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.

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

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

ADMMR map collection: Geologic Map Legend; 36 x 22 in.

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.

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. 2021. Matheus G.G. De Jong, Henk Pieter Sterk, Stacy Shinneman & Arie C. Seijmonsbergen. Journal of Maps 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 also created an online storymap (https://arcg.is/Xjvy4) of all three tiers for both areas, which scales automatically as the user zooms in and out between scales to show how the data are dynamically visualized in a GIS.

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.

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.

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

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

In order to use the standard color legend for Romanian soil type maps in the ESRI ArcMap-10 electronic format, a dataset consisting a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), four different .lyr files, and three 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 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 (ESRI, 2016). 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 soil classification system WRB-2014. The four different .lyr files presented here are: legend_soilcode_srts_wrb.lyr, legend_soilcode_wrb.lyr, legend_colourcode_srts_wrb.lyr, and legend_colourcode_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 ‘colour_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_colour_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 colour_codes.style. They use as name the soil acronym in SRTS classification, soil acronym in WRB classification, and, respectively, the color code.

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.

A legend of a soil map, providing Vietnamese-English translations for different soil types.

Street Overlay Map for the City of Liberty. This map shows streets that were overlaid the past 10 years as well as the current proposed overlay.This map is set up is set up with an interactive legend for each overlay year. You can filter by year by selecting the year in the legend and you can zoom to each year. You can show the past 10 years of overlay by selecting Show All. Street segments can be selected on the map to find out more information for said street overlay.

League Of Legends Map Detection

## Overview

League Of Legends Map Detection is a dataset for object detection tasks - it contains Test annotations for 8,791 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

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.

For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Map package for use in ArcGIS Pro containing three-tiered geomorphological data and geographical datasets such as rivers, roads and hillshading. Datasets were used to generate figures for publication: 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. All data is in MGI Austria GK West projected coordinate system (EPSG: 31254) and was clipped to the study area.

Data derived from the ATKIS Datenbestand:Legende for cascade

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