Cartography is the knowledge associated with the art, science, and technology of maps. Maps portray spatial relationships among selected phenomena of interest and increasingly are used for analysis and synthesis. Through digital cartography and web mapping, however, it is possible for almost anyone to produce a bad map in minutes. Although cartography has undergone a radical transformation through the introduction of digital technology, fundamental principles remain. Doing computer cartography well requires a broad understanding of graphicacy as a language (as well as numeracy and literacy). This course provides an introduction to the principles, concepts, software, and hardware necessary to produce good maps, especially in the context (and limitations) of geographic information systems (GIS) and the web.

You will be asked to work through a series of modules that present information relating to a specific topic. You will also complete a series of cartography projects to reinforce the material. Lastly, you will complete term projects. Please see the sequencing document for our suggestions as to the order in which to work through the material. We have also provided PDF versions of the lectures with the notes included.

This course teaches how to best symbolize your map data so that your audience gets the information that it needs.Goals Apply principles of map symbology to map features. Understand basic principles of map symbology.

This file includes a draft mapping from three experts (plus the corresponding discussion and alignment) to map the categories of the Metadata for Ontology Descriptions (MOD) to the FAIR principles.

Follow-up questions after map design variation (*this question was included for evaluating a possible response bias).

Appendices include the original survey, response data, and collated results related to the Open File Report. Geoscience maps, regardless of target body, are spatial and temporal representations of materials and processes recorded on planetary surfaces (Varnes, 1973; Spencer, 2000). The information and context provided by these maps promote basic and applied research within and across various geoscience disciplines. They also provide an important basis for programmatic and policy decisions (for example, H.R. 2763 – 102nd Congress, National Geologic Mapping Act of 1992). Since 1961, planetary (that is, all solid surface bodies in the Solar System beyond Earth) geoscience maps have been used in nearly every facet of planetary exploration, from landing site characterization for human (for example, Grolier, 1970) and robotic (for example, Anderson and Bell, 2010) missions to mineralogical analyses of water-alteration on Mars (for example, Loizeau and others, 2007). Modern planetary geoscience maps are either standardized (those published by the United States Geological Survey (USGS) that require adherence to cartographic standards, conventions, and principles) or non-standardized (those published by other venues that are not required to, but might, adhere to cartographic standards, conventions, and principles). Geoscience mapping and its resultant product, whether standardized or non-standardized, is widely considered a routine contextual investigation that should be performed in advance of and (or) in tandem with surface science investigations. Geoscience mapping campaigns are systematically included in mission proposals as anticipated derivative products (for example, Williams and others, 2014), along with other high-order cartographic data products such as controlled image mosaics and digital terrain models. Additionally, planning documents from multiple planetary science focused programs, organizations, and institutions identify geoscience maps as key scientific and technical contributors to planetary exploration (Planetary Decadal Survey, 2011; MEPAG, 2015; Roadmap to Ocean Worlds, 2018). In line with these community uses and priorities, the National Aeronautics and Space Administration (NASA), in cooperation with the USGS Astrogeology Science Center (Flagstaff, AZ), has built and maintained a non-trivial infrastructure dedicated not only to producing geoscience maps but also to building and disseminating mapping-based resources to the planetary science community.

Constructing maps suitable for autonomous vehicles (AVs) is a critical research focus in autonomous driving and AI, extending cartography’s challenges. Building on cartographic principles, we propose the concept of a road scene map along with its modeling method that incorporates dynamic/static traffic elements with geometric/semantic features. Current limitations include unclear road scene graph relationships and a lack of integration among 3D traffic entity detection, map element detection, and scene relation extraction. To address these issues, we propose a method for constructing road scene maps: (1) A multi-task detection model identifies traffic entities and map elements directly in bird’s-eye-view (BEV) space, providing precise location, geometry, and attribute data; (2) A unified road scene relation pattern enables rule-based spatial/semantic relationship extraction. Experiments on nuScenes demonstrate improvements: the detection model achieves 1.5% and 1.9% accuracy gains in traffic entity and map element detection over state-of-the-art methods, while the relation extraction method covers broader perceptual ranges and more complex interactions. Results confirm the effective integration of 3D object detection, map element recognition, and scene relation extraction into a unified map. This integration delivers critical environmental information (locations, geometries, attributes, and spatial/semantic relationships) to AVs, significantly enhancing their perception and reasoning in dynamic road scenarios.

The Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition and Addendum have been developed in collaboration with national, state and territory agencies as part of the Australian Collaborative Land Use and Management Program (ACLUMP).

The Addendum provides guidance on the implementation of mapping principles and procedures outlined in the Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition. The aim is to ensure that catchment scale mapping is relevant, up to date and reliable for decision-making. It focuses on the goals of catchment scale land use mapping, the potential to update land use mapping using ancillary information, and methods to improve the reliability of and confidence in catchment scale land use mapping.

Administrative Division Boundary_Direct-administered Municipalities, County (City) Map Compilation Principles Explanation, including mapping methods, operation procedures, and feature styles, etc., updated version in the 112th year.

The Center for International Forestry Research (CIFOR) completed extensive research on integrated landscape management and produced large-scale ecological vegetation maps for the whole province of West Kalimantan (GOLS-USAID funded project). These 1:50,000 scale ecological vegetation maps cover more than 60 classes of natural and man-made vegetation including various forest types, but also details on logged-over areas, peat swamps, heath forest, oil palm estate, various mixed agroforestry systems, mosaics of fallows and smallholder agriculture. Landscapes are pre-stratified according to climate, geomorphology, types of soil, catchment areas and elevation classes, and interpretation is a combination of supervised classification and manual digitization on-screen using LANDSAT satellite data (2015). The work is supplemented by extensive ground checking with detailed ecological surveys. The various types are denoted using colour coding and symbols based on the cartographic principles of ecological mapping, one colour representing one vegetation type and its succession. For example, a solid green colour is assigned to lowland forest and its first degradation level, logging, is represented with green mixed with horizontal white stripes, indicating the depletion of the original forest type. These large-scale vegetation maps are important sources of information for land allocation and ecosystem-based management, both for the private and public sectors and help as well recognize potential areas or specific forest types for conservation. This dataverse dataset supports .pdf format only. To download shape files of the maps, please go to https://www2.cifor.org/map/vegetation/

OptimalGrowthData

External Code

This repository relies on a modest amount of external code in order to run properly. Unfortunately, due to licensing concerns, that code cannot be directly included in this repository. If you want run the various scripts in this repository, you must first download the open source MATLAB software package gptoolbox. Among a great deal of additional functionality, this package contains the readOFF function which enables users to open the many .off mesh files. Add these functions to the MATLAB path using:

addpath(genpath('/Path/To/gptoolbox'));

Please note that you do not actually need to install gptoolbox. You merely have to clone the GitHub repository and add it to your path. If you would like to install it, please consult the extensive installation instructions on that GitHub page.

Mesh Data Format

Most of the data is surface mesh data stored in .off format. You can view th...

The studies carried out in the context of the development of the Epernay PPRi (map of hazards) were carried out on the scale of 1/10 000th, and mapped on a background IGN scan25 enlarged to 1/10 000th. Since regulatory zoning stems from the intersection of the hazard map and the stake map, the accuracy of this mapping cannot be greater than that of the hazards. Consequently, the scale of use of the regulatory zoning is that of 1/10 000 and exploitation on a smaller cadastral scale (1/5000 or 1/2000) is not recommended. However, municipalities wishing to do so may transpose the regulatory map into their planning documents provided that they comply with operating principles in order to take account of the uncertainty associated with the expansion of the zoning, particularly at the boundary of the area.

Indeed, it is not possible to improve the accuracy of the initial data which presents uncertainty about its contours of the order of 10 metres, which is relatively important on the scale of a plot in an urbanised area.

The transposition of the regulatory map into a cadastral planning document cannot therefore be limited to a mere enlargement, which would result in a false precision of the contours. Therefore, a guide defines the principles that would allow municipalities who wish to do so, a transposition into an urban planning document (PLU, municipal map) taking into account the uncertainties between each area. It must also make it possible to define the area regulation to be applied when considering planning permissions.

The hazard that made it possible to construct the Regulatory Zoning, as well as the stakes are located under gaspar No. 51DDT20170001

Spatial resolution: 1/2 500

Genealogy: The limits of the uncertainty band are not represented on the graphic documents of the RPP, they are not official in nature. The boundaries of the uncertainty band straddle the separation between two zones of the Regulatory Zonage, which do not follow cadastral or administrative boundaries. The width of this limit is set at 10 metres. A guide to the interpretation of this band sets out the principles for its operation.

The Kansas Cartographic Database (KCD) is an exact digital representation of selected features from the USGS 7.5 minute topographic map series. Features that are captured include: county boundaries, township boundaries, section corners, major transportation, railroads, and principle hydrology. Major transportation and principle hydrology are defined as those features that are found on the official USGS 1:500,000 state map. It represents the general hydrologic and transportation network in Kansas. More detailed hydrology (all streams and lakes) is available but has not been converted to Arc/Info. This can be requested through KGS. The data was captured using in-house software titled GIMMAP. It was imported into Arc/Info using the generate format and then cleaned or built. It was designed to be a cartographic database for use on state and county map production.

Map variation categories.

Regression models with SBC and p-value with task success, comfort, and confidence ratings as the dependent variables (see S4–S6 Tables for odds ratios of each model).

Abstract The Catchment Scale Land Use of Australia – Update December 2023 dataset is the national compilation of catchment scale land use data available for Australia (CLUM), as of December 2023. It replaces the Catchment Scale Land Use of Australia – Update December 2020. It is a seamless raster dataset that combines land use data for all state and territory jurisdictions, compiled at a resolution of 50 metres by 50 metres. The CLUM data shows a single dominant land use for a given area, based on the primary management objective of the land manager (as identified by state and territory agencies). Land use is classified according to the Australian Land Use and Management Classification version 8. It has been compiled from vector land use datasets collected as part of state and territory mapping programs and other authoritative sources, through the Australian Collaborative Land Use and Management Program. Catchment scale land use data was produced by combining land tenure and other types of land use information including, fine-scale satellite data, ancillary datasets, and information collected in the field. The date of mapping (2008 to 2023) and scale of mapping (1:5,000 to 1:250,000) vary, reflecting the source data, capture date and scale. Date and scale of mapping are provided in supporting datasets.

Currency Date modified: December 2023 Date Published: June 2024 Modification frequency: As needed (approximately annual) Data Extent Coordinate reference: WGS84 / Mercator Auxiliary Sphere Spatial Extent North: -9.995 South: -44.005 East: 154.004 West: 112.505 Source information Data, Metadata, Maps and Interactive views are available from Catchment Scale Land Use of Australia - Update 2023 Catchment Scale Land Use of Australia - Update 2023 – Descriptive metadata The data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license. Lineage Statement This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). 2023 updates include more current data and/or reclassification of existing data. The following areas have updated data since the December 2020 version:

New South Wales (2017 v1.5 from v1.2). Northern Territory (2022 from 2020). Tasmania (2021 from 2019). Victoria (2021 from 2017). Data were also added from the Great Barrier Reef Natural Resource Management (NRM) regions in Queensland (2021 from a variety of dates 2009 to 2017). the Australian Tree Crops. Australian Protected Cropping Structures and Queensland Soybean Crops maps as downloaded on 30 November 2023. The capital city of Adelaide was updated using 2021 mesh block information from the Australian Bureau of Statistics. Minor reclassifications were made for Western Australia and mining area within mining tenements more accurately delineated in South Australia.

Links to land use mapping datasets and metadata are available at the ACLUMP data download page at agriculture.gov.au. State and territory vector catchment scale land use data were produced by combining land tenure and other types of land use information, fine-scale satellite data and information collected in the field, as outlined in 'Guidelines for land use mapping in Australia: principles, procedures and definitions, 4th edition' (ABARES 2011). The Northern Territory, Queensland, South Australia, Tasmania, Victoria and Western Australia were mapped to version 8 of the ALUM classification (‘The Australian Land Use and Management Classification Version 8’, ABARES 2016). The Australian Capital Territory was mapped to version 7 of the ALUM classification and converted to version 8 using a look-up table based on Appendix 1 of ABARES (2016). Purpose for which the material was obtained: This catchment scale land use dataset provides the latest compilation of land use mapping information for Australia’s regions as at December 2023. It is used by the Department of Agriculture, Fisheries and Forestry, state agencies and regional natural resource management groups to address issues such as agricultural productivity and sustainability, biodiversity conservation, biosecurity, land use planning, natural disaster management and natural resource monitoring and investment. The data vary in date of mapping (2008 to 2023) and scale (1:5,000 to 1:250,000). Do not use this data to:

Derive national statistics. The Land use of Australia data series should be used for this purpose. Calculate land use change. The Land use of Australia data series should be used for this purpose.

It is not possible to calculate land use change statistics between annual CLUM national compilations as not all regions are updated each year; land use mapping methodologies, precision, accuracy and source data and satellite imagery have improved over the years; and the land use classification has changed over time. It is only possible to calculate change when earlier land use datasets have been revised and corrected to ensure that changes detected are real change and not an artefact of the mapping process. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in October 2024 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster was created with RGB fields as a colour map with Geoprocessing tools in ArcPro. Note: The Digital Atlas of Australia downloaded and created a copy of the source data in February 2025 that was suitable to be hosted through ArcGIS Image Server & Image Dedicated. A copy of the raster dataset was created with RGB fields as a colour map with Geoprocessing tools in ArcPro, and the raster dataset was re-projected from 1994 Australia Albers to WGS 1984 Web Mercator (Auxiliary Sphere). Data dictionary

Attribute name Description

OID Internal feature number that uniquely identifies each row.

Service Pixel value (Scale) The scale at which land use was mapped in the vector catchment scale land use data provided by state and territory agencies or others:1:5,000, 1:10,000, 1:20,000, 1:25,000, 1:50,000, 1:100,000 or 1:250,000

Count Count of the number of raster cells in each class of VALUE.

Label Reflecting the scale of the source data ranges from 1:5,000 to 1:250,000

Contact Department of Agriculture, Fisheries and Forestry (ABARES), info.ABARES@aff.gov.au

The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" "Standard" (https://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit for the entire United States. Some areas may also include additional subdivisions representing the 14- and 16-digit hydrologic unit (HU). At a minimum, the HUs are delineated at 1:24,000-scale in the conterminous United States, 1:25,000-scale in Hawaii, Pacific basin and the Cari ...

McHenry_etal_2016_Survey_DataThe data comes from a remotely operated vehicle (ROV) survey conducted during the summer months of 2010-2013 along the coastal Gulf of Maine shelf. The survey aimed 1) to characterize the distribution and abundance of benthic megafauna with respect to near-shore abiotic conditions, 2) to develop spatially-explicit maps of ecological attributes of near-shore benthic assemblages, and 3) use such maps to inform the application of ecological principles when engaging in marine spatial planning. This file contains a data matrix of species abundances for the most dominantly observed species (i.e., greater than 5 observations), assemblage biomass, economic value, and shannon-weiner species diversity by site, along with values of associated summertime abiotic conditions (i.e.,mean transect depth, substrate type, water-mass position, bottom temperature, bottom current speed/direction, and bottom salinity). Depth and substrate type values were recorded from the ROV...

The studies carried out in the context of the development of the PPRi de Châlons-en-Champagne (map of hazards) were carried out on the scale of 1/10 000th, and mapped on a background IGN scan25 enlarged to 1/10 000th. Since regulatory zoning stems from the intersection of the hazard map and the stake map, the accuracy of this mapping cannot be greater than that of the hazards. Consequently, the scale of use of the regulatory zoning is that of 1/10 000 and exploitation on a smaller cadastral scale (1/5000 or 1/2000) is not recommended. However, municipalities wishing to do so may transpose the regulatory map into their planning documents provided that they comply with operating principles in order to take account of the uncertainty associated with the expansion of the zoning, particularly at the boundary of the area.

Indeed, it is not possible to improve the accuracy of the initial data which presents uncertainty about its contours of the order of 10 metres, which is relatively important on the scale of a plot in an urbanised area.

The transposition of the regulatory map into a cadastral planning document cannot therefore be limited to a mere enlargement, which would result in a false precision of the contours. Therefore, a guide defines the principles that would allow municipalities who wish to do so, a transposition into an urban planning document (PLU, municipal map) taking into account the uncertainties between each area. It must also make it possible to define the area regulation to be applied when considering planning permissions.

Genealogy: The limits of the uncertainty band are not represented on the PPRi graphic documents, they are not official in nature. The boundaries of the uncertainty band are represented by a polygon straddling the separation between two zones of the regulatory Zonage, its width is 10 metres and it follows neither cadastral nor administrative boundaries. A guide to the interpretation of this band sets out the principles for its operation.

Administrative boundary - Township (town, city, district) map compilation principles explanation, including mapping methods, operation procedures, and feature styles, etc., updated version in the year 112.

Over a period of almost 50 years since the beginning of the state recording, the original recordings had not been reproduced due to the lack of military and civilian interest. It was not until around 1860 that interest changed from the civilian side. There was a real demand for 1:25,000 scale maps, particularly from the mining side. From 1868 onwards, the General Staff made these map sheets available to the Prussian Ministry of Commerce, which were originally only intended to be used to derive subsequent standards. However, since the map sheets now published had already been recorded between 1836 and 1850 and only came onto the market 20 years later without further updates, they were rejected in some parts of Prussia. In the period that followed, the call for up-to-date maps became more and more urgent. The foundation stone for the new admission was thus laid. From 1875, the entire Prussian territory was recorded again, now in the meter unit agreed by the International Meter Convention of 1875. Only the cut of the sheet, the projection and the scale were taken over from the original measuring table sheets. The terrain was no longer displayed as a hatched representation, but for the first time in the form of contour lines, with a level surface known as normal zero being introduced as a reference point for a uniform indication of altitude throughout Germany. Compared to the original recording, the modern cartographic design principles can be clearly recognized in this new recording, such as the structure of the path network, the representation and delimitation of the vegetation, the reproduction of the administrative districts, as well as the labeling and the sheet margin, which to this day characterize the content and appearance of the official topographic national map series. The manufacturing process chosen was mainly engraving on copper or drawing on lithographic stone. Originally, the new recording had its own numbering system, which was later adapted to the sheet numbers and sheet names of today's DTK25 for reasons of simplification.