You have been assigned a new project, which you have researched, and you have identified the data that you need.The next step is to gather, organize, and potentially create the data that you need for your project analysis.In this course, you will learn how to gather and organize data using ArcGIS Pro. You will also create a file geodatabase where you will store the data that you import and create.After completing this course, you will be able to perform the following tasks:Create a geodatabase in ArcGIS Pro.Create feature classes in ArcGIS Pro by exporting and importing data.Create a new, empty feature class in ArcGIS Pro.

In this course, you will learn about some common types of data used for GIS mapping and analysis, and practice adding data to a file geodatabase to support a planned project.Goals Create a file geodatabase. Add data to a file geodatabase. Create an empty geodatabase feature class.

There are many ways to create spatial data. In this tutorial, you'll use an editing tool to draw features on an imagery basemap. The features you create will be saved in a feature class in your project geodatabase.Estimated time: 30 minutesSoftware requirements: ArcGIS Pro

The National Hydrography Dataset Plus High Resolution (NHDplus High Resolution) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US Geological Survey, NHDPlus High Resolution provides mean annual flow and velocity estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.For more information on the NHDPlus High Resolution dataset see the User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territoriesGeographic Extent: The Contiguous United States, Hawaii, portions of Alaska, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: USGSUpdate Frequency: AnnualPublication Date: July 2022This layer was symbolized in the ArcGIS Map Viewer and while the features will draw in the Classic Map Viewer the advanced symbology will not. Prior to publication, the network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original dataset. No data values -9999 and -9998 were converted to Null values.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute.Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map.Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

This dataset contains 50-ft contours for the Hot Springs shallowest unit of the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric-surface shows altitude at which the water level would have risen in tightly-cased wells and represents synoptic conditions during the summer of 2017. Contours were constructed from 59 water-level measurements measured in selected wells (locations in the well point dataset). Major streams and creeks were selected in the study area from the USGS National Hydrography Dataset (U.S. Geological Survey, 2017), and the spring point dataset with 18 spring altitudes calculated from 10-meter digital elevation model (DEM) data (U.S. Geological Survey, 2015; U.S. Geological Survey, 2016). After collecting, processing, and plotting the data, a potentiometric surface was generated using the interpolation method Topo to Raster in ArcMap 10.5 (Esri, 2017a). This tool is specifically designed for the creation of digital elevation models and imposes constraints that ensure a connected drainage structure and a correct representation of the surface from the provided contour data (Esri, 2017a). Once the raster surface was created, 50-ft contour interval were generated using Contour (Spatial Analyst), a spatial analyst tool (available through ArcGIS 3D Analyst toolbox) that creates a line-feature class of contours (isolines) from the raster surface (Esri, 2017b). The Topo to Raster and contouring done by ArcMap 10.5 is a rapid way to interpolate data, but computer programs do not account for hydrologic connections between groundwater and surface water. For this reason, some contours were manually adjusted based on topographical influence, a comparison with the potentiometric surface of Kresse and Hays (2009), and data-point water-level altitudes to more accurately represent the potentiometric surface. Select References: Esri, 2017a, How Topo to Raster works—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/how-topo-to-raster-works.htm. Esri, 2017b, Contour—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro Raster Surface toolset at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/contour.htm. Kresse, T.M., and Hays, P.D., 2009, Geochemistry, Comparative Analysis, and Physical and Chemical Characteristics of the Thermal Waters East of Hot Springs National Park, Arkansas, 2006-09: U.S. Geological Survey 2009–5263, 48 p., accessed November 28, 2017, at https://pubs.usgs.gov/sir/2009/5263/. U.S. Geological Survey, 2015, USGS NED 1 arc-second n35w094 1 x 1 degree ArcGrid 2015, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html. U.S. Geological Survey, 2016, USGS NED 1 arc-second n35w093 1 x 1 degree ArcGrid 2016, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html.

The Geodatabase to Shapefile Warning Tool examines feature classes in input file geodatabases for characteristics and data that would be lost or altered if it were transformed into a shapefile. Checks include:
1) large files (feature classes with more than 255 fields or over 2GB), 2) field names longer than 10 characters
string fields longer than 254 characters, 3) date fields with time values 4) NULL values, 5) BLOB, guid, global id, and raster field types, 6) attribute domains or subtypes, and 7) annotation or topology

The results of this inspection are written to a text file ("warning_report_[geodatabase_name]") in the directory where the geodatabase is located. A section at the top provides a list of feature classes and information about the geodatabase as a whole. The report has a section for each valid feature class that returned a warning, with a summary of possible warnings and then more details about issues found.

The tool can process multiple file geodatabases at once. A separate text file report will be created for each geodatabase. The toolbox was created using ArcGIS Pro 3.7.11.

For more information about this and other related tools, explore the Geospatial Data Curation toolkit

The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Geographic Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: EPA and USGSUpdate Frequency: There is new new data since this 2019 version, so no updates planned in the futurePublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Abstract Built up area polygons represent where buildings are clustered together, such as urban areas. Layer can be used for activities such as monitoring urban grown, or responding to natural disasters. Product has been designed for AUSTopo - Australian Digital Topographic Map Series 250k. Built up area polygons designed for the AUSTopo - Australian Digital Topographic Map Series 250k. Feature class attributes include polygon area (in m2) and feature type (Builtup Area). This dataset provides valuable insights into the built environment of towns and cities, and serves as a crucial resource for urban planners, researchers, policymakers, and developers. Currency Date modified: 31 August 2023 Modification frequency: None Data extent Spatial extent North: -10.15° South: -43.44° East: 153.64° West: 113.42° Temporal extent From 1 January 2013 to 1 January 2018 Source information Catalog entry: Built Up Areas Dataset This dataset is generated from a publicly-available dataset: Bing Building Footprints, using the 'Delineate Built Up Area' tool in ArcGIS Pro. More information on the original source dataset can be found here. Lineage statement Dataset was generated by using the Bing Building Footprints of Australia (October 2020) dataset as an input. Built Up Area layer was created using the Delineate Built Up Areas tool in ArcGIS Pro in April 2023. This layer was produced as part of the update of AUSTopo - Australian Digital Topographic Map Series 250k. This dataset extracted on or before 4 SEPTEMBER 2023. This dataset has been projected from GDA2020 to Web Mercator as part of the Digital Atlas of Austalia project. Minor changes to symbology have been performed only as neccessary to meet the requirements of this project. Data dictionary All layers

Attribute name Description

Object ID Unique identifier for the area polygon

Area (sq. m) Measured area of the built-up region

Feature Type All features in this set are "Builtup Area"

SHAPE_Length Internal - length of the polygon perimeter

SHAPE_Area Internal - area of the generated polygon

Contact Geoscience Australia, clientservices@ga.gov.au

Important Note: This item is in mature support as of September 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The USGS Protected Areas Database of the United States (PAD-US) is the official inventory of public parks and other protected open space. The spatial data in PAD-US represents public lands held in trust by thousands of national, state and regional/local governments, as well as non-profit conservation organizations.GAP 1 and 2 areas are primarily managed for biodiversity, GAP 3 are managed for multiple uses including conservation and extraction, GAP 4 no known mandate for biodiversity protection. Provides a general overview of protection status including management designations. PAD-US is published by the U.S. Geological Survey (USGS) Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity conservation, recreation, public health, climate change adaptation, and infrastructure investment. See the GAP webpage for more information about GAP and other GAP data including species and land cover.The USGS Protected Areas Database of the United States (PAD-US) classifies lands into four GAP Status classes:GAP Status 1 - Areas managed for biodiversity where natural disturbances are allowed to proceedGAP Status 2 - Areas managed for biodiversity where natural disturbance is suppressedGAP Status 3 - Areas protected from land cover conversion but subject to extractive uses such as logging and miningGAP Status 4 - Areas with no known mandate for protectionIn the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, the Northern Mariana Islands and other Pacific Ocean IslandsVisible Scale: 1:1,000,000 and largerSource: USGS Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP) PAD-US version 3.0Publication Date: July 2022Attributes included in this layer are: CategoryOwner TypeOwner NameLocal OwnerManager TypeManager NameLocal ManagerDesignation TypeLocal DesignationUnit NameLocal NameSourcePublic AccessGAP Status - Status 1, 2, or 3GAP Status DescriptionInternational Union for Conservation of Nature (IUCN) Description - I: Strict Nature Reserve, II: National Park, III: Natural Monument or Feature, IV: Habitat/Species Management Area, V: Protected Landscape/Seascape, VI: Protected area with sustainable use of natural resources, Other conservation area, UnassignedDate of EstablishmentThe source data for this layer are available here. What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for Gap Status Code = 3 to create a map of only the GAP Status 3 areas.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Note that many features in the PAD-US database overlap. For example wilderness area designations overlap US Forest Service and other federal lands. Any analysis should take this into consideration. An imagery layer created from the same data set can be used for geoprocessing analysis with larger extents and eliminates some of the complications arising from overlapping polygons.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Erosion pin and data showing change in marsh edge position over one year for several locations along the marsh edge. Erosion pins were deployed at locations along the marsh edge with and without oyster reefs. Change in marsh morphology over time was tracked remotely through aerial photograph analysis and in-situ using erosion pins and land surveys. For aerial photograph analysis, photos were chosen based on availability, time intervals and image quality. The images were given spatial context through the georectification tool in ArcGIS Pro 2.6 using landmarks with a x and y coordinate, such as the edge of a building or road intersection, as ground control points. A new feature class was created in ArcGIS Pro 2.6 to trace and digitize shorelines (Figure 2). The vegetation line was used as a shoreline indicator because of its visibility and independence of tide (Taube, 2013).

In the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. The Protected Areas Database of the United States classifies lands into four GAP Status classes. This layer displays the two highest levels of protection GAP Status 1 and 2. These two classes are commonly referred to as protected areas.Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity (GAP Status 1 and 2)Units: MetersCell Size: 30.92208102 metersSource Type: DiscretePixel Type: 8-bit unsigned integerData Coordinate System: WGS 1984Mosaic Projection: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, the Northern Mariana Islands and other Pacific Ocean Islands.Source: USGS National Gap Analysis Program PAD-US version 2.1Publication Date: September 2020ArcGIS Server URL: https://landscape10.arcgis.com/arcgis/This layer displays protected areas from the Protected Areas Database of the United States version 2.1 created by the USGS National Gap Analysis Program. This layer displays GAP Status 1, areas managed for biodiversity where natural disturbances are allowed to proceed or are mimicked by management, and GAP Status 2, areas managed for biodiversity where natural disturbance is suppressed. The source data for this layer are available here. A feature layer published from this dataset is also available. The polygon vector layer was converted to raster layers using the Polygon to Raster Tool using the National Elevation Dataset 1 arc second product as a snap raster.The service behind this layer was published with 8 functions allowing the user to select different views of the service. Other layers created from this service using functions include:USA Protected from Land Cover ConversionUSA Unprotected AreasUSA Protected Areas - Gap Status 1-4USA Protected Areas - Gap Status 1USA Protected Areas - Gap Status 2USA Protected Areas - Gap Status 3USA Protected Areas - Gap Status 4What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "Protected Areas" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "Protected Areas" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

Urban Tree Canopy Assessment. This was created using the Urban Tree Canopy Syracuse 2010 (All Layers) file HERE.The data for this map was created using LIDAR and other spatial analysis tools to identify and measure tree canopy in the landscape. This was a collaboration between the US Forest Service Northern Research Station (USFS), the University of Vermont Spatial Laboratory, and SUNY ESF. Because the full map is too large to be viewed in ArcGIS Online, this has been reduced to a vector tile layer to allow it to be viewed online. To download and view the shapefiles and all of the layers, you can download the data HERE and view this in either ArcGIS Pro or QGIS.Data DictionaryDescription source  USDA Forest ServiceList of values  Value 1 Description Tree CanopyValue 2 Description Grass/ShrubValue 3 Description Bare SoilValue 4 Description WaterValue 5 Description BuildingsValue 6 Description Roads/RailroadsValue 7 Description Other PavedField Class Alias Class Data type String Width 20Geometric objects  Feature class name landcover_2010_syracusecity Object type  complex Object count 7ArcGIS Feature Class Properties Feature class name landcover_2010_syracusecity Feature type  Simple Geometry type Polygon Has topology FALSE Feature count 7 Spatial index TRUE Linear referencing  FALSEDistributionAvailable format  Name ShapefileTransfer options  Transfer size 163.805Description Downloadable DataFieldsDetails for object landcover_2010_syracusecityType Feature Class Row count  7 Definition  UTCField FIDAlias FID Data type OID Width  4 Precision 0 Scale 0Field descriptionInternal feature number.Description source ESRIDescription of valueSequential unique whole numbers that are automatically generated.Field ShapeAlias Shape Data type Geometry Width 0 Precision 0 Scale 0Field description Feature geometry.Description source  ESRIDescription of values Coordinates defining the features.Field CodeAlias Code Data type Number Width 4Overview Description  Metadata DetailsMetadata language  English Metadata character set utf8 - 8 bit UCS Transfer FormatScope of the data described by the metadata  dataset Scope name  datasetLast update 2011-06-02ArcGIS metadata properties Metadata format ArcGIS 1.0 Metadata style North American Profile of ISO19115 2003Created in ArcGIS for the item 2011-06-02 16:48:35 Last modified in ArcGIS for the item 2011-06-02 16:44:43Automatic updates Have been performed Yes Last update 2011-06-02 16:44:43Item location history  Item copied or moved 2011-06-02 16:48:35 From T:\TestSites\NY\Syracuse\Temp\landcover_2010_syracusecity To \T7500\F$\Export\LandCover_2010_SyracuseCity\landcover_2010_syracusecity

Parcels affected by the adoption of the 2015 International Wildland Urban-Interface Code (WUIC), which was adopted by Austin City Council April9, 2020, and implementation beginning January 1st, 2021. Parcels that are within 1.5 miles of a wildland area greater than 750 acres and parcels within 150 feet of a wildland area greater than 40 acres are wildland_urban_interface_code parcels. Parcels designated as "preserves" have been removed and are not subject to the WUI code.Dataset was created in 2020 by Austin Fire Department Wildfire Division. It was derived from the most recent Travis County Appraisal District (TCAD) Parcels, and queried based upon their planar distance to wildland areas. Wildlands are defined as undeveloped continuous areas,. The wildlands feature class is maintained by the Austin Fire Department and is derived from the City of Austin Planimetric dataset, also known as impervious cover data, and are updated every two years. ArcGIS Pro version 2 software was used to create this dataset. The data is meant to be ingested by a GIS system. Changes to the City of Austin & LTD jurisdiction warrant an update to this dataset. The data is scheduled to be updated every two years.Included in the attributes are parcel condition variables that determine the parcel's "fire hazard severity' class. These include the composite score of three variables: slope score, fuel score, and WUI class (proximity). Slope score was determined by the average degree slope of the area within each parcel and classified as less than 10%, 10% to 25%, or greater then 25%. Fuel score was determined by the average fuel class area within each parcels as defined by the Austin Travis County Community Wildfire Protection Plan (CWPP) and classified as light, medium, or heavy fuels. Proximity class was defined by the proximity of each parcel to wildlands, either as within 1.5 miles of wildlands greater than 750 acres, or within 150 feet of wildlands greater than 40 acres.Description of data fieldsGLOBALID_1 = Used for Global IdentificationOBJECTID = Object IdentificationSLOPE_DEGREE = The average slope of each parcel in degreesFIRE_HAZARD_SEVERITY = The "fire hazard severity" class of each parcelPROXIMITY_CLASS = The proximity class of each parcelSLOPE_CLASS = The slope classification of each parcelFUEL_CLASS = The fuel class of each parcelCREATED_BY = Creators nameCREATED_DATE = Date createdMODIFIED_BY = Modifiers nameMODIFIED_DATE = Date modifiedUNIQUE_ID = Unique Identification number (mirror object id)Shape_Area = Shape areaShape_Length = Shape lengthIteration ID: Parcels_AustinLTD4 2020Contact: Steven Casebeer at Steven.casebeer@austintexas.gov | Austin Fire Department Wildfire Division

SSURGO-QA ArcGIS Pro Toolbox1. SetupDownload SSURGO by Areasymbol - Use Soil Data Access and Web Soil Survey download page to get SSURGO datasets. User can a wildcard to query the database by Areasymbol or by age.Download SSURGO by Region - Downloads SSURGO Soil Survey Areas that are owned by a specific region including an approximiate 2 soil survey area buffer.Generate Regional Transactional Geodatabase - Used to create the Regional Transactional Spatial Database (RTSD) for SSURGO.Generate SSO SSURGO Datasets - Create a SSURGO file geodatabase for a selected MLRA Soil Survey Office.Import SSURGO Datasets in FGDB - This tooll will import SSURGO spatial and tabular datasets within a given location into a File Geodatabase and establish the necessary table and feature class relationships to interact with the dataset.Insert NATSYM and MUNAME Value - This tool adds the National Mapunit Symbol (NATMUSYM) and the Mapunit Name (MUNAME) values to the corresponding MUKEY. An MUKEY field is required to execute. A network connection is required in order to submit a query to SDacess.RTSD - Check SDJR Project Out - Designed to work with the RTSD to manage SDJR projects and export data for those projects to be sent to the MLRA SSO.

In the Prince William Sound region of Alaska, recent glacier retreat started in the mid-1800s and began to accelerate in the mid-2000s in response to warming air temperatures (Maraldo and others, 2020). Prince William Sound is surrounded by the central Chugach Mountains and consists of numerous ocean-terminating glaciers, with rapid deglaciation increasingly exposing oversteepened bedrock walls of fiords. Deglaciation may accelerate the occurrence of rapidly moving rock avalanches (RAs), which have the potential to generate tsunamis and adversely impact maritime vessels, marine activities, and coastal infrastructure and populations in the Prince William Sound region. RAs have been documented in the Chugach Mountains in the past (Post, 1967; McSaveney, 1978; Uhlmann and others, 2013), but a time series of RAs in the Chugach Mountains is not currently available. A systematic inventory of RAs in the Chugach is needed as a baseline to evaluate any future changes in RA frequency, magnitude, and mobility. This data release presents a comprehensive historical inventory of RAs in a 4600 km2 area of the Prince William Sound. The inventory was generated from: (1) visual inspection of 30-m resolution Landsat satellite images collected between July 1984 and August 2024; and (2) the use of an automated image classification script (Google earth Engine supRaglAciaL Debris INput dEtector (GERALDINE, Smith and others, 2020)) designed to detect new rock-on-snow events from repeat Landsat images from the same time period. RAs were visually identified and mapped in a Geographic Information System (GIS) from the near-infrared (NIR) band of Landsat satellite images. This band provides significant contrast between rock and snow to detect newly deposited rock debris. A total of 252 Landsat images were visually examined, with more images available in recent years compared to earlier years (Figure 1). Calendar year 1984 was the first year when 30-m resolution Landsat data were available, and thus provided a historical starting point from which RAs could be detected with consistent certainty. By 2017, higher resolution (<5-m) daily Planet satellite images became consistently available and were used to better constrain RA timing and extent. Figure 1. Diagram showing the number of usable Landsat images per year. This inventory reveals 118 RAs ranging in size from 0.1 km2 to 2.3 km2. All of these RAs occurred during the months of May through September (Figure 2). The data release includes three GIS feature classes (polygons, points, and polylines), each with its own attribute information. The polygon feature class contains the entire extent of individual RAs and does not differentiate the source and deposit areas. The point feature class contains headscarp and toe locations, and the polyline feature class contains curvilinear RA travel distance lines that connect the headscarp and toe points. Additional attribute information includes the following: _location of headscarp and toe points, date of earliest identified occurrence, if and when the RA was sequestered into the glacier, presence and delineation confidence levels (see Table 1 for definition of A, B, and C confidence levels), identification method (visual inspection versus automated detection), image platform, satellite, estimated cloud cover, if the RA is lobate, image ID, image year, image band, affected area in km2, length, height, length/height, height/length, notes, minimum and maximum elevation, aspect at the headscarp point, slope at the headscarp point, and geology at the headscarp point. Topographic information was derived from 5-m interferometric synthetic aperture radar (IfSAR) Digital Elevation Models (DEMs) that were downloaded from the USGS National Elevation Dataset website (U.S. Geological Survey, 2015) and were mosaicked together in ArcGIS Pro. The aspect and slope layers were generated from the downloaded 5-m DEM with the “Aspect” and “Slope” tools in ArcGIS Pro. Aspect and slope at the headscarp mid-point were then recorded in the attribute table. A shapefile of Alaska state geology was downloaded from Wilson and others (2015) and was used to determine the geology at the headscarp _location. The 118 identified RAs have the following confidence level breakdown for presence: 66 are A-level, 51 are B-level, and 1 is C-level. The 118 identified RAs have the following confidence level breakdown for delineation: 39 are A-level and 79 are B-level. Please see the provided attribute table spreadsheet for more detailed information. Figure 2. Diagram showing seasonal timing of mapped rock avalanches. Table 1. Rock avalanche presence and delineation confidence levels Category Grade Justification Presence A Feature is clearly visible in one or more satellite images. B Feature is clearly visible in one or more satellite images but has low contrast with the surroundings and may be surficial debris from rock fall, rather than from a rock avalanche. C Feature presence is possible but uncertain due to poor quality of imagery (e.g., heavy cloud cover or shadows) or lack of multiple views. Delineation A Exact outline of the feature from headscarp to toe is clear. B General shape of the feature is clear but the exact headscarp or toe _location is unclear (e.g., due to clouds or shadows). Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References Maraldo, D.R., 2020, Accelerated retreat of coastal glaciers in the Western Prince William Sound, Alaska: Arctic, Antarctic, and Alpine Research, v. 52, p. 617-634, https://doi.org/10.1080/15230430.2020.1837715 McSaveney, M.J., 1978, Sherman glacier rock avalanche, Alaska, U.S.A. in Voight, B., ed., Rockslides and Avalanches, Developments in Geotechnical Engineering, Amsterdam, Elsevier, v. 14, p. 197–258. Post, A., 1967, Effects of the March 1964 Alaska earthquake on glaciers: U.S. Geological Survey Professional Paper 544-D, Reston, Virgina, p. 42, https://pubs.usgs.gov/pp/0544d/ Smith, W. D., Dunning, S. A., Brough, S., Ross, N., and Telling, J., 2020, GERALDINE (Google Earth Engine supRaglAciaL Debris INput dEtector): A new tool for identifying and monitoring supraglacial landslide inputs: Earth Surface Dynamics, v. 8, p. 1053-1065, https://doi.org/10.5194/esurf-8-1053-2020 Uhlmann, M., Korup, O., Huggel, C., Fischer, L., and Kargel, J. S., 2013, Supra-glacial deposition and flux of catastrophic rock-slope failure debris, south-central Alaska: Earth Surface Processes and Landforms, v. 38, p. 675–682, https://doi.org/10.1002/esp.3311 U.S. Geological Survey, 2015, USGS NED Digital Surface Model AK IFSAR-Cell37 2010 TIFF 2015: U.S. Geological Survey, https://elevation.alaska.gov/#60.67183:-147.68372:8 Wilson, F.H., Hults, C.P., Mull, C.G, and Karl, S.M, compilers, 2015, Geologic map of Alaska: U.S. Geological Survey Scientific Investigations Map 3340, pamphlet p. 196, 2 sheets, scale 1:1,584,000, https://pubs.usgs.gov/publication/sim3340

This packaged data collection contains all of the processed datasets that were used to develop the resistance surface used in our primary model. This package includes the following data layers: Roads Forested Land Cover (binned OGSI) Rivers Waterbodies Non-forested Land Cover (GNN ESLF Codes) Bays and Estuaries Potentially Suitable Land Cover on Serpentine Soils (used in post-processing of Resistance Surface) Please refer to the embedded metadata and the information in our full report for details on the acquisition and development of these data layers. Packaged data are available in two formats: Geodatabase (.gdb): A related set of file geodatabase rasters and feature classes, packaged in an ESRI file geodatabase. ArcGIS Pro Map Package (.mpkx): The same data included in the geodatabase, presented as fully-symbolized layers in a map. Note that you must have ArcGIS Pro version 2.0 or greater to view. See Cross-References for links to individual datasets, which can be downloaded in raster GeoTIFF (.tif) format.

The towns of Connecticut (CT) Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2022 are part of a zipped file containing two items: CT parcels in geodatabases organized by COGs and associated CAMA files. The parcel information includes 169 out of 169 town organized with geodatabases for each of the 9 Council of Governments. Most of the parcel data sets can be linked to the CAMA data which has attribute information (e.g. value of house, number of bedrooms) about real property. The parcel features for each town are in shape files, feature classes, or within a geodatabase. Most parcels are organized by town and COG and placed within a geodatabases. The CAMA data sets have information about real property within the towns of CT. It may be linked to the parcels using a join process within a GIS package like ArcGIS Pro or QGIS. 154 out of 169 towns have complete CAMA information. Of the remaining 15 towns, four have no information and the remaining have some limited information mixed into the parcel attribute tables. These files were gathered from the CT towns by the COGs and then submitted to CT OPM. Town data is organized by COG. Attribute names, primary key, secondary key, naming conventions, and file formats are not fully consistent but some cleaning and reorganization was conducted to improve quality. This file was created on 03/08/2023 from data collected in 2021-2022.