H.J. Andrews Studies Map is a compilation of study site locations and GIS base layers (e.g. administrative boundaries, roads, streams, etc.). This was updated in 2019 during the transition to the ArcGIS Online and Enterprise platforms.

Mineral Land Classification studies are produced by the State Geologist as specified by the Surface Mining and Reclamation Act (SMARA, PRC 2710 et seq.) of 1975. To address mineral resource conservation, SMARA mandated a two-phase process called classification-designation. Classification is carried out by the State Geologist and designation is a function of the State Mining and Geology Board. The classification studies contained here evaluate the mineral resources and present this information in the form of Mineral Resource Zones. The objective of the classification-designation process is to ensure, through appropriate local lead agency policies and procedures, that mineral materials will be available when needed and do not become inaccessible as a result of inadequate information during the land-use decision-making process.

The number of dataset files divided into the original published studies (original) and expert-modified distributions (expert) with two overall time periods.

Recommendations for the suitable contents of the geospatial datasets presenting the distribution of languages including the benefits of each, and our solutions (selected in the case study) concerning the Uralic languages.

This case study document provides information on how Google Maps is using our open datasets and articulates citizen benefits. This case study document provides information on how Google Maps is using our open datasets and articulates citizen benefits.

The Excel file contains the raw data records of the dynamic map key study of the Research Group on Experimental Cartography at the Eötvös Loránd University (ktk.elte.hu). The data collection lasted between July and September 2016. The file contains one sheet holding the 937 data records.

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.

Purpose:This web map supports the SR-258 & 118 Corridor Study storymap. Linework has been styled using Classic Map Viewer. The study and storymap were created by WCG with Kyle Horton as the lead and Ryan Anderson as the Project Manager. The storymap and supporting content were transferred ownership to UDOT Region 4 GIS on 9/28/2025.Go Live Date:12/30/2021 Project PIN: 19528 ePM Project Name:SR-258 & SR-118; Corridor Vision & Access Study Owner: Bracken Davis (udotgisr4@utah.gov) Update Interval:Data is not updated. It is static from the time of the study. When a project is created based on information from the study the project information will be added manually to indicate that a project has been started. Support Layers:SR 258 and SR 118 Linework feature layerSevier County TMP Future Roads feature layerElsinore_Town_Data feature layerSR 258 and SR 118 Corridor Study Turning Movement Volumes feature layerSR 258 and SR 118 Study Roadway Links feature layerSR-258 & SR-118 Corridor Study Proximity of Existing Accesses feature layerSR 258 and SR 118 Corridor Study Zoning feature layerusRAP feature layerSR-258 & SR-118 Corridor Study Limits feature layerSR 258 and SR 118 Future Roadways feature layerExisting AT Facilities Service feature layerAssociated Apps:SR-258 & SR-118 Corridor Study storymap Expected Life of Data:This storymap will remain active and publicly available until all projects related to this study are completed, at which time the study will be archived.

RESTYLE pilot study results by neighborhood, c.o. Marissa Chan.

The map displays the study area boundaries submitted and certified by incumbent local exchange carriers and state commissions through May 5th, 2016. As a result of confidentiality requests, certain boundaries for Verizon and AT&T are not displayed.

Web map containing the features from the Cottonwood Canyon Study, mainly design features with some development features and road features

Dataset based on maps presented in the "Annales" and "Past & Present" journals, between 1950 and 2000, focusing on motion maps.The data are a set of organized maps but does not include the maps themselves (only data on the maps), which are in two different repositories: www.jstor.org and persee.fr. Every map registered in the table indicates a URL where the original map is available freely, at persee.fr, and by request at jstor.org.

The mapping of the damage caused by natural disasters is a crucial step in deciding on the actions to take at the international, national, and local levels. The large variety of representations that we have observed leads to problems of transfer and variations in analysis. In this article, we propose a representation, Regular Dot map (RD), and we compare it to 4 others routinely used to visualise post-disaster damage. Our comparison is based on a user study in which a set of participants carried out various tasks on multiple datasets using the various visualisations. We then analysed the behaviour during the experiment using three approaches: (1) quantitative analysis of user answers according to the reality on the ground, (2) quantitative analysis of user preferences in terms of perceived effectiveness and appearance, and (3) qualitative analysis of the data collected using an eye tracker. The results of this study lead us to believe that RD is the best compromise in terms of effectiveness among the various representations studied.

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).

This is the study area associated with the project: “Status and Trends of Deciduous Communities in the Bighorn Mountains”. The aim of the study is to assess the current trends of deciduous communities in the Bighorn National Forest in north-central Wyoming. The data here represents phase I of the project, completed in FY2017. The USGS created a synthesis map of coniferous and deciduous communities in the Bighorn Mountains of Wyoming using a species distribution modeling approach developed in the Wyoming Landscape Conservation Initiative (WLCI) (Assal et al. 2015). The modeling framework utilized a number of topographic covariates and temporal remote sensing data from the early, mid and late growing season to capitalize on phenological differences in vegetation types. We used the program RandomForest in the R statistical program to generate probability of occurrence models for deciduous and coniferous vegetation. The binary maps were combined into a synthesis map using the procedure from Assal et al. 2015. In Phase II of this project (to be completed in FY2018 and 2019), the USGS will conduct a preliminary assessment on the baseline condition of riparian deciduous communities. This will be a proof-of-concept study where the USGS will apply a framework used in prior research in upland aspen and sagebrush communities to detect trends in riparian vegetation condition from the mid-1980s to present. Literature Cited Assal et al. 2015: https://doi.org/10.1080/2150704X.2015.1072289

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

🇦🇺 Australia English This case study document provides information on how Google Maps is using our open datasets and articulates citizen benefits.

This case study document provides information on how Apple Maps is using our open datasets and articulates citizen benefits.

This reference contains maps from the Woodworth Study Station depicting historic vegetation transects and photopoints. The following records have been included as separate digital holdings; - Vegetation Transect Map, 1963-1989 + Photopoints - Woodworth Station Historic Photopoints, 2011 - Woodworth Station Historic Vegetation Transects, 2011

ImageGem Models

project page: https://maps-research.github.io/imagegem-iccv2025/ github repo with example usage: https://github.com/MAPS-research/imagegem ImageGem Images: https://huggingface.co/datasets/MAPS-research/ImageGem-images

Description

Name Dtype Source Description

modelId int64 model metadata

modelName string model metadata

modelVersionId int64 model version metadata each model may have multiple versions modelVersionName string model version metadata… See the full description on the dataset page: https://huggingface.co/datasets/MAPS-research/ImageGem-models.