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85 results for “Georeferencing”
ES: Mapa georreferenciado de las zonas básicas de salud de PAIS VASCO. Año 2017. España. || EN: Georeferenced map of primary care area of reference in PAIS VASCO. Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p>
ES: Mapa georreferenciado de las zonas básicas de salud de EXTREMADURA. Año 2017. España. || EN: Georeferenced map of primary care area of reference in EXTREMADURA . Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p>
ES: Mapa georreferenciado de las zonas básicas de salud de NAVARRA. Año 2017. España. || EN: Georeferenced map of primary care area of reference in NAVARRA. Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p>
ES: Mapa georreferenciado de las zonas básicas de salud de MURCIA. Año 2017. España. || EN: Georeferenced map of primary care area of reference in MURCIA . Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p>
ES: Mapa georreferenciado de las zonas básicas de salud de LA RIOJA. Año 2017. España. || EN: Georeferenced map of primary care area of reference in LA RIOJA. Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p> <p> </p>
ES: Mapa georreferenciado de las zonas básicas de salud de VALENCIA . Año 2017. España. || EN: Georeferenced map of primary care area of reference in VALENCIA . Year 2017. Spain.
<p>ES: Información geográfica y mapas relativos a las zonas básicas de salud de la Comunidad Autónoma [CCAA], España. Las zonas básicas de salud se refieren a las áreas de referencia de atención primaria. Cada zona básica de salud está determinada por la existencia de un Equipo de Atención Primaria, que asiste a la población de referencia de su zona desde un Centro de Salud de<br> Atención primaria. Los mapas están projectados en el sistema de referencia de coordenadas geográficas.</p> <p>|| EN: Geographical information and maps of the primary care settings of the Autonomous Community [CCAA], Spain. The primary care areas of reference are configured following the availability of a Primary Care Team (health professionals) assisting reference populations' health needs from a primary care centre within<br> the area. Maps are projected in the geographic coordinates reference system.</p> <p> </p>
Georeferenced birthplaces of identified DTA authors
<p>The dataset provides geo-coordinates of the birthplaces of more than 900 authors of the German Text Archive. Birthplaces were identified using the services of the German National Library (DNB), but also other sources such as Wikipedia, and then geocoordinated. </p> <p>The dataset was created in the study by Lameli (2018). It is requested to refer to this study when using the dataset:</p> <p>Lameli, Alfred. 2018. The replacement of diminutive suffixes in the New High German Period – A time series analysis in word formation. In: Journal of Historical Linguistics 8(2), 273–316. </p>
Georeferenced and cropped "Half Inch" (1:126,720) maps of Burma (colonial period)
<p>Georeferenced (to WGS1984) and cropped set of about 555 historic maps of Burma at a scale of 1 inch per two miles (1:126,720) covering most of the country. Those topographic maps, originally produced and published by the Great Trigonometrical Survey of India between 1878 and 1949, have been scanned and shared with the public as "Old Survey Of India Maps” Community under a CC BY 4.0 International Licence.</p> <p>Each of the map sheet scans was georeferenced using the Latitude-Longitude corner coordinates in Everest 1830 projection. Those map sheets were cropped, keeping only the map area - to allow a seamless mosaic without the mapframe overlapping adjacent map sheets when several map sheets are put together in a GIS. Those cropped map sheets were projected from Everest 1830 to WGS1984 (EPSG:4326) - standard GPS - projection to make them easier to use and combine with other GIS data.</p> <p>Many grid cells in this dataset are covered by 2 versions of map sheets - those with hill shade and only lat-lon grid and those without hill shade and featuring a LCC map grid. </p> <p>Those map sheets can be loaded directly in any GIS such as QGIS or ESRI ArcGIS.</p> <ul> <li>The mm_HI_JBv2024_epsg4326 folder contains the cropped end georeferenced map sheets in jpg-format as well as accompagning georeference and metadata incl.<br> <ul> <li>The mm_HI_JBv2024_epsg4326_kmlLinks contains a KML file for each map sheet facilitating their easy use in Google Earth byt linking them the georeferenced map sheet file located in the mm_HI_JBv2024_epsg4326 folder. </li> <li>The mm_historicHI_EPSG4326.gdb contains three ESRI mosaic datasets to easily load all mapsheets, only mapheets with hillshading and lat-lon grid and only "regular" mapsheets without hillshading and LCC grid into ArcGIS</li> </ul> </li> <li>The mm_HI_JBv2024_scanMaps folder contains the uncropped original map scans (renamed though) in jpg-format.</li> <li>The mm_historicTopoHI_JBv2024 is a masterlist cataloguing all map sheets for easier use and matching them with the original source files as shared via the "Old Survey Of India Maps” Community (e.g. to identify new mapsheets should new maps be released)</li> </ul> <p>All georeferenced map scans are based on maps shared as part of the "Old Survey Of India Maps” via Zenodo. Links to each file can be found in the above mentined excel file and most can be also accessed through the zenodo repository below.</p> <ul> <li><a href="../records/7894128">https://zenodo.org/records/8040798</a> (128k Maps of South Asia, version 4, Published May 3, 2023)</li> </ul> <p>The file naming convention is to first give the <strong><em>number</em></strong> of the 4 degree x 4 degree block followed by the <strong><em>letter (A to P)</em></strong> of the sixteen 1 degree x 1 degree blocks in each 4 degree block eg. 38 D, and this is followed by the <strong>cardinal direction letters</strong> (NE, NW, SE, SW) to indicate the 30x30 minutes sized map position in the 1 degree block. </p> <p>This <strong><em>Number - Letter - Cardinal direction letter </em></strong>designation is followed by the <strong>year of the edition, </strong>followed by the <strong>map series type</strong> either HI-hs (hillshaded) or HI-reg (regular), followed by the <strong><em>map sheet title/name</em></strong>.</p> <p>The original files as shared as part of the "<a href="https://zenodo.org/records/11661876">Old Survey Of India Maps</a>” have been renamed to further standardize the file naming, sometimes correcting them and to make them unique in the case several editions of the same map sheet were available.</p> <p>Lineage: This version (1.01, Upload 2024-08-20) has some file attributes fixed.</p>
Metadata and georeferencing of the publications in the academic journal 'L'Espace Géographique' (1972-2020)
<p>The zip file contains two tab-separated files (.tsv):</p> <ul> <li>"netscity_espacegeo.tsv"</li> </ul> <p>29 columns, 1645 lines</p> <p>It contains the metadata of 1451 articles and "positions de recherche" issued in the academic journal 'L'Espace Géographique' between 1972 and 2020. The affiliations of the authors have been geocoded using the web application NETSCITY. This dataset combines the result of the geocoding process (geographical coordinates) for each publication with geographical enrichments (urban areas and countries from which the publications have been authored). Additionnal information are available: titles of the publications, sections of the journal in which the publications were published, publication year, authors names, affiliations.</p> <ul> <li>"metadata.tsv"</li> </ul> <p>7 columns, 29 lines</p> <p>It contains a description for each variable of the dataset: "netscity_espacegeo.tsv"</p> <p> </p>
Georeferenced Spanish Soil Profile Database (SODES)
<p>The Georeferenced Spanish Soil Profile Database (SODES) contains soil information and data values for 1683 georereferenced soil profiles, compiled from an extensive bibliographic review. SODES allows the characterisation of the different peninsular Spanish soil types and is a suitable tool for assessments and decision making purposes dealing with different issues.</p>
ULS and UAV-MS Directly Georeferenced Point Clouds of the River Teme
<p>Directly Georeferenced Point Clouds of the River Teme for PhD research, provided as supporting information to methods described. These are unfiltered point clouds of a vegetated river reach in the UK, given in WGS UTM_30N CRS. UAV-MS are SfM derived point clouds and ULS UAV laser scanning based point clouds.</p>
Georeferenced literature records of annelid species along the Salento Peninsula
<p>This dataset includes information collected from published papers on georeferenced annelid distribution along the Salento Peninsula. The dataset includes information on 1815 records with information on species, location, including latitude and longitude in decimal degrees, type of sediment, depth and sampling dates.</p>
Georeferenced IFC files exported within the GeoBIM benchmark 2019 - Task 2
<p>Result of the georeferencing test performed within the Task 2 - georeferencing IFC of the GeoBIM benchmark 2019, funded as a Scientific Initiative 2019 by the International Society of Photogrammetry and Remote Sensing (ISPRS) and co-funded by the European association for Spatial Data Research (EuroSDR).</p> <p>Full details and additional resources about the project are available in the project website: https://3d.bk.tudelft.nl/projects/geobim-benchmark/</p> <p>The dataset results from the collaboration of the authors with all the participants to the benchmark, listed at https://3d.bk.tudelft.nl/projects/geobim-benchmark/participants.html</p>
Georeferenced datas of mean income of North-West Lausanne villages.
<p>Georeferenced datas of mean income of North-West Lausanne villages.</p>
GeoDAR: Georeferenced global Dams And Reservoirs dataset for bridging attributes and geolocations
<p>Documented March 19, 2023</p> <p><strong>!!NEW!!!</strong></p> <p><strong>GeoDAR reservoirs were registered to the drainage network! </strong>Please see the auxiliary data "<a href="../records/7750736">GeoDAR-TopoCat</a>" at <a href="../records/7750736">https://zenodo.org/records/7750736</a>. "GeoDAR-TopoCat" contains the <strong>drainage topology</strong> (reaches and upstream/downstream relationships) and catchment boundary for each reservoir in GeoDAR, based on the algorithm used for Lake-TopoCat (doi:10.5194/essd-15-3483-2023).</p> <p> </p> <p>Documented April 1, 2022</p> <p><strong>Citation</strong></p> <p>Wang, J., Walter, B. A., Yao, F., Song, C., Ding, M., Maroof, A. S., Zhu, J., Fan, C., McAlister, J. M., Sikder, M. S., Sheng, Y., Allen, G. H., Crétaux, J.-F., and Wada, Y.: GeoDAR: georeferenced global dams and reservoirs database for bridging attributes and geolocations. Earth System Science Data, 14, 1869–1899, 2022, https://doi.org/10.5194/essd-14-1869-2022.</p> <p>Please cite the reference above (which was fully peer-reviewed), NOT the preprint version. Thank you.</p> <p> </p> <p><strong>Contact</strong></p> <p>Dr. Jida Wang, jidawang@ksu.edu, gdbruins@ucla.edu</p> <p> </p> <p><strong>Data description and components</strong></p> <p>Data folder “<strong>GeoDAR_v10_v11</strong>” (.zip) contains two consecutive, peer-reviewed versions (<strong>v1.0</strong> and <strong>v1.1</strong>) of the Georeferenced global Dams And Reservoirs (GeoDAR) dataset:</p> <ul> <li><strong>GeoDAR_v10_dams</strong> (in both shapefile format and the comma-separated values (csv) format): GeoDAR version 1.0, including 22,560 dam points georeferenced based on the World Register of Dams (WRD), the International Commission on Large Dams (ICOLD; <a href="https://www.icold-cigb.org">https://www.icold-cigb.org</a>; last access on March 13th, 2019).</li> <li><strong>GeoDAR_v11_dams</strong> (in both shapefile and csv): GeoDAR version 1.1 dam points, including 24,783 dams which harmonized GeoDAR_v10_dams and the Global Reservoir and Dam Database (GRanD) v1.3 (Lehner et al., 2011).</li> <li><strong>GeoDAR_v11_reservoirs</strong> (in shapefile): GeoDAR version 1.1 reservoirs, including 21,515 reservoir polygons retrieved by associating GeoDAR_v11_dams with GRanD v1.3 reservoirs, HydroLAKES v1.0 (Messager et al., 2016), and the UCLA Circa 2015 Lake Inventory (Sheng et al., 2016). The reservoir retrieval follows a one-to-one relationship between dams and reservoirs.</li> </ul> <p>As by-products of GeoDAR harmonization, folder “GeoDAR_v10_v11” also contains:</p> <ul> <li><strong>GRanD_v13_issues.csv</strong>: This file contains the original records of all 7,320 dam points in GRanD v1.3, with 94 of them marked by our identified issues and suggested corrections. These 94 records are placed at the beginning of this table. They include 89 records showing possible georeferencing and/or attribute errors, and another 5 records documented as subsumed or replaced. Our added fields start from column BG and include: <ul> <li>“Issue”: main issue(s) of this record</li> <li>“Description”: more detailed explanation of the issue</li> <li>“Lat_corrected”: suggested correction for latitude (if any) in decimal degree</li> <li>“Lon_corrected”: suggested correction for longitude (if any) in decimal degree</li> <li>“Correction_source”: correction source(s)</li> <li>“Harmonized”: whether this GRanD dam was harmonized in GeoDAR v1.1 and the reason.</li> </ul> </li> <li><strong>Wada_et_al_2017_harmonized.csv</strong>: This csv file contains the original records of all 139 georeferenced large dams/reservoirs in Wada et al. (2017; doi:10.1007/s10712-016-9399-6), with our revised storage capacities and spatial coordinates for data harmonization. Our added fields start from column E and include: <ul> <li>Revised_capacity_km3: Our revised reservoir storage capacity in cubic kilometers used for harmonization</li> <li>Revised_lat: Revised latitude in decimal degree</li> <li>Revised_lon: Revised longitude in decimal degree</li> <li>Verification_notes: Description of the issues, verification sources, and other information used for harmonization.</li> </ul> </li> </ul> <p> </p> <p><strong>Attribute description</strong></p> <table> <tbody> <tr> <td> <p><strong>Attribute</strong></p> </td> <td> <p><strong>Description and values</strong></p> </td> </tr> <tr> <td> <p>v1.0 dams (file name: GeoDAR_v10_dams; format: comma-separated values (csv) and point shapefile)</p> </td> </tr> <tr> <td> <p><em>id_v10</em></p> </td> <td> <p>Dam ID for GeoDAR version 1.0 (type: integer). Note this is not the same as the International Code in ICOLD WRD but is linked to the International Code via encryption.</p> </td> </tr> <tr> <td> <p><em>lat</em></p> </td> <td> <p>Latitude of the dam point in decimal degree (type: float) based on datum World Geodetic System (WGS) 1984.</p> </td> </tr> <tr> <td> <p><em>lon </em></p> </td> <td> <p>Longitude of the dam point in decimal degree (type: float) on WGS 1984.</p> </td> </tr> <tr> <td> <p><em>geo_mtd</em></p> </td> <td> <p>Georeferencing method (type: text). Unique values include “geo-matching CanVec”, “geo-matching LRD”, “geo-matching MARS”, “geo-matching NID”, “geo-matching ODC”, “geo-matching ODM”, “geo-matching RSB”, “geocoding (Google Maps)”, and “Wada et al. (2017)”. Refer to Table 2 in Wang et al. (2022) for abbreviations.</p> </td> </tr> <tr> <td> <p><em>qa_rank</em></p> </td> <td> <p>Quality assurance (QA) ranking (type: text). Unique values include “M1”, “M2”, “M3”, “C1”, “C2”, “C3”, “C4”, and “C5”. The QA ranking provides a general measure for our georeferencing quality. Refer to Supplementary Tables S1 and S3 in Wang et al. (2022) for more explanation.</p> </td> </tr> <tr> <td> <p><em>rv_mcm</em></p> </td> <td> <p>Reservoir storage capacity in million cubic meters (type: float). Values are only available for large dams in Wada et al. (2017). Capacity values of other WRD records are not released due to ICOLD’s proprietary restriction. Also see Table S4 in Wang et al. (2022).</p> </td> </tr> <tr> <td> <p><em>val_scn</em></p> </td> <td> <p>Validation result (type: text). Unique values include “correct”, “register”, “mismatch”, “misplacement”, and “Google Maps”. Refer to Table 4 in Wang et al. (2022) for explanation.</p> </td> </tr> <tr> <td> <p><em>val_src</em></p> </td> <td> <p>Primary validation source (type: text). Values include “CanVec”, “Google Maps”, “JDF”, “LRD”, “MARS”, “NID”, “NPCGIS”, “NRLD”, “ODC”, “ODM”, “RSB”, and “Wada et al. (2017)”. Refer to Table 2 in Wang et al. (2022) for abbreviations.</p> </td> </tr> <tr> <td> <p><em>qc</em></p> </td> <td> <p>Roles and name initials of co-authors/participants during data quality control (QC) and validation. Name initials are given to each assigned dam or region and are listed generally in chronological order for each role. Collation and harmonization of large dams in Wada et al. (2017) (see Table S4 in Wang et al. (2022)) were performed by JW, and this information is not repeated in the <em>qc</em> attribute for a reduced file size. Although we tried to track the name initials thoroughly, the lists may not be always exhaustive, and other undocumented adjustments and corrections were most likely performed by JW.</p> </td> </tr> <tr> <td> <p>v1.1 dams (file name: GeoDAR_v11_dams; format: comma-separated values (csv) and point shapefile)</p> </td> </tr> <tr> <td> <p><em>id_v11</em></p> </td> <td> <p>Dam ID for GeoDAR version 1.1 (type: integer). Note this is not the same as the International Code in ICOLD WRD but is linked to the International Code via encryption.</p> </td> </tr> <tr> <td> <p><em>id_v10</em></p> </td> <td> <p>v1.0 ID of this dam/reservoir (as in <em>id_v10</em>) if it is also included in v1.0 (type: integer).</p> </td> </tr> <tr> <td> <p><em>id_grd_v13</em></p> </td> <td> <p>GRanD ID of this dam if also included in GRanD v1.3 (type: integer).</p> </td> </tr> <tr> <td> <p><em>lat</em></p> </td> <td> <p>Latitude of the dam point in decimal degree (type: float) on WGS 1984. Value may be different from that in v1.0.</p> </td> </tr> <tr> <td> <p><em>lon </em></p> </td> <td> <p>Longitude of the dam point in decimal degree (type: float) on WGS 1984. Value may be different from that in v1.0.</p> </td> </tr> <tr> <td> <p><em>geo_mtd</em></p> </td> <td> <p>Same as the value of <em>geo_mtd</em> in v1.0 if this dam is included in v1.0.</p> </td> </tr> <tr> <td> <p><em>qa_rank</em></p> </td> <td> <p>Same as the value of <em>qa_rank</em> in v1.0 if this dam is included in v1.0.</p> </td> </tr> <tr> <td> <p><em>val_scn</em></p> </td> <td> <p>Same as the value of <em>val_scn</em> in v1.0 if this dam is included in v1.0.</p> </td> </tr> <tr> <td> <p><em>val_src</em></p> </td> <td> <p>Same as the value of <em>val_src</em> in v1.0 if this dam is included in v1.0.</p> </td> </tr> <tr> <td> <p><em>rv_mcm_v10</em></p> </td> <td> <p>Same as the value of <em>rv_mcm </em>in v1.0 if this dam is included in v1.0.</p> </td> </tr> <tr> <td> <p><em>rv_mcm_v11</em></p> </td> <td> <p>Reservoir storage capacity in million cubic meters (type: float). Due to ICOLD’s proprietary restriction, provided values are limited to dams in Wada et al. (2017) and GRanD v1.3. If a dam is in both Wada et al. (2017) and GRanD v1.3, the value from the latter (if valid) takes precedence.</p> </td> </tr> <tr> <td> <p><em>har_src</em></p> </td> <td> <p>Source(s) to harmonize the dam points. Unique values include “GeoDAR v1.0 alone”, “GRanD v1.3 and GeoDAR 1.0”, “GRanD v1.3 and other ICOLD”, and “GRanD v1.3 alone”. Refer to Table 1 in Wang et al. (2022) for more details.</p> </td> </tr> <tr> <td> <p><em>pnt_src</em></p> </td> <td> <p>Source(s) of the dam point spatial coordinates. Unique values include “GeoDAR v1.0”, “original GRanD”, “adjusted GRanD” (meaning the original dam point location in GRanD has been adjusted to improve the accuracy), and “corrected GRanD” (meaning the original point in GRanD was misplaced and has been corrected). Also see Table S5 in Wang et al. (2022).</p> </td> </tr> <tr> <td> <p><em>qc</em></p> </td> <td> <p>Roles and name initials of co-authors/participants during data QC, validation, and other manual operations. Name initials are given to each assigned dam or region and are listed generally in chronological order for each role. Correction of GRanD (see Table S5 in Wang et al. (2022)) and reservoir polygon QC were performed by JW, and this information is not repeated in the <em>qc</em> attribute to reduce the file size. Although we tried to track the name initials thoroughly, the lists may not be always exhaustive, and other undocumented adjustments and corrections were most likely performed by JW.</p> </td> </tr> <tr> <td> <p>v1.1 reservoirs (file name: GeoDAR_v11_reservoirs; format: polygon shapefile)</p> </td> </tr> <tr> <td> <p><em>plg_src</em></p> </td> <td> <p>Source of the retrieved reservoir polygon (type: text). Unique values include “GRanD v1.3”, “HydroLAKES v1.0”, and “UCLA Circa 2015”. Refer to Table 1 in Wang et al. (2022) for more details.</p> </td> </tr> <tr> <td> <p><em>plg_a_km2</em></p> </td> <td> <p>Area of the retrieved reservoir polygon in square kilometres (calculated based on the cylindrical equal area projection on datum WGS 1984).</p> </td> </tr> <tr> <td> <p><em>All other attributes in v1.1 dams.</em></p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Data and code availability</strong></p> <p>GeoDAR v1.0 (dam points) and v1.1 (both dam points and reservoir polygons) are available under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license (<a href="https://creativecommons.org/licenses/by/4.0">https://creativecommons.org/licenses/by/4.0</a>). </p> <p>Any user who would like to link GeoDAR features to the proprietary WRD attributes the user has purchased in advance from ICOLD should contact the corresponding author JW.</p> <p>Python scripts for geo-matching, geocoding, and reservoir assignment are available at <a href="https://github.com/surf-hydro/georeferencing-ICOLD-dams-and-reservoirs">https://github.com/surf-hydro/georeferencing-ICOLD-dams-and-reservoirs</a>. We request users who adapt or use the scripts to cite Wang et al. (2022).</p> <p>We also request users to cite Wang et al. (2022) if they use our identified issues or suggested corrections for GRanD v1.3 (as provided in “GRanD_v13_issues.csv”).</p> <p> </p> <p><strong>Disclaimer</strong></p> <p>GeoDAR v1.0 and v1.1 contain knowledge derived from ICOLD WRD (<a href="https://www.icold-cigb.org/GB/world_register/acknowledgements_wrd.asp">https://www.icold-cigb.org/GB/world_register/acknowledgements_wrd.asp</a>) but release no original values of the proprietary WRD attributes (except the storage capacities of a few large dams used to verify/correct Wada et al. (2017); see Table S4 in Wang et al. (2022)). The production and dissemination of GeoDAR abide by ICOLD’s legal policies (<a href="https://www.icold-cigb.org/GB/legal.asp">https://www.icold-cigb.org/GB/legal.asp</a>) and were approved by ICOLD’s Central Office.</p> <p>GeoDAR v1.0 represents an initial effort of georeferencing WRD at the global scale. The resultant dam distribution may be skewed towards regions where georeferencing sources are more abundant, and therefore, may not accurately reflect the distribution of all WRD records. The authors are not responsible for any consequence arising from this limitation.</p> <p>GeoDAR v1.1 absorbed most of the spatial features (i.e., dam point coordinates and reservoir polygons) in GRanD v1.3. To acknowledge the originality of GRanD, we request users to cite Lehner et al. (2011) if they only use the subset of GeoDAR v1.1 from GRanD alone. If the user adopts the spatial coordinates we corrected for GRanD (see “GRanD_v13_issues.csv”), we recommend users citing Wang et al. (2022) as well.</p> <p>The source of each spatial feature in GeoDAR v1.1 is specified in the attributes “har_src” and “pnt_src” for dam points and the attribute “plg_src” for reservoir polygons. For any questions about data citation, please contact the corresponding author JW.</p> <p>Authors of this paper claim no responsibility or liability for any consequences related to the use, citation, or dissemination of GeoDAR.</p> <p> </p> <p><strong>Other notes</strong></p> <p>We provide another auxiliary folder “<strong>GeoDAR_beta_peer_review</strong>” (.zip), which stores the versions of GeoDAR before the completion of peer review with ESSD. We here keep these earlier GeoDAR versions on file, but since improvements and corrections were made during the peer review process, we do NOT recommend any application of these earlier versions. Instead, please use the fully peer-reviewed versions in folder “<strong>GeoDAR_v10_v11</strong>”. </p> <p>Please also see the readme files in each of the folders. </p>
Reports about the tools for georeferencing IFC delivered within the GeoBIM benchmark 2019 - Task 2
<p>Answers delivered through the online forms, about the tests performed by participants within the Task 2 - georeferencing IFC files of the GeoBIM benchmark 2019, funded as a Scientific Initiative 2019 by the International Society of Photogrammetry and Remote Sensing (ISPRS) and co-funded by the European association for Spatial Data Research (EuroSDR).</p> <p>Full details and additional resources about the project are available in the project website: https://3d.bk.tudelft.nl/projects/geobim-benchmark/</p> <p>The dataset results from the collaboration of the authors with all the participants to the benchmark, listed at https://3d.bk.tudelft.nl/projects/geobim-benchmark/participants.html</p> <p>It is composed by 2 files:</p> <p>- the answers to the delivered online forms, organised in excel sheet;</p> <p>- the same answers organised in a more human-readable PDF, with reliable images and links.</p>
Digitization, Georeferencing, and Modelling of Regan and Hinze's Barringer Crater Study
<p>This is a digitized data set of Regan and Hinze's (1975) Gravity and Magnetic Survey of Meteor Crater, AZ, also known as Barringer Crater, AZ. This data is interpolated from figures within the paper pertaining to the Residual Bouguer Anomaly, Total Bouguer Anomaly, Regional Bouguer Anomaly, and Terrain Correction, as the paper's original data set could not be recovered. We georeferenced the station coordinates to latitude/longitude and Zone 12 UTM coordinates using a LiDAR DEM in order to provide an updated terrain correction for the data set.</p>
Georeferenced semi-quantitative data of the jellyfish Rhizostoma pulmo (Cnidaria: Scyphozoa) from 1810 to 2019 in the Mediterranean and Black Seas
Open the record for dataset details and reuse information.
Georeferencing organic matter measurements on the VCR/LTER 1998
This dataset resulted from a student research project by Heather Kerkering which combined and georeferenced data on organic matter concentrations from a variety of Virginia Coast Reserve LTER researchers.
Georeferenced drone thermal video and related data, recorded on 6 and 28 August 2019 in Siikaneva peatland
<p>Data files in Matlab .mat format.</p> <p>1) EC_and_timeaxes.mat: Eddy Covariance data covering the drone measurement periods, time axes for drone 1Hz sequences and EC data;</p> <p>2) T_fluctuation_corr.mat: Four georeferenced sequences of surface temperature fluctuation T'(x,y,z) derived from the four measured thermal videos;</p> <p>3) T_georef_orig.mat: Four georeferenced sequences of surface temperature T(x,y,z) corresponding to the four measured thermal videos;</p> <p>4) UTMgrid_anemometer_RGBpic.mat: UTM grid for the T'(x,y,z) and T(x,y,z) sequences, pixel coordinates of anemometer location, georeferenced UAV RGB image (with the same UTM grid as the thermal images).</p>
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