The water area of Winthrop Harbor, IL was 0 in 2018.
Land Area
Water Area
Land area is a measurement providing the size, in square miles, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundary recorded for each entity in the Census Bureau's geographic database. Land area is based on current information in the TIGER® data base, calculated for use with Census 2010.
Water Area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of any lake, reservoir, pond, or similar body of water that is recorded in the Census Bureau's geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two- dimensional feature (rather than as a single line). The portions of the oceans and related large embayments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across. Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Area Datasets Involving Winthrop Harbor, IL
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Canal System Locks
data.ny.gov | Last Updated 2024-10-02T20:00:54.000ZThe New York State Canal System is a 524 mile inland waterway that includes 57 locks, which are used to transfer vessels from a navigation pool at one elevation to another. Information provided in this data set includes the name of each lock, its phone number and specific location by mileage along the canal and geographic coordinates. This dataset excludes the Utica Harbor Lock because at this time it is not open to the public.
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CPS Schools 2013-2014 Academic Year
data.cityofchicago.org | Last Updated 2013-11-26T20:27:57.000ZList of CPS schools for the 2013-2014 academic year. This dataset includes various identifiers used to identify school districts, including names; local, state, and federal IDs; and geographic descriptions on the location of each school.
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Iowa Geographic Names
mydata.iowa.gov | Last Updated 2024-09-20T22:00:21.000ZThis dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names. The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.
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Beach Lab Data
data.cityofchicago.org | Last Updated 2024-09-04T19:00:17.000ZThe Chicago Park District collects and analyzes water samples from beaches along Chicago’s Lake Michigan lakefront. The Chicago Park District partners with the University of Illinois at Chicago Department of Public Health Laboratory to analyze water samples using a new DNA testing method called Rapid Testing Method (qPCR analysis) which tests for Enterococci in order to monitor swimming safety. The rapid testing method (qPCR analysis) is a new method that measures levels of pathogenic DNA in beach water. Unlike the culture based test that requires up to 24 hours of processing, the new rapid testing method requires a 4-5 hours for results. The Chicago Park District can use results of the rapid test to notify the public when levels exceed UPEPA recommended levels, which is 1000* CCE. When DNA bacteria levels exceed 1000 CCE, a yellow swim advisory flag is implemented. For more information please refer to the USEPA Recreational Water Quality Criteria (http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation). Historically, the Chicago Park District used the culture based analysis method and statistical prediction models to monitor beach water quality. The culture based method tests for Escherichia coli (E. coli) bacteria which is an indicator species for the presence of disease-causing bacteria, viruses, and protozoans that may pose health risks to the public. This method requires 18-24 hours of processing to receive results. The Chicago Park District would use results of the culture based method to notify the public when levels exceed UPEPA recommended levels, which is 235* CFU. When bacteria levels exceed 235 CFU, a yellow swim advisory flag was implemented. This standard is still used at most beaches throughout the Great Lakes region. For more information please refer to the USEPA Recreational Water Quality Criteria. The statistical prediction model forecasted real-time Escherichia coli (E. coli) bacteria levels present in the water. The Chicago Park District (CPD) in partnership with the US Geological Survey, developed statistical prediction models by using weather data pulled from CPD buoys (https://data.cityofchicago.org/d/qmqz-2xku) and weather stations (https://data.cityofchicago.org/d/k7hf-8y75). The Chicago Park District would use results of the predictive model to notify the public when bacteria levels would exceed 235 CFU. When bacteria levels exceed 235 CFU, a yellow swim advisory flag was implemented. * The unit of measurement for Escherichia coli is Colony Forming Units (CFU) per 100 milliliters of water. (Culture Based Method / Statistical Prediction Model) *The unit of measuring DNA is Enterococci Calibrator Cell Equivalents (CCE) per 100 milliliters of water. (Rapid Testing Analysis)
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Assessor [Archived 05-31-2023] - Parcel Universe
datacatalog.cookcountyil.gov | Last Updated 2023-05-31T21:51:45.000ZA complete, historic universe of Cook County parcels with attached geographic, governmental, and spatial data. When working with Parcel Index Numbers (PINs) make sure to zero-pad them to 14 digits. Some datasets may lose leading zeros for PINs when downloaded. Additional notes:<ul><li>Data is attached via spatial join (st_contains) to each parcel's centroid.</li> <li>Centroids are based on <a href="https://datacatalog.cookcountyil.gov/Property-Taxation/ccgisdata-Parcel-2021/77tz-riq7">Cook County parcel shapefiles</a>.</li> <li>Older properties may be missing coordinates and thus also missing attached spatial data (usually they are missing a parcel boundary in the shapefile).</li> <li>Newer properties may be missing a mailing or property address, as they need to be assigned one by the postal service.</li> <li>Attached spatial data does NOT go all the way back to 1999. It is only available for more recent years, primarily those after 2012.</li> <li>The universe contains data for the current tax year, which may not be complete or final. PINs can still be added and removed to the universe up until the Board of Review closes appeals.</li> <li>Data will be updated monthly.</li> <li>Rowcount and characteristics for a given year are final once the Assessor <a href="https://www.cookcountyassessor.com/assessment-calendar-and-deadlines">has certified the assessment roll</a> for all townships.</li> <li>Depending on the time of year, some third-party and internal data will be missing for the most recent year. Assessments mailed this year represent values from last year, so this isn't an issue. By the time the Data Department models values for this year, those data will have populated.</li> <li>Current property class codes, their levels of assessment, and descriptions can be found <a href="https://prodassets.cookcountyassessor.com/s3fs-public/form_documents/classcode.pdf">on the Assessor's website</a>. Note that class codes details can change across time.</li> <li>Due to decrepencies between the systems used by the Assessor and Clerk's offices, <i>tax_district_code</i> is not currently up-to-date in this table.</li></ul> For more information on the sourcing of attached data and the preparation of this dataset, see the <a href="https://gitlab.com/ccao-data-science---modeling/data-architecture">Assessor's data architecture repo</a> on GitLab. <a href="https://datacatalog.cookcountyil.gov/stories/s/i22y-9sd2">Read about the Assessor's 2022 Open Data Refresh.</a>
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California Protected Area Database (HESS)
data.bayareametro.gov | Last Updated 2023-06-09T00:41:33.000ZCalifornia Protected Area Database (CPAD) for development of the Parcel Inventory dataset for the Housing Element Site Selection (HESS) Pre-Screening Tool. This feature set contains a subset of the statewide source. Its geographic extent covers the San Francisco Bay Region. CPAD inventories open space lands that have been protected for open space uses through fee ownerships. CPAD is not a database of all public lands – for example, it does not include public buildings, water treatment sites, or other non-open space public land. CPAD is suitable for a wide range of planning, assessment, analysis, and display purposes. CPAD should not be used as the basis for official regulatory, legal, or other such governmental actions without more detailed review of current official land records in the area of focus. This feature set contains the CPAD Super Unit features of the database. Super Units are aggregations of Units (which themselves are aggregations of Holdings) to create use-focused polygons for each site name (e.g. Las Trampas Regional Wilderness). Super Units are useful for recreation applications and for cartographic representation. Note: ● Super Units aggregate units based on the managing agency. ● Super Units maintain distinct units for different types of public access. ● Super Units cross county boundaries. ● Super Units have fewer attributes and are primarily used for cartography/display purposes, and to support recreational access applications. The lands in CPAD are defined by their owning and managing agencies at the Holdings and Units levels. At the Super Units level (a version of the release meant primarily for recreation applications, and for general cartography), CPAD lands are defined simply by name, managing agency, and public access. Access to CPAD GIS data is primarily through the State of California’s Atlas open data portal – a download link and more information about CPAD, including a PDF manual about the data, is at https://www.calands.org/cpad/. CPAD is released in shapefile format. The state site also hosts map services with CPAD data displayed by Access Type, Agency Classification, and Agency Level.
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SLR Annual High Wave Flooding - 2.0 Ft. Scenario
highways.hidot.hawaii.gov | Last Updated 2023-03-24T01:40:19.000ZHawaii is exposed to large waves annually on all open coasts due to its location in the Central North Pacific Ocean. The distance over which waves run-up and wash across the shoreline will increase with sea level rise. As water levels increase, less wave energy will be dissipated through breaking on nearshore reefs and waves will arrive at a higher elevation at the shoreline. Computer model simulations of future annual high wave flooding were conducted by the University of Hawaii Coastal Geology Group using the XBeach (for eXtreme Beach behavior) numerical model developed by a consortium of research institutions. The model propagates the maximum annually recurring wave, calculated from offshore wave buoy data, over the reef and to the shore along one-dimensional (1D) cross-shore profiles extracted from a 1-meter DEM. Profiles are spaced 20 meters apart along the coast. This approach was used to model the transformation of the wave as it breaks across the reef and includes shallow water wave processes such as wave set-up and overtopping. The IPCC AR5 RCP8.5 sea level rise scenario was used in modeling exposure to annual high wave flooding from sea level rise at 0.5, 1.1, 2.0, and 3.2 feet. This particular layer depicts annual high wave flooding using the 2.0-ft (0.5991-m) sea level rise scenario. While the RCP8.5 predicts that this scenario would be reached by the year 2075, questions remain around the exact timing of sea level rise and recent observations and projections suggest a sooner arrival. Historical data used to model annual high wave flooding include hourly measurements of significant wave height, peak wave period, and peak wave direction, and was acquired from offshore wave buoy data from PacIOOS. Maximum surface elevation and depth of the annual high wave flooding is calculated from the mean of the five highest modeled water elevations at each model location along each profile. Output from the simulations is interpolated between transects and compiled in a 5-meter map grid. Depth grid cells with values less than 10 centimeters are not included in the impact assessment. This was done to remove very thin layers of water excursions that (1) are beyond the accuracy of the model and (2) might not constitute a significant impact to land and resources when only occurring once annually. Any low-lying flooded areas that are not connected to the ocean are also removed. Annual high wave flood modeling covered wave-exposed coasts with low-lying development on Maui, Oahu, and Kauai. Annual high wave flooding was not available for the islands of Hawaii, Molokai, and Lanai, nor for harbors or other back-reef areas throughout all the islands. Additional studies would be needed to add the annual high wave flooding for those areas. The maximum annually recurring wave parameters (significant wave height, period, direction) were statistically determined using historical wave climate records and do not include potential changes in future wave climate, the effects of storm surge, or less-frequent high wave events (e.g., a 1-in-10 year wave event). In some locations, the extent of flooding modeled was limited by the extent of the 1-meter DEM. Changes in shoreline location due to coastal erosion are not included in this modeling. As shorelines retreat, annual high wave flooding will reach farther inland along retreating shorelines. Waves are propagated along a "bare earth" DEM which is void of shoreline structures, buildings, and vegetation, and waves are assumed to flow over an impermeable surface. The DEM represents a land surface at one particular time, and may not be representative of the beach shape during the season of most severe wave impact, particularly for highly variable north and west-exposed beaches. Undesirable artifacts of 1D modeling include over-predicted flooding along some transects with deep, shore-perpendicular indentations in the sea bottom such as nearshore reef channels. The 1D modeling does not account for the pres
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SLR Annual High Wave Flooding - 3.2 Ft. Scenario
highways.hidot.hawaii.gov | Last Updated 2023-03-24T01:41:54.000ZHawaii is exposed to large waves annually on all open coasts due to its location in the Central North Pacific Ocean. The distance over which waves run-up and wash across the shoreline will increase with sea level rise. As water levels increase, less wave energy will be dissipated through breaking on nearshore reefs and waves will arrive at a higher elevation at the shoreline. Computer model simulations of future annual high wave flooding were conducted by the University of Hawaii Coastal Geology Group using the XBeach (for eXtreme Beach behavior) numerical model developed by a consortium of research institutions. The model propagates the maximum annually recurring wave, calculated from offshore wave buoy data, over the reef and to the shore along one-dimensional (1D) cross-shore profiles extracted from a 1-meter DEM. Profiles are spaced 20 meters apart along the coast. This approach was used to model the transformation of the wave as it breaks across the reef and includes shallow water wave processes such as wave set-up and overtopping. The IPCC AR5 RCP8.5 sea level rise scenario was used in modeling exposure to annual high wave flooding from sea level rise at 0.5, 1.1, 2.0, and 3.2 feet. This particular layer depicts annual high wave flooding using the 3.2-ft (0.9767-m) sea level rise scenario. While the RCP8.5 predicts that this scenario would be reached by the year 2100, questions remain around the exact timing of sea level rise and recent observations and projections suggest a sooner arrival. Historical data used to model annual high wave flooding include hourly measurements of significant wave height, peak wave period, and peak wave direction, and was acquired from offshore wave buoy data from PacIOOS. Maximum surface elevation and depth of the annual high wave flooding is calculated from the mean of the five highest modeled water elevations at each model location along each profile. Output from the simulations is interpolated between transects and compiled in a 5-meter map grid. Depth grid cells with values less than 10 centimeters are not included in the impact assessment. This was done to remove very thin layers of water excursions that (1) are beyond the accuracy of the model and (2) might not constitute a significant impact to land and resources when only occurring once annually. Any low-lying flooded areas that are not connected to the ocean are also removed. Annual high wave flood modeling covered wave-exposed coasts with low-lying development on Maui, Oahu, and Kauai. Annual high wave flooding was not available for the islands of Hawaii, Molokai, and Lanai, nor for harbors or other back-reef areas throughout all the islands. Additional studies would be needed to add the annual high wave flooding for those areas. The maximum annually recurring wave parameters (significant wave height, period, direction) were statistically determined using historical wave climate records and do not include potential changes in future wave climate, the effects of storm surge, or less-frequent high wave events (e.g., a 1-in-10 year wave event). In some locations, the extent of flooding modeled was limited by the extent of the 1-meter DEM. Changes in shoreline location due to coastal erosion are not included in this modeling. As shorelines retreat, annual high wave flooding will reach farther inland along retreating shorelines. Waves are propagated along a "bare earth" DEM which is void of shoreline structures, buildings, and vegetation, and waves are assumed to flow over an impermeable surface. The DEM represents a land surface at one particular time, and may not be representative of the beach shape during the season of most severe wave impact, particularly for highly variable north and west-exposed beaches. Undesirable artifacts of 1D modeling include over-predicted flooding along some transects with deep, shore-perpendicular indentations in the sea bottom such as nearshore reef channels. The 1D modeling does not account for the pres
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SLR Annual High Wave Flooding - 0.5 Ft. Scenario
highways.hidot.hawaii.gov | Last Updated 2023-03-24T01:40:03.000ZHawaii is exposed to large waves annually on all open coasts due to its location in the Central North Pacific Ocean. The distance over which waves run-up and wash across the shoreline will increase with sea level rise. As water levels increase, less wave energy will be dissipated through breaking on nearshore reefs and waves will arrive at a higher elevation at the shoreline. Computer model simulations of future annual high wave flooding were conducted by the University of Hawaii Coastal Geology Group using the XBeach (for eXtreme Beach behavior) numerical model developed by a consortium of research institutions. The model propagates the maximum annually recurring wave, calculated from offshore wave buoy data, over the reef and to the shore along one-dimensional (1D) cross-shore profiles extracted from a 1-meter DEM. Profiles are spaced 20 meters apart along the coast. This approach was used to model the transformation of the wave as it breaks across the reef and includes shallow water wave processes such as wave set-up and overtopping. The IPCC AR5 RCP8.5 sea level rise scenario was used in modeling exposure to annual high wave flooding from sea level rise at 0.5, 1.1, 2.0, and 3.2 feet. This particular layer depicts annual high wave flooding using the 0.5-ft (0.1660-m) sea level rise scenario. While the RCP8.5 predicts that this scenario would be reached by the year 2030, questions remain around the exact timing of sea level rise and recent observations and projections suggest a sooner arrival. Historical data used to model annual high wave flooding include hourly measurements of significant wave height, peak wave period, and peak wave direction, and was acquired from offshore wave buoy data from PacIOOS. Maximum surface elevation and depth of the annual high wave flooding is calculated from the mean of the five highest modeled water elevations at each model location along each profile. Output from the simulations is interpolated between transects and compiled in a 5-meter map grid. Depth grid cells with values less than 10 centimeters are not included in the impact assessment. This was done to remove very thin layers of water excursions that (1) are beyond the accuracy of the model and (2) might not constitute a significant impact to land and resources when only occurring once annually. Any low-lying flooded areas that are not connected to the ocean are also removed. Annual high wave flood modeling covered wave-exposed coasts with low-lying development on Maui, Oahu, and Kauai. Annual high wave flooding was not available for the islands of Hawaii, Molokai, and Lanai, nor for harbors or other back-reef areas throughout all the islands. Additional studies would be needed to add the annual high wave flooding for those areas. The maximum annually recurring wave parameters (significant wave height, period, direction) were statistically determined using historical wave climate records and do not include potential changes in future wave climate, the effects of storm surge, or less-frequent high wave events (e.g., a 1-in-10 year wave event). In some locations, the extent of flooding modeled was limited by the extent of the 1-meter DEM. Changes in shoreline location due to coastal erosion are not included in this modeling. As shorelines retreat, annual high wave flooding will reach farther inland along retreating shorelines. Waves are propagated along a "bare earth" DEM which is void of shoreline structures, buildings, and vegetation, and waves are assumed to flow over an impermeable surface. The DEM represents a land surface at one particular time, and may not be representative of the beach shape during the season of most severe wave impact, particularly for highly variable north and west-exposed beaches. Undesirable artifacts of 1D modeling include over-predicted flooding along some transects with deep, shore-perpendicular indentations in the sea bottom such as nearshore reef channels. The 1D modeling does not account for the pres
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SLR Annual High Wave Flooding - 1.1 Ft. Scenario
highways.hidot.hawaii.gov | Last Updated 2023-03-24T01:40:36.000ZHawaii is exposed to large waves annually on all open coasts due to its location in the Central North Pacific Ocean. The distance over which waves run-up and wash across the shoreline will increase with sea level rise. As water levels increase, less wave energy will be dissipated through breaking on nearshore reefs and waves will arrive at a higher elevation at the shoreline. Computer model simulations of future annual high wave flooding were conducted by the University of Hawaii Coastal Geology Group using the XBeach (for eXtreme Beach behavior) numerical model developed by a consortium of research institutions. The model propagates the maximum annually recurring wave, calculated from offshore wave buoy data, over the reef and to the shore along one-dimensional (1D) cross-shore profiles extracted from a 1-meter DEM. Profiles are spaced 20 meters apart along the coast. This approach was used to model the transformation of the wave as it breaks across the reef and includes shallow water wave processes such as wave set-up and overtopping. The IPCC AR5 RCP8.5 sea level rise scenario was used in modeling exposure to annual high wave flooding from sea level rise at 0.5, 1.1, 2.0, and 3.2 feet. This particular layer depicts annual high wave flooding using the 1.1-ft (0.3224-m) sea level rise scenario. While the RCP8.5 predicts that this scenario would be reached by the year 2050, questions remain around the exact timing of sea level rise and recent observations and projections suggest a sooner arrival. Historical data used to model annual high wave flooding include hourly measurements of significant wave height, peak wave period, and peak wave direction, and was acquired from offshore wave buoy data from PacIOOS. Maximum surface elevation and depth of the annual high wave flooding is calculated from the mean of the five highest modeled water elevations at each model location along each profile. Output from the simulations is interpolated between transects and compiled in a 5-meter map grid. Depth grid cells with values less than 10 centimeters are not included in the impact assessment. This was done to remove very thin layers of water excursions that (1) are beyond the accuracy of the model and (2) might not constitute a significant impact to land and resources when only occurring once annually. Any low-lying flooded areas that are not connected to the ocean are also removed. Annual high wave flood modeling covered wave-exposed coasts with low-lying development on Maui, Oahu, and Kauai. Annual high wave flooding was not available for the islands of Hawaii, Molokai, and Lanai, nor for harbors or other back-reef areas throughout all the islands. Additional studies would be needed to add the annual high wave flooding for those areas. The maximum annually recurring wave parameters (significant wave height, period, direction) were statistically determined using historical wave climate records and do not include potential changes in future wave climate, the effects of storm surge, or less-frequent high wave events (e.g., a 1-in-10 year wave event). In some locations, the extent of flooding modeled was limited by the extent of the 1-meter DEM. Changes in shoreline location due to coastal erosion are not included in this modeling. As shorelines retreat, annual high wave flooding will reach farther inland along retreating shorelines. Waves are propagated along a "bare earth" DEM which is void of shoreline structures, buildings, and vegetation, and waves are assumed to flow over an impermeable surface. The DEM represents a land surface at one particular time, and may not be representative of the beach shape during the season of most severe wave impact, particularly for highly variable north and west-exposed beaches. Undesirable artifacts of 1D modeling include over-predicted flooding along some transects with deep, shore-perpendicular indentations in the sea bottom such as nearshore reef channels. The 1D modeling does not account for the pres