Sometimes a basic solid color for your map's labels and text just isn't going to cut it. Here is an ArcGIS Pro style with light and dark gradient fills and shadow/glow effects that you can apply to map text via the "Text fill symbol" picker in your label pane. Level up those labels! Make them look touchable. Glassy. Shady. Intriguing.Find a how-to here.Save this style, add it to your ArcGIS Pro project, then use it for any text (including labels).**UPDATE**I've added a symbol that makes text look like is being illuminated from below, casting a shadow upwards and behind. Pretty dramatic if you ask me. Here is an example:Happy Mapping! John Nelson

This web map is for use in the Joshua Tree National Park Climbing Management Plan Story Map. It features a heat map that visualizes estimates of climbing activity throughout the park, providing valuable insights for climbers and park management. This information is crucial for enhancing understanding and planning for climbing activities in the park. The map uses a color gradient to represent climbing activity levels. Blue indicates areas of less usage Red signifies areas of intense usageThe heat map is based on an analysis for four key characteristics that influence climbing activity:1.) Accessibility - Distance from parking areas to climbing routes2.) Route Difficulty - The range of difficulty levels available within the area3.) Popularity Rating - How frequently specific routes are climbed4.) Climbing Style - The types of climbing (e.g. trad, sport) that the location supportsThis estimated use heat map serves as a visual representation of climbing activity and does not indicate management areas or closures within the park. For any questions or further clarification on this web map or the underlying data, please contact the Joshua Tree National Park GIS team.The corresponding NPS DataStore on Integrated Resource Management Applications (IRMA) reference is Climbing Management Plan: Rock-Based Recreation in Joshua Tree National Park

Layer represents the geographic location of all water level stations that have computed sea level trends at that location. Changes in Mean Sea Level (MSL), either as sea level rise or sea level fall, have been computed at long-term water level stations using a minimum span of 30 years of observations at each location. The trends measured by tide gauges that are presented are local relative MSL trends and therefore include any vertical land motion, as opposed to the absolute global sea level trend. Attributes for each water level station have integrated animations of sea level rise. The plots change color over time, facilitating easier interpretation of local sea level trends. Historical data is plotted over a color gradient to represent trends, with a black line to designate each year’s progression.Data publicly available at: https://tidesandcurrents.noaa.gov/sltrends/mslUSTrendsTable.html

This is the National Forests in Mississippi prescribed fire history map. This map provides the last three years of prescribed fire history on the landscape. The map is not updated immediately as prescribed burns happen on the landscape, it is updated as the burns have been completed through the reporting process. The color gradient of the map goes from darkest (most recent) to the lighest (older).

This map shows the median # days out of water per previous waterbody state where watercraft owners' last visited waterbody was infested for either Zebra or Quagga mussels and then who passed through Idaho Watercraft Inspection Stations during the 2023 inspection season. All previous waterbody states with at least one inspection from an infested waterbody located in that state are shown on a color gradient ramp. Previous infested waterbody states shown in bright red indicate fewer days out of water where watercraft owners' last visited waterbody in that state was infested, and states shown in yellow indicate more days out of water where watercraft owners' last visited waterbody was infested. Zebra and Quagga mussels can survive out of water for up to 30 days. Watercraft Inspectors search for invasive Quagga/Zebra mussels in and on watercraft. Inspectors also look for aquatic noxious weeds.

This map shows the number of inspections aggregated to the state level where watercraft owners' last visited waterbody was infested for either Zebra or Quagga mussels and then who passed through Idaho Watercraft Inspection Stations during the 2022 inspection season. All previous waterbody states with at least one inspection from an infested waterbody located in that state are shown on a color gradient ramp. Previous infested waterbody states shown in bright red indicate a high volume of inspections where watercraft owners' last visited waterbody in that state was infested, and states shown in yellow indicate a lower volume of inspections where watercraft owners' last visited waterbody was infested. Watercraft Inspectors search for invasive Quagga/Zebra mussels in and on watercraft. Inspectors also look for aquatic noxious weeds.

This chart shows the number of watercraft inspections that occurred for every day of the week/hour of the day combination (rectangles) during the 2023 watercraft inspection season for all watercraft inspection stations in Idaho. The y axis shows the day of the week and the x axis shows the hour of the day. The darkness of each rectangle indicates the number of inspections that occurred during that day of the week/hour of the day combination. The heaviest periods of inspections are shaded in dark blue. The legend on the right matches the color gradient with the approximate number of inspections that occurred in each rectangle. Data was aggregated from individual inspections entered into the 2023 Idaho Watercraft Inspection survey database. These watercraft inspections mainly concentrate on finding Invasive Quagga/Zebra mussels on and in watercraft based on visual inspection and last waterbody visited. Station inspectors also look for aquatic noxious weeds that might be attached to watercraft.

This chart shows the number of watercraft inspections that occurred for every day of the week/hour of the day combination (rectangles) during the 2021 watercraft inspection season for all watercraft inspection stations in Idaho. The y axis shows the day of the week and the x axis shows the hour of the day. The darkness of each rectangle indicates the number of inspections that occurred during that day of the week/hour of the day combination. The heaviest periods of inspections are shaded in dark blue. The legend on the right matches the color gradient with the approximate number of inspections that occurred in each rectangle. Data was aggregated from individual inspections entered into the 2021 Idaho Watercraft Inspection survey database. These watercraft inspections mainly concentrate on finding Invasive Quagga/Zebra mussels on and in watercraft based on visual inspection and last waterbody visited. Station inspectors also look for aquatic noxious weeds that might be attached to watercraft.

Large segments each have unique row column sequence. Quad field lists full name as used in Datum_ID in architecture. Name field is abbreviated name to use for labelling during viewing and feature-naming processes. The field "completed" is a yes/no indicator for a quad that is completely mapped. PctComplete and AreaSvyd fields indicate how much of the area is actually surveyed, accounting for areas where quads run over the reserve boundary, and mapping only took place within the boundary.Grid for El Pilar Reserve study: Each Segment (1 - 9, clockwise inward spiral from top left to center) dived by row (a - z) and column (1-9). Display is best accomplished by setting symbology to categories<unique values; sorted by SEG, with a non-gradient color sequence.Additional display option, set symbology to categories<unique values, many; sorted by SEG and completed, seperately. Use the same type of color sequence, though it is necessary to manually go in and change all of the completed entries to some specific color (usually light blue). This displays the segments with unique colors, and additionally displays the portion of the map that's completed.Visited - Visited quads have no unvisited GoTo points, and contain track coverage. Visited quads appear on the map as plain boxes. Partial - Partially visited quads contain both unvisited and unknown points, as well as visited GoTo points, and track coverage. Partially visited quads appear on the map with single-hatching. Unvisited - Unvisited quads contain unvisited GoTo points, or no GoTo points whatsoever, and have minimal to no track coverage. Unvisited quads appear on the map as cross-hatched boxes.

This map shows the median # days out of water per previous waterbody state where watercraft owners' last visited waterbody was infested for either Zebra or Quagga mussels and then who passed through Idaho Watercraft Inspection Stations during the 2022 inspection season. All previous waterbody states with at least one inspection from an infested waterbody located in that state are shown on a color gradient ramp. Previous infested waterbody states shown in bright red indicate fewer days out of water where watercraft owners' last visited waterbody in that state was infested, and states shown in yellow indicate more days out of water where watercraft owners' last visited waterbody was infested. Zebra and Quagga mussels can survive out of water for up to 30 days. Watercraft Inspectors search for invasive Quagga/Zebra mussels in and on watercraft. Inspectors also look for aquatic noxious weeds.

This chart shows the number of watercraft inspections that occurred for every day of the week/hour of the day combination (rectangles) during the 2020 watercraft inspection season for all watercraft inspection stations in Idaho. The y axis shows the day of the week and the x axis shows the hour of the day. The darkness of each rectangle indicates the number of inspections that occurred during that day of the week/hour of the day combination. The heaviest periods of inspections are shaded in dark blue. The legend on the right matches the color gradient with the approximate number of inspections that occurred in each rectangle. Data was aggregated from individual inspections entered into the 2020 Idaho Watercraft Inspection survey database. These watercraft inspections mainly concentrate on finding Invasive Quagga/Zebra mussels on and in watercraft based on visual inspection and last waterbody visited. Station inspectors also look for aquatic noxious weeds that might be attached to watercraft.

Geospatial Analysis of Population Demographics and Traffic Density in MinneapolisIntroductionThis interactive web map provides a geospatial analysis of population distribution and traffic density for the city of Minneapolis, Minnesota. By integrating demographic data at the census tract level with real-time traffic information, the application serves as a critical tool for urban planning, transportation management, and sociological research.Data Visualization and SymbologyThe map employs distinct color schemes to represent the core datasets, allowing for intuitive visual analysis: Traffic Density: The city's road network is symbolized using a color gradient to indicate traffic volume. Segments rendered in deep red represent a high traffic density index, signifying areas of significant vehicular congestion. This transitions to a light yellow for segments experiencing lower traffic flow. Population Density: The demographic landscape is visualized using a green color ramp applied to census tract polygons. Dark green shades correspond to areas with a high population concentration, whereas lighter green shades denote regions with a lower population density. Analytical Utility and ApplicationsThe juxtaposition of these datasets reveals spatial correlations between residential density and transportation bottlenecks. This allows for data-driven inquiry into key urban challenges. The patterns visualized can help city planners and transportation authorities identify specific corridors where infrastructure investment could be most effective. Strategic improvements in these areas have the potential to optimize traffic flow, reduce commuter travel times, and decrease vehicle fuel consumption and emissions, thereby enhancing the overall sustainability and livability of Minneapolis.Interactive Features and Data ExplorationUsers are encouraged to engage with the map's interactive features for a deeper understanding of the data: Layers and Legend: Utilize the "Layers" and "Legend" tools to deconstruct the map's composition and understand the specific values associated with the color symbology. Pop-up Information: Click on individual census tracts or road segments to activate pop-up windows. These provide detailed attribute information, such as total population counts, demographic breakdowns, household income statistics, and spatial relationship metrics like nearest neighbor analysis. This application is built upon a foundational demographic data layer for Minneapolis and is enhanced by the integration of a dynamic traffic layer from the ArcGIS Living Atlas of the World.

The Heat Vulnerability Index (HVI) layer is hosted by the WI Department of Health Services which employs a color gradient to signify varying levels of heat vulnerability across different geographic regions of WI. This layer incorporates critical data layers, including population density, age demographics, existing health conditions, and access to cooling resources, to create a multifaceted view of risk factors. This data serves as a vital tool for public health officials to assess where interventions are most needed during extreme heat events. By highlighting areas with heightened vulnerability, stakeholders can implement targeted outreach and preparation efforts. Additionally, the HVI layer can assist in strategic planning for future urban development and climate resilience initiatives.This copy of this layer was updated on February 12, 2024. Link to data source for download: https://data.dhsgis.wi.gov/datasets/wi-dhs::wisconsin-heat-vulnerability-index/explore

The purpose of this map is to show tree canopy coverage at the community and block level. The boundary features are Columbus Communities and Census Blocks symbolized as a color gradient indicating tree canopy coverage with pop-ups configured to show more information about each feature. NAIP imagery becomes visible at the block level and may be turned off by the user. This map was created for the City of Columbus Recreation and Parks Department's Urban Forestry Master Plan project. Tree canopy and other land cover information were derived from 2013 NAIP imagery by Plan-It Geo in 2015 for the Urban Tree Canopy Assessment of Columbus, Ohio and it is not updated. Census Block boundaries are from 2010. The NAIP imagery shown in this map is the latest available.

Used in Storymap https://storymaps.arcgis.com/stories/7951d5b1fdfe4c3dae8498aaa6a9a687 and/or InstantApp https://niwa.maps.arcgis.com/apps/instant/media/index.html?appid=29edc889a3b340cab4d382f5a9155c06OverviewNIWA was tasked by Te Kaunihera o Tāmaki Makaurau / Auckland Council to undertake a series of benthic terrain analyses of datasets collected across the wider Hauraki Gulf to produce a desktop habitat study. With nearly 70% of the area managed by Te Kaunihera o Tāmaki Makaurau / Auckland Council located offshore, results from a desktop habitat study provide further insights into Hauraki Gulf benthic habitats and can assist in prioritising areas for management and future research. DataData for these analyses come from two different sources, NIWA’s own internal archive (NIWA voyage TAN1211) and LINZ’s archive of hydrographic surveys: HS52 – Approaches to Auckland (LINZ) HS53 – Kawau Island (LINZ) HS54 – Tamaki Strait (LINZ) TAN1211 – NIWA multibeam mapping voyage Although all the data analyzed were collected for different purposes, reusing legacy multibeam echosounder (MBES) data shows the strength of the ‘map once – use multiple times’ approach that is now standard practice. To achieve the best outcome for scientific interpretation, NIWA has partially reprocessed the bathymetry and seafloor backscatter information from data provided to LINZ. This has improved the data for the purpose of scientific interpretation.

Our analysis of these data focused on: building derivatives and classifying the bathymetry data, processing the seafloor backscatter data in a qualified way for feature detection and classification, creating scientifically justified interpretations of the seafloor bathymetry and backscatter data. Results from these studies provide a comprehensive overview of seabed morphology and activity across a large region of the Hauraki Gulf, covering a broad range of marine environments.Bathymetry

Bathymetry (shape and depth of seafloor) is illustrated as a digital elevation model (DEM). This is the processed layer that represents thousands of individual depth measurements collated to form a single continuous DEM. The resolution of each DEM depends on a range of factors including data quality, water depth, and echo sounder settings. The higher the resolution (grid cell size) of the DEM, the greater detail we are able to see on the seabed. From bathymetry data, other layers can be produced to assist in understanding key features of interest within the survey region. These layers are often referred to as derivatives and they are described in detail below.

To aid in depth perception, hillshades have been generated and visualised in conjunction with the bathymetry layer to allow for seafloor structures and depth to be seen. Hillshade layers are derivatives of bathymetry and can be generated with a range of illumination and altitude angles to reveal different components of the dataset. In this dataset, a multidirectional Hillshade was produced 3 times vertical exaggeration. Multidirectional Hillshade is generated by producing hillshades from six different directions (rather than just one direction used in a default Hillshade) and enables complex and subtle features to be visualised without obscuring details in otherwise non-illuminated regions.

Slope

The slope derivative is a measure of how steep the seafloor is. Slope is measured from the horizontal (i.e., 0°, or flat) and increases to 90° (i.e., vertical). To calculate a slope derivative, the depth values within each cell are compared to adjacent cells (within a user-defined window) to determine the seafloor gradient across the whole dataset.

Rugosity

Rugosity is a measure of roughness and terrain complexity and is captured as bathymetric variation in three dimensions. Ecological diversity can generally be correlated with the complexity of the physical environment and as such, rugosity can help identify areas where high biodiversity may exist on the seafloor.

Aspect

Aspect is the direction of down-slope dip and can also be thought of as the slope direction. The Aspect derivative produces a layer with cell values that correspond to compass directions presented in degrees from 0/360° (due north) clockwise to 90° (east), 180° (south) and 270° (west). Areas with zero slope will also show no aspect.

Curvature

The curvature derivative describes the shape of slope, and is sometimes referred to as the second derivative of bathymetry. Positive curvature at a location indicates that the surface is upwardly convex, e.g., a mound. Negative curvature indicates that the surface is upwardly concave, e.g., a depression. A neutral value of 0 indicates that the surface is flat. The colour gradient is symmetrical about zero curvature to emphasise curved versus flat seafloor.

Seafloor Backscatter

Seafloor backscatter data is collected at the same time as bathymetry data but measures the energy of the returning acoustic signal. The acoustic energy can be correlated to seafloor substrate and can effectively delineate substrate boundaries that may not be observable in the bathymetry data or derivatives.

Benthic Terrain Model

Based on NIWA’s National Benthic Terrain Classification, the Benthic Terrain Model uses a range of bathymetric derivatives to classify the physical structure of the seafloor into geomorphic zones, e.g., flat plains, ridges, depressions etc. These classifications are in accordance with a national standard and can be used to compare with other regions.HS52 Features

Collected in 2017, the hydrographic survey HS52 – Approaches to Auckland covers an area of 280 km2 between Auckland’s Northshore, Rangitoto and the Whangaparāoa Peninsula. The water depth within the HS52 survey ranges from less than 1 m along the coastline, to approximately 40 m in the northeastern portion, east of Tiritiri Matangi Island. Bathymetry data reveal the variability of the seafloor from the near coastal rocky reefs to the broad flat seabed within the Hauraki Gulf channels.

<!-Nearshore Strata Faulting

Nearshore rocky outcrop showing tilted parallel rock units dipping to the west and offset by faults. These outcrops are likely the offshore extension of Late Oligocene Early Miocene-age deep water mud and sandstones of the Waitemata Group.

Backscatter imagery highlights the boundary between the hard rocky substrate (lighter) compared to the deeper and likely soft sediment substrate (darker)

<!Tessellated Reef

Tessellated rocky reef possibly representing a more textured, highly fractured, unit of the Waitemata Group.

Backscatter imagery highlights the more textured hard rocky reef substrate (lighter) compared to the deeper and smoother soft sediment substrate (darker).

<!-Channels

Channels between the mainland and Hauraki Gulf Islands display a unique seabed backscatter signature compared to adjacent seafloor. Varying backscatter is indicative of a substrate boundary. For example, lighter regions near the coast and within the channel may be indicative of larger sediment grains such as sand, compared to the flat plains with darker backscatter which could be dominated by muddy sediment.

 Linear Sediment Waves

Linear sediment waves on the eastern side of the channel between Whangaparāoa Peninsula and Tiritiri Matangi Island. Sediment wave crests are oriented approximately east-west and may be related to currents between the coast and the Hauraki Gulf Islands.

<!-Rounded Depressions

A cluster of rounded depressions may be indicative of relict or active seabed seepage and potential sites of sensitive ecosystems. Seafloor backscatter reveals the sloping rim of these features may have a harder substrate compared to their base.

<!-Pockmarks

Pockmarks following distinctive linear arrangement, oriented NW-SE. This provides evidence of seafloor fluid seepage, possibly along faults. The pockmarks are well expressed in seafloor backscatter as light circular dots on the darker seabed background.

<!--Rocky Reef at ~30 m

Rocky reef patch located in ~30 m water depth. Possible important habitat for benthos that require hard/rocky substrate for community building. This feature is a distinctive high backscatter region, surrounded by lower backscatter seafloor.

<!-Rugose and Textured Seafloor

Rugose and textured seafloor characterised by higher backscatter return compared to surrounding seafloor, possibly formed via current winnowing and/or may represent important habitats for hard substrate benthos.

<!--Imprint of Pipeline

Bathymetric imprint of pipeline from Mairangi Bay. Expression extends over 400 m in length and 60 m width. Seafloor backscatter highlights pipeline well, showing it as a high-intensity feature (indicative of a harder substrate) relative to surrounding seafloor.

<!- Anchoring Footprint

Anchoring footprint on the seabed. Linear scours caused by anchor deployment and feathering marks caused by gauging of the anchor chain scope whilst vessel swings. Regions with anchoring impacts have a lighter backscatter return compared to the surrounding seabed.

HS53 Features

Surveyed in 2016-17 for hydrographic charting, survey HS53 – Kawau Island covers an area of 184 km2 between Tāwharanui Peninsula, Mahurangi Peninsula and the region surrounding Kawau Island. The water depth within the HS53 – Kawau Bay survey ranges from the coast to ~61 m water depth, with an average depth of 28 m. The seafloor is shallowest within Kawau Bay and deepens eastward into the central Hauraki Gulf/Tīkapa Moana through the North and South Channels. Within Kawau Bay, away from the coast, the seabed morphology is generally gentle and undulating.

R oRocky Platform of Tilted Units

Extensive rocky reef platform to the east of Mahurangi East Peninsula and Big Bay. The rocky outcrop shows tilted parallel rock units offset by faults. These outcrops are likely the offshore extension of Pakiri Formation of Warkworth

The variables extracted from this dataset are Daytime and Nighttime land surface temperatures in degrees Celsius. The data covers the period from January 1, 2020, to December 31, 2023, offering a comprehensive view over four years. It includes quality control assessments, observation times, view zenith angles, clear-sky coverages, and emissivity values for different land cover types.The dataset integrates spatial boundaries from shapefiles with the imagery raster files to provide data at various geographical levels, including state, county, census tract, and zip code, although your specific analysis seems to focus on the state level in Oklahoma.The data is updated every 8 days, aligning with the ground track repeat period of the Terra and Aqua platforms. The provided data link directs to the Earth Engine catalog, offering access to the MOD11A2 dataset.Column NameDescriptionStateNameName of the stateStateFipsState FIPS codeZipCodeZipcode of geographical areaDateDate at which temperature is recordedLST_Day_1kmDay land surface temperature in degrees CelsiusLST_Night_1kmNight land surface temperatureEach column represents a different attribute of the data, such as the name of the state, its FIPS code, zipcode, date of temperature recording, daytime land surface temperature, and nighttime land surface temperature.

The objective of this classification was to create a simplified set of stream and river habitat types based on the Northeast Aquatic Habitat Classification System (Olivero and Anderson 2008) and GIS map for 13 northeastern states that could be used in the Northeast Stream and River Habitat Guide (available at http://nature.ly/HabGuide). The goal was to collapse the existing 258 types down to ~25 types for reporting in the habitat guide. The habitat guide contains a description of each stream and river type, a distribution map, a photo, associated common and rare species, a crosswalk to state aquatic community types, and a summary of current condition information. Given the scope of the project, the existing Northeast Aquatic Habitat Classification System (Olivero and Anderson 2008) and GIS map (NHD Plus V1. 1:100,000) was used as the foundation. Resources were not available for remapping at a finer scale or reanalyzing the detailed stream and river types in the region, although a new tidal stream and river class was developed as part of this simplification project. The simplification method was developed with guidance from a steering committee of state freshwater ecologists. The steering committee recommended using a simplification framework based on the NY Freshwater Blueprint (White et al. 2011). To keep the number of regional types to a manageable number yet still maintain key ecological information, we developed a 58 type simplification that used size, gradient, geology, temperature, and tidal classes. However, the above five variables were not used to define every habitat type. For example, headwaters through small rivers were split using size, gradient, geology and temperature, while medium to large rivers were only split by gradient and temperature. Tidal habitats were split by three size classes. This simplification yielded a set of stream and river types that many felt would be useful to agencies and managers across the region. For the general audience of the habitat guide, the 58 types were further collapsed into 23 major types. The 23 major types were created by collapsing the geology classes for headwaters through small rivers and collapsing the gradient classes for medium to large rivers. Although the expected natural community types within the various geology classes of headwaters through small rivers will vary, particularly among the macroinvertebrate and aquatic plant communities, we wanted to focus the general audience on the more dominant patterns of size, gradient, and temperature for headwaters through small rivers. Similarly for medium to large rivers, we focused on the dominant patterns of size and temperature variation within these larger rivers. The habitat guide maps still show the finer distribution of the full 58 types using different colors for geology types within headwaters-small rivers and different colors for gradient classes for medium-large rivers, however the accompanying habitat guide descriptions, associated species, and condition statistics reflect patterns across the simplified 23 types.

This interactive web map presents a geospatial visualisation of one of the most devastating natural disasters in recent history—the 2004 Boxing Day Earthquake and Tsunami. The map includes two key layers:Boxing Day Earthquake EpicenterThis layer marks the location of the earthquake that struck off the west coast of northern Sumatra, Indonesia, on December 26, 2004.Tsunami Energy Distribution LayerUsing a gradient color scheme, this layer illustrates the energy map of the Boxing Day Tsunami. This Web Map was created in 2025 and is for use in the GIS in Schools Boxing Day Tsunami Story Map Lesson.