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5,312 results for “New Zealand”
Media Mentions of Elite New Zealand Athletes
<p>Provides data about every New Zealand athlete who has competed in the Olympic Games and the Commonwealth Games. The data was collected from the <a href="http://www.olympic.org.nz/">New Zealand Olympic Committee</a> website and combined with media mentions found within an archive of New Zealand media articles maintained by data science consultancy <a href="http://www.dotlovesdata.com">DOT loves data</a>.</p> <p>This dataset supports the conference paper, "Gender bias and the New Zealand media's reporting of elite athletes" (MathSport 2018).</p> <p>Includes the following variables:</p> <ul> <li>Athlete Name (athlete_name)</li> <li>Source URL (source_url)</li> <li>Gender (gender)</li> <li>Sport (sport)</li> <li>Birth Date (birthdate)</li> <li>Number of Elite Games Attended (n_games_attended)</li> <li>Number of Gold Medals Won (n_gold_medals)</li> <li>Number of Silver Medals Won (n_silver_medals)</li> <li>Number of Bronze Medals Won (n_bronze_medals)</li> <li>Total Number of Medals Won (n_medals)</li> <li>Number of Media Mentions (n_media_mentions)</li> </ul> <p>Note: the Sport variable is a variable-length list that is delimited by three spaces (" ")</p>
Map of Co-Seismic Landslides for the M 7.8 Kaikoura, New Zealand Earthquake
<p>Prepared by the Research Group on Earthquake Geology in Greece (http://eqgeogr.weebly.com/)</p> <p>Version 2 (updated)</p> <p>With the release of new Sentinel-2 images, and other available resources for the M7.8 Kaikoura earthquake, we present an update of the Map of Co-Seismic Landslides and Surfaces Ruptures (As of 27/11/2016). Landslides were mapped using Sentinel-2 satellite images from Copernicus, European Space Agency, dated November and December 2016. Images were visually compared with previous last available S2A images without cloud cover (13 September and 26 October) and landslides and large slope failures were manually mapped. Areas covered by cloud are omitted and shown on map. 5875 landslide sites are shown in the map. A small number of landslides could have been mis-identified due to insufficient resolution of the images, small gaps of cloud cover or for other reasons. Also, re-activated landslides on the central mountainous area were unabled to identify due to imagery restrictions (medium resolution, relief shadows etc). Some local gaps in Sentinel imagery still exist due to cloud cover, but we believe the current map is very close to the major distribution of mass movement effects. Surface ruptures were mapped using Sentinel-2 imagery and approximate position from photos of the post-earthquake aerial surveys of Environment Canterbury Regional Council (http://ecan.govt.nz)</p> <p>KML file contains7355 landslide spots.</p>
National Checklists 2017: New Zealand Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from New Zealand collected using effechecka and geonames polygons
National Checklists 2019: New Zealand Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from New Zealand collected using effechecka and geonames polygons
Supplemental to: Physical and mechanical depth relationships of rocks from the Rotokawa Geothermal Reservoir, Taupō Volcanic Zone, New Zealand
<p>This contains supplementary informations for the Manuscript </p> <p>Physical and mechanical depth relationships of rocks from the Rotokawa Geothermal Reservoir, TaupōVolcanic Zone, New Zealand</p> <p>submitted for review at the New Zealand Journal of Geology and Geophysics</p>
ICP Displacement Fields from the 2016 Mw 7.8 Kaikōura Earthquake over the Papatea Fault, New Zealand
<p>Three-dimensional displacement fields produced over the Papatea Fault, South Island, New Zealand following the 2016 Mw 7.8 Kaikōura earthquake. The dataset was generated from pre- and post-event aerial image point clouds using a windowed implementation of the iterative closest point algorithm.</p> <p>Creation Date: 8/28/2021</p> <p>Authors: Colin Bloom (University of Canterbury, Christchurch, New Zealand), Tim Stahl (University of Canterbury), and Andy Howell (University of Canterbury/GNS Science, Lower Hutt, New Zealand)</p> <p>Projection: New Zealand Transverse Mercator</p> <p>Scale: 25 m/pixel</p> <p>Notes: There are three displacement directions, east, north, and vertical. Positive values represent east, north, and up in the vertical direction respectively in relation to the pre-event surface. Displacement values are in meters. Extremely high or low data values likely represent noise in the dataset.</p>
Dataset of five years of in-situ and satellite derived chlorophyll a concentrations and its spatiotemporal variability in the Rotorua Lakes, New Zealand
<p><strong>rotorua_chl_fields_2015-2020.nc</strong> is a time series of 283 <em>Chl</em> fields of 13 of the lakes derived from Sentinel-2 MSI images with a regionalised parametrization of the C2RCC algorithm at 60 m pixel resolution. It also includes C2RCC and Idepix masks as well as a shoreline-and-shallow-water-buffer for flexible quality flagging.</p> <p><strong>rotorua_chl_spatial_variability.tif</strong> is a GeoTIFF that illustrates the representativeness of each grid cell for the <em>Chl</em> distribution in each lake and thus indicates recurring spatial patterns. The file contains three bands. Each band shows the relative frequency (in %) which <em>Chl</em> concentration was found near the median, or upper or lower quartile, respectively. The intervals around the median and quartiles are 5% to either side.</p> <p><strong>rotorua_insitu_chl_2015-2019.csv</strong> contains 831 in situ <em>Chl</em> measurements from 12 of the lakes collected between 2015 and 2019. The majority of these measurements (802) have been taken as part of the monthly Bay of Plenty lake water quality monitoring programme, in which 11 lakes are monitored. The data set also contains samples from field work under the <em>Eye on Lakes</em> project (University of Waikato) obtained by one of the authors (MKL). These 29 samples also include two measurements at Lake Rotokakahi, which is not part of the monthly monitoring program.</p> <p><strong>shoreline_shallow_water_buffer.zip</strong> contains a shapefile with polygons of the valid water pixels of all lakes to remove areas contaminated by bottom reflectance in remote sensing products. Each lake has a 120 m shoreline buffer to avoid mixed land-water pixels to reduce adjacency effects. It further excludes lake areas shallower than the 95%-quantile of all Secchi depth measurements of the Bay of Plenty lake water quality monitoring programme.</p>
Rees River, New Zealand - Geomorphic Change Detection - Example Dataset
<p>A simple<a href="https://gcd.riverscapes.net/Tutorials/example-data-sets.html"> Example GCD Dataset </a>illustrating topographic change detection on a long (31 km) dataset. Great for learning about analyses with DEMs produced from a hybrid of survey types. Used in <a href="https://gcd.riverscapes.net/Tutorials/ErrorModelling/multimethoderror.html">Multi-Method Error Estimation Tutorial</a> and <a href="https://gcd.riverscapes.net/Tutorials/GeomorphicInterpretation/morphological-approach.html">Morphological Approach Tutorial</a>. This is part of the dataset from:</p> <ul> <li>2011. Richard Williams, James Brasington, Damia Vericat, Murray Hicks, Fred Labrosse, Mark Neal. Chapter Twenty - Monitoring Braided River Change Using Terrestrial Laser Scanning and Optical Bathymetric Mapping. Editor(s): Mike J. Smith, Paolo Paron, James S. Griffiths. Developments in Earth Surface Processes. Elsevier, Volume 15, Pages 507-532, ISSN 0928-2025. DOI: <a href="https://doi.org/10.1016/B978-0-444-53446-0.00020-3">10.1016/B978-0-444-53446-0.00020-3</a>.</li> </ul> <p>Dataset is from:</p> <ul> <li>2km of braided river near <a href="https://www.google.com/maps/place/44%C2%B046'38.6%22S+168%C2%B024'17.9%22E/@-44.7767196,168.3891697,7451m/data=!3m1!1e3!4m5!3m4!1s0x0:0x0!8m2!3d-44.777379!4d168.404972">Queenstown, New Zealand</a></li> <li>Two LiDAR surveys</li> <li>0.5m cell resolution</li> <li><a href="https://s3-us-west-2.amazonaws.com/etalweb.joewheaton.org/GCD/GCD7/Tutorials/GeoTERM_Rees.zip">Download Full</a></li> <li><a href="https://s3-us-west-2.amazonaws.com/etalweb.joewheaton.org/GCD/GCD7/Tutorials/MaskOnly_MorphologicalApproach.zip">Download Morphological Only</a></li> </ul> <p>Dataset includes raw data to run exercises, as well as full *.gcd projects that can be opened. </p>
New Zealand Seismic Hazard Z Factors
<p>This dataset presents our interpretation of the <em>Z</em> factor as a continuous surface across New Zealand. The GeoTiFF has been derived through a range of publicly available online resources including the MBIE website, reports, journal publications, and the <a href="https://gazetteer.linz.govt.nz/">New Zealand Gazetter</a> for matching placenames to locations, amongst others. The coordinate system is EPSG:2193 with ~5 km resolution. The raster has a single band and values are rounded to two decimal places.</p> <p>The <em>Z</em> factor is used to scale the 5% damped design seismic response spectrum based on the magnitude of the expected seismic hazard in different regions in New Zealand, as demonstrated through <a href="https://www.standards.govt.nz/shop/nzs-1170-52004/">NZS 1170.5:2004</a> and referred to in the seismic assessment of potentially earthquake prone buildings (EPB). It is underpinned by the 2001 National Seismic Hazard Model and is influenced by a wide range of factors such as proximity to faults and fault rupture mechanisms, geological and soil characteristics, and topography, amongst others. <em>Z</em> ranges from 0.10 (Northland Region) to 0.60 (Otira/Arthur’s Pass surrounds). Generally speaking, low seismic risk is where <em>Z</em> < 0.15; medium seismic risk where 0.15 ≤ <em>Z</em> < 0.30; and high seismic risk where <em>Z</em> ≥ 0.30.</p> <p>This GIS dataset is intended for educational purposes where students can download the dataset, create their own contours, or directly sample the raster. For more information see the numerous online resources and the official standard <a href="https://www.standards.govt.nz/shop/nzs-1170-52004/">NZS 1170.5:2004</a> where it is available for purchase from Standards NZ.</p>
16-year WRF simulation for the Southern Alps of New Zealand (monthly output)
<p>The climatological dataset was produced using the Weather and Research Forecasting (WRF) model configured with two nested domains at 10 km (D1) and 2 km (D2) horizontal grid spacing. It covers the bulk of the South Island of New Zealand and is centered over Brewster Glacier in the Southern Alps. The model was forced every three hours by ERA5 reanalysis data at its outer lateral boundaries. The dataset covers the period of 1 January 2005 to 31 December 2020, providing daily output in the outer domain (D1) and 3-hourly output in the innermost domain (D2). </p> <p>The dataset was generated as part of a DFG-funded project aimed at investigating the atmospheric processes causing impacts of sea surface temperature changes around New Zealand on variations of glacier surface climate and mass balance in the Southern Alps (using Brewster Glacier as a benchmark glacier).</p> <p>The data provided here are a selection of monthly averages from the finest WRF domain (D2; 2-km grid spacing). They are distributed among three different file types containing 4-dimensional, 3-dimensional and invariant output variables, respectively. For the 4-dimensional variables, the data were cropped to below ~200 hPa. In addition, perturbation and base-state atmospheric pressure (WRF variables P and PB) and geopotential (PH and PHB) were combined to produce full model fields, and perturbation potential temperature (T) was converted to total potential temperature.</p>
Data on the fleas of house mice and ship rats in the Orongorongo Valley, New Zealand
<p>Data on autopsies and fleas of individual rats and mice snap-trapped in 80 quarterly 3-day trapping sessions over 1971-1991 in the Orongorongo Valley, Wellington, New Zealand. The fleas are preserved as slides in the Pilgrim Collection of Te Papa Tongarewa Museum of New Zealand, Wellington. The data are analysed in a forthcoming paper by Fitzgerald, Efford and Karl.</p> <p>'Autopsy data.csv' is the main spreadsheet.</p> <p>'Data format.csv' defines columns and codes.</p> <p>The autopsy data are a subset of those reported by Fitzgerald, Efford<br> and Karl (2004) and Efford, Fitzgerald, Karl and Berben (2006), both<br> with respect to the sampling period (trapping continued after May 1991,<br> but rats and mice were not searched for fleas) and data columns<br> (some reproductive fields have been omitted).</p> <p>The autopsy data may be read from the csv file into R (R Core Team 2023)<br> with the statement:</p> <p>autopsyF <- read.csv(file = 'Orongorongo fleas 1971-1991 Autopsy data.csv')</p> <p>The resulting dataframe has 31 columns and 3006 rows:</p> <p>names(autopsyF)<br> [1] "Autopsy" "Line" "Date" "Analysis.Year" "Session" <br> [6] "Day" "Season" "Trap" "Traptype" "Alive.dead" <br> [11] "Species" "Sex" "Age" "Weight" "TotLth" <br> [16] "TailLth" "Fleas" "LsegnisM" "LsegnisF" "LsegnisU" <br> [21] "Lsegnis" "NfascM" "NfascF" "NfascU" "Nfasc" <br> [26] "Vagina" "Lact" "Uterus" "EmbryosT" "ScarCond" <br> [31] "Testes" <br> <br> nrow(autopsyF)<br> [1] 3006</p> <p>For completeness, the autopsy data include 64 hosts from these trapping sessions that were<br> not searched for fleas (coded as Fleas = 2).</p> <p>Quarterly indices of host density were tabulated by Fitzgerald et al. (2004; mice) and<br> Efford et al. (2006; rats).</p> <p>References</p> <p>Efford MG, Fitzgerald BM, Karl BJ, Berben PH. 2006. Population dynamics<br> of the ship rat <em>Rattus rattus</em> L. in the Orongorongo Valley, New Zealand.<br> New Zealand Journal of Zoology 33:273-297.</p> <p>Fitzgerald BM, Efford MG, Karl BJ. 2004. Breeding of house mice and the<br> mast seeding of southern beeches in the Orongorongo Valley, New Zealand.<br> New Zealand Journal of Zoology 31:167-184.</p> <p>Fitzgerald BM, Efford MG, Karl BJ. 2023. The fleas of house mice (<em>Mus musculus</em>)<br> and ship rats (<em>Rattus rattus</em>) in forest of the Orongorongo Valley, New Zealand.<br> For submission to New Zealand Journal of Zoology.</p> <p>R Core Team 2023. R: A Language and Environment for Statistical Computing.<br> R Foundation for Statistical Computing, Vienna, Austria.<br> https://www.R-project.org/</p>
Extreme Weather Event database over Aotearoa New Zealand
<p><strong>The Aotearoa New Zealand (ANZ) Extreme Weather Events (EWE) database </strong>(EWE_database_V1.0.0.xlsx)<strong> is a comprehensive record of extreme weather events in ANZ. The events listed in this database have been carefully assessed and categorized based on their meteorological significance, considering their rarity and whether they broke records or triggered official weather warnings. Some of the metrics used to classify each event rely on subjective judgment and expert opinions. The database captures meteorologically significant events, including those that have caused substantial damage to properties or led to casualties, and, in some cases, includes supplementary information about their socioeconomic impacts. The information in the EWE database is primarily sourced from the Meteorological Service of New Zealand Ltd (MetService) and the National Institute of Water and Atmospheric Research (NIWA). Additional impact data have been added from various media sources, with insured loss data for some events sourced from the Insurance Council of New Zealand (ICNZ).</strong></p> <p>Note - For more information about the database and the other additional files, please look into the Metadata (Metadata_EWE_V.1.0.0.docx) and the supplementary document (Supplementary document on EWE_V.1.0.0.docx).</p>
Supplementary files for the manuscript "Elevation-dependent periglacial and paraglacial processes modulate tectonically-controlled erosion of the Western Southern Alps, New Zealand", submitted to JGR Earth Surface
<p>This repository contains supplementary files to the manuscript ""Elevation-dependent periglacial and paraglacial processes modulate tectonically-controlled erosion of the Western Southern Alps, New Zealand" submitted to JGR: Earth Surface. It contains: </p> <p>- The Matlab script used to find the optimal distance-from-fault and elevation windows ("elevation_distance_window_optimization"), and 3 text files used for input in this script ("data_erates" contains the erosion rates, "data_elev" the number of pixels in each elevation bin, "data_distAF" the number of pixels in each distance-from-fault bin). </p> <p>- An Excel spreadsheet with the same information that the input text files contain, but specifiying the elevation or distance from fault bin values ("elevation and distance from fault with bins")</p> <p>- A shapefile of catchment outlines ("WSAcatch") for the catchments sampled for CRN denudation rates</p> <p>- Raw CRN data ("Table 2_new_CRN_data")</p> <p>- Excel spreadsheet with the compilation of themochronometric cooling ages used in the age2exhume code (van der Beek & Schildgen, 2023; <a href="https://doi.org/10.5281/zenodo.7341603">https://doi.org/10.5281/zenodo.7341603</a>).</p> <p>CRN data and catchment outlines will also be uploaded to the OCTOPUS database (<a href="https://octopusdata.org/">https://octopusdata.org/</a>) after manuscript acceptance.</p>
Lake surface areas and watershed areas for 4012 lakes in the USA and New Zealand
A compilation of lake surface areas and watershed areas for 4012 lakes in the USA and New Zealand. Lakes are also identified by region and lake origin/type, using designations provided in the original datasets if available.
Fig. 9 in Iphimediidae of New Zealand (Crustacea, Amphipoda)
Fig. 9. Labriphimedia martinae nov. sp., holotype ♂, 6.5 mm, NIWA 84743. A. Gnathopod 1. B. Chela of gnathopod 1. C. Gnathopod 2. D. Chela of gnathopod 2. E. Pereopod 3. F. Presumed carpus to dactylus of pereopod 3. Scale bars: A, C, E-F = 100 µm.
Fig. 3 in Iphimediidae of New Zealand (Crustacea, Amphipoda)
Fig. 3. Labriphimedia meikae nov. sp., holotype ♂, 6 mm, NIWA 84598. A. Maxilla 1. B. Outlines of maxilliped. C. Palp of maxilliped. D. Outer plate of maxilliped. E. Inner plate of maxilliped. Scale bars: A, C-E = 100 µm, B = 200 µm.
Fig. 5 in Iphimediidae of New Zealand (Crustacea, Amphipoda)
Fig. 5. Labriphimedia meikae nov. sp., holotype ♂, 6 mm, NIWA 84598. A. Pereopod 3. B. Pereopod 4. C. Pereopod 5. Scale bars: A-B = 100 µm. C = 200 µm.
Fig. 4 in Iphimediidae of New Zealand (Crustacea, Amphipoda)
Fig. 4. Labriphimedia meikae nov. sp., holotype ♂, 6 mm, NIWA 84598. A. Gnathopod 1. B. Chela of gnathopod 1. C. Gnathopod 2. Scale bars: A, C = 100 µm.
Fig. 17 in Two new genera and five new species of Selachinematidae (Nematoda, Chromadorida) from the continental slope of New Zealand
Fig. 17. Map of the New Zealand region with 1000 m water depth contours. A. Location of the sites sampled on Chatham Rise and Challenger Plateau. – B-F. Distributions of individual species. – B. Pseudocheironchus ingluviosus gen. et sp. nov. C. Synonchiella rotundicauda sp. nov. D. Cobbionema trigamma sp. nov. E. Gammanema agglutinans sp. nov. F. Bendiella thalassa gen. et sp. nov.
Fig. 16 in Two new genera and five new species of Selachinematidae (Nematoda, Chromadorida) from the continental slope of New Zealand
Fig. 16. Bendiella thalassa gen. et sp. nov. Light micrographs. A. Lateral view of male cuticle. B. Female head, showing shape of buccal cavity. C. Female head, showing details of rhabdions in anterior and posterior buccal cavity. Scale bar = 10 μm.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.