Navigator for ArcGIS is a mobile app that gets your field workforce where it needs to be, unlocking efficiency gains and improving reliability. Learn how it works offline in seamless interaction with ArcGIS field apps. Experience how to use the data provided, your own custom data, or both to search and navigate directly to your organization's assets.This seminar was developed to support ArcGIS Online and Navigator for ArcGIS.

An ArcGIS Field Maps map used by a mobile worker to add lead service line data.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

At https://learn.arcgis.com, users find scenario-based tutorials, using specific tools, built by Esri and users. Explore filters at top left of the gallery. K12 students and educators may explore tutorials that engage software in the ArcGIS School Bundle -- ArcGIS Online (includes Map Viewer, Scene Viewer, Survey123, Field Maps, QuickCapture, Dashboard, Story Maps, Experience Builder, Hub, Instant Apps, Web AppBuilder), Business Analyst, Community Analyst, GeoPlanner, Insights, ArcGIS Pro, ArcGIS Urban, and Drone2Map.These tutorials rely on the user having a proper license. K12 students and teachers may use these tutorials via their assigned school Org login, which should prevent sharing personally identifiable information.

Equivalence (the equal-area property of a map projection) is important to some categories of maps. However, unlike for conformal projections, completely general techniques have not been developed for creating new, computationally reasonable equal-area projections. The literature describes many specific equal-area projections and a few equal-area projections that are more or less configurable, but flexibility is still sparse. This work develops a tractable technique for generating a continuum of equal-area projections between two chosen equal-area projections. The technique gives map projection designers unlimited choice in tailoring the projection to the need. The technique is particularly suited to maps that dynamically adapt optimally to changing scale and region of interest, such as required for online maps.

There has been a limited amount of research focused on the design of landslide maps, which are considered as one of the potential means to communicate disaster risks to the public. Hence, this article aims to conduct a systematic review of the process involved in creating landslide maps specifically for the purpose of disaster risk communication with non-expert users. While this topic is still under-studied, it has gained increasing coverage in the peer-reviewed literature over the past five years. The review examines the variations in the process of creating landslide maps, considering aspects such as planning, mapping techniques, presentation, and dissemination. However, there are several areas that require improvement, including diversifying the types of maps, considering the role and involvement of users, developing more user-friendly designs, and reducing reliance on experts during the dissemination process. The findings of this review provide valuable insights into the current limitations in establishing these maps and offer guidance for future research in this field.

Contents: This is an ArcGIS Pro zip file that you can download and use for creating map books based on United States National Grid (USNG). It contains a geodatabase, layouts, and tasks designed to teach you how to create a basic map book.Version 1.0.0 Uploaded on May 24th and created with ArcGIS Pro 2.1.3 - Please see the README below before getting started!Updated to 1.1.0 on August 20thUpdated to 1.2.0 on September 7thUpdated to 2.0.0 on October 12thUpdate to 2.1.0 on December 29thBack to 1.2.0 due to breaking changes in the templateBack to 1.0.0 due to breaking changes in the template as of June 11th 2019Updated to 2.1.1 on October 8th 2019Audience: GIS Professionals and new users of ArcGIS Pro who support Public Safety agencies with map books. If you are looking for apps that can be used by any public safety professional, see the USNG Lookup Viewer.Purpose: To teach you how to make a map book with critical infrastructure and a basemap, based on USNG. You NEED to follow the steps in the task and not try to take shortcuts the first time you use this task in order to receive the full benefits. Background: This ArcGIS Pro template is meant to be a starting point for your map book projects and is based on best practices by the USNG National Implementation Center (TUNIC) at Delta State University and is hosted by the NAPSG Foundation. This does not replace previous templates created in ArcMap, but is a new experimental approach to making map books. We will continue to refine this template and work with other organizations to make improvements over time. So please send us your feedback admin@publicsafetygis.org and comments below. Instructions: Download the zip file by clicking on the thumbnail or the Download button.Unzip the file to an appropriate location on your computer (C:\Users\YourUsername\Documents\ArcGIS\Projects is a common location for ArcGIS Pro Projects).Open the USNG Map book Project File (APRX).If the Task is not already open by default, navigate to Catalog > Tasks > and open 'Create a US National Grid Map Book' Follow the instructions! This task will have some automated processes and models that run in the background but you should pay close attention to the instructions so you also learn all of the steps. This will allow you to innovate and customize the template for your own use.FAQsWhat is US National Grid? The US National Grid (USNG) is a point and area reference system that provides for actionable location information in a uniform format. Its use helps achieve consistent situational awareness across all levels of government, disciplines, and threats & hazards – regardless of your role in an incident.One of the key resources NAPSG makes available to support emergency responders is a basic USNG situational awareness application. See the NAPSG Foundation and USNG Center websites for more information.What is an ArcGIS Pro Task? A task is a set of preconfigured steps that guide you and others through a workflow or business process. A task can be used to implement a best-practice workflow, improve the efficiency of a workflow, or create a series of interactive tutorial steps. See "What is a Task?" for more information.Do I need to be proficient in ArcGIS Pro to use this template? We feel that this is a good starting point if you have already taken the ArcGIS Pro QuickStart Tutorials. While the task will automate many steps, you will want to get comfortable with the map layouts and other new features in ArcGIS Pro.Is this template free? This resources is provided at no-cost, but also with no guarantees of quality assurance or support at this time. Can't I just use ArcMap? Ok - here you go. USNG 1:24K Map Template for ArcMapKnown Limitations and BugsZoom To: It appears there may be a bug or limitation with automatically zooming the map to the proper extent, so get comfortable with navigation or zoom to feature via the attribute table.FGDC Compliance: We are seeking feedback from experts in the field to make sure that this meets minimum requirements. At this point in time we do not claim to have any official endorsement of standardization. File Size: Highly detailed basemaps can really add up and contribute to your overall file size, especially over a large area / many pages. Consider making a simple "Basemap" of street centerlines and building footprints.We will do the best we can to address limitations and are very open to feedback!

The Community Map (World Edition) web map provides a customized world basemap that is uniquely symbolized and optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and sports amenities like tennis courts, football and baseball field lines, and more. This basemap, included in the ArcGIS Living Atlas of the World, uses the Community vector tile layer. The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the layer items referenced in this map.

Abstract The analysis of the dynamics of changes in patterns of land use and occupation, which is essential for the planning of urban areas, can be done indirectly through remote sensing orbital images. Orbital images have proven to be important tools for measuring and monitoring human activities on Earth. Thus, this paper aims to map the surrounding areas of Passeio das Águas Shopping Center, located in the northern region of Goiânia, Brazil, assigning to it the condition of Travel Generator (TG). Hence, this study analysed the dynamics of change in land use and cover in its surroundings. The methodology used was based on the digital processing of orbital images in a Geographic Information System (GIS) environment. The results showed that, in a 10-year interval, there was a reduction of the vegetation area, and a significant increase in the paved and built areas, promoting significant changes in the land use pattern after the implementation of the TG.

This is the final report describing the work that Frenchman Cambridge Irrigation District performed in the project. The objective of this research project is to design, develop, and test a pilot collaborative environment between two Irrigation Districts and Reclamation within the Missouri Basin (MB Region). The collaborative environment will utilize ArcGIS Online, ArcGIS Pro, and Field Maps. Through robust testing, the design process, procedural standards, and lessons learned in the implementing stages will be documented and shared with all Regions.

Geographical areas covered by a design code.

This data is digitized from the "Yinchuan Land Use Status Map" of the drawing, which is a key scientific and technological research project in the "Seventh Five-Year Plan" of the country: "Three North" Shelter Forest Remote Sensing Comprehensive Survey, one of the series maps of Ganqingning Type Area, with the following information: * Chief Editor: Wang Yimou * Deputy Editors: Feng Yushun, You Xianxiang, Shen Yuancun * Editors: Wang Xian, Wang Jingquan, Qiu Mingxin, Quan Zhijie, Mou Xindai, Qu Chunning, Yao Fafen, Qian Tianjiu, Huang Autonomy, Mei Chengrui, Han Xichun, Li Yujiu, Hu Shuangxi * Responsible Editor: Huang Meihua * Editorial: Feng Yushun and Yao Fafen * Compilation: Yao Fafen, Li Zhenshan, Wang Xizhang, Zhu Che, Ma Bin, Yang Ping * Editors: Feng Yushun and Wang Yimou * Qing Hua: Wang Jianhua, Yao Fafen, Ma Bin, Li Zhenshan * Cartographic unit: compiled by Desert Research Office of Chinese Academy of Sciences * Publishing House: Xi 'an Map Publishing House * Scale: 1: 500000 * Publication time: not yet available 2. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Desertification type map (desert), Yinchuan landuse map (landuse), railway, residential _ poly, residential, River, Road, Water_poly 3. Data Fields and Attributes Type number land_type Desert shape Paddy field Paddy field 12 Irrigated field 131 Plain non-irrigated field Valley non-irrigate field Slope non-irrigated field, 133 slope dryland 134 dryland Terrace non-irrigat field 14 Vegetable plot vegetable plot 15 Abandoned farmland Orchard orchard 31 Woodland ......... Specific attribute contents refer to data documents 2. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000

CDFW BIOS GIS Dataset, Contact: Kristeen Penrod, Description: The Critical Linkages: Bay Area & Beyond project was initiated in 2010 to identify areas that are vital for connectivity within the nine-county Bay Area and beyond to ensure the region is connected to the larger landscapes to the north and south.

This repository contains sub-mm wavelength sky images of the combined Herschel Stripe 82 Survey (HerS; [1]) and Herschel Large Mode Survey (HeLMS; [2]) fields as observed by the SPIRE photometer [3] on the Herschel Space Observatory [4] at 250, 350, and 500 microns. These regions were selected to overlap with the SDSS-Stripe82 [5] and ACT-CMB [6] fields in a contiguous fashion. The maps cover areas of approximately 360 square degrees at 6, 8.3, and 12 arcsec/pixel.

The data in this repository improve on previous analyses of these data, which were heterogeneously analyzed, served on non-permanent archives, and occasionally had errors discovered by the user community. The previous analyses include:
- HerS survey maps constructed ~2012 with the SHIM map maker, described in [1]
- HeLMS maps constructed ~2015 with the SANEPIC map maker, described in [7]
- HerS+HeLMS+XMM maps constructed ~2016 with the SHIM map maker, described in [8].
- HerS and HeLMS individual maps constructed ~2019 with the CADE map maker, described in [9].
While all of these maps are currently circulating in the community, we expect their availability to wane as time goes on. Further, in many cases the detailed reduction steps and provenance of the served products are unclear. In this repository we have uploaded vetted and error-free fits files constructed in a consistent way as follows.

To start, we use the Herschel Interactive Processing Environment (HIPE, version 15.0.1) and the most recent calibration files (version 14.3) to reduce the level zero observations to level one data products. The code and calibration tree are the last released by the Herschel team, and we do not expect improvements or updates to them in the future. For the products available in this download, our processing consists of the standard scanline calibration pipeline for SPIRE that comes pre-packaged in HIPE (Photometer Large Map Pipeline) with a few changes. The pipeline converts the detector timelines from products in engineering units (satellite pointing and voltages) to science products (sky pointing and flux units) with corrections for cross-talk, signal jumps, glitches, cooler burps, the low pass filter response, and the bolometer time response. We chose to turn off the temperature drift correction as we found that the SHIM map-maker performs better without it and we opt to use the sigma-kappa deglitcher rather than the wavelet deglitcher. We also do not perform any destriping or baseline subtraction of the scan lines with HIPE. The HIPE script is available as part of this download for inspection.

We apply this HIPE reduction to the 33 observation IDs listed below (21 from proposal ID OT2_mviero_2 [HerS; 10] and 12 from proposal ID GT2_mviero_1 [HeLMS; 11]), which are retrieved with HIPE from the Herschel Science Archive (HSA; http://archives.esac.esa.int/hsa/whsa/).

The level one observations are saved as HIPE-format fits files that are input into the map-maker as follows. Spatial maps of the astrophysical emission are produced using the SHIM map maker [12, with additional processing details provided in 13], which has been found to out-perform other map makers in terms of retaining fidelity on all angular scales [14]. SHIM is a Herschel-SPIRE specific implementation of an iterative baseline removal and detector noise weighting algorithm originally described in [15]. The data are processed scan-wise, i.e. baselines and weights are calculated per one pass of the photometer across a region of sky. A noise map is created by propagating detector noise as estimated by the variance of the residuals and computing the weighted inverse sum in the map pixels. This detector noise propagation methodology gives a better measure of noise variations across the map and is more robust when the number of samples per pixel is low and the standard deviation becomes a poor estimate of the statistical error in the measurement. Also included in the fits files are exposure and flag information. The images are in units of [Jy/beam], which can be converted to units of surface brightness in [MJy/Sr] by applying the multiplicative conversion factors 90.646, 51.181, and 23.580 at 250, 350, and 500 microns, respectively. The error maps are reported as the square root of the variance of the statistical noise in each pixel, and do not include the (large) effect of confusion noise in these maps [see eg 16]. Though we do not explicitly provide map transfer function estimates, the transfer function is 1% to angular scales of ~1 degree, and thereafter falls exponentially with a 3dB point of ~6 degrees.

The FITS files provided in this repository are labeled with the SPIRE band names PSW, PMW, and PLW, which correspond to 250, 350, and 500 microns, respectively. Each FITS file contains a header data unit list (HDU, HDUL) with a primary HDU containing only very basic header info and four image HDUs with more extensive header info and the image data. The table below gives some information on the HDUL.

The 'image' extension contains the science mosaics calibrated in F_nu, the 'error' extension contains the errors corresponding to the science mosaic (and are derived as described above), the 'exposure' extension is the effective number of seconds of integration in each map pixel, and finally the 'mask' extension contains the image mask, which is currently an array of zeros as no masking has been applied to these images. Each image extension also contains information to reference to the world coordinate system.

Maps are derived from field maps and published maps of the site.

Landscape metrics description.

Geoform is a configurable app template for form based data editing of a Feature Service. This application allows users to enter data through a form instead of a map's pop-up while leveraging the power of the Web Map and editable Feature Services. This app geo-enables data and workflows by lowering the barrier of entry for completing simple tasks. Use CasesProvides a form-based experience for entering data through a form instead of a map pop-up. This is a good choice for users who find forms a more intuitive format than pop-ups for entering data.Useful to collect new point data from a large audience of non technical staff or members of the community.Configurable OptionsGeoform has an interactive builder used to configure the app in a step-by-step process. Use Geoform to collect new point data and configure it using the following options:Choose a web map and the editable layer(s) to be used for collection.Provide a title, logo image, and form instructions/details.Control and choose what attribute fields will be present in the form. Customize how they appear in the form, the order they appear in, and add hint text.Select from over 15 different layout themes.Choose the display field that will be used for sorting when viewing submitted entries.Enable offline support, social media sharing, default map extent, locate on load, and a basemap toggle button.Choose which locate methods are available in the form, including: current location, search, latitude and longitude, USNG coordinates, MGRS coordinates, and UTM coordinates.Supported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis web app includes the capability to edit a hosted feature service or an ArcGIS Server feature service. Creating hosted feature services requires an ArcGIS Online organizational subscription or an ArcGIS Developer account. Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to Create a Web AppOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

IDPR's Idaho Trails App Dataset, Web Map, and Web App have been extensively retooled for 2024.

Feature Service

The new App is served by this Hosted Feature Layer dataset which can be updated more frequently and on-the-fly-- changes will appear on the App and through the feature Service in real time. The newest web presentation technology under AGOL, Experience Builder, served by this dataset, will make possible several extended features to come in future updates to the App. This packaged release replaces the App created with predecessor technology Web App Builder. Web App Builder technology is scheduled to be phased out by Esri by the end of 2024.

Under the hood

Linear routes, closure routes and areas, and boundary area data are ported through a Web Map from the underlying Hosted Feature Service (HFS). In addition to view settings for attributes popups set in the Web Map, additional visibility option not available directly included in the HFS data or controllable in the Web Map will be further processed in the Experience App presentation.

Underlaying Classes in the Dataset:

One single linear class "Idaho Routes" contains all road and trail features (60,000+ route segments):

Routes characterized as recreational in nature include "High Clearance" (previously "Jeep" treated as a road type, now as a full-width "trail" type): High-clearance, Special Vehicle Designation (mostly OHVs >50"), OHVs 50" and under, and single-track (each width class separated by seasonal and not); E-Bike; and, non-motorized and non-mechanized. Routes where vehicles either must be highway-legal (OHVs prohibited; typically paved roads), or routes requiring Restricted plate for legal OHV travel (mostly JURISDICTION = County); combined from previously-separate Layers: Highway-legal, Automobile, Other Roads (each with subcategories for seasonal access restrictions).

(Note: Different route types are no longer kept in separate layers as with the legacy Map Service dataset. Route symbology, and selectable visibility will be filtered based on the value in the SYMBOL attribute from the above linear class within the Web Map and Experience-based App. If dynamically consuming the Feature Service, provisions will need to be made to filter to select visibility by road and trail types based on the value in the SYMBOL field.)

"Points of Interest" (point type data) is comprised of a layer previously titled "Trailheads" and now includes the flexibility of other types of lat/lon point-based information such as links to external maps and "attractions" information such as site seeing destinations not previously included in IDPR's map presentation.
"Emergency Route Closures" contains linear route Closures (overlays any route where a Closure Order applies in web map) "Area Restrictions" is added for areas such as defined by human exclusion Orders (polygon; usually planned annual human or vehicle exclusion areas, but can be emergency closure as well) Multiple "Boundary" polygon classes contain boundary outlines and attributes information for IDPR Regions (3), Counties (44), Wildernesses (42), National Forests and Ranger Districts (39), and BLM District and Field Offices (12), and BLM land units (700+). These separate classes reduce the data footprint of the Routes data and are joined in App popups by geographic Intersection logic.

Bonus Material:

Added to the App are several optional, dynamic layers via publicly-available REST services selectable for visibility:

Idaho Department of Lands- Lands Available for Recreational Use (visible by-default) Idaho Department of Fish & Game Hunting Units boundaries and numbers BLM Surface Management Agency layer for all local, state, and federal agencies which manage public lands (accessible, and not)
US Forest Service Motor Vehicle Use Map, National Dataset (mirrors local MVUM paper and GeoPDF maps, where data available, lags local data when changes are made) National Park Service (NPS) Parks and Monuments areas and boundaries NOAA Snow Depth Other REST Services to be added based on utility in researching recreational access

This dataset is published for the use of the individuals who fund this Program. Organizations wishing to consume this Feature Service into their own application should inquire to IDPR to obtain a use agreement and schema information to aid in development.AGOL Experience App here: https://experience.arcgis.com/experience/97a42a2a73c944ba918042faf518c689

Inquire to maps@idpr.idaho.gov

The County Council has identified each area of the County as urban, suburban, or rural for road code Urban Road: a road segment in or abutting a Metro Station Policy Area, Town Center Policy Area, or other urban area expressly identified in a Council resolution.Rural Road: a road segment located in a rural policy area as defined in the County Growth Policy; Suburban Road: a road segment located elsewhere in the County.For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

As one of iCorridor applications, MEPDG web map provides site specific traffic data (Level 1) such as AADTT, vehicle class distribution, number of axle per truck, and axle load distribution for AASHTOWare Pavement ME Design. This program can generate the following three data files for any specific LHRS sections: Traffic data input file in XML format that contains the AADTT, vehicle class distribution, axle per truck, and axle spacing & configuration. Axle load spectrum file in ALF format that contains the axle load spectrum tables of single, tandem, tridem and quad axle types. A summary file in spreadsheet format that contains the above traffic data. The above XMF and ALF files can be directly input into AASHTOWare Pavement ME Design to run the analysis. If traffic data is insufficient within the LHRS section, the tables for Southern or Northern Ontario will be generated.NON-DIRECTIONAL option will provide an overall AADT and AADTT of the selected LHRS section in both directions. The pavement designer should enter the corresponding percent split of traffic volume for the design direction (typical 50%) to the ‘Percent trucks in design direction’ field. DIRECTIONAL option will provide the AADT and AADTT of the specific direction of the selected LHRS section, and the designer requires to enter 100% to the ‘Percent trucks in design direction’ field. Note that the designer requires to zoom in very close to the map in order to identify which direction to be chosen. Under rare circumstances should the designer require to select this option. If necessary, the data for AADT and AADTT as provided in iCorridor shall be overridden by the latest data provided by other sources, and the number of lanes at the design section should be verified with the designer or owner