This project file contains row research data and result data that have been used for the paper entitled "GIS-based multi-criteria analysis for Arabica coffee expansion in Rwanda" by Innocent Nzeyimana, Alfred E. Hartemink, Violette Geissen. http://dx.doi.org/10.6084/m9.figshare.1128594- See more at: http://figshare.com/preview/_preview/1128594#sthash.QkGK7m8Y.dpuf

These tables contain the tabular results of the VIewshed 2 tool when instructed to measure the frequency of observers per pixel within 10km of tomb constellations.

Students in geographic information systems and science (GIS) require significant experience outside of spatial analysis, cartography, and other traditional geographic topics. Computer science knowledge, skills, and practices exist as essential components of GIS practice, but coursework in this area is not universally offered in geography or GIS degrees. To support those interested in developing such courses, this paper describes the design and implementation of a server-focused course in WebGIS at University Texas A&M University. We provide an in-depth discussion of the equipment and resources required to build and operate an on-premise CyberGIS server infrastructure suitable for supporting such classes, providing comparisons with an equivalent solution built on Amazon Web Services (AWS). We consider the comparative costs of these systems, including benefits and drawbacks of each. In comparing these deployment options, we outline the technical expertise, monetary investments, operational expenses, and organizational strategies necessary to run server-based CyberGIS courses. Finally, we reflect on assignments and feedback from students and consider their experiences in a course of this nature. This article provides a resource for GIS instructors, academic departments, or other academic units to consider during infrastructure investment, curriculum redesign, the addition of courses in degree plans, or for the development of CyberGIS components.

Building shape data and codes that support the findings of our paper entitled "Graph convolutional autoencoder model for the shape coding and cognition of buildings in maps" (https://doi.org/10.1080/13658816.2020.1768260)

This file contains the generated line of sight data regarding visibility from the modeled corridor to mountaintop tomb points in Western Tibet.

Heard Island and McDonald Islands, vegetation layer. This is a polygon dataset stored in the Geographical Information System (GIS). The data represents approximately the areas of vegetation cover on these islands.

UniGR cross-border study DFHI-ISFATES: Computer Science and Web Engineering (B.Sc.) Source: DFHI-ISFATES Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=2272&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/707caedf-304d-4509-bd33-32092fe35a58 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Cross_border_programmes_science_mathematics_computing_2023_WMS/guest with layer name(s): -DFHI_ISFATES_Computer_Science_web_engineering_BSc

Results of ongoing surveys to gauge the amount of litter located on Snowdon in North Wales, close to paths popular with walkers and other casual visitors. It is intended to show the types of litter as an indicator of behaviour and littering-motivation.

3D Simulation and Geometric Assessment of The Effects of Law and Regulations on The Urban Fabric: Testing The Block-Check Index in Ginza, Tokyo

This data supports the paper entitled "Mapping the landscape of geospatial data citations". The dataset covers geospatial data-intensive research papers published between 2015-2018 retrieved using Scopus. The article's citations were assessed for data citation occurances, and coded using a data citation classification. Data were enhanced and linked to subject coverage and journal policy status information using Excel & SPSS. For more information about how the data were created and coded please review the 'Methodology' section of the paper. More information is provided below, including supplemental documentation and related publications. Abstract (paper) ABSTRACT Data citations, similar to article and other research citations, are important references to research data that underlie published research results. In support of open science directives, these citations must adhere to specific conventions in terms of consistency of both placement within an article, and the actual availability or access to research data. To better understand the level to which geospatial research data are currently cited, we undertook a study to analyse the rate of data citation within a set of data-intensive geospatial research articles. After analysing 1717 scholarly articles published between 2015 and 2018, we found that very few, or 78 (5%), meaningfully cited primary or secondary geospatial data sources in the cited references section of the article. Even fewer researchers, only 25 or 1.5%, were found to have cited data using a DOI. Given the relatively low data citation rate, a focus on contributing factors including barriers to citing geospatial data is needed. And while open sharing requirements for geospatial data may change over time, driving data citation as a result, understanding benchmarks for data citation for monitoring purposes is useful.

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.

The MapBiomas annual land use/land cover time series data is the result of a collaborative network of biomes, land use, remote sensing, GIS, and computer science experts working together to monitor change across the country of Brazil. MapBiomas LULC maps are derived using 30-meter Landsat Level-2 cloud-free composite imagery mosaics and machine learning/deep learning classification algorithms. More.Data SummaryGeographic Coverage: BrazilTemporal Coverage: 2015 - 2021Temporal Resolution: AnnualSpatial Resolution: ~30-metersSource Imagery: Landsat Level-2Version: Collection 7.1**The collections represent changes in the coverage periods of the annual map, changes in the legend, and/or corrections to the previous version.Class AttributionCitationMapBiomas Project – Collection 7.1 of the Annual Series of Coverage and Land Use Maps of Brazil, accessed on June 29, 2023 via the link: https://brasil.mapbiomas.org/en/colecoes-mapbiomas/

Scullin and Murray Monoliths 1:25000 Topographic GIS Dataset. Features include coastline, areas of exposed rock, melt lakes, spot heights and 100 metre interval contours.

Heard Island, ice layer. This is a polygon dataset stored in the Geographical Information System (GIS). The ice layer shows ice/snow as depicted on the Heard Island satellite image map, published in 1991. The amount of ice/snow is as captured on the SPOT image 9 Jan 1988.

This dataset is GIS data representing waypoints and routes in the area of the Windmill Islands, Antarctica. The waypoint and route data held by the Australian Antarctic Data Centre is updated after each summer season using feedback provided by the Australian Antarctic Division's Field Training Officers with approval for changes given by the Australian Antarctic Division's Field Support Coordinator.

The Digital Data Series encompasses a broad range of digital data, including computer programs, interpreted results of investigations, comprehensive reviewed data bases, spatial data sets, digital images and animation, and multimedia presentations that are not intended for printed release. Scientific reports in this series cover a wide variety of subjects on all facets of U.S. Geological Survey investigations and research that are of lasting scientific interest and value. Releases in the Digital Data Series offer access to scientific information that is available in digital form; the information is primarily for viewing, processing, and (or) analyzing by computer

Available on CD Rom through the Map and Data Library. CD #008.

Key differences between American Viticultural Area (AVA) descriptions in Federal Register and observations in modeled geospatial datasets.

These data were produced by GA for the Computer Education Group of the ACT for the purposes of basic GIS training in ACT schools. Geological data consists mainly of polygons of rock units grouped according to rock type and geological age. Data have been derived from 1:250 000 and 1:100 000 scale geological maps produced by GA. The complete training dataset includes basic geology, Landsat TM images, and a portion of the 9 Second DEM of Australia.

This line shapefile represents the following features of the Antarctic Circumpolar Current: Subtropical Front (STF); Subantarctic Front (SAF); Southern Antarctic Circumpolar Current Front (sACCf); Polar Front (PF); Southern Boundary of the Antarctic Circumpolar Current

as described in

Alejandro H. Orsi, Thomas Whitworth III, and Worth D. Nowlin Jr (1995) On the meridional extent and fronts of the Antarctic Circumpolar Current. Deep-Sea Research 42 (5), 641-673.

The shapefile was created from data provided by lead author Alejandro Orsi to the Australian Antarctic Data Centre in August 2001. The data in the files from Alejandro Orsi was also combined in a csv file.
The data available for download includes the original data, the shapefile and the csv file.

A simplified geology of the Vestfold Hills is shown as a 1:250 000 scale inset in the map 'Geology of the Northern Vestfold Hills - East Antarctica', map number 12717 in the SCAR Map Catalogue. The data divides the Vestfold Hills into three rock types: Chelnok Paragneiss, Crooked Hill Gneiss and Mossel Gneiss.