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!

Everything is awesome!Of course I don't need to convince you of the charm, educational utility, considered minimalism, and pure joy that Lego brings to the world. So why would I need to convince you that making maps in a Lego aesthetic is worth your while?This ArcGIS Pro style makes any vector point, line, or polygon layer look like a grid of little plastic nobly studs, ready to capture eyeballs and whip up unbridled excitement for skeuomorphic cartography! Plus it always re-sorts itself as you zoom in and out, always looking nice and blocky.Created in collaboration with Warren Davison, this style is ready to assemble your map into little Lego wonders.Here are some snapshots for you to peruse.Based mainly on these two texture overlays (sitting atop a dynamically colorable background element: Happy assembling! John Nelson

Coastal grid of 6-acre cells containing 2010 and 2019 canopy estimates, change values, and site visit observations for incorporated areas in Chatham, Glynn, Bryan, Liberty, McIntosh, and Camden Counties, Georgia. Grid created using the Fishnet tool in ArcGIS Pro. 2010 and 2019 canopy data was aggregated to each grid cell to determine change. Cells with significant change +- 3 acres of loss or gain were visually inspected to determine areas for site visits.

The dataset consists of nitrogen dioxide, meteorological data, and traffic data from January to June 2019, which were generated taking into account the spatial distribution of the monitoring stations. Using the ArcGIS Pro software, a grid was created (Top -4,486,449.725263 m; Bottom - 4,466,449.725263 m; Left - 434,215.234430 m; Right - 451,215.234430 m) with a cell size having a width and height equal to 1000 m. There are 340 cells in total (20 by 17). Each cell value includes nitrogen dioxide, meteorological, and traffic attributes from assigned stations at a certain time. The cell value without stations was assigned to zero. The generated grid was exported as Comma Separated Values (CSV) files. Overall, 4,344 CSV files were generated every hour during the first six months of 2019. Meteorological data include ultraviolet radiation, wind speed, wind direction, temperature, relative humidity, barometric pressure, solar irradiance, and precipitation, traffic data includes intensity, occupation, load, and average speed. The datasets have an hourly rate. The data were obtained from the Open Data portal of the Madrid City Council. There are 24 air quality monitoring stations, 26 meteorological monitoring stations, and more than 4,000 traffic measurement points (the location of the measurement points was provided on a monthly basis as these points changed monthly).

This file contains the map layers that were used to create the Eddy Arboretum - Web Map, which was then used to create the Eddy Arboretum Interactive Map. These files were created in ArcGIS Pro and then imported into ArcGIS Online. This file contains the files that were used to create a simulation of the original grid of the arboretum, including the minimum bounding geometry and the point_grid, which were created using ArcPy. The polygons were made on two separate grids for the east and northwest sections and then merged into one shapefile. Only the IFG_Arboretum_Lichen and the arboretum_merge are currently in the Web Map. arboretum_merge was renamed to Tree Species by Conservation Status.The grid was interpretted from the original 1937 map of the Eddy Arboretum, and was verified using a high-accuracy GPS. This is the first digitized version of this product. The lichen locations are less precise as they were GPSed with mobile satellite.You can find the full Eddy Arboretum Interactive Map (Web Experience) here. If you have questions or comments about the creation of this map or any specific details regarding the information within, please contact Kara Kaur Sanghera. Kara is now affiliated with the Department of Geography at the University of California, Los Angeles, and can be reached at karakaur01@ucla.edu. If you need to update the ArcGIS shapefiles found in this map, please contact Courtney Canning (courtney.a.canning@usda.gov) or Christopher Looney (christopher.looney@usda.gov).

This large-format map, created for Discover Gilbert, showcases the town’s unique features and history through bright photography and engaging callouts. It highlights riparian preserves, foodie destinations, and a vibrant arts and culture scene, while a photojournalistic timeline traces Gilbert’s evolution from “Hay Shipping Capital” to “Phoenix’s Coolest Suburb.” Parks, golf courses, and cultural landmarks are located via a reference grid aligned to the town’s original surveyed Sections, a design choice that marries cartographic function with place-based storytelling. The design adopts Discover Gilbert’s lively palette and distinctive fonts, with locator insets for the greater Phoenix area, and drive time and direction. A silhouette of the Superstitions and the iconic Water Tower anchors the map in its sense of place.This map was almost entirely created in ArcGIS Pro. One of my favorite features is the reference grid that uses the street network. Fun fact: the purple alphanumeric tabs around the edges of the map are repeated in the side panels to help locate points of interest, and use text formatting tags for background, border, color, and font to show the coordinates in a purple box in-line with the text. Other fine cartographic details include the timeline, where the distribution of years is to scale, and the Drive Time and Direction map, where destinations and surrounding towns are placed accurately along concentric circles representing hours from Gilbert, positioned in the correct direction as the crow flies. Data sources include the HIFLD (now deprecated), Maricopa County, Town of Gilbert, Maricopa Association of Governments (a source that I discovered via the AGIC listserv!), Maricopa County Assessor, FAA, USGS NHD, OpenStreetMap, AZ GeoHub (thanks, AGIC!), NHPN, and Esri.

State radiometric concentration grids were created by merging the data recorded across many airborne radiometric surveys. This was an update to previous State grids to include recent surveys such as the extensive Gawler Craton Airborne Survey.... State radiometric concentration grids were created by merging the data recorded across many airborne radiometric surveys. This was an update to previous State grids to include recent surveys such as the extensive Gawler Craton Airborne Survey. Data was levelled using a combination of the AWAGS2 (Australia Wide Airborne Geophysical Survey) and vehicle-borne streaming radiometric tie-lines. Additional levelling procedures were employed using software routines developed by Geoscience Australia. Grids were low-pass filtered using a 7-point, degree-3 Savitzky-Golay filter (Savitzky, A. and Golay, Analytical Chemistry, 36: 1627-1639). In some regions grid resolution was improved using an upward continuation of one cell size. Concentration grids Potassium (K), Thorium (Th), Uranium (U) and Total Count (TC) grids were created using Intrepid grid merge with open file surveys. The previous state grid (2016) was used as the base map and merged with new or reprocessed grids. - SA_RAD_K_2024 - Potassium (%K), 57 new or reprocessed grids - SA_RAD_Th_2024 - Thorium (equivalent (e) ppm eTh), 118 new or reprocessed grids - SA_RAD_U_2024 - Uranium (equivalent (e) ppm eU), 162 new or reprocessed grids - SA_RAD_TC_2024 – Total Count (cps), 139 new or reprocessed grids Ternary Grid (SA_RAD_KThU_RGB_2024) A ternary (3 band) ERMapper raster consisting of the concentration grids: - Red – Potassium (SA_RAD_K_2024) - Green – Thorium (SA_RAD_Th_2024) - Blue –Uranium (SA_RAD_U_2024) U2 / Th (SA_RAD_U2Th_2024) A single band ERMapper grid of uranium squared divided by thorium. Most values are between 0 – 20 but outliers are extreme so best viewed with quantiles colour stretch rather than intervals. Log Normalised Scaled (SA_RAD_LNS_RGB_2024) A technique published by Mark Grujic1 for increasing contrast in areas dominated by extreme low or high values for one element. The grid has been named LNS to reflect the general process and was produced using WinDisp™. Log Normalised Scaled (LNS) 1. Log transform K,Th and U grids 2. Normalise log grids to between 0 and 1 3. Divide normalised values by sum of the three normalised values. An ESRI .lyr file has been created for each GDA94 & GDA2020 raster which includes an overlay of Total Count as a sunshade layer. 1: https://www.linkedin.com/pulse/visualising-regional-radiometics-data-mark-grujic/ Please note that the Hillshade does not always automatically load into ArcMap and ArcGIS Pro projects. If this happens, please load the SA_RAD_TC_2024_GDA2020_DD.ers (or SA_RAD_TC_2024_GDA94_DD.ers) into your project first, then reload the other layer.

Datasets supporting the publication: Analyzing satellite-derived 3D building inventories and quantifying urban growth towards active faults: a case study of Bishkek, Kyrgyzstan. https://doi.org/10.3390/rs14225790

-Please refer to the publication for details on the production of each dataset. -Datasets are ordered following the publication figures. -Please cite the publication and this dataset repository when using the data.

Structure: File ID

-[fields:] description

KH9_1979_builtup.shp -KH9 1979 built-up area classification

S2_2021_builtup.tif -Sentinel-2 2021 built-up area classification.

S2_2021_corine_land_cover_class.tif -Sentinel-2 2021 land cover classification in Corine 2018 land-cover classes.

S2_KH9_DN_change_aggregated.shp -Proportional DN change aggregated to a 1 km^2 grid for areas ≥50% built-up.

building_characteristics.shp -build_count: building count in 500 m square grid cell. -mean_area: mean building size (m^2) in 500 m square grid cell. -median_area: median building size(m^2) in 500 m square grid cell. -cell_coverage: %building coverage of 500 m square grid cell.

pleiades_buildings_all.shp -All building detections from Pleiades data. Confidence values are output from the deep learning model.

pleiades_buildings_heights.shp -Building detections from the Pleiades data that were allocated heights (m). -Zmean, Zmedian,... refer to heights (m)

wv2_buildings_all.shp -All building detections from WorldView-2 data. Confidence values are output from the deep learning model.

wv2_buildings_heights.shp -Building detections from the WorldView-2 data that were allocated heights (m). -Zmean, Zmedian,... refer to heights (m)

trained_rcnn.zip -ArcGIS Pro deep learning model (DLPK) used to extract building footprints.

This tiled map service displays bathymetric contours derived from the General Bathymetric Chart of the Oceans GEBCO_2024 grid, which is a global bathymetry compilation at 15 arc-second resolution. Depths are displayed in meters. At large scales (1:5,000,000 and closer), the contour interval is 500m; at medium scales (1:5,000,000 to 1:30,000,000) the contour interval is 1000m; and at small scales (1:30,000,000 and greater), the contour interval is 2000m. Supplementary contours are shown in shallow waters (less than 500m).A "smoothing" process was done in ArcGIS Pro to generate these contours:Create a version of the GEBCO grid using the Convolution raster function "Smoothing 3x3" option.Generate contours at selected intervals using "Contour List".Generalize the contours using "Simplify Line" with a tolerance of 0.005 degrees.These contours are also available as a downloadable file geodatabase.Please also see NOAA/NCEI's color shaded-relief visualization of the GEBCO grid.See here for a map with both hillshade and contours included.

A series of annual geochemical models were created by RockWare utilizing RockWorks v2021 which were interpolated based on the 1,4-dioxane levels that were measured during 1986 through 2020. In cases where the same intervals were samples on more than one occasion during a given year, the highest 1,4-dioxane values were used. The extent of each annual model were limited to polygons based on only the wells that were sampled during the associated year to eliminate interpolating in areas where data is not present. The annual geochemical models were then filtered based on lithology to eliminate any voxels within the areas deemed impermeable based on lithology. The models were further constrained by utilizing the maximum historical water level surface (MHWLS) grid model to further restrict the interpolation from areas lacking measured data. Finally, the voxel models were converted to annual grid models, in which the cell values are based on the highest value within the corresponding column of voxels. The 2020 plume presented here was created from the RockWorks project database files on June 09, 2021 (Gelman3.sqlite v2021-04-29). The grid file titled 2020-01-01_to_2020-12-31.RwGrd (v20210710) was converted by The Mannik and Smith Group (MSG) to a raster file compatible in ArcGIS and a custom color scheme was applied with the shades becoming darker as concentrations increase. Iso-concentration lines were then generated at the following concentrations: 4 ppb, 7.2 ppb, 85 ppb, 150 ppb, 280 ppb, 500 ppb, 1000 ppb, 1900 ppb, 3000 ppb, and 5000 ppb. The 7.2 ppb lines were created because it represents the current EGLE Part 201 generic residential cleanup criterion (GRCC). The 85 ppb lines were created to represent the Consent Judgement 3 (CJ3) drinking water criteria. The 280 ppb lines were created because that is the new EGLE groundwater-surface water interface (GSI) criterion, and 1900 ppb is the Vapor Intrusion criteria. EGLE is contouring the 4 ppb level because that could become a new trigger for response if detected in sentinel wells if the proposed 4th Consent Judgment is approved.To host the plume files on EGLE's ArcGIS Online, MSG prepared the raster file, contour layer, and the input points used as the input for the specified year model in ArcGIS Pro. The points were labeled using three levels of detail. When zoomed out beyond 1:5000 no labels appear at the points because it would be too dense to read and cover the underlying plume. When zoomed in between 1:5000 and 1:1200, the bore name and maximum 1,4-dioxane at that well in 2020 appear. When zoomed in closer than 1:1200, the labels show the boring name, sample depth interval, and maximum 1,4-dioxane at that interval for 2020. The plume layer was set to 7.5% transparency (this can be adjusted later) and shared as a web tile layer using the ArcGIS Online / Bing Maps / Google Maps tiling scheme for levels of detail 12 – 19.This is a previous version of the data. The newest vintage is available at: Gelman Site of 1,4-Dioxane Contamination - Dioxane Plume (2023 Data).This data is used in the Gelman Site of 1,4-Dioxane Contamination web map (item details). If you have questions regarding the Gelman Sciences, Inc site of contamination contact Chris Svoboda at 517-256-2849 or svobodac@michigan.gov. Report problems or data functionality suggestions to EGLE-Maps@Michigan.gov.

A series of annual geochemical models were created by RockWare utilizing RockWorks v2021 which were interpolated based on the 1,4-dioxane levels that were measured during 1986 through 2020. In cases where the same intervals were samples on more than one occasion during a given year, the highest 1,4-dioxane values were used. The extent of each annual model were limited to polygons based on only the wells that were sampled during the associated year to eliminate interpolating in areas where data is not present. The annual geochemical models were then filtered based on lithology to eliminate any voxels within the areas deemed impermeable based on lithology. The models were further constrained by utilizing the maximum historical water level surface (MHWLS) grid model to further restrict the interpolation from areas lacking measured data. Finally, the voxel models were converted to annual grid models, in which the cell values are based on the highest value within the corresponding column of voxels. The 2020 plume presented here was created from the RockWorks project database files on June 09, 2021 (Gelman3.sqlite v2021-04-29). The grid file titled 2020-01-01_to_2020-12-31.RwGrd (v20210710) was converted by The Mannik and Smith Group (MSG) to a raster file compatible in ArcGIS and a custom color scheme was applied with the shades becoming darker as concentrations increase. Iso-concentration lines were then generated at the following concentrations: 4 ppb, 7.2 ppb, 85 ppb, 150 ppb, 280 ppb, 500 ppb, 1000 ppb, 1900 ppb, 3000 ppb, and 5000 ppb. The 7.2 ppb lines were created because it represents the current EGLE Part 201 generic residential cleanup criterion (GRCC). The 85 ppb lines were created to represent the Consent Judgement 3 (CJ3) drinking water criteria. The 280 ppb lines were created because that is the new EGLE groundwater-surface water interface (GSI) criterion, and 1900 ppb is the Vapor Intrusion criteria. EGLE is contouring the 4 ppb level because that could become a new trigger for response if detected in sentinel wells if the proposed 4th Consent Judgment is approved.To host the plume files on EGLE's ArcGIS Online, MSG prepared the raster file, contour layer, and the input points used as the input for the specified year model in ArcGIS Pro. The points were labeled using three levels of detail. When zoomed out beyond 1:5000 no labels appear at the points because it would be too dense to read and cover the underlying plume. When zoomed in between 1:5000 and 1:1200, the bore name and maximum 1,4-dioxane at that well in 2020 appear. When zoomed in closer than 1:1200, the labels show the boring name, sample depth interval, and maximum 1,4-dioxane at that interval for 2020. The plume layer was set to 7.5% transparency (this can be adjusted later) and shared as a web tile layer using the ArcGIS Online / Bing Maps / Google Maps tiling scheme for levels of detail 12 – 19.This is a previous version of the data. The newest vintage is available at: Gelman Site of 1,4-Dioxane Contamination - Dioxane Plume (2023 Data).This data is used in the Gelman Site of 1,4-Dioxane Contamination web map (item details). If you have questions regarding the Gelman Sciences, Inc site of contamination contact Chris Svoboda at 517-256-2849 or svobodac@michigan.gov. Report problems or data functionality suggestions to EGLE-Maps@Michigan.gov.

Florida Ecological Greenways Network 2021 (layer name fegn2021_polygon): This vector layer was created from the original raster grid version (fegn2021) created by the University of Florida Center for Landscape Conservation Planning to provide an ecological component to the Statewide Greenways System plan developed by the Department of Environmental Protection, Office of Greenways and Trails (OGT). The FEGN guides OGT ecological greenway conservation efforts and promotes public awareness of the need for and benefits of a statewide ecological greenways network. It is also used as the primary data layer to inform the Florida Forever and other state and regional land acquisition programs regarding the location of the most important wildlife and ecological corridors and large, intact landscapes in the state. The FEGN identifies areas of opportunity for protecting a statewide network of ecological hubs (large areas of ecological significance) and linkages designed to maintain large landscape-scale ecological functions including priority species habitat and ecosystem services throughout the state. Inclusion in the FEGN means the area is either part of a large landscape-scale “hub”, or an ecological corridor connecting two or more hubs. Hubs indicate core landscapes that are large enough to maintain populations of wide-ranging or fragmentation-sensitive species including black bear or panther and areas that are more likely to support functional ecosystem services. Highest priorities indicate the most significant hubs and corridors in relation to completing a functionally connected statewide ecological network, but all priority levels have conservation value. FEGN Priorities 1, 2, and 3 are the most important for protecting a ecologically functional connected statewide network of public and private conservation lands, and these three priority levels (P1, P2, and P3) are now called the Florida Wildlife Corridor as per the Florida Wildlife Corridor legislation passed and signed into law by the Florida Legislature and Governor and 2021, which makes protection of these wildlife and ecological hubs and corridors a high priority as part of a strategic plan for Florida’s future. To accomplish this goal, we need robust state, federal, and local conservation land protection program funding for Florida Forever, Rural and Family Lands Protection Program, Natural Resources Conservation Service easements and incentives, federal Land and Waters Conservation Fund, payments for ecosystem services, etc.For more information http://conservation.dcp.ufl.edu/fegnproject/

A series of annual geochemical models were created by RockWare utilizing RockWorks v2021 which were interpolated based on the 1,4-dioxane levels that were measured during 1986 through 2020. In cases where the same intervals were samples on more than one occasion during a given year, the highest 1,4-dioxane values were used. The extent of each annual model were limited to polygons based on only the wells that were sampled during the associated year to eliminate interpolating in areas where data is not present. The annual geochemical models were then filtered based on lithology to eliminate any voxels within the areas deemed impermeable based on lithology. The models were further constrained by utilizing the maximum historical water level surface (MHWLS) grid model to further restrict the interpolation from areas lacking measured data. Finally, the voxel models were converted to annual grid models, in which the cell values are based on the highest value within the corresponding column of voxels. The 2020 plume presented here was created from the RockWorks project database files on June 09, 2021 (Gelman3.sqlite v2021-04-29). The grid file titled 2020-01-01_to_2020-12-31.RwGrd (v20210710) was converted by The Mannik and Smith Group (MSG) to a raster file compatible in ArcGIS and a custom color scheme was applied with the shades becoming darker as concentrations increase. Iso-concentration lines were then generated at the following concentrations: 4 ppb, 7.2 ppb, 85 ppb, 150 ppb, 280 ppb, 500 ppb, 1000 ppb, 1900 ppb, 3000 ppb, and 5000 ppb. The 7.2 ppb lines were created because it represents the current EGLE Part 201 generic residential cleanup criterion (GRCC). The 85 ppb lines were created to represent the Consent Judgement 3 (CJ3) drinking water criteria. The 280 ppb lines were created because that is the new EGLE groundwater-surface water interface (GSI) criterion, and 1900 ppb is the Vapor Intrusion criteria. EGLE is contouring the 4 ppb level because that could become a new trigger for response if detected in sentinel wells if the proposed 4th Consent Judgment is approved.To host the plume files on EGLE's ArcGIS Online, MSG prepared the raster file, contour layer, and the input points used as the input for the specified year model in ArcGIS Pro. The points were labeled using three levels of detail. When zoomed out beyond 1:5000 no labels appear at the points because it would be too dense to read and cover the underlying plume. When zoomed in between 1:5000 and 1:1200, the bore name and maximum 1,4-dioxane at that well in 2020 appear. When zoomed in closer than 1:1200, the labels show the boring name, sample depth interval, and maximum 1,4-dioxane at that interval for 2020. The plume layer was set to 7.5% transparency (this can be adjusted later) and shared as a web tile layer using the ArcGIS Online / Bing Maps / Google Maps tiling scheme for levels of detail 12 – 19.This is a previous version of the data. The newest vintage is available at: Gelman Site of 1,4-Dioxane Contamination - Dioxane Plume (2023 Data).This data is used in the Gelman Site of 1,4-Dioxane Contamination web map (item details). If you have questions regarding the Gelman Sciences, Inc site of contamination contact Chris Svoboda at 517-256-2849 or svobodac@michigan.gov. Report problems or data functionality suggestions to EGLE-Maps@Michigan.gov.

A series of annual geochemical models were created by RockWare utilizing RockWorks v2021 which were interpolated based on the 1,4-dioxane levels that were measured during 1986 through 2020. In cases where the same intervals were samples on more than one occasion during a given year, the highest 1,4-dioxane values were used. The extent of each annual model were limited to polygons based on only the wells that were sampled during the associated year to eliminate interpolating in areas where data is not present. The annual geochemical models were then filtered based on lithology to eliminate any voxels within the areas deemed impermeable based on lithology. The models were further constrained by utilizing the maximum historical water level surface (MHWLS) grid model to further restrict the interpolation from areas lacking measured data. Finally, the voxel models were converted to annual grid models, in which the cell values are based on the highest value within the corresponding column of voxels. The 2020 plume presented here was created from the RockWorks project database files on June 09, 2021 (Gelman3.sqlite v2021-04-29). The grid file titled 2020-01-01_to_2020-12-31.RwGrd (v20210710) was converted by The Mannik and Smith Group (MSG) to a raster file compatible in ArcGIS and a custom color scheme was applied with the shades becoming darker as concentrations increase. Iso-concentration lines were then generated at the following concentrations: 4 ppb, 7.2 ppb, 85 ppb, 150 ppb, 280 ppb, 500 ppb, 1000 ppb, 1900 ppb, 3000 ppb, and 5000 ppb. The 7.2 ppb lines were created because it represents the current EGLE Part 201 generic residential cleanup criterion (GRCC). The 85 ppb lines were created to represent the Consent Judgement 3 (CJ3) drinking water criteria. The 280 ppb lines were created because that is the new EGLE groundwater-surface water interface (GSI) criterion, and 1900 ppb is the Vapor Intrusion criteria. EGLE is contouring the 4 ppb level because that could become a new trigger for response if detected in sentinel wells if the proposed 4th Consent Judgment is approved.To host the plume files on EGLE's ArcGIS Online, MSG prepared the raster file, contour layer, and the input points used as the input for the specified year model in ArcGIS Pro. The points were labeled using three levels of detail. When zoomed out beyond 1:5000 no labels appear at the points because it would be too dense to read and cover the underlying plume. When zoomed in between 1:5000 and 1:1200, the bore name and maximum 1,4-dioxane at that well in 2020 appear. When zoomed in closer than 1:1200, the labels show the boring name, sample depth interval, and maximum 1,4-dioxane at that interval for 2020. The plume layer was set to 7.5% transparency (this can be adjusted later) and shared as a web tile layer using the ArcGIS Online / Bing Maps / Google Maps tiling scheme for levels of detail 12 – 19.This is a previous version of the data. The newest vintage is available at: Gelman Site of 1,4-Dioxane Contamination - Dioxane Plume (2023 Data).This data is used in the Gelman Site of 1,4-Dioxane Contamination web map (item details). If you have questions regarding the Gelman Sciences, Inc site of contamination contact Chris Svoboda at 517-256-2849 or svobodac@michigan.gov. Report problems or data functionality suggestions to EGLE-Maps@Michigan.gov.

The map of runoff conditions for the Angola project contains the following layers:flowacclog10 - Represents the overland flow paths. This is the FlowAccumulation layer (created with ArcHydroPro), which was subsequently logarithmized (Log10) for better data presentation. The darker the blue, the more likely it is that a concentrated surface runoff will occur.watershed_angola - Represents a layer of delinieated local watersheds created using the Catchment Grid Delineation tool (ArcHydroPro). The value of 9 km2 was used to define individual watersheds. Note: All layers were generated on the basis of a digital elevation model from the ALOS PALSAR project with a cell size of 12.5 mMapa odtokových poměrů pro projekt Angola obsahuje následující vrstvy:flowacclog10 - Představuje dráhy soustředěného odtoku. Jedná se o vrstvu FlowAccumulation (vytvořená za pomocí ArcHydroPro), která byla následně zlogaritmována (log10) -> pro lepší prezentaci dat. Čím tmavší modrá, tím větší pravděpodobnost, že se v daném místě bude koncentrovat voda.watershed_angola - Představuje vrstvu vygenerovaných lokálních povodí pomocí nástroje Catchment Grid Delineation (ArcHydroPro) a následné vektorizaci. Při definici povodí byla použita hodnota 10 km2Pozn. Všechny vrstvy byly vygenerovány na podkladu digitálního modelu reliéfu z projektu ALOS PALSAR o velikosti buňky 12,5 m.