Maps exist to convey information to people, whether that information is how to get from one point to another or how many oil fields are located in a given region. Effective cartography can convey that information efficiently to map users.In this course, you will be introduced to a five-step workflow for designing and creating maps. This workflow can be applied to any map or output medium (print or digital). This course will cover all steps of the workflow in general terms, emphasizing the first two steps: the cartographic planning process and data evaluation.After completing this course, you will be able to perform the following tasks:Identify and describe the cartographic workflow steps.Explain cartographic design controls and how they drive map creation.Apply the planning step of the cartographic workflow.Evaluate data sources to determine applicability.Discuss why basemap and operational layers are important.Assign the correct coordinate system to data based on the geographic extent and map objective.Assess the level of detail required for a map and apply generalization techniques when appropriate.

LAWRENCE — Fall break is barely behind us, but a group of University of Kansas students has just finished an innovative eight-week course in using drones to develop aerial maps. Over the past two months, they’ve visited sites in KU's West District and at the Baker Wetlands, taking still images and videos over those areas. “The drone mapping course has been excellent in providing a hands-on experience with the drones,” said Siddharth Shankar, graduate student from Lucknow, India. “The course has focused not just on drones and how to fly them but also has made us aware of the FAA rules and regulations about drone flying and safety precautions. “My research has been in glaciology, with the study of icebergs in Greenland. The drone mapping course has provided new insights into incorporating it with my research in the near future.” The course, offered annually during the fall semester, is designed to teach students about the rapidly growing technology of small unmanned aerial systems, referred to as drones, and its wide-ranging applications — which include search-and-rescue, real estate and environmental monitoring. Students in the course come from a variety of disciplines including geography & atmospheric science, geology, ecology & evolutionary biology and civil engineering. Enthusiasm for the course has been very high, and it has filled rapidly each time it has been offered.

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 layer contains the following map information at a scale of 1.1000 for the municipalities of Navarra: communication routes, buildings, hydrography, themed soil, altimetry, unique buildings, mapped area, infrastructure networks and other place names. The list of municipalities mapped is in the following url: https://idena.navarra.es/downloads/List_of_municipalities_map_1000.pdf

Learn the key factors to consider when planning a cartography project and preparing data that supports your map's purpose, audience, and format.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The Geofabric Surface Cartography product provides a set of related feature classes to be used as the basis for the production of consistent hydrological cartographic maps. This product contains a geometric representation of the (major) surface water features of Australia (excluding external territories). Primarily, these are natural surface hydrology features but the product also contains some man-made features (notably reservoirs, canals and other hydrographic features).

The product is fully topologically correct which means that all the stream segments flow in the correct direction.

This product contains fifteen feature types including: Waterbody, Mapped Stream, Mapped Node, Mapped Connectivity (Upstream), Mapped Connectivity (Downstream), Sea, Estuary, Dam, Structure, Canal Line, Water Pipeline, Terrain Break Line, Hydro Point, Hydro Line and Hydro Area.

Purpose

This product contains a geometric representation of the (major) surface water features of 'geographic Australia' excluding external territories. It is intended to be used as the basis for the production of consistent hydrological cartographic map products, as well as the visualisation of surface hydrology within a GIS to support the selection of features for inclusion in cartographic map production.

This product can also be used for stream tracing operations both upstream and downstream however, as this is a mapped representation, streams may be represented as interrupted or intermittent features. In contrast, the Geofabric Surface Network product represents the same stream as a continuous connected feature, that is, the path that stream would take (according to the terrain model) if sufficient water were available for flow. Therefore, for stream tracing operations where full stream connectivity is required, the Geofabric Surface Network product should be used.

Dataset History

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Geofabric Surface Cartography is part of a suite of Geofabric products produced by the Australian Bureau of Meteorology. The source data input for the Geofabric Surface Cartography product is the AusHydro v1.7.2 (AusHydro) surface hydrology data set. The AusHydro database provides a seamless surface hydrology layer for Australia at a nominal scale of 1:250,000. It consists of lines, points and polygons representing natural and man-made features such as watercourses, lakes, dams and other water bodies. The natural watercourse layer consists of a linear network with a consistent topology of links and nodes that provide directional flow paths through the network for hydrological analysis.

This network was used to produce the GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3 of Australia (https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&catno=66006).

Geofabric Surface Cartography is an amalgamation of two primary datasets. The first is the hydrographic component of the GEODATA TOPO 250K Series 3 (GEODATA 3) product released by Geoscience Australia (GA) in 2006. The GEODATA 3 dataset contains the following hydrographic features: canal lines, locks, rapid lines, spillways, waterfall points, bores, canal areas, flats, lakes, pondage areas, rapid areas, reservoirs, springs, watercourse areas, waterholes, water points, marine hazard areas, marine hazard points and foreshore flats.

It also provides information on naming, hierarchy and perenniality. The dataset also contains cultural and transport features that may intersect with hydrographic features. These include: railway tunnels, rail crossings, railway bridges, road tunnels, road bridges, road crossings, water pipelines.

Refer to the GEODATA 3 User Guide http://www.ga.gov.au/meta/ANZCW0703008969.html for additional information.

The second primary dataset is based on the GEODATA TOPO-250K Series 1 (GEODATA 1) watercourse lines completed by GA in 1994, which was supplemented by additional line work captured by the Australian National University (ANU) during the production of the DEM-9S to improve the representation of surface water flow. This natural watercourse dataset consists of directional flow paths and provides a direct link to the flow paths derived from the DEM. There are approximately 700,000 more line segments in this version of the data.

AusHydro uses the natural watercourse geometry from the ANU enhanced GEODATA 1 data, and the attributes (names, perenniality and hierarchy) associated with GEODATA 3 to produce a fully attributed data set with topologically correct flow paths. The attributes from GEODATA 3 were attached using spatial queries to identify common features between the two datasets. Additional semi-automated and manual editing was undertaken to ensure consistent attribution along the entire network.

AusHydro dataset includes a unique identifier for each line, point and polygon. AusHydro-ID will be used to maintain the dataset and to incorporate higher resolution datasets in the future. The AusHydro-ID will be linked to the ANUDEM streams through a common segment identifier and ultimately to a set of National Catchments Boundaries (NCBs).

Changes at v2.1

! New Water Storages in the WaterBody FC.

Changes at v2.1.1

! 16 New BoM Water Storages attributed in the AHGFWaterBody feature class

and 1 completely new water storage feature added.



- Correction to spelling of Numeralla river in AHGFMappedStream (formerly

Numaralla).



- Flow direction of Geometric Network set.

Processing steps:

1. AusHydro Surface Hydrology dataset is received and loaded into the Geofabric development GIS environment

2. feature classes from AusHydro are recomposed into composited Geofabric hydrography dataset feature classes in the Geofabric Maintenance Geodatabase.

3. re-composited feature classes in the Geofabric Maintenance Geodatabase Hydrography Dataset are assigned unique Hydro-IDs using ESRI ArcHydro for Surface Water (ArcHydro: 1.4.0.180 and ApFramework: 3.1.0.84)

4. feature classes from the Geofabric Maintenance Geodatabase hydrography dataset are extracted and reassigned to the Geofabric Surface Cartography Feature Dataset within the Geofabric Surface Cartography Geodatabase.

A complete set of data mappings, from input source data to Geofabric Products, is included in the Geofabric Product Guide, Appendices.

Dataset Citation

Bureau of Meteorology (2014) Geofabric Surface Cartography - V2.1.1. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/ce5b77bf-5a02-4cf8-9cf2-be4a2cee2677.

CONABIO provides online cartography through cartographic metadata distributed following the guidelines in the Standards for Digital Geospatial Metadata of FGDC-NBII (Federal Geographic Data Committee – National Biological Information Infrastructure), 1996. The cartographic information is queried through a database that is organized based on themes (biotic, physical and social aspects, regionalization and others), scales, and geographic area. The metadata content is presented as basic information, reports of the information (methodology) and spatial data information. The cartography is available online at no charge in distinct formats like: export file for Arc/Info (.E00) and shape file (ESRI), and DXF (Drawing eXchange Format). Maps is presented in cartographic projections: Lambert Conic Conformal, UTM and geographic coordinates system. GIF format of map images can be obtained as well.

We introduce the Lateral Transfer Map (LTM), a tool for students to actively and visually explore the transfer of ideas, skills, and concepts across concurrent coursework. The LTM is an extension of a concept map, replacing interconnected concepts with courses. Just as a concept map represents the interconnectivity of concepts and ideas, the LTM represent the connectedness of courses, illustrating how knowledge and information learned in one course is used in another. LTMs draw from the theory of knowledge transfer across disciplinary domains and contexts. LTMs are appropriate for use in any course; we describe its use in an introductory course for STEM majors to help students understand connections and motivations in first-year courses. LTMs also represent a useful diagnostic for instructors to better understand and address how students view connections (or lack thereof) among disciplines or concurrent coursework.

Primary Image: A lateral transfer map drawn by a student in the Metacognition course to illustrate how she transfers information or skills from one class to another.

Seattle Parks and Recreation ARCGIS park feature map layer web services are hosted on Seattle Public Utilities' ARCGIS server. This web services URL provides a live read only data connection to the Seattle Parks and Recreations Golf Courses dataset.

Mapping between the Course-IDs and the corresponding Organization-IDs in WS08

This dataset consists of the 1km raster, dominant target class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km dominant coverage product is based on the 1km percentage product and reports the habitat class with the highest percentage cover for each 1km pixel. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019. Full details about this dataset can be found at https://doi.org/10.5285/c4035f3d-d93e-4d63-a8f3-b00096f597f5

Mapping between the Course-IDs and the corresponding Organization-IDs in WS19

Participants in this course will learn about remote sensing of wildfires from instructors at the University of Alaska Fairbanks, located in one of the world’s most active wildfire zones. Students will learn about wildfire behavior, and get hands-on experience with tools and resources used by professionals to create geospatial maps that support firefighters on the ground. Upon completion, students will be able to: Access web resources that provide near real-time updates on active wildfires, Navigate databases of remote sensing imagery and data, Analyze geospatial data to detect fire hot spots, map burn areas, and assess severity, Process image and GIS data in open source tools like QGIS and Google Earth Engine.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. James W. Sewall Company developed a complete GIS coverage for the park and revised the preliminary vegetation map classes to better match the results from the cluster analysis and NMS ordination. Polygons representing vegetation stands were digitized on-screen in ArcGIS 8.3, and later in ArcMap 9.1 and 9.2, using lines drawn on the acetate overlays, base layers of 1:8,000 CIR aerial photography, orthorectified photo composite image, and plot location and data. The minimum map unit used was 0.5 ha (1.24 ac). Stereo pairs were used to double check stand signatures during the digitizing process. Photo interpretation and polygon digitization extended outside the NPS boundary, especially where vegetation units were arbitrarily truncated by the boundary. Each polygon was attributed with the name of a vegetation map class or an Anderson Level II land use category based on plot data, field observations, aerial photography signatures, and topographic maps. Data fields identifying the USNVC association inclusions within the vegetation map class were attributed to the vegetation polygons in the shapefile. The GIS coverages and shapefiles were projected to Universal Transverse Mercator (UTM) Zone 19 North American Datum 1983 (NAD83). FGDC compliant metadata (FGDC 1998a) were created with the NPS-MP ESRI extension and included with the vegetation map shapefile. A photointerpretation key to the map classes for the 2006 draft vegetation map is included as Appendix A. The composite vegetation coverage was clipped to the NPS 2002 MIMA boundary shapefile for accuracy assessment (AA). After the 2006 vegetation map was completed, the thematic accuracy of this map was assessed.

Mapping between the Course-IDs and the corresponding Organization-IDs in WS13

Our “course introduction map” is an interactive tool designed for large soil and landscape-related courses, providing a brief (5-minute) introduction. Students access a link to mark their place of origin or current residence on a map of the Netherlands, with the collective data of all participants displayed alongside a summary information about the related physical-geographic regions. This approach immediately engages students, and allows teachers to display and reference the group’s results throughout the landscape-related course.

This vector dataset provides polygons that represent significant golf course facility locations in Suffolk County. These courses can be publicly (State, County, Town, Village) or privately owned. This dataset can be linked with the GolfCoursePoint feature class by the FACILITYID field. In some cases, there may be multiple Golf Course Points for a single Golf Course Polygon. These data are organized for consumption in desktop and web applications.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Spatial data from field observation points and quantitative plots were used to edit the formation-level maps of Petersburg National Battlefield to better reflect vegetation classes. Using ArcView 3.3, polygon boundaries were revised onscreen over leaf-off photography. Units used to label polygons on the map (i.e. map classes) are equivalent to one or more vegetation classes from the regional vegetation classification, or to a land-use class from the Anderson (Anderson et al. 1976) Level II classification system. Each polygon on the Petersburg National Battlefield map was assigned to one of twenty map classes based on plot data, field observations, aerial photography signatures, and topographic maps. The mapping boundary was based on park boundary data obtained from Petersburg National Battlefield in May 2006. Spatial data depicting the locations of earthworks was obtained from the park and used to identify polygons of the cultural map classes Open Earthworks and Forested Earthworks. One map class used to attribute polygons combines two similar associations that, in some circumstances, are difficult to distinguish in the field. The vegetation map was clipped at the park boundary because areas outside the park were not surveyed or included in the accuracy assessment. Twenty map classes were used in the vegetation map for Petersburg National Battlefield. Map classes are equivalent to one or more vegetation classes from the regional vegetation classification, or to a land-use class from the Anderson (Anderson et al. 1976) Level II classification system.

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This dataset contains a cartographic mask polygon shapefiles for maps created in COO product 1.5. These polygons are used for clear annotation and to mask-out unwanted features in report maps. ## Purpose For cartographic use only ## Dataset History Polygon mask features were created using the 'Features Outline Masks (Cartography)' tool (ArcMap) on annotation layers in maps for product CLM 1.2. For this dataset, masks were created from the annotations created from the following layer (dataset): 1. PopulatedPlaces Feature Class from the "GEODATA TOPO 250K Series 3" dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f). Masks polygons were also created for clear visualisation of graticules and state annotation graphics in the same maps. ## Dataset Citation Bioregional Assessment Programme (XXXX) Cartographic masks for map products COO 150. Bioregional Assessment Derived Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/43131c46-d0d8-44de-a272-9487c1cd5f2b. ## Dataset Ancestors * Derived From GEODATA TOPO 250K Series 3

Materials created by James Baker in June 2014 for the 108 Mapping Data course of the British Library Digital Scholarship Training Programme.