WQI Map Legend for the Water Quality Index Dashboard. This legend was created in an ArcGIS Pro layout, then captured as a JPG screenshot.

Application for search and view legend of Geological maps at a scale of 1 : 50,000 (GEOČR50).

Application for search items of geological map legend 1 : 25,000.

MapLegendExtraction

This dataset contains high-resolution geological maps annotated with the bounding boxes of their embedded map legends, along with structured JSON representations of legend content. Designed for training models in legend detection, legend parsing, and map understanding.

This is a guide that describes how to use the layer list and legend widgets in web maps where the functionality is available. Not all widgets or functionality is available in every web map.

For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Original model developed in 2016-17 in ArcGIS by Henk Pieter Sterk (www.rfase.org), with minor updates in 2021 by Stacy Shinneman and Henk Pieter Sterk. Model used to generate publication results:Hierarchical geomorphological mapping in mountainous areas Matheus G.G. De Jong, Henk Pieter Sterk, Stacy Shinneman & Arie C. Seijmonsbergen. Submitted to Journal of Maps 2020, revisions made in 2021.This model creates tiers (columns) of geomorphological features (Tier 1, Tier 2 and Tier 3) in the landscape of Vorarlberg, Austria, each with an increasing level of detail. The input dataset needed to create this 'three-tier-legend' is a geomorphological map of Vorarlberg with a Tier 3 category (e.g. 1111, for glacially eroded bedrock). The model then automatically adds Tier 1, Tier 2 and Tier 3 categories based on the Tier 3 code in the 'Geomorph' field. The model replaces the input file with an updated shapefile of the geomorphology of Vorarlberg, now including three tiers of geomorphological features. Python script files and .lyr symbology files are also provided here.

We provide legend images for map data provided by the open platform. If you send the request URL to the server along with the authenticated key value, you can receive a legend in PNG / JPG / XML format. The OGC (Open Geospatial Consortium) standard API is an international standard developed for sharing and interoperability of spatial data, enabling efficient provision and use of various geographic information such as maps, features, and rasters on the web. The latest OGC API adopts a RESTful structure to enhance development convenience and expandability, and provides legend information used in WMS and WFS.

Danville Transit provides bus services to help residents and visitors travel around the city and surrounding areas. The primary role of Danville Transit is to offer affordable and reliable transportation for individuals who may not have access to private vehicles or prefer not to drive. The Danville Transit System map provides a visual representation of the routes, bus stops, and major transfer points for public transportation in the city of Danville, Virginia.

Use the Interactive Legend template to allow users to filter layers in your map by toggling the visibility of features based categories and ranges in the legend. Choose from paired feature-specific effects, such as bloom and blur, to distinguish between selected items in the legend and the remaining data. Choose from several options to emphasize selected items in the legend while other items remain on the map in muted colors. Examples: Form a better understanding of the spatial relationship between map features by changing the visibility of the content. Present economic data relevant to numerical range values of interest during a seminar. Analyze crime data to facilitate decision making of law enforcement distribution pertaining to specific crime categories. Data requirements The Interactive Legend template requires a feature layer to use all of its capabilities. The following drawing styles are supported: Location (Single Symbol) Types (Unique symbols) Counts and amounts (Size) - Classify Data Checked Counts and Amounts (Color) - Classify Data Checked Relationship Relationship and Size (Partially Interactive) Predominant Category Predominant Category and Size (Partially interactive) Types and Size (Partially interactive) Key app capabilities Layer effects - Use layer effects to differentiate between features included and excluded in a filter, and specify how features are emphasized and de-emphasized when a filter is applied using the legend. Zoom to button - Allow users to zoom to features selected in the legend. Feature count - Include a feature count for items that are selected in the legend Export - Capture an image (PDF, JPG, or PNG) from the app that a user can save. Time filter - Filter features in the map using time enabled layers Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

In order to use the Romanian color standard for soil type map legends, a dataset of ESRI ArcMap-10 files, consisting of a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), four different .lyr files, and three different .style files (https://desktop.arcgis.com/en/arcmap/10.3/map/ : saving-layers-and-layer-packages, about-creating-new-symbols, what-are-symbols-and-styles-), have been prepared. The shapefile set is not a “real” georeferenced layer/coverage; it is designed only to handle all the instants of soil types from the standard legend.

This legend contains 67 standard items: 63 proper colors (different color hues, each of them having, generally, 2 - 4 degrees of lightness and/or chroma, four shades of grey, and white color), and four hatching patterns on white background. The “color difference DE*ab” between any two legend colors, calculated with the color perceptually-uniform model CIELAB, is greater than 10 units, thus ensuring acceptably-distinguishable colors in the legend. The 67 standard items are assigned to 60 main soils existing in Romania, four main nonsoils, and three special cases of unsurveyed land. The soils are specified in terms of the current Romanian system of soil taxonomy, SRTS-2012+, and of the international system WRB-2014.

The four different .lyr files presented here are: legend_soilcode_srts_wrb.lyr, legend_soilcode_wrb.lyr, legend_colorcode_srts_wrb.lyr, and legend_colorcode_wrb.lyr. The first two of them are built using as value field the “Soil_codes” field, and as labels (explanation texts) the “Soil_name” field (storing the soil types according to SRTS/WRB classification), respectively, the “WRB” field (the soil type according to WRB classification), while the last two .lyr files are built using as value field the “color_code” field (storing the color codes) and as labels the soil name in SRTS and WRB, respectively, in WRB classification.

In order to exemplify how the legend is displayed, two .jpg files are also presented: legend_soil_srts_wrb.jpg and legend_color_wrb.jpg. The first displays the legend (symbols and labels) according to the SRTS classification order, the second according to the WRB classification.

The three different .style files presented here are: soil_symbols.style, wrb_codes.style, and color_codes.style. They use as name the soil acronym in SRTS classification, soil acronym in WRB classification, and, respectively, the color code.

The presented file set may be used to directly implement the Romanian color standard in digital soil type map legends, or may be adjusted/modified to other specific requirements.

Soil Taxonomic Units in the map legend are named with the following convention: the four first letters abbreviate the taxon up to Subgroup level, a number differentiate among similar Subgroups, and the last two characters are linked to a lithostratigraphic unit. If defined, series are shown between brackets (Information source: Gómez-Miguel et al. 2015).

This dataset contains a Questionnaire used to evaluate the quality of the Romanian Standard of colors for soil type map legends (StdCol) by map users and map designers. The Standard of colors resulted from the application of the specific method proposed by authors for developing reliably-distinguishable color schemes for legends of natural resource taxonomy-based maps. It was applied, in its turn, in developing the Dominant Soil Map of Romania at the 1:700,000 scale (DSM700).

The Questionnaire contains the description of the Standard of colors, the items whose readability are to be evaluated (the color pairs of the Standard, the Standard as a whole, and two map excerpts), the guidelines of evaluation, and the requested general information regarding the evaluator.

A table that presents the test/evaluation data that were obtained from 46 evaluators is given.

ABSTRACT Reliable environmental monitoring and evaluation require high-quality maps of land use and land cover. For the Amazon biome, the TerraClass and MapBiomas projects apply different methodologies to create these maps. We evaluated the agreement between land cover and land use maps generated by TerraClass and MapBiomas (Collections 2 and 3) for the Brazilian Amazon biome, from 2004 to 2014. Specifically, we: (1) described both project legends based on the LCCS (Land Cover Classification System); (2) analyzed the differences between their classes; and (3) compared the mapping differences among the Brazilian states that are totally or partially covered by the Amazon biome. We compared the classifications with a per-pixel approach and performed an evaluation based on agreement matrices. The overall agreement between the projects was 87.4% (TerraClass x MapBiomas 2) and 92.0% (TerraClass x MapBiomas 3). We analyzed methodological differences to explain the disagreements in class identification. We conclude that using these maps together without a properly adapted legend is not recommended for the analysis of land use and land cover change. Depending on the application, one mapping system may be more suitable than the other.

Geological map legend, North and North-East Greenland, 1:250 000

In this skill builder, you'll learn how your can save maps. You'll do the following:Save a PDF of the map, optionally including a legend and pop-up Save an image (PNG) of the map, optionally including a legend and pop-up Save an interactive map, optionally sharing it with others Saved maps includes layers you've added, sketching you've done, and the extent (scale and location) you have focused the map.

We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance. Developing such knowledge is essential to design effective interfaces for digital earth systems. One of the two legends contained an alphabetical ordering of categories, while the other used a perceptual grouping based on the Munsell color space. We tested the two legends for 4 tasks with 20 experts (in geography-related domains). We analyzed traditional usability metrics and participants’ eye movements to identify the possible reasons behind their success and failure in the experimental tasks. Surprisingly, an overwhelming majority of the participants failed to arrive at the correct responses for two of the four tasks, irrespective of the legend design. Furthermore, participants’ prior knowledge of soils and map interpretation abilities led to interesting performance differences between the two legend types. We discuss how participant background might have played a role in performance and why some tasks were particularly hard to solve despite participants’ relatively high levels of experience in map reading. Based on our observations, we caution soil cartographers to be aware of the perceptual complexity of soil-landscape maps.

This image is utilized in the Risk and Resilience section of the US-40 Story map. Questions regarding this image can be directed towards udotgisr3@utah.gov.

In order to use the standard hatch legend for Romanian soil texture maps in the ESRI ArcMap-10 electronic format, a dataset consisting a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), two different .lyr files, and two different .style files have been prepared (ESRI, 2016). The shapefile set is not a “real” georeferenced layer/coverage; it is designed only to handle all the instants of soil texture items from the standard legend. This legend is related to the current Romanian system of soil taxonomy, SRTS-2012+, and consists of three sub-standards, corresponding to three taxonomic levels: soil qualifiers, soil textural classes, and soil textural subclasses. At the first level there are five hatches for the four soil qualifiers related to soil texture and for the “Skeletic” soil, and two miscellaneous items (various textures and unspecified texture), at the second level there are eight hatches for the seven soil textural classes and for the Skeletic soil, and the two miscellaneous items, and at the third level there are 14 hatches for the 13 soil textural subclasses and for the Skeletic soil, and three miscellaneous items. The correlation with the FAO soil textural classes/subclasses, used by the international soil classification system WRB, is very approximate, given that the Romanian soil classification systems use the Atterberg system to define soil particle size fractions and a specific definition of soil texture classes/subclasses – different from that of FAO. All the standard hatches may be combined to indicate an association of two soil textural classes/sub-classes in a map delineation. Also, the hatch legend may be joined to a color legend for developing a mixed map of soil type and soil texture. The two different .lyr files presented here are: legend_txtcode_srts_en.lyr, and legend_txtcode_en.lyr. Both of them are built using as value field the ‘CODE_TXT3’ field, coding the soil texture subclass at a more detailed level, but the first one uses as labels (explanation texts) the ‘TEXT_RE’ field, storing the soil texture subclass name in SRTS-2012+ and in English language, while the second one, the ‘TEXT_WRB3’ field, storing the SRTS-2012+ soil texture subclass name in English language. In order to exemplify how the legend is displayed, a .jpg file is also presented: legend_txt.jpg, displaying the legend (symbols and labels) according to the first .lyr file. The two different .style files presented here are: txt_codes.style and txt_abbrev.style. The symbol (hatches) for each different map feature has been built and stored in these two .style files, using as name the soil texture subclass code and, respectively, the SRTS-2012+ soil texture subclass name abbreviation.

Legend for 1963 Vegetation Cover Map found in Roller (1974) is attached to this feature service. This map is published as a hosted tile layer: ESGR Vegetation Cover 1963.

This MS Excel spreadsheet implements the procedure for calculating the CIELAB perceptually-uniform color attributes and color differences from the primary-defined RGB color coordinates. It may be used by map designers to obtain specific map legends comprising a large number of colors - all reliably-distinguishable from one another. The spreadsheet contains a starting list of 63 such colors – the Romanian color standard for soil type map legends (color-ordered, including lightness/chroma degrees, one color in a row).

The CIELAB color attributes, color attribute differences and overall color difference are those defined by the CIELAB color model/space (CIE S 014-4:2007. Colorimetry - Part 4: CIE 1976 L*a*b* Colour space). This model/space represents a color by using three abstract coordinates (orthogonal axes): L* has values between 0 (black) and 100 (white), indicating the color lightness; a* has positive values indicating amounts of red, negative values indicating the amounts of green and the value zero indicating neutral grey; b* has positive values indicating amounts of yellow, negative values indicating the amounts of blue and the value zero indicating neutral grey. From these three coordinates, other important perceptually-uniform color attributes can be easily calculated: CIELAB chroma (C*ab), CIELAB hue angle (hab), CIELAB attribute differences (DL*, Da*, Db*, DC*ab, Dhab) and overall CIELAB color difference (DE*ab).

The color differences calculated regarding a color are those between that color and the immediately-preceding color in the list. The list being color-ordered, the adjacent colors are normally the closest colors in the list, thus the color differences between them may be easily checked. Different other colors that appear as close in the list may be duplicated near others to see the color differences between them.

The implemented calculation procedure consists of the following steps: (i) transformation of RGB coordinates to CIEXYZ coordinates, (ii) transformation of CIEXYZ coordinates to CIELAB coordinates (perceptually-uniform) and calculation of other CIELAB color attributes, and (iii) calculation of CIELAB color differences (perceptually-uniform).

In order to obtain color lists (legends) appropriate for specific requirements, by using the "trial and error" method, the RGB coordinates (integer numbers between zero and 255) of the list colors can be easily modified/adjusted to define other colors that are reliably-distinguishable from one another, and/or new colors can be inserted into the list in an appropriate place (order). Usually, a color difference threshold of 10 DE*ab units ensures acceptably-distinguishable colors, but, naturally, this threshold may be increased. The “Recolor” button refreshes the colors in the “Colors” column of the spreadsheet, after RGB coordinates have been modified.