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287 results for “GIS”
ArcGIS Map Packages and GIS Data for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al. (2019)
<p><strong>ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)</strong></p> <p>**When using the GIS data included in these map packages, please cite all of the following:</p> <blockquote> <p>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. <a href="http://doi.org/10.1371/journal.pone.0220457">http://doi.org/10.1371/journal.pone.0220457</a></p> <p>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. <a href="https://doi.org/10.5281/zenodo.2572018">https://doi.org/10.5281/zenodo.2572018</a></p> </blockquote> <p><strong>OVERVIEW OF CONTENTS</strong></p> <p>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:</p> <ul> <li>Raw DEM and Soils data <ul> <li>Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the <a href="https://viewer.nationalmap.gov/basic/">National Elevation Dataset</a>) <ul> <li><strong>DEM_Individual_Tiles</strong>: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.</li> <li><strong>DEMs_Merged</strong>: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM. </li> </ul> </li> <li> Soils Data (Map services and data available from <a href="https://data.nal.usda.gov/dataset/natural-resources-conservation-service-web-soil-survey">Natural Resources Conservation Service Web Soil Survey</a>, U.S. Department of Agriculture) <ul> <li><strong>Animas-Dolores_Area_Soils</strong>: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).</li> <li><strong>Cortez_Area_Soils</strong>: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).</li> </ul> </li> </ul> </li> <li>ArcGIS Map Packages <ul> <li><strong>Goodman_Watershed_Full_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).</li> <li><strong>Goodman_Watershed_Mesa-Only_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.</li> <li><strong>Crow_Canyon_Watershed_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).</li> <li><strong>Coffey_Watershed_SMPM_Analysis</strong>: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).</li> </ul> </li> </ul> <p>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."</p> <p><strong>LICENSES</strong></p> <p>Code: <a href="http://opensource.org/licenses/MIT">MIT</a> year: 2019 <br> Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton</p> <p><strong>CONTACT</strong></p> <p><strong>Andrew Gillreath-Brown, PhD Candidate, RPA</strong><br> <a href="https://anthro.wsu.edu/">Department of Anthropology</a>, Washington State University<br> <a href="mailto:andrew.brown1234@gmail.com">andrew.brown1234@gmail.com</a> – Email<br> <a href="https://andrewgillreathbrown.wordpress.com/">andrewgillreathbrown.wordpress.com</a> – Web</p>
Historical GIS and Guidebooks: Czechoslovak Tourist Attractions
<p>The following dataset of geolocated travel guide toponyms was compiled in the process of a research project <em>Historical GIS and Guidebooks: A Scalable Reading of Czechoslovak Tourist Attractions </em>(Bechmann Pedersen & Johansson, forthcoming) in which we performed a scalable reading of three travel guides of the former Czechoslovak lands as they were cirka 1959. We used a specialized, open-sourced tool <a href="https://github.com/MatJohaDH/citadel">CITADEL</a> created for this project, which in itself relies on open-sourced data from GeoNames and WikiData.</p> <p> </p> <p> </p> <p>Our primary sources were the following three travel guides:</p> <ul> <li>Čedok/Nagel, 1959, <em>Czechoslovakia</em></li> <li>Čedok, 1928 <em>Guide to the Czechoslovak Republic</em></li> <li>Baedker, 1905 <em>Austria–Hungary including Dalmatia and Bosnia</em></li> </ul> <p>All files are tab separated values (.tsv) files with utf-8 encoding.</p> <ol> <li>Three lists of positions with associated toponyms</li> <li>Two lists of clusters</li> </ol> <p>There are three files of the first type:</p> <p>CITADEL_1905Baedeker_toponyms.tsv<br> CITADEL_1928Cedok_toponyms.tsv<br> CITADEL_1959Nagel_toponyms.tsv</p> Columns for toponym files <table><tbody><tr> <th>Column</th> <th>Explanation</th> </tr> </tbody><tbody> <tr> <td>Toponym_first_used</td> <td>First toponym recorded in the database that is linked to the position</td> </tr> <tr> <td>Toponym_added</td> <td>The toponym as spellled in the travel guide</td> </tr> <tr> <td>Source</td> <td>A shorthand used to identify the travel guide</td> </tr> <tr> <td>PositionID</td> <td>The unique identifier of a position, using the GeoNames or WikiData identifiers where applicable.</td> </tr> <tr> <td>Longitude</td> <td>-</td> </tr> <tr> <td>Latitude</td> <td>-</td> </tr> <tr> <td>Year</td> <td>The year of the travel guide</td> </tr> <tr> <td>Weight</td> <td>The weight reflects the number of entries the toponym has in the index. Nagel1928 does not use this convention, and the weight is instead based on the relative page count.</td> </tr> </tbody> </table> <p> </p> <p>There are two files of the second type:</p> <p>CITADEL_1905,1928,1959_4km_clusters.tsv<br> CITADEL_1928,1959_4km_clusters.tsv</p> Columns for the cluster files <table><tbody><tr> <th>Column</th> <th>Explanation</th> </tr> </tbody><tbody> <tr> <td>years</td> <td>The years represented in the cluster</td> </tr> <tr> <td>Latitude</td> <td>-</td> </tr> <tr> <td>Longitude</td> <td>-</td> </tr> <tr> <td>cnt_points</td> <td> <p>The number of points represented in the cluster</p> </td> </tr> <tr> <td>cnt_toponyms</td> <td>The number of toponyms represented in the cluster</td> </tr> <tr> <td>cnt_toponyms_<source></td> <td>The number of toponyms from <source> represented in the cluster</td> </tr> </tbody> </table>
GIS Shapefiles for In Situ Geologic Map based on PMars 2020 Perseverance Rover Observations
<p>These are shapefiles for in situ geologic maps illustrated in Crumpler et al., 2023. n Situ Geologic Context Mapping Transect on the Floor of Jezero Crater from Mars 2020 Perseverance Rover Observations. Journal of Geophysical Research-Planets, Mars 2020 Results Special Collection</p>
DEMIX GIS Database Version 2
<p>This database supports the work of the Digital Elevation Model Intercomparison eXperiment (DEMIX) working group (Strobl and others, 2021; Guth and others, 2021; Bielski and others, 2023, 2024). The two files have the database in CSV format, and a metadata file describing the contents of each field in the database.</p> <p>To understand the use of the database, see the prepint (Bielski and others, 2023).</p> <p>Changes to version 2 which is the only version you should use:</p> <p>1. Added 2 new areas, Stateline and Canary Islands East which should have minimal differences between the DSM and the DTM and no significant changes over the last 20 years.</p> <p>2. Added the country to the database</p> <p>3. Added a number of areas in France</p> <p>4. Added some additional tiles for a few areas</p> <p>5. Total number of tiles almost doubled</p> <p>6. Now using GDAL to compute the datum shift, horizontal and vertical, for USGS 3DEP</p> <p>7. Fixed some anomalies computing pixel-is-area DEMs</p> <p>8. Recomputed all the reference data and the version 1.0 GIS database (Guth, 2022)</p> <p>9. New file naming conventions</p> <p><strong>References:</strong></p> <p>Bielski, C.; López-Vázquez, C.; Guth. P.L.; Grohmann, C.H. and the TMSG DEMIX Working Group, 2023. DEMIX Wine Contest Method Ranks ALOS AW3D30, COPDEM, and FABDEM as Top 1” Global DEMs: <a href="https://arxiv.org/pdf/2302.08425.pdf"> https://arxiv.org/pdf/2302.08425.pdf</a></p> <p><span>Bielski, C.; López-Vázquez, C.; Grohmann, C.H.; Guth. P.L.; Hawker, L.; Gesch, D.; Trevisani, S.; Herrera-Cruz, V.; Riazanoff, S.; Corseaux, A.; Reuter, H.; Strobl, P., 2024. Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography. IEEE Transactions on Geoscience & Remote Sensing. </span> <span> vol. 62, pp. 1-22, 2024, Art no. 4503922, </span> <a href="https://doi.org/10.1109/TGRS.2024.3368015"> <span>https://doi.org/10.1109/TGRS.2024.3368015</span></a></p> <p>Guth, P.L.; Van Niekerk, A.; Grohmann, C.H.; Muller, J.-P.; Hawker, L.; Florinsky, I.V.; Gesch, D.; Reuter, H.I.; Herrera-Cruz, V.; Riazanoff, S.; López-Vázquez, C.; Carabajal, C.C.; Albinet, C.; Strobl, P. Digital Elevation Models: Terminology and Definitions. Remote Sens. 2021, 13, 3581. <a href="https://doi.org/10.3390/rs13183581">https://doi.org/10.3390/rs13183581</a></p> <p>Strobl, P.A.; Bielski, C.; Guth, P.L.; Grohmann, C.H.; Muller, J.P.; López-Vázquez, C.; Gesch, D.B.; Amatulli, G.; Riazanoff, S.; Carabajal, C. The Digital Elevation Model Intercomparison eXperiment DEMIX, a community based approach at global DEM benchmarking. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2021, XLIII-B4-2021, 395–400. <a href="https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-395-2021">https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-395-2021</a></p>
Confini di Lunigiana - GIS
<p>GIS_Lunigiana_confini contiene i GIS del volume E. Salvatori, <i>Il fegato del vescovo. Studi di confine sui confini della Lunigiana</i>, Pisa, Pisa University Press, in corso di stampa</p>
Little Tennessee River Riparian Buffer change GIS data: 1998 - 2015
Using high resolution orthoimagery, riparian conditions between 1998 and 2015 were mapped and quantified in the rural upper Little Tennessee River basin in Macon County, North Carolina. Low elevation valley streams in residential areas were targeted, excluding stream segments on U.S. Forest Service (USFS) lands. Impoundments and streams within existing urban centers were also excluded from GIS analysis. Tributary streams were included if they were National Hydrography Dataset (NHD) mapped streams and if they met the study criteria, i.e. low-elevation residential valley streams outside existing urban areas and USFS lands. Due to the size of the watershed and time constraints, only the mainstem Little Tennessee and a portion of its tributary streams could be mapped. A total of 658 km (including both banks) of streams in the study area were mapped and classified. All classifications were made by one interpreter between June 2018 and August 2018. The GIS files are are in .zip archives labeled by imagery year (1998 and 2015). The 1998 GIS files are mislabeled '1999' which was corrected during analysis using R. The code used for analysis is provided in R markdown files.
Site environmental, climate, water levels and temperatures, vegetation cover, and GIS change detection for assessing permafrost change in fens on the Tanana Flats, central Alaska
This data package provides data used to assess the roles of climate extremes, ecological succession, and hydrology in repeated permafrost aggradation and degradation in fens on the Tanana Flats, central Alaska. The package provides data on site environmental information, Fairbanks climate, vegetation cover, water levels and temperatures, as well as GIS files for fen change detection. The Site data include information on observers, locations, geomorphology, hydrology, soils, vegetation, and disturbance. The table has numerous fields that uses coding for class characteristics and these codes are described in the metadata as well as compiled in the ELS_Arctic_Boreal_Site_Soil_Veg_Code_Sheet_2020.docx. Alaska Climate records for Fairbanks (UAF Experiment Station) from 1904 to 2019 were acquired from the National Oceanic and Atmospheric Administration (https://www.ncdc.noaa.gov/cdo-web/). Additional data were obtained for the Nenana station (about 70 km southwest of Fairbanks), to fill in small data gaps (particularly precipitation/snow depth ruler measurements) in the Fairbanks record. We attributed the data with fields for summer (May-September) and winter periods (November-March) and hydrologic year (October-September) and calculated mean air temperature, precipitation, and snow depth by seasonal period (average of daily values) and year. The broad summer and winter periods were of interest because warmer and wetter summers increase soil heat input and warmer and snowier winters reduce soil heat loss. Fen hydrology data include information on fen water level/pressure and temperatures collected every two hours at seven sites within fens from 2011 to 2014. Vegetation composition and cover of fens, scrub, and forests was sampled to assess effects of thermokarst on vegetation change. Plant cover was determined by point-sampling at 100 points (including repetitive “hits” for all layers) distributed along 5 equally spaced rows (4-m long, 20 points per row) across the 10-m l
LAGOS-NE-GIS v1.0: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 2013-1925
This data package, LAGOS-NE-GIS v1.0, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes. (2) LAGOS-NE-GEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO v1.087.1: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NE-GEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE GIS v1.0 module includes GIS datasets for: lake polygons and their hydrologic classification; wetland polygons and their classification; streams as a line coverage and their classification by stream order; the zones used for this study (state and county; hydrologic units [at the 4, 8 and 12 scales]); and, lake watersheds (IWS). We also include boundaries of U.S. stat
GIS point locations for Forest Soils Laboratory, SALRM research sites: 1967 - 2000
This is a collection of study site GIS locations for the Forest Soils Lab research locations. There are sites from within BCEF and CPCRW.
Caribou Poker Creek Research Watershed GIS Data: Steam Lines
Stream lines generated for 63,360 Digital Line Graphics (DLG) in and near our research areas in the Caribou Poker Creek Research Watershed. Geospatial_Data_Presentation_Form: vector digital data.
Caribou Poker Creek Research Watershed GIS Data: Spot 5 Imagery
Spot 5 pan-sharpened satellite image in the North Fairbanks area of the Tanana Valley, Alaska. This image was acquired and processed as part of the "Vegetation and Community Mapping of the Tanana Valley" project, conducted cooperatively by the State of Alaska Department of Natural Resources, Division of Forestry and Tanana Chiefs Conference. Originator: State of Alaska, Dept. of Nat. Resources, Division of Forestry. Publication_Date: 3/21/05. Geospatial_Data_Presentation_Form: remote-sensing image.
Caribou Poker Creek Research Watershed GIS Data: Permafrost
Permafrost distribution areas that have been mapped throughout the Caribou - Poker Creek Research Watershed are presented in ArcGIS format. Geospatial_Data_Presentation_Form: vector digital data.
Caribou Poker Creek Research Watershed GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: cpcrw_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
Caribou Poker Creek Research Watershed GIS Data: Reasearch Area Boundary (NAD83)
This is the perimeter boundary line around the Caribou - Poker Creek Research Watershed that has been packaged into an ArcGIS file. Geospatial_Data_Presentation_Form: vector digital data.
Bonanza Creek LTER GIS Data: Core Research Plot Locations
This data package contains the point locations for the core research plots maintained by the Bonanza Creek LTER program. Geospatial_Data_Presentation_Form: vector digital data.
Bonanza Creek Experimental Forest GIS Data: Stream Lines
This data package contains the streams lines generated for 63,360 Digital Line Grafics (DLG) in and near our research areas in the Bonanza Creek Experimental forest. Geospatial_Data_Presentation_Form: vector digital data.
Bonanza Creek Experimental Forest GIS Data: Spot 5 Imagery
Spot 5 pan-sharpened satellite image in the Standard Creek area of the Tanana Valley, Alaska. This image was acquired and processed as part of the "Vegetation and Community Mapping of the Tanana Valley" project, conducted cooperatively by the State of Alaska Department of Natural Resources, Division of Forestry and Tanana Chiefs Conference. Originator: State of Alaska, Dept. of Nat. Resources, Division of Forestry. Publication_Date: 3/21/05. Geospatial_Data_Presentation_Form: remote-sensing image.
Bonanza Creek Experimental Forest GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: bcef_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
Bonanza Creek Experimental Forest GIS Data: Reasearch Area Boundary (NAD83)
This data package contains the area boundary line for the Bonanza Creek Experimental forest in ArcGIS format. Geospatial_Data_Presentation_Form: vector digital data.
Bonanza Creek LTER GIS Data: Roads and Trails within 100km of Fairbanks
This data package contains roads and trails for the Bonanza Creek Experimental Forest in ArcGIS format. Geospatial_Data_Presentation_Form: vector digital data.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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International Brain Laboratory public data
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OpenNeuro
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