This layer contains details about access to open space in King County. This digital document has been developed for the Determinant of Equity - Parks and Natural Resources presentation. It includes information about Access to Open Green Space equity indicator. Fields describe the total population (Total Pop), number of people who live within 1/4 mile for urban areas 2 miles for rural areas of a green space (Quarter_and_2mi_WithinPop), and the percentage of people who live within 1/4 mile for urban areas 2 miles for rural areas of a green space (Percent_Quarter_or_2mile).

The data was compiled by King County GIS Center. The current Urban Growth Area/Boundary from the Comprehensive Plan was used to determine whether a residence (address point used as a population point) was considered urban (with criteria within ¼ mile of an open space) or rural (with criteria within 2 miles of an open space). Open space was defined by the countywide PARK layer and any other areas within the PSRC Open Space layer that were not already included in the PARK layer. In this analysis, a vacant, brush covered lot with no way to tell it is owned by a parks department has the same value as a developed park with ball fields and play areas. Regional Trails are also included as open space, when the surrounding property is publicly owned. A traditional buffer is used for this open space analysis, because to do a network analysis would require the location of road access points for all 1400+ parks in King County. While a network analysis would be more accurate, this is less of a difference in urban areas with highly developed road networks that make road access to a park more direct.For more information about King County's equity efforts, please see:Equity, Racial & Social Justice VisionOrdinance 16948 describing the determinates of equityDeterminants of Equity and Data Tool

This is a combined feature class from 158 individual line feature classes derived from flow accumulation rasters for each of the analysis area tiles. Stream networks were generated using the ArcGIS Spatial Analyst Derive Continuous Flow tool against each DEM tile, converting to stream rasters with Strahler Order network segment values, then clipping the result to analysis area polygons to derive stream network network raster with a minimum segment watershed size of 2500 sq ft. The stream raster for each tile was exported to a vector Line feature class, combined into a single feature class. Each segment was provided with a Mounded Landform polygon ID, and statistics for segment length and total streamline length were computed and conflated to HydroAnalysis table fields for analyzing stream statistics.

This dataset contains a simplified network representation of bike paths across City of Melbourne. The dataset can be used to create a digital bicycle network with route modelling capabilities that integrated existing bicycle infrastructure. The network has been created to be used with ArcGIS network analyst. The resulting network was connected to the City of Melbourne property layer through centroids created for this project:

The network can assist in multiple modelling tasks including catchment analysis and route analysis. The download is a zip file containing compressed .json files

Please see the metadata attached for further information.

UPDATED VERSION 2024-09-26. (Previous version 2023-09-28). Note this 2024 version includes some additional sites based on dam removals and feedback received since the first release in 2023.Data Download: The flowlines and polygons representing the Freshwater Resilient and Connected Network are available as an ESRI File Geodatabase.DETAILED DESCRIPTIONThis Freshwater Resilient and Connected Network (FRCN) polygon area dataset represents the FRCN watershed areas (HUC12-FCN-biodiversity areas) that make up the FRCN. The FRCN can also be represented using the Freshwater Resilient and Connected Network (FRCN) flowline dataset to represent the network flowlines (streams, rivers, waterbody centerlines) that were within the FRCN watershed polygon areas. The FRCN polygon units were coded into nine classes that can be collapsed into five or just two simple classes by loading the appropriately named .lyrx file in ArcPro. The Freshwater Resilient and Connected Network (FRCN) is a key output of TNC's Freshwater Resilience Analysis and represents a subset of the higher scoring units analyzed. We defined "Freshwater Resilience" as the ability of a stream network or other aquatic setting to maintain biologic diversity even as the system changes in composition and structure in response to changes in climate. Our hypothesis for mapping freshwater resilience was that the physical setting and its intactness, together with water availability and its alteration, drive resilience in freshwater systems by providing habitat options and the conditions to maintain ecological function. We use the term “functional connectivity” to refer to the area of a river network available for a fish or aquatic organism to move through before they encounter a dam or other barrier. The characteristics of this “functionally connected network” - its size, diversity, condition, and available water – determine its ability to support aquatic diversity under changing climates. To assemble the Freshwater Resilient Connected Network (FRCN), we intersected the resilience analysis units (HUC12-FCN polygons) with areas of freshwater recognized biodiversity value to identify resilient areas with recognized biodiversity value and/or areas that were near resilient with recognized biodiversity value. The units that qualified for inclusion in the FRCN were placed into four primary groups representing key strategies: PROTECT Resilient. These are large, diverse, and connected river networks in good condition with ample unaltered water. The main conservation strategy for these systems is to protect their current state. RESTORE AND PROTECT. These river networks meet the resilience criteria in all but one primary category. Restore Condition. These are potentially resilient river networks in poor condition due to watershed fragmentation, degraded floodplain habitat, or poor water quality. The main conservation strategy is to restore the condition of these networks. Restore Flow. These are potentially resilient river networks with altered flow regimes due to the compound effects of upstream dams, water withdrawal, impervious surface, and/or groundwater depletion. The main conservation strategy is to restore flow—or ensure these river networks better simulate—natural flow regimes. In some cases, particularly in the agricultural Midwest, we accepted sites into this category if they were below average in both flow and condition as these factors are intertwined and because inclusion of these sites was necessary for adequate representation of Midwestern freshwater systems in the FRCN.Reconnect. These are potentially resilient river networks that are too small to provide many options to their resident species due to a dam or dams. The main conservation strategy is to remove the dam[s] or adjust dam operations in order to reconnect the river to its adjacent network.The above four classes can be further described by one of the 9 FRCN more detailed classes of which they are composed of. The specific criteria for each of the nine categories is described below. (note “RecBio” refers to recognized freshwater biodiversity)PROTECT GROUP: All units are Resilient scoring. 1. Protect: Highly Resilient (Resilient FAA-AA, with RecBio): ): Resilience Above Average (AA > 1 - 2 SD) or Far Above Average (FAA >2 SD) , and overlapping freshwater recognized biodiversity area2. Protect: Highly Resilient (without recognized biodiversity) (Resilient FAA-AA, without RecBio): Resilience Above Average (AA > 1 - 2 SD) or Far Above Average (FAA >2 SD), without overlapping freshwater recognized biodiversity areas3. Protect: Resilient (Resilient SAA, with RecBio): Resilience Slightly Above Average ( SAA > 0.5-1 SD) and overlapping freshwater recognized biodiversity areaRESTORE GROUP: All units have recognized biodiversity value overlap and are "Average Resilience' scoring. These units are relatively close to resilient scoring and have enabling conditions that could likely allow them to move up into the resilient group with improvement in primarily a single factor that they are currently scoring below average in and that our restoration actions could address.4. Restore: Condition (Restore Condition, with RecBio): Units meeting following criteria:In Humid Freshwater Ecoregions: Average Resilience, Condition Slightly Below Average or Below Average (but not Far Below Average), Size-Diversity and Water Alteration Average or better, and any Water Availability.In Arid Non-xeric Freshwater Ecoregions: Average Resilience, Condition Slightly Below Average or Below Average (but not Far Below Average), Size-Diversity and Water Alteration Average or better, and Water Availability Average or better. In Arid xeric Freshwater Ecoregions: Average Resilience, Condition Slightly Below Average or Below Average (but not Far Below Average), Size-Diversity and Water Alteration Average or better, and Water Availability Slightly Above Average or better. 5. Restore: River Flow and Condition (Restore Flow and Condition, with RecBio): Must contain > 0 km of river flowline (>100 sq.km drainage area) AND be of Average Resilience with Flow Alteration and Condition both Slightly Below Average or worse, Size-Diversity Average or better, and any Water Availability score. 6. Restore: River Flow (Restore Flow, with RecBio): Must contain > 0 km of river flowline (>100 sq.km drainage area) AND be of Average Resilience with Flow Alteration Slightly Below Average or worse, Size-Diversity and Condition Average or better, and any Water Availability score. 7. Restore: Reconnect (Reconnect, with RecBio): Because “Size” of the connected river habitat in this analysis is innately an FCN attribute, the criteria used for the “Reconnect” query included a set of FCN scale criteria to identify higher scoring FCN with certain enabling conditions, and then a finer spatial scale set of HUC12 criteria to identify the highly qualifying “seed” area or smaller HUC12s within qualifying FCNs. Only areas meeting BOTH the HUC12 and FCN criteria for enabling conditions are included. Additionally only "qualifying HUC12 areas also overlapping with Recognized biodiversity are included. The final full criteria for a HUC12FCN unit to qualify for inclusion in the "Reconnect" set of priorities included:FCN Size was Slightly Below Average or Below Average (not Far Below Average) and the FCN was bounded by dams and the current network was 60% or less of its natural size (e.g., removing a dam or multiple dams could restore it to a substantially larger length), AND the FCN resilience score (area weighted average of internal hucfcn units) was Average or better, AND HUC12 resilience score was Average (e.g. FCN and HUC12 units were both relatively close to resilient already -- so improving size alone could likely move the unit into resilience)AND the FCN (area weighted average of internal hucfcn units) and HUC12 Flow Alteration and Condition were Average or better, AND in arid ecoregions the FCN (area weighted average of internal hucfcn units) and HUC Water Availability was also “Average” or better.8. Possible Addition: Verify Water (Possible Addition: Verify Water, with RecBio): This additional set of possible FRCN sites includes areas with recognized biodiversity that are the highest scoring in their ecoregion (>0.5) and have Average or higher key attributes, BUT appear to potentially be water limited because they score Average for Water Availability in an arid ecoregion. The detailed query includes those units in arid ecoregions that were Best in Ecoregion (either terrestrial or freshwater ecoregion), with Average Resilience, Average in Flow Alteration, Condition, Size Diversity, and Water Availability. These units were not previously added to the “Best in Ecoregion” override because they were too limited in Potential Water Availability. If water is verified in these areas, they are priorities to add to the FRCN.9. Additional Area: Reconnect FCN (full FCN extent) (Possible Addition: Reconnect FCN (full FCN extent)). This category highlights all arcs within an FCN where there was a “seed hucfcn area” within that FCN that was highlighted for “Reconnect, with biodiversity.” This is a category to help visually see the extent of the whole FCN that would benefit from a dam removal. We limited this query to a set of FCNs that contained sufficient HUC12 areas within that qualified for “Reconnect with biodiversity.” Sufficient area was defined as > 10 sq.km of seed HUC12 “Reconnect with bio”, or >5% of the whole FCN area covered by the seed area. Arcs were also limited to those that didn’t qualify for any of the above eight previous queries.

Polygon feature class showing distance to tsunami safety (in feet) along predetermined routes outside of the Cascadia Subduction Zone (CSZ) tsunami inundation zone. For this project, the predetermined routes are generally hard surfaces/roads. USGS Pedestrian Evacuation Analyst Tool (PEAT) computes the distance from the location to the Hazus Boundary shapefile using a modified Road Network shapefile (both shapefiles accompany this distribution). Further processing converted the path distance to polygon shapefile in 50-foot bins. The modified Road Network factored in potential loss of use for selected bridges due to antecedent earthquake ground motion/liquefaction. ROUTES TO TSUNAMI SAFETY PRESENTED HEREIN ARE FOR FIRST-PASS STATEWIDE ANALYSIS PURPOSES AND SHOULD NOT BE CONSIDERED OFFICIAL. PLEASE CONSULT LOCAL EMERGENCY MANAGMENT PERSONNEL FOR OFFICIAL TSUNAMI EVACUATION ROUTES AND ASSEMBLY POINTS.

Reason for SelectionRiver networks with a variety of connected stream size classes are more likely to have a wide range of available habitat to support a greater number of species. This will help retain aquatic biodiversity in a changing climate by allowing species to access climate refugia and move between habitats (Morelli et al. 2016). Input Data Southeast Aquatic Resources Partnership’s Network Complexity metric The Southeast Aquatic Resources Partnership (SARP) developed metrics for their Southeast Aquatic Barrier Prioritization Tool. In February 2023, Brendan Ward with Astute Spruce (software developer working on behalf of SARP) shared high resolution NHDPlus flowlines with attributes depicting the network complexity attribute for each functional network (see definition of “functional network” below). The network complexity attribute calculates the total number of different stream size classes within each functional network. SARP assigned stream and river reaches to size classes based on total drainage area:1a: Headwaters (<3.861 sq mi)1b: Creeks (≥3.861 and <8.61 sq mi)2: Small Rivers (≥38.61 and <200 sq mi)3a: Medium Tributary Rivers (≥200 and <1,000 sq mi)3b: Medium Mainstem Rivers (≥1,000 and <3,861 sq mi)4: Large Rivers (≥3,861 and <9,653 sq mi)5: Great Rivers (≥9,653 sq mi)Functional NetworkSARP compiles the Southeast Aquatic Barrier Inventory from national, regional, state, and local partner databases across the Southeast region. These include the National Inventory of Dams (2018), National Anthropogenic Barrier Dataset (2012), databases from state dam safety programs and other state agencies, information from local partners, and dam locations estimated by SARP. Waterfalls are compiled from national datasets and local partners. Dams and waterfalls are snapped to hydrologic networks extracted from the National Hydrography Dataset (NHD) - High Resolution Beta version. All dams and waterfalls are treated as “hard” barriers for network connectivity analysis. Aquatic networks are cut at the location of each barrier. All network “loops” (non-primary flowlines) are omitted from the analysis. An upstream functional network is constructed by traversing upstream from each barrier through all tributaries to the upstream-most origination point or upstream barrier, whichever comes first. Additional functional networks are defined from downstream-most non-barrier termination points, such as marine areas or other downstream termination points. The total length of all network segments within a functional network is summed to calculate the total network length of each functional network. Each flowline segment within the NHD is assigned to a size class based on total drainage area. This was used to calculate the number of unique size classes per functional network. Federal Emergency Management Agency (FEMA) National Flood Hazard Layer flood zones for Puerto Rico and the U.S. Virgin Islands, accessed 10-22-2022; to download the data, visit the FEMA Flood Map Service Center, search by jurisdiction (Puerto Rico or Virgin Islands), download all FIRM (Flood Insurance Rate Maps) panels, and locate the “S_FLD_HAZ_AR” shapefile in each download package. We used the “FLD_ZONE” attribute of the S_FLD_HAZ_AR shapefile to define an estimated floodplain depicting areas predicted to be inundated by a 100-year flood (also known as the 1% annual chance flood). To create the estimated floodplain for Puerto Rico and the U.S. Virgin Islands, we combined all areas with flood zone codes beginning with the letter “A”. These zones represent the inland (non-coastal) portions of FEMA Special Flood Hazard Areas considered at high risk of flooding. This excludes coastal areas where the high risk of flooding stems from storm waves, areas of moderate-low flood risk, and areas with possible but undetermined flood hazards where no hazard analysis has been conducted. For more details on FEMA flood zones, read this FEMA blog or visit the FEMA glossary (detailed definitions are under “Z” for “zones”). National Hydrography Dataset Plus High Resolution (NHDPlus HR) National Release catchments and flowlines, accessed 11-30-2022; download the dataCatchmentsA catchment is the local drainage area of a specific stream segment based on the surrounding elevation. Catchments are defined based on surface water features, watershed boundaries, and elevation data. It can be difficult to conceptualize the size of a catchment because they vary significantly in size based on the length of a particular stream segment and its surrounding topography—as well as the level of detail used to map those characteristics. To learn more about catchments and how they’re defined, check out these resources:An article from USGS explaining the differences between various NHD productsThe glossary at the bottom of this tutorial for an EPA water resources viewer, which defines some key terms Southeast Blueprint 2023 subregions: Caribbean Southeast Blueprint 2023 extentMapping Steps Convert the SARP network complexity values from the NHDPlus HR flowlines to a 30 m raster.The original NHDPlus HR catchment data was missing coverage of a small area on the west coast of Puerto Rico (just east of Parcelas Aguas Claras). Create an additional catchment polygon for this missing area so that the indicator covers the entire island of Puerto Rico.The missing area is essentially outlined by extremely thin catchment polygons. To fill the gap, make a new rectangular feature class covering the missing area, then union it together with the original NHDPlus HR catchments. From that output, select the newly created polygon that fills in the hole. The resulting polygon is a multipart feature, so use the explode tool to separate out just the missing catchment. Export it as a shapefile.Union together the missing catchment with the other NHDPlus HR catchments and use that combined output as the catchment layer for the rest of the mapping steps.Apply the network complexity values to the NHDPlus HR catchments using the ArcPy Zonal Statistic “MAJORITY” function. This results in a raster where each catchment is given the majority network complexity value that intersects the catchment. Most catchments have only one intersecting line, but for catchments with interior dams, the analysis uses the majority network complexity value. This creates a raster with network complexity value assigned to catchments.Convert the FEMA floodplain polygons to a 30 m raster, giving floodplain areas a value of 1.Extract the stream and river lines from the NHDPlus HR flowlines (ftype IN (460, 558)). Convert extracted stream and river lines to a 30 m raster. Use the ArcPy Spatial Analysis Expand function to “buffer” the streams by 1 cell. This is the method that SARP uses to create a total stream width of approximately 90 m. Combine the FEMA floodplains and buffered flowlines using the Mosaic function to make an enhanced floodplain layer.Clip the raster with network complexity values assigned to catchments to the enhanced floodplain layer. This limits the indicator values to the floodplain areas, where they are most relevant.Some areas of the floodplain are not scored in the resulting layer because they are missing SARP network complexity values. This is due to the fact that some small reaches, such as braids and loops in the stream network, are not assigned a network complexity value. SARP has to remove loops and braided streams in order to calculate network complexity because the analysis can only accommodate a one-way flow of water. Identify these holes in the floodplain and fill them in by looking at the network complexity value of the surrounding pixels and assigning the maximum value to the missing catchments in the floodplain. Note: This explanation simplifies a complex series of analysis steps. For more specifics, please consult the code.Assign zero values to all areas that are covered by the NHDPlus HR catchments, but that are outside the enhanced floodplain layer. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.Clip to the Caribbean Blueprint 2023 subregion.As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available in the Southeast Blueprint Data Download under > 6_Code. Final indicator valuesIndicator values are assigned as follows:4 = 4 connected stream classes3 = 3 connected stream classes2 = 2 connected stream classes1 = 1 connected stream class0 = Not identified as floodplainKnown Issues This indicator does not include other smaller scale attributes of complexity (e.g., sinuosity, mixtures of riffles/pools/runs) that influence the habitat quality of the connections.This indicator likely overestimates the number of connected stream classes in some areas due to missing barriers in the inventory, such as smaller dams or road-stream crossings. It could also underestimate the number of connected stream classes, given the extensive ongoing restoration work to improve aquatic connectivity across the SECAS geography. If you identify a missing barrier or a removed barrier, please let SARP know by emailing Kat Hoenke at kat@southeastaquatics.net. You can learn more about the current inventory of dams and road-stream crossings by visiting https://connectivity.sarpdata.com/. SARP did a lot of work to snap the dam locations to the line network, but there are likely still dams (including some large ones) that didn’t get snapped correctly due to the large distance between the centerpoint of the dam and the nearest flowline. If you see any of these cases when reviewing the data, please let SARP know (the giveaway is networks that look longer than they should on a map).The NHDPlus flowlines in the headwaters could represent intermittent or ephemeral streams. They were not excluded, so the

Defra Network WMS server provided by the Environment Agency. See full dataset here.The Most Probable Overland Flow Pathway dataset is a polyline GIS vector dataset that describes the likely flow routes of water along with potential accumulations of diffuse pollution and soil erosion features over the land.It is a complete network for the entire country (England) produced from a hydro-enforced LIDAR 1-metre resolution digital terrain model (bare earth DTM) produced from the 2022 LIDAR Composite 1m Digital Terrain Model. Extensive processing on the data using auxiliary datasets (Selected OS Water Network, OS MasterMap features as well as some manual intervention) has resulted in a hydro-enforced DTM that significantly reduces the amount of non-real-world obstructions in the DTM. Although it does not consider infiltration potential of different land surfaces and soil types, it is instructive in broadly identifying potential problem areas in the landscape.The flow network is based upon theoretical one-hectare flow accumulations, meaning that any point along a network feature is likely to have a minimum of one-hectare of land potentially contributing to it. Each segment is attributed with an estimate of the mean slope along it.The product is comprised of 3 vector datasets; Probable Overland Flow Pathways, Detailed Watershed and Ponding and Errors. Where Flow Direction Grids have been derived, the D8 option was applied. All processing was carried out using ARCGIS Pro’s Spatial Analyst Hydrology tools. Outlined below is a description of each of the feature class.Probable Overland Flow Pathways The Probable Overland Flow Pathways layer is a polyline vector dataset that describes the probable locations accumulation of water over the Earth’s surface where it is assumed that there is no absorption of water through the soil. Every point along each of the features predicts an uphill contribution of a minimum of 1 hectare of land. The hydro-enforced LIDAR Digital Terrain Model 1-Metre Composite (2022) has been used to derive this data layer. Every effort has been used to digitally unblock real-world drainage features; however, some blockages remain (e.g. culverts and bridges. In these places the flow pathways should be disregarded. The Ponding field can be used to identify these erroneous pathways. They are flagged in the Ponding field with a “1”. Flow pathways are also attributed with a mean slope value which is calculated from the Length and the difference of the start and end point elevations. The maximum uphill flow accumulation area is also indicated for each flow pathway feature.Detailed Watersheds The Detailed Watersheds layer is a polygon vector dataset that describes theoretical catchment boundaries that have been derived from pour points extracted from every junction or node of a 1km2 Flow Accumulation dataset. The hydro-enforced LIDAR Digital Terrain Model 1-Metre Composite (2022) has been used to derive this data layer.Ponding Errors The Ponding and Errors layer is a polygon vector dataset that describes the presence of depressions in the landscape after the hydro-enforcing routine has been applied to the Digital Terrain Model. The Type field indicates whether the feature is Off-Line or On-Line. Off-Line is indicative of a feature that intersects with a watercourse and is likely to be an error in the Overland Flow pathways. On-line features do not intersect with watercourses and are more likely to be depressions in the landscape where standing water may accumulate. Only features of greater than 100m2 with a depth of greater than 20cm have been included. The layer was derived by filling the hydro-enforced DTM then subtracting the hydro-enforced DTM from the filled hydro-enforced DTM.Please use with caution in very flat areas and areas with highly modified drainage systems (e.g. fenlands of East Anglia and Somerset Levels). There will occasionally be errors associated with bridges, viaducts and culverts that were unable to be resolved with the hydro-enforcement process.