Interactive GIS map hosted by the City of Portland on the ArcGIS platform. This digital map features detailed geographical data and infrastructure information pertaining to Portland. It includes layers that users can toggle to view various city components such as zoning districts, public facilities, transportation networks, and residential areas. The map is designed to be user-friendly, providing tools for searching specific addresses or points of interest, measuring distances, and even creating customized views. This resource is particularly valuable for city planners, residents, and anyone interested in the spatial layout and planning of Portland.

This is a downloadable PDF of the City of Bend Sign Districts.This map is part of the City of Bend's printable map library and only updated periodically. Many of the maps have been formatted to print using large-format plotters and may not be legible when printed on letter-sized paper. Printed maps are available for purchase in a variety of sizes. Custom maps may also be requested. Please see our Fees and Services page for prices.An Interactive Map is also available which provides access to many of the same data layers that were used to create the maps found belowMap Last Updated: January 2025

The City of Frederick GIS Department maintains a number of interactive web mapping applications for use by both City employees and citizens collectively known as SpiresGIS. These applications allow users to find specific information such as property zoning and plat information as well as print custom paper maps.These mapping applications were developed using ESRI's Javascript Application Programming Interface in conjunction with ESRI's ArcServer. More applications are under development, and will be listed on this page in the near future.

Aquatic environmental DNA (eDNA) sampling is the collection of DNA released by a target species into streams, rivers, ponds, lakes, and wetlands. Detection of stream fish with eDNA can be remarkably sensitive—100% detection efficiency of target species has been achieved despite order-of-magnitude changes in stream discharge. The eDNA samples in the eDNAtlas database describe species occurrence locations and were collected by the U.S. Forest Service and numerous agencies that have partnered with the National Genomics Center for Wildlife and Fish Conservation (NGC) throughout the United States. The data were collected for a variety of project-specific purposes that included: species status assessments, trend monitoring at one or many sites, development of predictive species distribution models, detection and tracking of non-native species invasions, and assessments of habitat restoration efforts. The eDNAtlas database consists of two feature classes. The first component (eDNAtlas_West_AGOL_ResultsOnly) is a database of georeferenced species occurrence locations based on eDNA field sampling results, which are downloadable by species through a dynamic ArcGIS Online (AGOL) mapping tool. The earliest eDNA samples in the database were collected in 2015 but new samples and results are added annually to the database, which houses thousands of species occurrence records. The second component (eDNAtlas_West_SampleGridAndResults) is a systematically-spaced 1-kilometer grid of potential sample points in streams and rivers throughout the western United States. Future versions will include the eastern United States as well. The points in the sampling grid are arrayed along the medium-resolution National Hydrography Dataset Version 2 (NHDPlusV2) and can be used to develop custom eDNA sampling strategies for many purposes. Each sample point has a unique identity code that enables efficient integration of processed eDNA sample results with the species occurrence database. The eDNAtlas is accessed via an interactive ArcGIS Online (AGOL) map that allows users to view and download sample site information and lab results of species occurrence for the U.S. The results are primarily based on samples analyzed at the National Genomics Center for Wildlife and Fish Conservation (NGC) and associated with geospatial attributes created by the Boise Spatial Streams Group (BSSG). The AGOL map displays results for all species sampled within an 8-digit USGS hydrologic unit or series of units. The map initially opens to the project extent, but allows users to zoom to areas of interest. Symbols indicate whether a field sample has been collected and processed at a specific location, and if the latter, whether the target species was present. Each flowing-water site is assigned a unique identification code in the database to ensure that it can be tracked and matched to geospatial habitat descriptors or other attributes for subsequent analyses and reports. Because no comparable database has been built for standing water, results for those sites lack this additional information but still provide data on the sample and species detected. Resources in this dataset:Resource Title: The Aquatic eDNAtlas Project: Lab Results Map - USFS RMRS. File Name: Web Page, url: https://usfs.maps.arcgis.com/apps/webappviewer/index.html?id=b496812d1a8847038687ff1328c481fa The eDNAtlas is accessed via an interactive ArcGIS Online (AGOL) map that allows users to view and download sample site information and lab results of species occurrence for the U.S. The results are primarily based on samples analyzed at the National Genomics Center for Wildlife and Fish Conservation (NGC) and associated with geospatial attributes created by the Boise Spatial Streams Group (BSSG). The AGOL map displays results for all species sampled within an 8-digit USGS hydrologic unit or series of units. The map initially opens to the project extent, but allows users to zoom to areas of interest. Symbols indicate whether a field sample has been collected and processed at a specific location, and if the latter, whether the target species was present. Each flowing-water site is assigned a unique identification code in the database to ensure that it can be tracked and matched to geospatial habitat descriptors or other attributes for subsequent analyses and reports. Because no comparable database has been built for standing water, results for those sites lack this additional information but still provide data on the sample and species detected. For details on using the map see the Aquatic eDNAtlas Project: Lab Results ArcGIS Online Map Guide.

The agsview extension for CKAN provides view plugins designed to display Esri ArcGIS Server data directly within CKAN resources. Specifically, it enables visualization of ArcGIS Map services and Feature layer services, leveraging an Esri Leaflet Viewer for interactive display. As such, this extension enhances CKAN by providing native support for displaying commonly used geospatial data formats, increasing the usability of CKAN for geospatial data catalogs through built-in rendering capabilities when used by your organization's CKAN end users. Key Features: ArcGIS Feature Layer Viewer (agsfsview): Allows visualization of ArcGIS Feature Layers found within either MapServices or FeatureServices, offering a means by which you or your end users can expose specific layers, enabling selective display of datasets. Configuration option: ags_url: Specifies the ArcGIS Server layer endpoint, including the layer ID for targeted data access ensuring the correct layer or service is connected to your CKAN resource. Configuration option: basemapurl: Allows customization of the basemap by specifying either an Esri basemap name or a generic tile URL template, to tailor the visual context of the displayed ArcGIS data. ArcGIS MapService Viewer (agsmsview): Provides functionality to render ArcGIS MapServices, giving control over which layers within the service are displayed. Configuration option: ags_url: Defines the ArcGIS Server MapService endpoint, directing the viewer to the desired MapService resource for inclusion in your CKAN resource. Configuration option: list_ids: Enables filtering of layers within the MapService by providing a comma-delimited list of layer IDs for selective display. An empty list will display all layers, offering you flexibility in configuring the data viewed in CKAN. Configuration option: basemapurl: Permits customization of the basemap, accepting either an Esri basemap name or a generic tile URL template, ensuring flexibility in the map presentation. Configurable Default Basemap: Using your CKAN .ini configuration, you can set a default basemap for all ArcGIS views, providing consistency and improving usability. You can specify either an Esri basemap name or a tile URL template as the default. Technical Integration: The agsview extension integrates with CKAN by adding view plugins (agsfsview and agsmsview). To enable the extension, you must add the plugin names to the ckan.plugins setting in the CKAN configuration file (e.g., production.ini). After updating you CKAN file, and restarting the CKAN instance, the ArcGIS viewers become available options when creating a CKAN resource in the 'View' section assuming the resource has URLs that are supported by the viewing feature. Benefits & Impact: By implementing the agsview extension, CKAN instances can natively display ArcGIS Server MapServices and Feature Layers, eliminating the need for external viewers or custom development. This significantly enhances CKAN's utility for organizations managing and sharing geospatial data, as users can readily visualize Esri ArcGIS data directly within the CKAN interface. The configuration options further allow for customization of the display, improving the user experience.

This is a downloadable PDF of the Comprehensive Plan.This map is part of the City of Bend's printable map library and only updated periodically. Many of the maps have been formatted to print using large-format plotters and may not be legible when printed on letter-sized paper. Printed maps are available for purchase in a variety of sizes. Custom maps may also be requested. Please see our Fees and Services page for prices.An Interactive Map is also available which provides access to many of the same data layers that were used to create the maps found belowMap Last Updated: Jan 2025

Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations. Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals. Data from thegSSURGO databasewas used to create this layer. To download ready-to-use project packages of useful soil data derived from the SSURGO dataset, please visit the USA SSURGO Downloader app. Dataset Summary Phenomenon Mapped:Soils of the United States and associated territoriesGeographic Extent:The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaCoordinate System:Web Mercator Auxiliary SphereVisible Scale:1:144,000 to 1:1,000Source:USDA Natural Resources Conservation Service Update Frequency:AnnualPublication Date:December 2024 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 Online Add this layer to a map in the map viewer. The layer is limited to scales of approximately 1:144,000 or larger but avector tile layercreated from the same data can be used at smaller scales to produce awebmapthat displays across the full scale range. 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 forFarmland Class= "All areas are prime farmland" to create a map of only prime farmland.Add labels and set their propertiesCustomize the pop-upArcGIS Pro Add 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.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 theLiving Atlas of the Worldthat provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics. Data DictionaryAttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them. Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units. Area SymbolSpatial VersionMap Unit Symbol Map Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field. Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability Rating Legend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field. Project Scale Survey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields. Survey Area VersionTabular Version Map Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field. Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - Presence Rating for Manure and Food Processing Waste - Weighted Average Component Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected. Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent Key Component Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r). Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence -

About this itemSmall organizations, including many that work on natural resource issues, often lack the capacity to use spatial data in their decision making processes. This has generally required expensive software and specialized training. Researchers at the Natural Resources Research Institute, along with collaborators at the University of Minnesota Center and Minnesota Sea Grant, have worked to remove those barriers through the development of the Minnesota Natural Resource Atlas. This interactive online Atlas provides a basic set of GIS tools for exploring, visualizing, and analyzing spatial data. Users have access to over 450 data layers across the state of Minnesota and the ability to measure, access attribute data, conduct basic summaries, query features, and view different combinations of these data. Information can be shared by exporting analysis results and map images or by creating a unique URL that other users can follow to a custom map. The Atlas is offered as a free public resource.Author/ContributorKristi NixonOrganizationNatural Resources Research InstituteOrg Websitenrri.umn.edu

Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm

The demographic data displayed in this theme of Florida’s Roadmap to Living Healthy are quantitative measures that exhibit the socioeconomic state of Florida’s communities. The data sets comprising this themed map include topics such as population, race, income level, age, education, housing, and lifestyle data for all of Florida’s 67 counties, and other basic demographic characteristics. The Florida Department of Agriculture and Consumer Services has utilized the most current demographic statistical data from trusted sources such as the U.S. Census Bureau, U.S. Department of Housing and Urban Development, U.S. Department of Labor Bureau of Labor Statistics, Florida Department of Children and Families, and Esri to craft this custom visualization. Demographics provide profound perspective to your data analytics and will help you recognize the distinctive characteristics of a population based on its location. This demographic-themed mapping tool will simplify your ability to identify the specific socioeconomic needs of every community in Florida.