Want to keep the data in your Hosted Feature Service current? Not interested in writing a lot of code?Leverage this Python Script from the command line, Windows Scheduled Task, or from within your own code to automate the replacement of data in an existing Hosted Feature Service. It can also be leveraged by your Notebook environment and automatically managed by the MNCD Tool!See the Sampler Notebook that features the OverwriteFS tool run from Online to update a Feature Service. It leverages MNCD to cache the OverwriteFS script for import to the Notebook. A great way to jump start your Feature Service update workflow! RequirementsPython v3.xArcGIS Python APIStored Connection Profile, defined by Python API 'GIS' module. Also accepts 'pro', to specify using the active ArcGIS Pro connection. Will require ArcGIS Pro and Arcpy!Pre-Existing Hosted Feature ServiceCapabilitiesOverwrite a Feature Service, refreshing the Service Item and DataBackup and reapply Service, Layer, and Item properties - New at v2.0.0Manage Service to Service or Service to Data relationships - New at v2.0.0Repair Lost Service File Item to Service Relationships, re-enabling Service Overwrite - New at v2.0.0'Swap Layer' capability for Views, allowing two Services to support a View, acting as Active and Idle role during Updates - New at v2.0.0Data Conversion capability, able to invoke following a download and before Service update - New at v2.0.0Includes 'Rss2Json' Conversion routine, able to read a RSS or GeoRSS source and generate GeoJson for Service Update - New at v2.0.0Renamed 'Rss2Json' to 'Xml2GeoJSON' for its enhanced capabilities, 'Rss2Json' remains for compatability - Revised at v2.1.0Added 'Json2GeoJSON' Conversion routine, able to read and manipulate Json or GeoJSON data for Service Updates - New at v2.1.0Can update other File item types like PDF, Word, Excel, and so on - New at v2.1.0Supports ArcGIS Python API v2.0 - New at v2.1.2RevisionsSep 29, 2021: Long awaited update to v2.0.0!Sep 30, 2021: v2.0.1, Patch to correct Outcome Status when download or Coversion resulted in no change. Also updated documentation.Oct 7, 2021: v2.0.2, workflow Patch correcting Extent update of Views when Overwriting Service, discovered following recent ArcGIS Online update. Enhancements to 'datetimeUtil' Support script.Nov 30, 2021: v2.1.0, added new 'Json2GeoJSON' Converter, enhanced 'Xml2GeoJSON' Converter, retired 'Rss2Json' Converter, added new Option Switches 'IgnoreAge' and 'UpdateTarget' for source age control and QA/QC workflows, revised Optimization logic and CRC comparison on downloads.Dec 1, 2021: v2.1.1, Only a patch to Conversion routines: Corrected handling of null Z-values in Geometries (discovered immediately following release 2.1.0), improve error trapping while processing rows, and added deprecation message to retired 'Rss2Json' conversion routine.Feb 22, 2022: v2.1.2, Patch to detect and re-apply case-insensitive field indexes. Update to allow Swapping Layers to Service without an associated file item. Added cache refresh following updates. Patch to support Python API 2.0 service 'table' property. Patches to 'Json2GeoJSON' and 'Xml2GeoJSON' converter routines.Sep 5, 2024: v2.1.4, Patch service manager refresh failure issue. Added trace report to Convert execution on exception. Set 'ignore-DataItemCheck' property to True when 'GetTarget' action initiated. Hardened Async job status check. Update 'overwriteFeatureService' to support GeoPackage type and file item type when item.name includes a period, updated retry loop to try one final overwrite after del, fixed error stop issue on failed overwrite attempts. Removed restriction on uploading files larger than 2GB. Restores missing 'itemInfo' file on service File items. Corrected false swap success when view has no layers. Lifted restriction of Overwrite/Swap Layers for OGC. Added 'serviceDescription' to service detail backup. Added 'thumbnail' to item backup/restore logic. Added 'byLayerOrder' parameter to 'swapFeatureViewLayers'. Added 'SwapByOrder' action switch. Patch added to overwriteFeatureService 'status' check. Patch for June 2024 update made to 'managers.overwrite' API script that blocks uploads > 25MB, API v2.3.0.3. Patch 'overwriteFeatureService' to correctly identify overwrite file if service has multiple Service2Data relationships.Includes documentation updates!

SSURGO PortalThe newest version of SSURGO Portal with Soil Data Viewer is available via the Quick Start Guide. Install Python to C:\Program Files. This is a different version than what ArcGIS Pro uses.If you need data for multiple states, we also offer a prebuilt large database with all SSURGO for the entire United States and all Islands. The prebuilt saves you time but it’s large and takes a while to download.You can also use the prebuilt gNATSGO GeoPackage database in SSURGO Portal – Soil Data Viewer. Read the ReadMe.txt in the folder. More about gNATSGO here. You can also import STATSGO2 data into SSURGO Portal and create a database to use in Soil Data Viewer – Available for download via the Soils Box folder. SSURGO Portal NotesThis 10 minute video covers it all, other than installation of SSURGO Portal and the GIS tool. Installation is typically smooth and easy.There is also a user guide on the SSURGO Portal website that can be very helpful. It has info about using the data in ArcGIS Pro or QGIS. SQLite SSURGO database be opened and queried with DB Browser. It’s essentially free Microsoft Access.Guidance about setting up DB Browser to easily open SQLite databases is available in section 4 of this Installation Guide.Workflow if you need to make your own databaseInstall SSURGO PortalInstall SSURGO Downloader GIS tool (Refer to the Installation and User Guide for assistance)There is one for QGIS and one for ArcGIS Pro. They both do the same thing. Quickly download California SSURGO data with toolEnter two digit state symbol followed by asterisk in “Search by Areasymbol” to download all data for state.For example, enter CA* to batch download all data for CaliforniaOpen SSURGO Portal and create a new SQLite SSURGO Template database (Refer to the User Guide for assistance)Import SSURGO data you downloaded into databaseYou can import SSURGO data from many states at once, building a database that spans many statesAfter SSURGO data is done importing, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a map (Refer to the User Guide for assistance)Workflow if you need use large prebuilt database (don’t make own database) Install SSURGO PortalIn SSURGO Portal, browse to unzipped prebuilt GeoPackage database with all SSURGOprebuilt large database with all SSURGOgNATSGO GeoPackage databaseIn SSURGO Portal, click on Soil Data Viewer tab and run ratingsThese are the exact same ratings as Web Soil SurveyA new table is added to your database for each ratingYou can search for ratings by keywordIf desired, open database in GIS and make a mapIf you have trouble installing SSURGO Portal. Its usually the connection with Python. Create Desktop short cut that tells SSURGO Portal which Python to useThese were created for Windows 11 Right click anywhere on your desktop and choose New > ShortcutIn the text bar enter your path to the python.exe and your path to the SSURGO Portal.pyz. Notes:Example of format:"C:\Program Files\Python310\python.exe" "C:\SSURGO Portal\SSURGO_Portal-0.3.0.8.pyz"Include quotation marks.Paths may be different on your machine. To avoid typing, you can browse to python.exe in windows explorer, right click and select "Copy as Path and paste results into box. Paste into short location and then do the same for SSURGO Portal.pyz file, but paste to the right of the python.exe path. Click NextName the shortcut anything you want.

Reason for Selection Protected natural areas in urban environments provide urban residents a nearby place to connect with nature and offer refugia for some species. They help foster a conservation ethic by providing opportunities for people to connect with nature, and also support ecosystem services like offsetting heat island effects (Greene and Millward 2017, Simpson 1998), water filtration, stormwater retention, and more (Hoover and Hopton 2019). In addition, parks, greenspace, and greenways can help improve physical and psychological health in communities (Gies 2006). Urban park size complements the equitable access to potential parks indicator by capturing the value of existing parks.Input DataSoutheast Blueprint 2024 extentFWS National Realty Tracts, accessed 12-13-2023Protected Areas Database of the United States(PAD-US):PAD-US 3.0 national geodatabase -Combined Proclamation Marine Fee Designation Easement, accessed 12-6-20232020 Census Urban Areas from the Census Bureau’s urban-rural classification; download the data, read more about how urban areas were redefined following the 2020 censusOpenStreetMap data “multipolygons” layer, accessed 12-5-2023A polygon from this dataset is considered a beach if the value in the “natural” tag attribute is “beach”. Data for coastal states (VA, NC, SC, GA, FL, AL, MS, LA, TX) were downloaded in .pbf format and translated to an ESRI shapefile using R code. OpenStreetMap® is open data, licensed under theOpen Data Commons Open Database License (ODbL) by theOpenStreetMap Foundation (OSMF). Additional credit to OSM contributors. Read more onthe OSM copyright page.2021 National Land Cover Database (NLCD): Percentdevelopedimperviousness2023NOAA coastal relief model: volumes 2 (Southeast Atlantic), 3 (Florida and East Gulf of America), 4 (Central Gulf of America), and 5 (Western Gulf of America), accessed 3-27-2024Mapping StepsCreate a seamless vector layer to constrain the extent of the urban park size indicator to inland and nearshore marine areas <10 m in depth. The deep offshore areas of marine parks do not meet the intent of this indicator to capture nearby opportunities for urban residents to connect with nature. Shallow areas are more accessible for recreational activities like snorkeling, which typically has a maximum recommended depth of 12-15 meters. This step mirrors the approach taken in the Caribbean version of this indicator.Merge all coastal relief model rasters (.nc format) together using QGIS “create virtual raster”.Save merged raster to .tif and import into ArcPro.Reclassify the NOAA coastal relief model data to assign areas with an elevation of land to -10 m a value of 1. Assign all other areas (deep marine) a value of 0.Convert the raster produced above to vector using the “RasterToPolygon” tool.Clip to 2024 subregions using “Pairwise Clip” tool.Break apart multipart polygons using “Multipart to single parts” tool.Hand-edit to remove deep marine polygon.Dissolve the resulting data layer.This produces a seamless polygon defining land and shallow marine areas.Clip the Census urban area layer to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Clip PAD-US 3.0 to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Remove the following areas from PAD-US 3.0, which are outside the scope of this indicator to represent parks:All School Trust Lands in Oklahoma and Mississippi (Loc Des = “School Lands” or “School Trust Lands”). These extensive lands are leased out and are not open to the public.All tribal and military lands (“Des_Tp” = "TRIBL" or “Des_Tp” = "MIL"). Generally, these lands are not intended for public recreational use.All BOEM marine lease blocks (“Own_Name” = "BOEM"). These Outer Continental Shelf lease blocks do not represent actively protected marine parks, but serve as the “legal definition for BOEM offshore boundary coordinates...for leasing and administrative purposes” (BOEM).All lands designated as “proclamation” (“Des_Tp” = "PROC"). These typically represent the approved boundary of public lands, within which land protection is authorized to occur, but not all lands within the proclamation boundary are necessarily currently in a conserved status.Retain only selected attribute fields from PAD-US to get rid of irrelevant attributes.Merged the filtered PAD-US layer produced above with the OSM beaches and FWS National Realty Tracts to produce a combined protected areas dataset.The resulting merged data layer contains overlapping polygons. To remove overlapping polygons, use the Dissolve function.Clip the resulting data layer to the inland and nearshore extent.Process all multipart polygons (e.g., separate parcels within a National Wildlife Refuge) to single parts (referred to in Arc software as an “explode”).Select all polygons that intersect the Census urban extent within 0.5 miles. We chose 0.5 miles to represent a reasonable walking distance based on input and feedback from park access experts. Assuming a moderate intensity walking pace of 3 miles per hour, as defined by the U.S. Department of Health and Human Service’s physical activity guidelines, the 0.5 mi distance also corresponds to the 10-minute walk threshold used in the equitable access to potential parks indicator.Dissolve all the park polygons that were selected in the previous step.Process all multipart polygons to single parts (“explode”) again.Add a unique ID to the selected parks. This value will be used in a later step to join the parks to their buffers.Create a 0.5 mi (805 m) buffer ring around each park using the multiring plugin in QGIS. Ensure that “dissolve buffers” is disabled so that a single 0.5 mi buffer is created for each park.Assess the amount of overlap between the buffered park and the Census urban area using “overlap analysis”. This step is necessary to identify parks that do not intersect the urban area, but which lie within an urban matrix (e.g., Umstead Park in Raleigh, NC and Davidson-Arabia Mountain Nature Preserve in Atlanta, GA). This step creates a table that is joined back to the park polygons using the UniqueID.Remove parks that had ≤10% overlap with the urban areas when buffered. This excludes mostly non-urban parks that do not meet the intent of this indicator to capture parks that provide nearby access for urban residents. Note: The 10% threshold is a judgement call based on testing which known urban parks and urban National Wildlife Refuges are captured at different overlap cutoffs and is intended to be as inclusive as possible.Calculate the GIS acres of each remaining park unit using the Add Geometry Attributes function.Buffer the selected parks by 15 m. Buffering prevents very small and narrow parks from being left out of the indicator when the polygons are converted to raster.Reclassify the parks based on their area into the 7 classes seen in the final indicator values below. These thresholds were informed by park classification guidelines from the National Recreation and Park Association, which classify neighborhood parks as 5-10 acres, community parks as 30-50 acres, and large urban parks as optimally 75+ acres (Mertes and Hall 1995).Assess the impervious surface composition of each park using the NLCD 2021 impervious layer and the Zonal Statistics “MEAN” function. Retain only the mean percent impervious value for each park.Extract only parks with a mean impervious pixel value <80%. This step excludes parks that do not meet the intent of the indicator to capture opportunities to connect with nature and offer refugia for species (e.g., the Superdome in New Orleans, LA, the Astrodome in Houston, TX, and City Plaza in Raleigh, NC).Extract again to the inland and nearshore extent.Export the final vector file to a shapefile and import to ArcGIS Pro.Convert the resulting polygons to raster using the ArcPy Feature to Raster function and the area class field.Assign a value of 0 to all other pixels in the Southeast Blueprint 2024 extent not already identified as an urban park in the mapping steps above. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.Use the land and shallow marine layer and “extract by mask” tool to save the final version of this indicator.Add color and legend to raster attribute table.As a final step, clip to the spatial extent of Southeast Blueprint 2024.Note: For more details on the mapping steps, code used to create this layer is available in theSoutheast Blueprint Data Downloadunder > 6_Code. Final indicator valuesIndicator values are assigned as follows:6= 75+ acre urban park5= 50 to <75 acre urban park4= 30 to <50 acre urban park3= 10 to <30 acre urban park2=5 to <10acreurbanpark1 = <5 acre urban park0 = Not identified as an urban parkKnown IssuesThis indicator does not include park amenities that influence how well the park serves people and should not be the only tool used for parks and recreation planning. Park standards should be determined at a local level to account for various community issues, values, needs, and available resources.This indicator includes some protected areas that are not open to the public and not typically thought of as “parks”, like mitigation lands, private easements, and private golf courses. While we experimented with excluding them using the public access attribute in PAD, due to numerous inaccuracies, this inadvertently removed protected lands that are known to be publicly accessible. As a result, we erred on the side of including the non-publicly accessible lands.The NLCD percent impervious layer contains classification inaccuracies. As a result, this indicator may exclude parks that are mostly natural because they are misclassified as mostly impervious. Conversely, this indicator may include parks that are mostly impervious because they are misclassified as mostly