Web GIS GeoProcessor (http://www.geo.iitp.ru/app.php?link=gis:geoproc2) is targeted to perform analysis of spatial geographic information as well as to solve problems of spatial forecasting. The field of application comprises spatial-data analysis, geological environment research and decision-making support in such problems as seismic hazard assessment and environmental zonation. Analytical abilities of GIS are supplemented by visual research methods, vector and grid-based data calculations, operations of spatial forecasting and pattern recognition, etc. Considering examples of earthquake damage assessment, seismic hazard analysis, geophysical properties forecasting, GeoProcessor 2.0 proved to be an effective tool for fundamental and applied problem investigation.

Web-GIS GeoTime 2.0 is intended for spatio-temporal process analysis and simulation. The field of application comprises seismic hazard, earthquake precursor analysis etc. The system consists of the kernel and a set of user-defined plug-ins that make the system capable to solve the problems in the specific areas of study. The animated visualization facilities of GIS provide visual exploration of 3D raster fields and 4D event catalogues as well. The system possesses a wide range of advanced analytical functions. Along with common vector and 3D grid-based calculations there are a number of additional plug-ins designed for computation of spatio-temporal fields of seismic characteristics. They comprise plug-in for minimal representative magnitude field estimation (Mmin), b-value, seismic activity, RTL, plug-in for detection and significance estimation of spatio-temporal earthquake precursors etc.

Open-Source GIS plays a pivotal role in advancing GIS education, fostering research collaboration, and supporting global sustainability by enabling the sharing of data, models, and knowledge. However, the integration of big data, deep learning methods, and artificial intelligence deep learning in geospatial research presents significant challenges for GIS education. These include increasing software learning costs, higher computational power demand, and the management of fragmented information in the Web 2.0 context. Addressing these challenges while integrating emerging GIS innovations and restructuring GIS knowledge systems is crucial for the evolution of GIS Education 3.0. This study introduces a Visual Programming-based Geospatial Cyberinfrastructure (V-GCI) framework, integrated with the replicable and reproducible (R&R) framework, to enhance GIS function compatibility, learning scalability, and web GIS application interoperability. Through a case study on spatial accessibility using the generalized two-step floating catchment area method (G2SFCA), this paper demonstrates how V-GCI can reshape the GIS knowledge tree and its potential to enhance replicability and reproducibility within open-source GIS Education 3.0.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://communities.geoplatform.gov/ngda-cadastre/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. This PAD-US Version 3.0 dataset includes a variety of updates from the previous Version 2.1 dataset (USGS, 2020, https://doi.org/10.5066/P92QM3NT ), achieving goals to: 1) Annually update and improve spatial data representing the federal estate for PAD-US applications; 2) Update state and local lands data as state data-steward and PAD-US Team resources allow; and 3) Automate data translation efforts to increase PAD-US update efficiency. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in the PAD-US (other data were transferred from PAD-US 2.1). Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in annual PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. The following is a list of updates or revisions associated with the federal estate: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations where available), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), and National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/ ). 2) Improved the representation (boundaries and attributes) of the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. 3) Added a Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) to the PAD-US 3.0 geodatabase to facilitate the extraction (by Data Provider, Dataset Name, and/or Aggregator Source) of authoritative data provided directly (or recommended) by federal managing agencies from the full PAD-US inventory. A summary of the number of records (Frequency) and calculated GIS Acres (vs Documented Acres) associated with features provided by each Aggregator Source is included; however, the number of records may vary from source data as the "State Name" standard is applied to national files. The Feature Class (FeatClass) field in the table and geodatabase describe the data type to highlight overlapping features in the full inventory (e.g. Designation features often overlap Fee features) and to assist users in building queries for applications as needed. 4) Scripted the translation of the Department of Defense, Census Bureau, and Natural Resource Conservation Service source data into the PAD-US format to increase update efficiency. 5) Revised conservation measures (GAP Status Code, IUCN Category) to more accurately represent protected and conserved areas. For example, Fish and Wildlife Service (FWS) Waterfowl Production Area Wetland Easements changed from GAP Status Code 2 to 4 as spatial data currently represents the complete parcel (about 10.54 million acres primarily in North Dakota and South Dakota). Only aliquot parts of these parcels are documented under wetland easement (1.64 million acres). These acreages are provided by the U.S. Fish and Wildlife Service and are referenced in the PAD-US geodatabase Easement feature class 'Comments' field. State updates - The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates, as resources allow. The USGS supported efforts to significantly increase state inventory completeness with the integration of local parks data in the PAD-US 2.1, and developed a state-to-PAD-US data translation script during PAD-US 3.0 development to pilot in future updates. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the following three states: 1) California - added or updated state, regional, local, and nonprofit lands data from the California Protected Areas Database (CPAD), managed by GreenInfo Network, and integrated conservation and recreation measure changes following review coordinated by the data-steward with state managing agencies. Developed a data translation Python script (see Process Step 2 Source Data Documentation) in collaboration with the data-steward to increase the accuracy and efficiency of future PAD-US updates from CPAD. 2) Virginia - added or updated state, local, and nonprofit protected areas data (and removed legacy data) from the Virginia Conservation Lands Database, provided by the Virginia Department of Conservation and Recreation's Natural Heritage Program, and integrated conservation and recreation measure changes following review by the data-steward. 3) West Virginia - added or updated state, local, and nonprofit protected areas data provided by the West Virginia University, GIS Technical Center. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-history for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.

The research focus in the field of remotely sensed imagery has shifted from collection and warehousing of data ' tasks for which a mature technology already exists, to auto-extraction of information and knowledge discovery from this valuable resource ' tasks for which technology is still under active development. In particular, intelligent algorithms for analysis of very large rasters, either high resolutions images or medium resolution global datasets, that are becoming more and more prevalent, are lacking. We propose to develop the Geospatial Pattern Analysis Toolbox (GeoPAT) a computationally efficient, scalable, and robust suite of algorithms that supports GIS processes such as segmentation, unsupervised/supervised classification of segments, query and retrieval, and change detection in giga-pixel and larger rasters. At the core of the technology that underpins GeoPAT is the novel concept of pattern-based image analysis. Unlike pixel-based or object-based (OBIA) image analysis, GeoPAT partitions an image into overlapping square scenes containing 1,000'100,000 pixels and performs further processing on those scenes using pattern signature and pattern similarity ' concepts first developed in the field of Content-Based Image Retrieval. This fusion of methods from two different areas of research results in orders of magnitude performance boost in application to very large images without sacrificing quality of the output.

GeoPAT v.1.0 already exists as the GRASS GIS add-on that has been developed and tested on medium resolution continental-scale datasets including the National Land Cover Dataset and the National Elevation Dataset. Proposed project will develop GeoPAT v.2.0 ' much improved and extended version of the present software. We estimate an overall entry TRL for GeoPAT v.1.0 to be 3-4 and the planned exit TRL for GeoPAT v.2.0 to be 5-6. Moreover, several new important functionalities will be added. Proposed improvements includes conversion of GeoPAT from being the GRASS add-on to stand-alone software capable of being integrated with other systems, full implementation of web-based interface, writing new modules to extent it applicability to high resolution images/rasters and medium resolution climate data, extension to spatio-temporal domain, enabling hierarchical search and segmentation, development of improved pattern signature and their similarity measures, parallelization of the code, implementation of divide and conquer strategy to speed up selected modules.

The proposed technology will contribute to a wide range of Earth Science investigations and missions through enabling extraction of information from diverse types of very large datasets. Analyzing the entire dataset without the need of sub-dividing it due to software limitations offers important advantage of uniformity and consistency. We propose to demonstrate the utilization of GeoPAT technology on two specific applications. The first application is a web-based, real time, visual search engine for local physiography utilizing query-by-example on the entire, global-extent SRTM 90 m resolution dataset. User selects region where process of interest is known to occur and the search engine identifies other areas around the world with similar physiographic character and thus potential for similar process. The second application is monitoring urban areas in their entirety at the high resolution including mapping of impervious surface and identifying settlements for improved disaggregation of census data.

LUCY: NJ's Cultural Resources GIS Online Map Viewer

The New Jersey Historic Preservation Office (HPO) is pleased to provide LUCY 2.0, an updated and revised online viewer for New Jersey’s cultural resources inventory. LUCY fulfills an important mandate to disseminate cultural resources inventory data to constituents and the public. The updated application expands the list of available data layers, provides lists of related reports and typologies, and provides tools for better search and export of cultural resources data.

The HPO has defined the following layers to represent cultural resources in GIS applications: Historic District Polygons, Historic Property Polygons, Historic Property Feature Points, and Archaeological Site Grid. The data provided in these layers represents historic resources that:Are National Historic Landmarks (NHL),Are included in the NJ and/or National Registers of Historic Places (LISTED),Have formal determinations of eligibility for inclusion in the Registers (ELIGIBLE),Have been designated as local landmarks and districts by municipalities (LOCAL), orHave been documented and evaluated through cultural resources survey efforts statewide (IDENTIFIED).These layers also include resources no longer considered as historic, that:Have been formally determined not-eligible for inclusion in the Registers (NOT ELIGIBLE), orHave been formally de-listed and removed from the NJ and/or National Registers of Historic Places (DELISTED).A updated User Guide to assist users with the map application and its various tools will be available soon. The existing user guide is available on HPO's website. See HPO's GIS page for additional information about ongoing GIS initiatives.

Click here for general information about HPO and programs to identify, protect, preserve and sustain NJ's cultural resources.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

NRCS SSURGO Soils web map service. This is an Open GIS Consortium standard Web Map Service (WMS).Soil Data Access WMS 1.3.0 & WFS 2.0.0 Web Services HelpThe current Soil Data Access Web Map Service (WMS) supports Open Geospatial Consortium (OGC) WMS version 1.3.0 requests while the current Soil Data Access Web Feature Services (WFS) support OGC WFS version 2.0.0 (GML2/GML3) requests. GML is an acronym for Geography Markup Language, and is the XML grammar defined by the Open Geospatial Consortium (OGC) to express geographical features. GML serves as a modeling language for geographic systems as well as an open interchange format for geographic transactions on the Internet. EPSG is an acronym used throughout the Soil Data Access web pages. It stands for European Petroleum Survey Group. They publish a database of coordinate system information plus some very good related documents on map projections and datums.The current Soil Data Access WMS service is supported by the following ArcGIS Pro versions:ArcGIS PRO 3.xArcGIS PRO 2.xArcGIS PRO 1.4The current Soil Data Access WMS service is supported by the following ArcGIS Desktop versions:ArcGIS 10.8The current Soil Data Access WMS services are supported by the following ArcGIS Enterprise versions:ArcGIS Enterprise 10.6ArcGIS Enterprise 10.5The current Soil Data Access WFS services are supported by the following ArcGIS Enterprise versions:ArcGIS Enterprise 11.xArcGIS Enterprise 10.9ArcGIS Enterprise 10.8ArcGIS Enterprise 10.7ArcGIS Enterprise 10.6ArcGIS Enterprise 10.5

The Fireshed Registry 2.0 Web Map contains all data used in the Fireshed Registry 2.0 ArcGIS Experience Builder application. The Fireshed Registry is a U.S. Forest Service (USFS) application that organizes information about wildfire risk, ecosystem values and community characteristics into geographic landscape containers called firesheds that are used to describe past activity, present conditions, and past and predicted wildfires. The original Fireshed Registry Dashboard application was initially released in 2021 in response to the impacts of the 2020 fire season that prompted wide-ranging policy discussions about the role of active forest management to reduce hazardous fuels on federal and private wildlands (Ager et. al 2021). The Fireshed Registry is the data backbone for the Scenario Investment Planning Platform, which simulates specific investment scenarios and resulting possible outcomes for reducing wildfire transmission to communities. This updated Fireshed Registry 2.0 is a public-facing ArcGIS Online Experience Builder application that presents updated data and information used in the original Fireshed Registry dashboard, but also utilizes data directly from the Enterprise Data Warehouse (EDW) where authoritative data published by the USFS is stored. The Fireshed Registry 2.0 also incorporates Expanded Fireshed Exposure Map data layers that were compiled to support identification of potential additional landscapes for focused work under the Wildfire Crisis Strategy (WCS). Utilizing authoritative EDW data allows for more rapidly refreshed and up-to-date data to be incorporated, while data compiled to support identification of additional WCS landscapes allows for the visualization of additional ecological and community values to identify exposure and vulnerability.More information about the Fireshed Registry 2.0 and source data can be found in the Fireshed Registry 2.0 Data Documentation PDF. References:Ager, Alan A.; Day, Michelle A.; Ringo, Chris; Evers, Cody R.; Alcasena, Fermin J.; Houtman, Rachel M.; Scanlon, Michael; Ellersick, Tania. 2021. Development and application of the fireshed registry. Gen. Tech. Rep. RMRS-GTR-425. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 47 p. https://doi.org/10.2737/RMRS-GTR-425.

NaturalVue® 2.0 global imagery provides a seamless, virtually cloud-fee, basemap for geospatial and web-based mapping applications, military/defense logistics, GIS backdrops, flight simulation, cartographic mapping, 3-D visualization, and more.Spatial Coverage: GlobalSpatial Resolution: 15 meters per pixelSpatial Accuracy: +/- 12.6 meters RMSEImage Currency: Predominantly 2014-2016Image Source: 95% Landsat 8The imagery in this layer is presented in an ArcGIS Web Mercator tiling scheme.

A general-pupose basemap designed to support a wide variety of web-based mapping needs. Through its countywide display of highways and streets, waterbodies, incorporated cities, and parks, the map is suitable as a stand-alone, general-reference map and as a base for thematic data display using operational map overlays. The map was designed specifically for use in ArcGIS Server applications, with scale-dependent layers and label classes customized for the Google/Bing Web Mercator tiling scheme, but it is also useful as a "quick-and-dirty" basemap for other map projects (although as a cached map service the map content is unalterable).

From the dawn of the internet, water resources data scientists and engineers have continually and boldly engaged with the challenge of developing and deploying interactive water data visualization and analysis web sites. This challenge is characterized by ever-changing internet technologies, new and endlessly varying programming languages and libraries, rapidly growing datasets, and increasingly complex analytical and modeling techniques. Indeed, the ideal water web site is always just out of reach because of these always changing tools and growing needs. It is likely that such challenges will exist for many future generations of hydroinformaticists. However, we reason that it ought to be possible to at least reduce the gap between what we can readily accomplish with existing tools and technologies and what our ideal might be. Towards this end, the Tethys Platform for water resources web apps has been developed. This platform combines a number of key visualization and data management technologies within a Django-based Python programming environment that simplifies deploying GIS-enabled water resources web apps. The system provides developers and users with an app portal, not entirely unlike the app paradigm that is common on tablets and mobile phones, where each app is developed, tested, deployed, and operated independently of other apps in the same portal. The app development framework includes OpenLayers map visualization, 52North geoprocessing capabilities, PostgreSQL database access, and a number of so-called "gizmos" that simplify user interface development. This presentation will give an architectural overview of the free and open source Tethys Platform and will illustrate the capabilities of the framework using several apps developed using the recently released Tethys version 2.0.

Presentation at 2018 AWRA Spring Specialty Conference: Geographic Information Systems (GIS) and Water Resources X, Orlando, Florida, April 23-25, http://awra.org/meetings/Orlando2018/

This web map includes the GEOGLOWS 2.0 ECMWF Streamflow Model (10-Day Forecast) and a customized vector base map.The individual base layers (Reference and Base) were created from similar Esri Vector Basemaps (World Terrain Reference Local Language and Dark Gray Canvas) using the Vector Style Editor.Each layer was customized specifically for the Global Water Sustainability (GEOGLOWS) and the European Centre for Medium-range Weather Forecasting (ECMWF) Streamflow Model 2.0 (10-Day Forecast).

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using over twenty-five attributes and five feature classes representing the U.S. protected areas network in separate feature classes: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. Five additional feature classes include various combinations of the primary layers (for example, Combined_Fee_Easement) to support data management, queries, web mapping services, and analyses. This PAD-US Version 2.1 dataset includes a variety of updates and new data from the previous Version 2.0 dataset (USGS, 2018 https://doi.org/10.5066/P955KPLE ), achieving the primary goal to "Complete the PAD-US Inventory by 2020" (https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision) by addressing known data gaps with newly available data. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in PAD-US, along with continued improvements and regular maintenance of the federal theme. Completing the PAD-US Inventory: 1) Integration of over 75,000 city parks in all 50 States (and the District of Columbia) from The Trust for Public Land's (TPL) ParkServe data development initiative (https://parkserve.tpl.org/) added nearly 2.7 million acres of protected area and significantly reduced the primary known data gap in previous PAD-US versions (local government lands). 2) First-time integration of the Census American Indian/Alaskan Native Areas (AIA) dataset (https://www2.census.gov/geo/tiger/TIGER2019/AIANNH) representing the boundaries for federally recognized American Indian reservations and off-reservation trust lands across the nation (as of January 1, 2020, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey) addressed another major PAD-US data gap. 3) Aggregation of nearly 5,000 protected areas owned by local land trusts in 13 states, aggregated by Ducks Unlimited through data calls for easements to update the National Conservation Easement Database (https://www.conservationeasement.us/), increased PAD-US protected areas by over 350,000 acres. Maintaining regular Federal updates: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 2) Complete National Marine Protected Areas (MPA) update: from the National Oceanic and Atmospheric Administration (NOAA) MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; Other changes: 1) PAD-US field name change - The "Public Access" field name changed from 'Access' to 'Pub_Access' to avoid unintended scripting errors associated with the script command 'access'. 2) Additional field - The "Feature Class" (FeatClass) field was added to all layers within PAD-US 2.1 (only included in the "Combined" layers of PAD-US 2.0 to describe which feature class data originated from). 3) Categorical GAP Status Code default changes - National Monuments are categorically assigned GAP Status Code = 2 (previously GAP 3), in the absence of other information, to better represent biodiversity protection restrictions associated with the designation. The Bureau of Land Management Areas of Environmental Concern (ACECs) are categorically assigned GAP Status Code = 3 (previously GAP 2) as the areas are administratively protected, not permanent. More information is available upon request. 4) Agency Name (FWS) geodatabase domain description changed to U.S. Fish and Wildlife Service (previously U.S. Fish & Wildlife Service). 5) Select areas in the provisional PAD-US 2.1 Proclamation feature class were removed following a consultation with the data-steward (Census Bureau). Tribal designated statistical areas are purely a geographic area for providing Census statistics with no land base. Most affected areas are relatively small; however, 4,341,120 acres and 37 records were removed in total. Contact Mason Croft (masoncroft@boisestate) for more information about how to identify these records. For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual .

EPA Beach Advisory ViewerBEach Advisory and Closing Online Notification (BEACON) systemUnder the Beaches Environmental Assessment and Coastal Health (BEACH) Act of 2000, EPA provides annual grants to coastal and Great Lakes states, territories, and eligible tribes to help local authorities monitor their coastal and Great Lakes beaches and notify the public of water quality conditions that may be unsafe for swimming. To learn more about the Beach Program, please visit the Beach Program Home Page.The U.S. Environmental Protection Agency (EPA) created the BEach Advisory and Closing Online Notification (BEACON) system to meet the Agency's requirement to provide to the public a database of pollution occurrences for coastal recreation waters. EPA's response to this requirement, BEACON, contains state-reported beach monitoring and notification data and is available online. The “States” (including Tribes and Territories) are not required to submit their beach season data to EPA until the beginning of the following calendar year and then we work with them to verify that the data is presented accurately on EPA's BEACON website. For links to state webpages, please see: https://www.epa.gov/beaches/state-and-local-beach-programs. The BEACON 2.0 User's Guide describes how to use the online BEACON 2.0 system to obtain state-reported beach monitoring and notification data.

Have an Emergency or think you are close to a fire? Dial 911 or contact your local public safety agency for instructions. For evacuation information - see the local law enforcement agency website or call them directly. If your local agency provides a map of any of this information - use their map! What is on this map and when does this map update?This is a map made with publicly available information and is being updated from government data sources, not the map author. There are four key sources of fire information in this map:New Wildfire Crowdsourced Locations from #FireMappers - This is a feed from a Prototype Survey123 Form for reporting new fire locations (e.g., Initial Attack) quickly and in a spatially explicit manner, from a variety of sources (i.e., social media, scanner traffic, flight radar, agency websites, etc.). It is maintained by GISCorps volunteers and is meant to be a way to quickly map new fires.Active Fires (Nationwide - IRWIN) from computer aided dispatch - This layer provides a near real-time view of the data being shared through the Integrated Reporting of Wildland-Fire Information (IRWIN) service. IRWIN provides data exchange capabilities between participating wildfire systems, including federal, state and local agencies. Data is synchronized across participating organizations to make sure the most current information is available. These points will "time out" of the map if Fire Discovery Date Time is more than two days ago but Calculated Acres is not at least 0.1.Wildfire Perimeters (NIFC) - The estimated burned area determined by the incident management team. These are generally based on overnight observations from aircraft with infrared sensors, but will update each day for large fires around 1130AM Pacific Time. Satellite Hot Spot Detection (MODIS and VIIRS) - [Turned off by default] The approximate locations of heat detected by NASA Satellites which will update several times per day. These points are indicative only and subject to horizontal accuracy issues and errors, for more information see FIRMS FAQ.Want to know more about #FireMappers? See our Story Map https://arcg.is/1bKS8f Are you a public safety agency and want to make your own public information map? See Public Information Map Resources from NAPSG Foundation.Would you like to share this map on your website?You can use the share widget functionality built into the application. Please attribute the #FireMappers and do reach out to admin@publicsagetygis.org so we know you are using the map. Click on any link under Layers below for more information about that data source.

Notice - Replacement of the English and French Web services (WMS and ESRI REST) with a bilingual one. The NRN product is distributed in the form of thirteen provincial or territorial datasets and consists of two linear entities (Road Segment and Ferry Connection Segment) and three punctual entities (Junction, Blocked Passage, Toll Point) with which is associated a series of descriptive attributes such as, among others: First House Number, Last House Number, Street Name Body, Place Name, Functional Road Class, Pavement Status, Number Of Lanes, Structure Type, Route Number, Route Name, Exit Number. The development of the NRN was realized by means of individual meetings and national workshops with interested data providers from the federal, provincial, territorial and municipal governments. In 2005, the NRN edition 2.0 was alternately adopted by members from the Inter-Agency Committee on Geomatics (IACG) and the Canadian Council on Geomatics (CCOG). The NRN content largely conforms to the ISO 14825 from ISO/TC 204.

Internet access in the United States varies greatly based on where you live. This map illustrates the state of high speed Internet access across the US. Darker colors indicate areas with less access to high speed Internet, while lighter areas indicate areas of high access.You can click any feature in the map for more information about Internet access and basic demographics. Zoom in to see ZIP Code data.Greater Access to High Speed InternetLower Access to High Speed InternetThis map uses index values from Esri's Market Potential data. An index value of 100 represents the national average for access to high speed Internet. A value of 110 indicates an area is 10% more likely than the national average to have access to high speed Internet.

Web Map used in the Forests 2 Faucets 2.0 Web App (F2F Web App). This map contains the layers used to display infographic information as well as run Upstream/Downstream, PWS, and individual watershed reporting in the web app.

This is the Montgomery County Government GIS Open Data Website based on Esri's Open Data 2.0 Platform. It can be used for exploring and downloading public GIS Datasets. You can analyze and combine different GIS Open Datasets.