available for your area of interest, you can also download your Flood Hazard Zones data from the FEMA Flood Map Service Center. In the search, use the FEMA ID. Once downloaded, save the data in your project folder and use it as an input.Note 2:In this task, the default hazard being used are the National Flood Hazard Zones. If you would like to use a different hazard, you will need to add the new hazard layer to the map and update all query expressions accordingly.For questions, bug reports, or new requirements contact pdoherty@publicsafetygis.org
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TwitterStop Summary files represent average daily ridership at the stop level over the course of a sign-up period. The data is calculated from a variety of sources depending on the route and year. This data provides a basic geographic overview of SEPTA’s ridership. These data files represent average daily fall ridership from 2014 – present. Accurate weekend data was not available until 2017 at which point SEPTA had more widespread APC coverage. No data is available from the Fall of 2020 due to the malware attack. APC data was not available for articulated vehicles and the Boulevard Direct from August 2020 through February 2022 due to the malware attack.
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TwitterThe Minnesota DNR Toolbox provides a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR.
Toolsets included in MNDNR Tools:
- Analysis Tools
- Conversion Tools
- General Tools
- LiDAR and DEM Tools
- Sampling Tools
The application download includes a comprehensive help document, which you can also access separately here: ArcGISPro_MNDNR_Toolbox_Pro_User_Guide.pdf
These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.
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TwitterThis dataset comes from the Annual Community Survey question related to residents’ feeling of safety and their perceptions about their likelihood of becoming a victim of violent or property crimes. The fear of crime refers to the fear of being a victim of crime as opposed to the actual probability of being a victim of crime. The Annual Community Survey question that relates to this dataset is: “Please indicate how often you worry about each of the following: a) Getting mugged; b) Having your home burglarized when you are not there; c) Being attacked or threatened with a weapon; d) Having your car stolen or broken into; e) Being a victim of identity theft?” Respondents are asked to rate how often they worry about being a victim on a scale of 5 to 1, where 5 means “Frequently” and 1 means “Never” (without "don't know" as an option).This page provides details about the Worry About Being a Victim performance measure. Click on the Showcases tab for any available stories or dashboards related to this data.The performance measure dashboard is available at 1.10 Worry About Being a VictimAdditional InformationSource: Community Attitude SurveyContact: Wydale HolmesContact E-Mail: Wydale_Holmes@tempe.govData Source Type: CSVPreparation Method: Data received from vendor and entered in CSVPublish Frequency: AnnualPublish Method: ManualData Dictionary
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TwitterPotential stewardship for Residential parcels in Baltimore City summarized by block group. Residential parcels was defined as only those parcels with a land use code of residential (LU_CODE = "R") based on the 2003 Maryland Property View A&T database. PRIZM 5, 15, and 62 classes are also present. PRIZM is the Potential Rating Index by Zip code Markets produced by the Claritas Corporation - > http://www.clusterbigip1.claritas.com/claritas/Default.jsp>. Total Potential stewardship is that land within a parcels not occupied by buildings, that is land that could potentially support vegetation, regardless of whether or not any vegetation is present. Realized Potential Stewardship is land that is currently occupied by vegetation. Not Realized Potential Stewardship is the land not occupied by buildings or existing vegetation, and is thus the land that is potentially available for "greening" initiatives. Normalization for realized and not realized potential stewardship is carried out by dividing by the total potential stewardship. The potential stewardship was calculated using parcel data, building footprints, and GDT census block groups. Building footprints were erased from the parcel area, resulting in a layer indicating the potential stewardship for each parcel. The potential stewardship layer was then unioned MD DNR's 2001 SUFA vegetation layer. All polygons corresponding to water features were deleted since water features cannot undergo "greening." All polygons that did fall in the potential stewardship area were deleted. This resulted in a layer in which the polygons represented the potential stewardship land along with the potential stewardship land occupied by either grass or trees. This layer was then intersected with the census block group layer resulting in a layer that had the potential stewardship land, potential stewardship vegetation, and block group IDs. All attributes were then summarized at the block group level. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Certain block groups with very high Normalized Total Potential Stewardship values may be indicative of the fact that building footprint data was missing, although the extent of this problem is unknown. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis.
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TwitterBaltimore City boundary limits. This is the "official" city boundary used by many Baltimore agencies. It DOES NOT agree with the universal MSA boundaries dervied from GDT census data.
This is part of a collection of Baltimore Ecosystem Study metadata records that point to a geodatabase.
The geodatabase itself is available online at beslter.org or lternet.edu. It is considerably large. Upon request, it can be shipped to you on media, such as a flash drive.
The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.
Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.
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TwitterThis dataset provides Customer Service Satisfaction results from the Annual Community Survey. The survey questions assess satisfaction with overall customer service for individuals who had contacted the city in the past year. For years where there are multiple questions related to overall customer service and treatment, the average of those responses is provided in this dataset. Responses for each question are shown in the detailed dataset.For years 2010-2014, respondents were first asked, "Have you contacted the city in the past year?". If they answered that they had contacted the city, then they were asked additional questions about their experience. The "number of respondents" field represents the number of people who answered yes to the contact question.Responses of "don't know" are not included in this dataset, but can be found in the dataset for the entire Community Survey. A survey was not completed for 2015.The performance measure dashboard is available at 2.02 Customer Service Satisfaction.Additional InformationSource: Community Attitude SurveyContact: Wydale HolmesContact E-Mail: Wydale_Holmes@tempe.govData Source Type: Excel and PDFPreparation Method: Extracted from Annual Community Survey resultsPublish Frequency: AnnualPublish Method: ManualData Dictionary
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TwitterParcels_2007_BACO
File Geodatabase Feature Class
Thumbnail Not Available
Tags
BES
Summary
There is no summary for this item.
Description
Baltimore County parcels received on March 2, 2007 from Don Outen. This data has not yet been evaluated for accuracy or consistency. No metadata was received with this layer.
Credits
UVM Spatial Analysis Lab
Use limitations
There are no access and use limitations for this item.
Extent
West -76.912421 East -76.319117
North 39.726917 South 39.188766
Scale Range
There is no scale range for this item.
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The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.
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TwitterThis dataset comes from the Annual Community Survey questions about satisfaction with Community Service Programs. The Community Survey question relating to the Community Services Programs performance measure: "Please rate your level of satisfaction with each of the following: a) Quality of Before & After School (Kid Zone) programs; b) Quality of City library programs & services; c) Quality of City recreation programs & services; d) Quality of Tempe Center for the Arts programs." Respondents are asked to rate their satisfaction level on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (responses of "don't know" are excluded).The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.This page provides data for the Community Services Programs performance measure.The performance measure dashboard is available at 3.17 Community Services Programs.Note: Kid Zone is being removed from the measure as it no longer resides in Community Services.Additional InformationSource: Community Attitude Survey (Vendor: ETC Institute)Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: Excel and PDF ReportPreparation Method: Extracted from Annual Community Survey resultsPublish Frequency: AnnualPublish Method: ManualData Dictionary
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TwitterThis page provides data for the 3rd Grade Reading Level Proficiency performance measure.The dataset includes the student performance results on the English/Language Arts section of the AzMERIT from the Fall 2017 and Spring 2018. Data is representive of students in third grade in public elementary schools in Tempe. This includes schools from both Tempe Elementary and Kyrene districts. Results are by school and provide the total number of students tested, total percentage passing and percentage of students scoring at each of the four levels of proficiency. The performance measure dashboard is available at 3.07 3rd Grade Reading Level Proficiency.Additional InformationSource: Arizona Department of EducationContact: Ann Lynn DiDomenicoContact E-Mail: Ann_DiDomenico@tempe.govData Source Type: Excel/ CSVPreparation Method: Filters on original dataset: within "Schools" Tab School District [select Tempe School District and Kyrene School District]; School Name [deselect Kyrene SD not in Tempe city limits]; Content Area [select English Language Arts]; Test Level [select Grade 3]; Subgroup/Ethnicity [select All Students] Remove irrelevant fields; Add Fiscal YearPublish Frequency: Annually as data becomes availablePublish Method: ManualData Dictionary
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TwitterThis dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.
© MarineCadastre.gov This layer is a component of BOEMRE Layers.
This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.
For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov
The REST services for National Level Data can be found here:
http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer
REST services for regional level data can be found by clicking on the region of interest from the following URL:
http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE
Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL:
http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx
Currently the following layers are available from this REST location:
OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.
OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.
OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.
Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.
BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.
BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.
Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.
Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip
BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest.
http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.
BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf
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TwitterLast Revised: February 2016 Map InformationThis nowCOAST™ time-enabled map service provides maps depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is a method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in; however, all cloud cover values are presently displayed using the "Missing" symbol due to a problem with the source data. Present weather information is also not available for display at this time. Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs, which indicate wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds.Due to software limitations, the observations included in this map service are organized into three separate group layers: 1) Wind velocity (wind barb) observations, 2) Cloud Cover observations, and 3) All other observations, which are displayed as numerical values (e.g. Air Temperature, Wind Gust, Visibility, Sea Surface Temperature, etc.).Additionally, due to the density of weather/ocean observations in this map service, each of these group data layers has been split into ten individual "Scale Band" layers, with each one visible for a certain range of map scales. Thus, to ensure observations are displayed at any scale, users should make sure to always specify all ten corresponding scale band layers in every map request. This will result in the scale band most appropriate for your present zoom level being shown, resulting in a clean, uncluttered display. As you zoom in, additional observations will appear.The observations in this nowCOAST™ map service are updated approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observations for a particular station may update only once per hour. For more detailed information about layer update frequency and timing, please reference the nowCOAST™ Dataset Update Schedule.Background InformationThe maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing stations from the U.S.A. and other countries. For terrestrial networks, the platforms include but are not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Real-Time System (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until approximately 23 minutes past top of the hour for land-based stations and 33 minutes past the top of the hour for maritime stations.Time InformationThis map service is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.This service is configured with time coverage support, meaning that the service will always return the most relevant available data, if any, to the specified time value. For example, if the service contains data valid today at 12:00 and 12:10 UTC, but a map request specifies a time value of today at 12:07 UTC, the data valid at 12:10 UTC will be returned to the user. This behavior allows more flexibility for users, especially when displaying multiple time-enabled layers together despite slight differences in temporal resolution or update frequency.When interacting with this time-enabled service, only a single instantaneous time value should be specified in each request. If instead a time range is specified in a request (i.e. separate start time and end time values are given), the data returned may be different than what was intended.Care must be taken to ensure the time value specified in each request falls within the current time coverage of the service. Because this service is frequently updated as new data becomes available, the user must periodically determine the service's time extent. However, due to software limitations, the time extent of the service and map layers as advertised by ArcGIS Server does not always provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time extent of the service:Issue a returnUpdates=true request (ArcGIS REST protocol only) for an individual layer or for the service itself, which will return the current start and end times of available data, in epoch time format (milliseconds since 00:00 January 1, 1970). To see an example, click on the "Return Updates" link at the bottom of the REST Service page under "Supported Operations". Refer to the ArcGIS REST API Map Service Documentation for more information.Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against the proper layer corresponding with the target dataset. For raster data, this would be the "Image Footprints with Time Attributes" layer in the same group as the target "Image" layer being displayed. For vector (point, line, or polygon) data, the target layer can be queried directly. In either case, the attributes returned for the matching raster(s) or vector feature(s) will include the following:validtime: Valid timestamp.starttime: Display start time.endtime: Display end time.reftime: Reference time (sometimes referred to as issuance time, cycle time, or initialization time).projmins: Number of minutes from reference time to valid time.desigreftime: Designated reference time; used as a common reference time for all items when individual reference times do not match.desigprojmins: Number of minutes from designated reference time to valid time.Query the nowCOAST™ LayerInfo web service, which has been created to provide additional information about each data layer in a service, including a list of all available "time stops" (i.e. "valid times"), individual timestamps, or the valid time of a layer's latest available data (i.e. "Product Time"). For more information about the LayerInfo web service, including examples of various types of requests, refer to the nowCOAST™ LayerInfo Help DocumentationReferencesNWS, 2013: Sample Station Plot, NWS/NCEP/WPC, College Park, MD (Available at http://www.wpc.ncep.noaa.gov/html/stationplot.shtml).NWS, 2013: Terminology and Weather Symbols, NWS/NCEP/OPC, College Park, MD (Available at http://www.opc.ncep.noaa.gov/product_description/keyterm.shtml).NWS, 2013: How to read Surface weather maps, JetStream an Online School for Weather (Available at http://www.srh.noaa.gov/jetstream/synoptic/wxmaps.htm).
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TwitterParcel-level potential stewardship for Baltimore City. Potential stewardship is that land within a parcel not occupied by buildings, that is land that could potentially undergo "greening." This dataset contians polygons that represent potential stewardship land along with the vegetation that falls within the potential stewardship land. Potential stewardship should be estimated using the polygons with a land use (LU) code equal to 0. Parcel land use codes and census block group information is also present. A cursory analysis of the parcel data indicated that parcel data was outdated for the following block groups: 245102503031, 245102503032, and 245102503033. Note: transportation networks are not part of the parcel data, and thus were appropriately not part of this analysis. In addition a single BLOCKLOT may consist of two or more parcels in certain instances.
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Twitter[Metadata] Flood Hazard Areas for the State of Hawaii as of May, 2021, downloaded from the FEMA Flood Map Service Center, May 1, 2021. The Statewide GIS Program created the statewide layer by merging all county layers (downloaded on May 1, 2021), as the Statewide layer was not available from the FEMA Map Service Center. For more information, please refer to summary metadata: https://files.hawaii.gov/dbedt/op/gis/data/s_fld_haz_ar_state.pdf. The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk 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 NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.
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TwitterParcels_2003_BACI
File Geodatabase Feature Class
Thumbnail Not Available
Tags
BES
Summary
There is no summary for this item.
Description
Parcel Data for Baltimore City obatined from BNIA will all extraneous fields removed.
Editing in progress
The following edits were performed:
1) Resolved edge matching issues with Baltimore County parcels that border it and fall within the Gwynns Falls Watershed.
2) BLOCKLOT errors were noted and if necessary corrected. The BLOCKLOT ID is used to link the parcel data to the MD Property View A&T database. It should be pointed out that in some instances a single BLOCKLOT ID in the Property View A&T database may correspond to more than one parcel. There are only 14 instances were a single BLOCKLOT ID corresponds to 4 or more parcels, these are typically railroads, utility, or government properties. In other cases a single BLOCKLOT ID may correspond to two separate parcels that are essentially one property bisected by a road. There are other instances where there appears no logical explanation for a single BLOCKLOT ID corresponding to multiple parcels.
Credits
UVM Spatial Analysis Lab
Use limitations
There are no access and use limitations for this item.
Extent
West -76.713328 East -76.525885
North 39.374474 South 39.195051
Scale Range
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TwitterTags social system, socio-economic resources, justice, BES, Environmental disamentities, Environmental Justice, Zoning Board of Appeals Summary For use in the environmental injustices study of Baltimore relating to patterns of environmental disamenties in relation to low income/minority communities. Description This feature class layer is a point dataset of authorizing ordinances from the Baltimore City Council and Mayor from 1930 until 1999 concerning identified environmental disamentities. The data was gathered from records from the City Council since 1930 relating to decisions concerning land-uses considered to be environmental disamentities and is to be used to examine environmental injustices involving low income/minority communities in Baltimore. To examine if environmental injustices exist in Baltimore, this point layer will be overlayed with race/income data to determine if patterns of inequity exist. Points were placed manually using the associated addresses from the Ordinance_master dataset and using ISTAR 2004 data in conjunction with Baltimore parcel data. The Ordinance_ID number associated with each point relates to its appeal number from the City Council. Multiple points on the data layer have the same Ordinance_ID. This point layer can be joined with the Ordinance_master data layer based on the field "Ordinance_ID" and using the relationship "Ordinance_point_relationship". Credits UVM Spatial Analysis Lab Use limitations None. There are no restrictions on the use of this dataset. The authors of this dataset make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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As GIS and computing technologies advanced rapidly, many indoor space studies began to adopt GIS technology, data models, and analysis methods. However, even with a considerable amount of research on indoor GIS and various indoor systems developed for different applications, there has not been much attention devoted to adopting indoor GIS for the evaluation space usage. Applying indoor GIS for space usage assessment can not only provide a map-based interface for data collection, but also brings spatial analysis and reporting capabilities for this purpose. This study aims to explore best practice of using an indoor GIS platform to assess space usage and design a complete indoor GIS solution to facilitate and streamline the data collection, a management and reporting workflow. The design has a user-friendly interface for data collectors and an automated mechanism to aggregate and visualize the space usage statistics. A case study was carried out at the Purdue University Libraries to assess study space usage. The system is efficient and effective in collecting student counts and activities and generating reports to interested parties in a timely manner. The analysis results of the collected data provide insights into the user preferences in terms of space usage. This study demonstrates the advantages of applying an indoor GIS solution to evaluate space usage as well as providing a framework to design and implement such a system. The system can be easily extended and applied to other buildings for space usage assessment purposes with minimal development efforts.
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TwitterThis dataset indicates whether or not the City of Tempe met the regulations prescribed by the Environmental Protection Agency limiting the amount of certain contaminants in water provided by public water systems.This page provides data for the Safe Drinking Water performance measure. The performance measure dashboard is available at 1.13 Safe Drinking WaterAdditional InformationSource: Consumer Confidence Reports; https://www.tempe.gov/government/municipal-utilities/water/water-qualityContact: Tara FordContact E-Mail: tara_ford@tempe.govData Source Type: ExcelPreparation Method: The Consumer Confidence Report is published each year and includes the results for required water quality tests. Those results indicate whether or not the City meets the regulations. That designation is included in the dataset, indicating "met regulations."Publish Frequency: AnnuallyPublish Method: ManualData Dictionary
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TwitterSummary of Block Group level analyses for Baltimore City. This dataset contains block group level summary information for riparian vegetation, PROW (public right-of-way) vegetation, private land vegetation, and median age of homes. PRIZM codes are also present. The block group boundaries used in this dataset are from year 2000 GDT census data. The riparian analysis involved summarizing the riparian vegetation (forest and grass only) within a 100ft buffer of all 1:24K streams in Baltimore City for only those block groups that intersect the stream buffers. Vegetation data used in this analysis came from the 2001 MD DNR Forest Service IKONOS-derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of riparian forest, grass, and total vegetation was summarized on a block group level. In addition the percent riparian forest, grass, and total vegetation was summarized at block group level by dividing by the area of riparian land. The PROW analysis involved summarizing all PROW (non-parcel) vegetation (forest and grass) in Baltimore City. The PROW area consists of all roads and rights of way along roads. This area was delineated using Baltimore City parcel data by identifying all "non-parcel" areas. A cursory analysis of the "non-parcel" areas indicated that errors of omission were present due to insufficient parcel data. Vegetation data used in this analysis came from the 2001 MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of urparian forest, grass, and total vegetation was summarized on a block group level. In addition the percent urparian forest, grass, and total vegetation was summarized at block group level by dividing by the area of urparian land. The private land area consists of all parcels not classified as "Exempt" or "Exempt Commerical." A cursory analysis of the parcel data indicated that errors of omission were present due to insufficient parcel data in certain block groups. Vegetation data used in this analysis came from the MD DNR Forest Service IKONOS derived Strategic Urban Forest Assessment (SUFA) vegetation layer. The amount of private land forest, grass, and total vegetation was summarized on a block group level. In addition the percent private land forest, grass, and total vegetation was summarized at block group level by dividing by the area of private land. PRIZM codes are generated from demographic and socioeconomic factors drawn from the U.S. Census data, the Claritas Company's PRIZM system classifies over 260,000 U.S. neighborhood markets into clusters. PRIZM codes can be linked with survey information. More information on PRIZM is available at http://www.clusterbigip1.claritas.com/claritas/Default.jsp?main=3&submenu=seg&subcat=segprizm. Median home age was summarized by block group from U.S. Census data. Credits
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Purpose: This is an ArcGIS Pro template that GIS Specialists can use to identify vulnerable populations and special needs infrastructure most at risk to flooding events.How does it work?Determine and understand the Place Vulnerability (based on Cutter et al. 1997) and the Special Needs Infrastructure for an area of interest based on Special Flood Hazard Zones, Social Vulnerability Index, and the distribution of its Population and Housing units. The final product will be charts of the data distribution and a Hosted Feature Layer. See this Story Map example for a more detailed explanation.This uses the FEMA National Flood Hazard Layer as an input (although you can substitute your own flood hazard data), check availability for your County before beginning the Task: FEMA NFHL ViewerThe solution consists of several tasks that allow you to:Select an area of interest for your Place Vulnerability Analysis. Select a Hazard that may occur within your area of interest.Select the Social Vulnerability Index (SVI) features contained within your area of interest using the CDC’s Social Vulnerability Index (SVI) – 2016 overall SVI layer at the census tract level in the map.Determine and understand the Social Vulnerability Index for the hazard zones identified within you area of interest.Identify the Special Needs Infrastructure features located within the hazard zones identified within you area of interest.Share your data to ArcGIS Online as a Hosted Feature Layer.FIRST STEPS:Create a folder C:\GIS\ if you do not already have this folder created. (This is a suggested step as the ArcGIS Pro Tasks does not appear to keep relative paths)Download the ZIP file.Extract the ZIP file and save it to the C:\GIS\ location on your computer. Open the PlaceVulnerabilityAnalysis.aprx file.Once the Project file (.aprx) opens, we suggest the following setup to easily view the Tasks instructions, the Map and its Contents, and the Databases (.gdb) from the Catalog pane.The following public web map is included as a Template in the ArcGIS Pro solution file: Place Vulnerability Template Web MapNote 1:As this is a beta version, please take note of some pain points:Data input and output locations may need to be manually populated from the related workspaces (.gdb) or the tools may fail to run. Make sure to unzip/extract the file to the C:\GIS\ location on your computer to avoid issues.Switching from one step to the next may not be totally seamless yet.If you are experiencing any issues with the Flood Hazard Zones service provided, or if the data is not available for your area of interest, you can also download your Flood Hazard Zones data from the FEMA Flood Map Service Center. In the search, use the FEMA ID. Once downloaded, save the data in your project folder and use it as an input.Note 2:In this task, the default hazard being used are the National Flood Hazard Zones. If you would like to use a different hazard, you will need to add the new hazard layer to the map and update all query expressions accordingly.For questions, bug reports, or new requirements contact pdoherty@publicsafetygis.org