8 datasets found
  1. DPD council districts shore clip - Possible TC - Vegetation (%)

    • hub.arcgis.com
    • data.seattle.gov
    • +2more
    Updated Jun 29, 2023
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    City of Seattle ArcGIS Online (2023). DPD council districts shore clip - Possible TC - Vegetation (%) [Dataset]. https://hub.arcgis.com/datasets/a3601075d98f431dae346c57342d1d39
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    Dataset updated
    Jun 29, 2023
    Dataset provided by
    Authors
    City of Seattle ArcGIS Online
    Area covered
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

  2. a

    DPD council districts shore clip - Absolute % Change

    • data-seattlecitygis.opendata.arcgis.com
    • data.seattle.gov
    • +2more
    Updated Jun 29, 2023
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    City of Seattle ArcGIS Online (2023). DPD council districts shore clip - Absolute % Change [Dataset]. https://data-seattlecitygis.opendata.arcgis.com/datasets/a3601075d98f431dae346c57342d1d39
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    Dataset updated
    Jun 29, 2023
    Dataset authored and provided by
    City of Seattle ArcGIS Online
    Area covered
    Description

    This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

  3. WISE provisional reference GIS Water Framework Directive (WFD) dataset on...

    • sdi.eea.europa.eu
    Updated Oct 17, 2012
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    European Environment Agency (2012). WISE provisional reference GIS Water Framework Directive (WFD) dataset on Groundwater Bodies - PUBLIC VERSION, Oct. 2012 [Dataset]. https://sdi.eea.europa.eu/catalogue/srv/api/records/01c9d364-6c84-4b3f-8feb-1b99eff56e07
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    Dataset updated
    Oct 17, 2012
    Dataset provided by
    European Environment Agencyhttp://www.eea.europa.eu/
    License

    http://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitationshttp://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/noLimitations

    Time period covered
    Jan 1, 2009 - Dec 31, 2011
    Area covered
    Description

    A Groundwater Body (GWB) under the Water Framework Directive (WFD) Art. 2 is defined as a distinct volume of groundwater within an aquifer or aquifers, whereas an aquifer is defined as a geological layer with significant groundwater flow. This definition of a GWB allows a wide scope of interpretations. EU Member States (MS) are under obligation to report the GWBs including the results of the GWB survey periodically according to the schedule of the WFD. Reportnet is used for the submission of GWB data to the EEA by MS and includes spatial data as GIS polygons and GWB characteristics in an XML schema.

    The WISE provisional reference GIS WFD Dataset on GWBs combines spatial data consisting of several shape files and certain GWB attributes in a single table submitted by the MS according to Art. 13. The GWBs are divided into horizons, which represent distinct vertical layers of groundwater resources. All GWBs assigned to a certain horizon from one to five are merged into one shape file. GWBs assigned to horizons six or seven are combined in a single further shape file. Another two shape files comprise the GWBs of Reunion Island in the southern hemisphere and the GWBs from Switzerland as a non EU MS, all of which assigned to horizon 1.

    The dbf tables of the shape files include the columns “EU_CD_GW” as the GWB identifier and “Horizon” describing the vertical positioning. The polygon identifier “Polygon_ID” was added subsequently, because some GWBs consist of several polygons with identical “EU_CD_GW”even in the same horizon. Some further GWB characteristics are provided with the Microsoft Excel file “GWB_attributes_2012June.xls” including the column “EU_CD_GW”, which serves as a key for joining spatial and attribute data. There is no corresponding spatial data for GWBs in the Microsoft Excel table without an entry in column “EU_CD_GW”. The spatial resolution is given for about a half of the GWBs in the column “Scale” of the xls file, which is varying between the MS from 1 : 10,000 to 1 : 1,000,000 and mostly in the range from 1 : 50,000 to 1 : 250,000. The processing of some of the GWB shape files by GIS routines as clip or intersect in combination with a test polygon resulted in errors. Therefore a correction of erroneous topological features causing routine failures was carried out. However, the GWB layer includes a multitude of in parts very tiny, distinct areas resulting in a highly detailed or fragmented pattern. In certain parts topological inconsistencies appear quite frequently and delineation methodologies are currently varying between the MS in terms of size and three dimensional positioning of GWBs. This version of the dataset has to be considered as a first step towards a consistent GWB picture throughout Europe, but it is not yet of a sufficient quality to support spatial analyses i.e. it is not a fully developed reference GIS dataset. Therefore, the layer is published as a preliminary version and use of this data is subject to certain restrictions outlined in the explanatory notes.

    It should be underlined that the methodology used is still under discussion (Working Group C -Groundwater) and is not fully harmonised throughout the EU MS.

    For the external publication the whole United Kingdom had to be removed due to licensing restrictions.

  4. a

    MPO Basemap Development

    • opendata-palmbeachtpa.hub.arcgis.com
    Updated Oct 29, 2025
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    The citation is currently not available for this dataset.
    Explore at:
    Dataset updated
    Oct 29, 2025
    Dataset authored and provided by
    PalmBeachMPO
    Description

    This package contains National, Statewide, and Palm Beach County elements. Links are provided where available but do note that staff geoprocess files to create a more personalized MPO-purposed basemap.MPO Basemap PackageLayer/Groups*Additional InformationCounty BoundaryThis layer utilizes staff defined Definition Queries depending on the scenario (i.e. only PBC vs the Region).API: https://services1.arcgis.com/T0NPfOCJr9tmBN93/arcgis/rest/services/Florida_Counties/FeatureServerRoadway Labels*This following group contains several FDOT maintained layers bulleted below. Additional these roadway layers utilize specialized icon labels along with staff defined Definition Queries (DQs) to help manipulate them based on the current need.InterstatesAPI: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/Interstates_TDA/FeatureServerUS HighwaysAPI: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/US_Routes_TDA/FeatureServerToll RoadsAPI: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/Toll_Roads_TDA/FeatureServerThis layer's labels utilized two classes each incorporating SQL queries to separate Toll symbologies from the main Turnpike one.State RoadsAPI: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/State_Roads_TDA/FeatureServerCounty RoadwaysAPI: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/County_Roads_TDA/FeatureServerMajor RoadwaysThis FDOT Functional Classification layer utilizes staff defined Definition Queries for Major Roadway symbolization.API: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/Functional_Classification_TDA/FeatureServerRailroadsThis ESRI layer utilizes staff defined Definition Queries for general Railroad symbolization.API: https://services.arcgis.com/xOi1kZaI0eWDREZv/arcgis/rest/services/NTAD_North_American_Rail_Network_Lines/FeatureServerstate_fl_uabThis geoprocessed layer is clip to the state_fl_basemap for a cleaner version of the FDOT Smoothed Urban Boundaries layer along coastlines; linked below for reference.API: https://services1.arcgis.com/O1JpcwDW8sjYuddV/arcgis/rest/services/FDOT_FHWA_Smoothed_Urban_Boundaries_TDA/FeatureServercounty_pal*This following group contains several Palm Beach County and MPO maintained layers bulleted below. Additional staff defined Definition Queries (DQ) and noted below:county_pal_roadways (County)API: https://maps.co.palm-beach.fl.us/arcgis/rest/services/OpenData/Transportation_Open_Data/MapServerPBC localized road network. If not using DQs note that is may lag on older/slower systems to render.county_pal_water (County)API: https://maps.co.palm-beach.fl.us/arcgis/rest/services/OpenData/Environment_Open_Data/MapServerDQ: Detailed and Not Detailed (automatically enabled) versions of PBC water features. Detailed may lag somewhat.county_pal_municipal (MPO)API: https://services5.arcgis.com/79IoFXBn9ZeqmVlC/arcgis/rest/services/Test_File/FeatureServerDQ: Automatically enabled the “geo” attribute to “Municipality” to render only PBC municipalities. This MPO file also contains commissioner districts, special districts, community redevelopment agency (CRA) districts, the Port of Palm Beach, and a County outline if needed.natural_areas*This following group contains State and MPO maintained layers bulleted below. These layers and their symbologies are used to help match the ESRI Topographic Basemap.all_natural_areas (State)API: https://services.arcgis.com/9Jk4Zl9KofTtvg3x/ArcGIS/rest/services/FL_Conservation_Lands_web/FeatureServerUtilizes the marsh style symbology.static_county_natural_areas (MPO)API: Geoprocessed in file.A clipped version of the api layer below. This was to make geometry along coastlines cleaner.api_county_natural_areas (State)API: https://services.arcgis.com/9Jk4Zl9KofTtvg3x/ArcGIS/rest/services/FL_Conservation_Lands_web/FeatureServerDQ: To match the ESRI Topographic Basemap, a staff defined Definition Query was developed to highlight certain areas. The OBJECTID's included are: 105,109,755,823,1260,1359,1410,1723,1724,2426,2539,2713,2046,2045,1297,2654,826,592,2643,1404,204,900,832,2200,2803,233,53,2680,2056,747,1302,1397state_fl_basemapThis staff created layer was developed to consolidate the previous many separate county, Lake Okeechobee, and coastline geometries for easier use.API: Geoprocessed in file.State Boundary's API used as a base: https://geodata.myfwc.com/datasets/myfwc::florida-state-waters-and-land-boundary/explore?location=25.629877%2C-81.683769%2C6.98state_fl_waterThis staff created layer was developed to consolidate the previous many separate water layers by county for easier use.API: Geoprocessed in file.Lake Okeechobee water used as a base: https://services.arcgis.com/V4Rx2DXlIHdEvTZA/arcgis/rest/services/Okeechobee_lake/FeatureServer

  5. n

    State Shoreline

    • opdgig.dos.ny.gov
    • data.gis.ny.gov
    • +2more
    Updated Dec 20, 2022
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    ShareGIS NY (2022). State Shoreline [Dataset]. https://opdgig.dos.ny.gov/maps/sharegisny::state-shoreline
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    Dataset updated
    Dec 20, 2022
    Dataset authored and provided by
    ShareGIS NY
    Area covered
    Description

    Publication Date: May 2025.


    Updated as needed. Current as of the Publication Date.

    A vector polygon layer that includes 1) the New York State boundary over land areas and 2) the state shoreline, including islands, in areas where the state boundary extends over major hydrographic features. The purpose is to provide an “outline” of the state for GIS and cartographic uses. It can be used to clip the boundaries in the Cities, Towns, or Cities_Towns layers back to the shoreline if it is desired to only use or depict the land areas covered by those jurisdictions around the perimeter of the state. The boundaries were revised to 1:24,000-scale accuracy. Ongoing work will adjust the shorelines to 1:24,000-scale accuracy.

    Additional metadata, including field descriptions, can be found at the NYS GIS Clearinghouse: https://gis.ny.gov/civil-boundaries.

    Spatial Reference of Source Data: NAD 1983 UTM Zone 18N. Spatial Reference of Map Service: WGS 1984 Web Mercator Auxiliary Sphere.

    This map service is available to the public.


    The State of New York, acting through the New York State Office of Information Technology Services, makes no representations or warranties, express or implied, with respect to the use of or reliance on the Data provided. The User accepts the Data provided “as is” with no guarantees that it is error free, complete, accurate, current or fit for any particular purpose and assumes all risks associated with its use. The State disclaims any responsibility or legal liability to Users for damages of any kind, relating to the providing of the Data or the use of it. Users should be aware that temporal changes may have occurred since this Data was created.

  6. C

    SF Bay Eelgrass (BCDC 2020)

    • data.ca.gov
    • data.cnra.ca.gov
    • +6more
    Updated Aug 10, 2021
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    San Francisco Bay Conservation and Development Commission (2021). SF Bay Eelgrass (BCDC 2020) [Dataset]. https://data.ca.gov/dataset/sf-bay-eelgrass-bcdc-2020
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    txt, arcgis geoservices rest api, kml, gdb, geojson, csv, gpkg, zip, html, xlsxAvailable download formats
    Dataset updated
    Aug 10, 2021
    Dataset authored and provided by
    San Francisco Bay Conservation and Development Commissionhttps://bcdc.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    San Francisco Bay
    Description

    This eelgrass layer includes the maximum extent of eelgrass beds that have been surveyed in the San Francisco Bay shown in green. It was created by merging the Bay-wide eelgrass surveys conducted by Merkel & Associates, Inc. (Merkel) in 2003, 2009, 2014, and a Richardson Bay survey conducted by Merkel in 2019. Merkel has granted permission for public use of these data. These eelgrass surveys represent the best available data on comprehensive eelgrass extent throughout San Francisco Bay in 2021 and are developed using a combination of acoustic and aerial surveys and site-specific ground truthing. This layer may be used as a reference to determine potential direct and indirect impacts to eelgrass habitat from dredging projects. These data do not replace the need for site-specific eelgrass surveys.

    Data from the 2003, 2009, and 2014 eelgrass surveys and associated Merkel reports which include information on mapping methodology are available for download on the San Francisco Estuary Institute’s (SFEI) website.


    Methods for creating this layer are as follows:

    Downloaded the Merkel Baywide Eelgrass Surveys for 2003, 2009, and 2014 from SFEI and combined into a single layer. Obtained original Richardson Bay 2019 eelgrass survey data from Merkel. Loaded all layers into ArcGIS Pro © ESRI and re-projected all data to the NAD 1983 UTM Zone 10N coordinate system. Ran union of both the SFEI and Richardson Bay 2019 layers. Merged features to create one single attribute table for eelgrass cover from all survey years. Removed extraneous columns in the attribute table, recalculated area fields based on new extent, and applied symbology.

  7. d

    Geology constrains biomineralization expression and functional trait...

    • datadryad.org
    zip
    Updated Aug 22, 2023
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    T. Mason Linscott; Nicole Recla; Christine Parent (2023). Geology constrains biomineralization expression and functional trait distribution in the Mountainsnails (Oreohelix) [Dataset]. http://doi.org/10.5061/dryad.0k6djhb40
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    zipAvailable download formats
    Dataset updated
    Aug 22, 2023
    Dataset provided by
    Dryad
    Authors
    T. Mason Linscott; Nicole Recla; Christine Parent
    Time period covered
    Apr 28, 2023
    Description

    ArcGIS Pro/QGIS to modify layers R for scripts

  8. a

    LEP combined 2014 -1988

    • byron-shire-council-map-and-data-portal-1-byron-council.hub.arcgis.com
    Updated Aug 28, 2023
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    Byron Shire Council (2023). LEP combined 2014 -1988 [Dataset]. https://byron-shire-council-map-and-data-portal-1-byron-council.hub.arcgis.com/datasets/12758e1c90694d6b83f6504705637b87
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    Dataset updated
    Aug 28, 2023
    Dataset authored and provided by
    Byron Shire Council
    Area covered
    Description

    LEP 2014 - " LZN" - zoning layer. This dataset has been developed using a cadastre that has large sections of misaligned boundaries.10/10/13 - Created to repair holes in 'Final_LZN_s68_081013_10cm_Dissolved_2.shp'.A shire wide polygon shapefile was ERASED with 'Final_LZN_s68_081013_10cm_Dissolved_2.shp' to create a shapefile of "donut" holes. This "donut hole" layer was then used to UPDATE 'Final_LZN_s68_081013_10cm_Dissolved_2.shp' which created "Final_LZN_s68_081013_10cm_Dissolved_2_Updated_shire_poly".shp A further DISSOLVE was run on "Final_LZN_s68_081013_10cm_Dissolved_2_Updated_shire_poly".shp to produce "Final_LZN_s68_081013_10cm_Dissolved_3.shp", after which all E2/E3/E4 zones were selected (using SQL query) and reclassified as "Deferred Matter" in accordance with Council resolution on 19 Sept 2013 (Final_LZN_s68_081013_INCL_DEF_MATTERS.shp). 10/3/15 - Edits to zone boundary running along rear of properties in Melaleuca Drive Mullumbimby following edits to the cadastre for Tallowood Ridge Estate stage 3A. Zone boundary on eastern side of PN 11430 also edited and DM polygon within PN 113730 edited. Sue Green4/8/15 - LEP Amendment No 5 Gazetted 31/7/15 - Lot 5 DP 880917 PN 221940 - Zoning of part of parcel zoned RE1. (Sue Green)27/1/16- LEP Amendment No 7 Gazetted 22/1/16 - part Lot 10 DP 748099 PN 143070 - Rezoning to part R2 and part SP3 (Melissa Moore)28/1/16- LEP Amendment No 6 Gazetted 22/1/16 - part of Lot 7 DP 626084 PN 45750 - Rezoning to IN1 (Melissa Moore)8/3/16 - LEP Amendment No 9 Gazetted 19/2/16 - Lots 231-233 DP 1194657 PN 267277 267278 & 267279 - Rezoning to R2 (Sue Green)17/1/17 - Misalignment of zone boundary snapped to cadastral boundary PN 201750 66990 120170. Misalignment was less than 1 metre and correction approved by Alex Caras. (Sue Green)28/2/17 - Boundary of E1 zone snapped to cadastral boundary PN 65220 268510 following realignment of railway corridor and to reflect boundary as per gazetted maps. Refer #E2017/14107. (Sue Green)22/3/17 - LEP Amendment No 12 Gazetted 17/3/17. Minor amendments to a number of parcels of land as per gazetted maps. (Sue Green)5/4/17 - B4 & R2 Zone Boundary snapping anomaly corrected to snap to property boundaries PN 21890 & 53400. Refer #E2017/23514. (Sue Green)25/9/17 - LEP Amendment No 14 Gazetted 22/9/17. PN 268750 268751 268048 268049 Tallowood Ridge Estate. #E2017/92171 (Sue Green)26/9/17 - LEP Amendment No 13 Gazetted 22/9/17. PN 240482, 240483, 119790, 238081. #E2017/92166 (Sue Green)27/11/17 - Area of Bangalow in Blackwood Cres & to the south and east of Ballina Road area realigned to cadastre following cadastral adjustments. (Sue Green)13/12/17 - Snapped SP2 & RU1, RU2 edge to cadastre PN67720. (Sue Green)30/1/19 - LOT: 4 DP: 576360 PN 141960 - After discussions with Alex Caras E1 & DM zone boundary adjustment due to realignment of cadastre on eastern boundary along creek. (Sue Green)12/3/19 - Following discussion with Alex Caras adjustments to zone boundary to snap to realigned cadastre following processing of DP1235920. Section of R5 adjacent to PN 241915 & 269340 realigned to road reserve. Other parcels affected include PN 269344, 269341, 369340, 269339. (Sue Green)5/6/19 - Following discussions with Alex Caras adjustments to zone boundary on PN 13860 & adjoining road reserve to the south to remove small sliver of 1(a) land and to snap the zoning to the lot boundary. Refer #E2019/40938 (Sue Green)22/7/19 - Following discussions with Alex Caras adjustments to zone boundaries in Omega Circuit Brunswick Head to align with adjusted cadastre. Refer #E2019/53697 (Sue Green)19/11/19 - Following discussions with Alex Caras zone boundaries in relation to PN 267109 Lot 12 DP 1189646 Bayshore Drive were adjusted to align with lot boundaries in latest gazetted LZN map 1350_COM_LZN_003CC_020_20161121. Refer #E2019/84773. (Sue Green)23/3/20 - Updated following gazettal of LEP Amendment No. 17 28/2/20. (Sue Green)6/4/20 - Error from Amendment 17 update corrected on PN 238081. Refer #E2020/24925. (Sue Green)6/5/20 - This layer was amended following discussion with Alex Caras and realignment of the shire boundary in the vicinity of the Pacific Motorway south of Bangalow to align with the state local government boundary along with some adjustments to DP1229946 & DP1229072 this layer was amended. Refer to #E2020/32295. (Sue Green)3/6/20 - Zone boundary snapped to cadastre at PN 15940, 15930 & 15910 following adjustment to cadastre in preparation for mapping for LEP Amendment 22. (Sue Green)3/6/20 - Zoning amended following removal of slivers of (1a) land from hybrid layer. PN 108600, 5350, 98640, 240605, 99620, 240604, 103010, 102980, 200480. Refer #E2020/41220. (Sue Green) 6/7/20 - Updated following gazettal of LEP Amendment No. 18 3/7/20. (Sue Green)4/8/20 - Corrected misalignments at Broken Head Reserve Road PN 269414 & 240566. Refer to email from Alex Caras #E2020/54543. (Sue Green) 14/9/20 - Merged adjoining polygons of same zoning from LEP Amendment 17. (Sue Green)13/10/20 - Boundary between B2 and R2 zones adjusted following plan of consolidation DP1263368. Refer email from Alex Caras #E2020/79392 (Melissa Moore)27/11/20 - Boundary between RU2 and R5 zones adjusted following plan of subdivision DP1267961. Refer email from Alex Caras #E2020/95689 (Melissa Moore)27/11/20 - Zone boundary snapped to cadastre at PN270477 following plan of subdivision for road widening DP1268676. Refer email from Alex Caras #E2020/95711 (Melissa Moore)1/12/20 - Zone boundary snapped to cadastre at PN 240318, 11720 & 205370 to reflect gazetted map sheet LZN_003CD. Refer to email from Alex Caras #E2020/89980 (Sue Green)7/12/20 - Zone boundary realigned to remove 1(b1) sliver PN 269088 & 13370. (Sue Green)6/1/20 - Zone boundary realigned to remove overlap with RU1 & SP2 in PN 67680, 166280 & 67720. (Sue Green)16/2/21 - Updated following gazettal of LEP Amendment No. 225/2/21. (Sue Green)17/2/21 - Updated following gazettal of LEP Amendment No. 24 12/2/21 (Melissa Moore)2/3/21 - Updated following gazettal of LEP Amendment No 25 26/2/21 (Sue Green)11/5/21 Updated following gazettal of LEP Amendment No 23 12/2/21 (Sue Green)19/5/21 Updated following gazettal of LEP Amendment No 26 14/5/21 (Sue Green)23/7/21 Zone boundary snapped to cadastre at 270794, 270795, 270796 following plan of subdivision DP1269332. Refer email from Alex Caras #E2021/94777(Melissa Moore)4/8/21 - R2 zone boundary snapped to cadastre at PN 121740, 6710, 6720, 6730, 11880, 11870. Refer email from Alex Caras #E2021/98736 (Sue Green)8/9/21 -3E2 polygons removed in creek area adjacent to PN 240038 and restored to 1(b1) after discrepancy discovered by Dept Planning between our LZN layer (and hence hybrid layer) and the gazetted maps. Refer to Item 2 pg 7 of #E2021/106486. (Sue Green)30/9/21 - Zoning fixed to match lot boundary PN 197850 & gazetted zoning map LZN_002A Amendment No 23 (Sue Green)3/11/21 - Updated following gazettal of LEP Amendment No 29 29/10/21 (Sue Green)22/11/21 - Realigned to match cadastre and shire boundary at PN 241731 & 241733 (Sue Green)1/12/21 - Updated attribute table to change E1, E2, and E3 zone to C1, C2 and C3 zone following changed to legislation 5/11/21 effective 1/12/21. (Sue Green)11/1/22 - Updated following gazettal of LEP Map Amendment No 1 22/12/21. (Sue Green)9/3/22 - Error corrected and zones realigned at PN 118770, 13270, 203830. Refer to #E2022/21429. (Sue Green)12/4/22 - Polygon on polygon - 1(a) Polygon clipped out of RU2 area on PN 270665 & 270666 an RU2 areas merged. (Sue Green)17/5/22 - Updated following gazettal of LEP Amendment No 33 6/5/22. (Sue Green)24/5/22 - Realigned and snapped to cadastre at PN 20060, 20070, 20050, 228170 & 238283 Dudgeons Lane Bangalow. Refer to #E2022/47312. (Sue Green)24/5/22 - Realigned zoning to snap to cadastre at PN 271096 following consolidation of lots DP1281936. (Sue Green)15/6/22 - Updated following gazettal of LEP Map Amendment No 2 10/6/22 (Sue Green)22/8/22 - Layer clipped to shire boundary at PN 270839, 208790 & 41570 following realignment of cadastre. (Sue Green)16/9/22 - Realigned to cadastre at PN271191 following processing of DP1283927. (Melissa Moore)30/11/22 - Recreated following gazettal of LEP Map Amendment No 3. Edited version of the Department of Planning LZN layer LZN_CZones_Deleted_20220907_DOP was used. DM areas exported and saved as a shp file. DM removed from the Department's layer. The DM was used to clip the 1988 zone layer to produce the 1988 zones for these areas. This was then pasted into the Dept's LZN with the DM removed. (Sue Green)16/12/22 - Realigned to cadastre at PN271259 following processing of SP105499 (Melissa Moore)3/1/23 - Updated following gazettal of LEP Map Amendment No 4 16/12/22. PN 46360 (Sue Green)30/1/23 - PN 271299 aligned to cadastre following consolidation of lot and road realignment. Refer to email from Alex Caras #E2023/9615. (Sue Green)30/1/23 - PN 47490 - area of DM land in realigned to snap to cadastre. Property was part of LEP Amendment No 23. Refer to email #E2023/9807. (Sue Green)1/3/23 - Realigned to cadastre at PN 271330 following plan of subdivision DP1289363. Refer #E2023/25370 (Melissa Moore)26/4/23 - Updated to implement Employment Zones gazetted in December 2022 and effective 26/5/23. (Sue Green)31/5/23 - Sliver of DM ie 1988 zones removed from PN 21270 and aligned to cadastre. (Sue Green)29/06/23 - Updated following gazettal Map Amendment No. 5 16/06/23 (Anthony Murphy)7/7/23 - Realigned to cadastre at PN 271486 following plan of subdivision DP1295639. Refer #E2023/70138 (Melissa Moore)

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City of Seattle ArcGIS Online (2023). DPD council districts shore clip - Possible TC - Vegetation (%) [Dataset]. https://hub.arcgis.com/datasets/a3601075d98f431dae346c57342d1d39
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DPD council districts shore clip - Possible TC - Vegetation (%)

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Dataset updated
Jun 29, 2023
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City of Seattle ArcGIS Online
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Description

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

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