Virginia Department of Transportation 2025 Quarter One Linear Referencing SystemVDOT 25.1 LRS Release Map PackagePackage will be downloaded to your local 'Downloads' folder by default. Map package as downloaded is compressed. In ArcGIS Pro, browse to the Map Package in a local folder, and select 'Add and Open'.
This ArcGIS map package includes multiple spatial datasets that are subsets of the CREST layers and which were used to make the maps in the accompanying article on A Global Representation Of CIty-Region Systems .
This package contains a project specific geodatabase and map (.mxd) for River Basin and modeling projects. For directions on using this file, see the GIS Standards Technical Memorandum on the Standards Page.
This package contains a project specific geodatabase and map (.mxd) for Watershed study projects. For directions on using this file, see the GIS Standards Technical Memorandum on the Standards Page.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
For complete collection of data and models, see https://doi.org/10.21942/uva.c.5290546.Map package for use in ArcMap containing three-tiered geomorphological data and geographical datasets such as rivers 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.
Map that shows the normalized yes votes per county for California's 2012 ballot measure that would require labeling of genetically modified organisms (GMOs) in food.
ArcGIS and QGIS map packages, with ESRI shapefiles for the DSM2 Model Grid. These are not finalized products. Locations in these shapefiles are approximate.
Monitoring Stations - shapefile with approximate locations of monitoring stations.
7/12/2022: The document "DSM2 v8.2.1, historical version grid map release notes (PDF)" was corrected by removing section 4.4, which incorrectly stated that the grid included channels 710-714, representing the Toe Drain, and that the Yolo Flyway restoration area was included.
These are map packages used to visualize geochemical particle-tracking analysis results in ArcGIS. It includes individual map packages for several regions of New Mexico including: Acoma, Rincon, Gila, Las Cruces, Socorro and Truth or Consequences.
This package contains a project specific geodatabase and map (.mxd) for Drinking Water projects. For directions on using this file, see the GIS Standards Technical Memorandum on the Standards Page.
Web maps are available for the following nine Kansas federal reservoirs considered for study in this project:Cheney ReservoirClinton LakeEl Dorado LakeHillsdale LakeMarion ReservoirMelvern LakeMilford LakePerry LakeTuttle Creek Lake
Mobile map packages are available for the following nine Kansas federal reservoirs considered for study in this project:Cheney ReservoirClinton LakeEl Dorado LakeHillsdale LakeMarion ReservoirMelvern LakeMilford LakePerry LakeTuttle Creek Lake
This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data. See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.
This map package references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis map package consists of tree canopy data covering the following categories:50-acre HexagonsCouncil DistrictsSDOT Urban Forestry Management UnitsManagement Units - Dissolved with ROWParcels Right of WayBlock GroupsRSE Census TractsPublic SchoolsBasinsFor more information, please see the 2021 Tree Canopy Assessment.
Mobile map packages are available for the following nine Kansas federal reservoirs considered for study in this project:Cheney ReservoirClinton LakeEl Dorado LakeHillsdale LakeMarion ReservoirMelvern LakeMilford LakePerry LakeTuttle Creek Lake
The types, locations, and density of information used to prepare the Dakota County atlas are shown on this map. The Database Map serves as a guide to the precision of the other maps in the atlas. It shows where data are sparse or lacking and interpretation and extrapolation were required to prepare the maps.
This package contains a project specific geodatabase and map (.mxd) for Level I Master Plan projects. For directions on using this file, see the GIS Standards Technical Memorandum on the Standards Page.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)
**When using the GIS data included in these map packages, please cite all of the following:
Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457
Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018
OVERVIEW OF CONTENTS
This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:
For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."
LICENSES
Code: MIT year: 2019
Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton
CONTACT
Andrew Gillreath-Brown, PhD Candidate, RPA
Department of Anthropology, Washington State University
andrew.brown1234@gmail.com – Email
andrewgillreathbrown.wordpress.com – Web
Web maps are available for the following nine Kansas federal reservoirs considered for study in this project:Cheney ReservoirClinton LakeEl Dorado LakeHillsdale LakeMarion ReservoirMelvern LakeMilford LakePerry LakeTuttle Creek Lake
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 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.
R package 'alm' : R code and associated shiny application dedicated to the automated mapping of landscapes. The package 'alm' allows users to select and combine layers of geographical information (shapefiles) to map the land covers of a specified buffer or set of buffers.
Virginia Department of Transportation 2025 Quarter One Linear Referencing SystemVDOT 25.1 LRS Release Map PackagePackage will be downloaded to your local 'Downloads' folder by default. Map package as downloaded is compressed. In ArcGIS Pro, browse to the Map Package in a local folder, and select 'Add and Open'.