cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7739325
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2018

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 500m spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2018. Please <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2017</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2019</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2018 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7739324
title: MUSES Leaf Area Index (LAI) Monthly Global 500m SIN Grid in 2018

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 500m spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2018. Please <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2017</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2019</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2018 Spatial Resolution: 500m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7741395
title: Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment

description: Selection of the data in the following paper:<br> Sengers, B. A. M., Steinfeld, G., Hulsman, P., & Kuehn, M. (2023). Validation of an interpretable data-driven wake model using lidar measurements from a free-field wake steering experiment. Wind Energy Science Discussions, 1-32. This data subset provides input parameters commonly used in wake models, as well as ten-minuted averaged cross sections of the flow field at 4 rotor diameters downstream, as measured by a nacelle-mounted lidar. Cite this as:<br> B.A.M. Sengers (2023). Dataset: Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment. https://doi.org/10.5281/zenodo.7741395
DOI: 10.5281/zenodo.7741394
title: Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment

description: Selection of the data in the following paper:<br> Sengers, B. A. M., Steinfeld, G., Hulsman, P., & Kuehn, M. (2023). Validation of an interpretable data-driven wake model using lidar measurements from a free-field wake steering experiment. Wind Energy Science Discussions, 1-32. This data subset provides input parameters commonly used in wake models, as well as ten-minuted averaged cross sections of the flow field at 4 rotor diameters downstream, as measured by a nacelle-mounted lidar. Cite this as:<br> B.A.M. Sengers (2023). Dataset: Validation of an interpretable data-driven wake model using lidar measurements from a field wake steering experiment. https://doi.org/10.5281/zenodo.7741395
DOI: 10.22008/fk2/gpkqxh/g4yaey
title: GRF27831_ZTEM.zip

description: :unav
DOI: 10.22008/fk2/gpkqxh
title: ZTEM and airborne magnetic survey in Kuugannguaq and Ilugissoq, northern Disko and Nuussuaq, central West Greenland

description: For description of data set see: Geotech Disko and Nuussuaq surveys details.Size: 219 MB.
DOI: 10.5281/zenodo.7274277
title: Subset of #MeToo-tweets in English, German, Spanish from 2019 and 2021

description: The zip contains two tables with tweets on #MeToo in English, Spanish and German from the months 2019-07, 2019-08, 2021-07 and 2021-08. Tweets were mostly annotated with evaluative categories (positive, negative, neutral, ambiguous) and whether they represent a concrete or a meta discourse.
DOI: 10.5281/zenodo.7274278
title: Subset of #MeToo-tweets in English, German, Spanish from 2019 and 2021

description: The zip contains two tables with tweets on #MeToo in English, Spanish and German from the months 2019-07, 2019-08, 2021-07 and 2021-08. Tweets were mostly annotated with evaluative categories (positive, negative, neutral, ambiguous) and whether they represent a concrete or a meta discourse.
DOI: 10.5066/p92c21f6
title: Field-scale investigation of per- and polyfluoroalkyl substances (PFAS) leaching from shallow soils to groundwater at two sites in New Hampshire, 2021-2022

description: Per- and polyfluoroalkyl substances (PFAS) and related chemical and physical data are presented from shallow soil and groundwater at two sites in New Hampshire. The two sites, the former Brentwood Fire Training Area and White Farm, were selected because materials known to contain PFAS were used at each site. White Farm is an active farm where biosolids have been applied for several years. At the former Brentwood Fire Training Area, PFAS-containing aqueous film-forming foams were applied as part of regular fire training exercises. At each site, soil samples were collected in a gridded pattern over the site. Soil horizons within the sampling intervals were described using the National Soil Survey Center Natural Resources Conservation Service U.S. Department of Agriculture Field Book for Describing and Sampling Soils (Schoeneberger and others, 2012). Analyses included 36 PFAS compounds, 36 PFAS compounds post-total oxidizable precursor assay (TOPA), total organic carbon (TOC), moisture content, pH, autoclaved-citrate extractable protein, grain size, major ions and other physical and physicochemical parameters. Groundwater samples were collected and analyzed for PFAS during two sampling events at each site from temporary wells, existing monitoring wells, and/or pushpoint samplers. Additionally, a lysimeter was installed at the center of each site and a composite sample through the duration of each water sampling event (approximately 7 days) was collected. Quality control samples included source-solution blanks, equipment blanks, and replicates. Reference: Schoeneberger, P.J., Wysocki, D.A., Benham, E.C., and Soil Survey Staff, 2012, Field book for describing and sampling soils, Version 3.0: Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE.
DOI: 10.25345/c5028pp7v
title: MassIVE MSV000091498 - GNPS Nudibranch Analysis_Trial
title: GNPS Study for Nudibranch sp. from Okinawa| Feb 2. 2022
DOI: 10.3886/e130542v1-134084
title: National Neighborhood Data Archive (NaNDA): Urbanicity by Census Tract, United States, 2010

description: This dataset contains measures of the urban/rural characteristics of each census tract in the United States. These include proportions of urban and rural population, population density, rural/urban commuting area (RUCA) codes, and RUCA-based four- and seven- category urbanicity scales. <br><br>A curated version of this data is available through ICPSR at https://www.icpsr.umich.edu/web/ICPSR/studies/38606/versions/V1<br>
description: All census tracts in the United States, including Puerto Rico. . Smallest Geographic Unit: census tract
DOI: 10.5281/zenodo.7741427
title: UK Grid Frequency data in Open-ENF .fredb format

description: This file contains the mains grid frequency for each second betwen 1st Jan 2014 00:00 UTC and 1st Jan 2022 00:00 UTC. This data was originally published by the UK National Grid, and subsequently cleaned and reformatted in OpenENF .freqdb format
DOI: 10.5281/zenodo.7741426
title: UK Grid Frequency data in Open-ENF .fredb format

description: This file contains the mains grid frequency for each second betwen 1st Jan 2014 00:00 UTC and 1st Jan 2022 00:00 UTC. This data was originally published by the UK National Grid, and subsequently cleaned and reformatted in OpenENF .freqdb format
DOI: 10.5519/qd.uzxpteja
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2290 records)
DOI: 10.17028/rd.lboro.22285282
title: Supplementary information files for Temperature control of diffusive memristor hysteresis and artificial neuron spiking

description: Supplementary files for article Temperature control of diffusive memristor hysteresis and artificial neuron spiking <br> Memristive devices are promising elements for energy-efficient neuromorphic computing and future artificial intelligence systems. For diffusive memristors, resistive switching occurs because of the sequential formation and rupture of conduction filaments between device electrodes due to drift and diffusion of silver nanoparticles in the dielectric matrix. This process is governed by the applied electric voltage. Here, both in experiment and in simulations we demonstrate that varying temperature offers an efficient control of memristor states and charges transport in the device. By raising and lowering the device temperature it was shown that the memristive state can be reset, even if it cannot be done by varying the applied voltage. In addition, a change in the spiking regime was observed when the spiking was generated in the memristive circuit at a constant applied voltage, but different device temperatures. Our simulations demonstrate a good qualitative agreement with the experiments, and help to explain the effects reported.
DOI: 10.17028/rd.lboro.22285282.v1
title: Supplementary information files for Temperature control of diffusive memristor hysteresis and artificial neuron spiking

description: Supplementary files for article Temperature control of diffusive memristor hysteresis and artificial neuron spiking <br> Memristive devices are promising elements for energy-efficient neuromorphic computing and future artificial intelligence systems. For diffusive memristors, resistive switching occurs because of the sequential formation and rupture of conduction filaments between device electrodes due to drift and diffusion of silver nanoparticles in the dielectric matrix. This process is governed by the applied electric voltage. Here, both in experiment and in simulations we demonstrate that varying temperature offers an efficient control of memristor states and charges transport in the device. By raising and lowering the device temperature it was shown that the memristive state can be reset, even if it cannot be done by varying the applied voltage. In addition, a change in the spiking regime was observed when the spiking was generated in the memristive circuit at a constant applied voltage, but different device temperatures. Our simulations demonstrate a good qualitative agreement with the experiments, and help to explain the effects reported.
DOI: 10.22008/fk2/ts7urv/nbnahe
title: Klitdal_vd1-enh_2013.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/fqxrzg
title: Klitdal_sheet2_fp.map

description: :unav
DOI: 10.22008/fk2/ts7urv/onev9s
title: Wegener_Halvo_vd1.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/t2vpkp
title: Klitdal_tmi-enh_2013.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/bwylak
title: Klitdal.gdb

description: :unav
DOI: 10.22008/fk2/ts7urv/lij1ir
title: Wegener_Halvo_tmi.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/8ketim
title: Klitdal_vd1_2013.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/dvfzsy
title: Wegener_Halvo_tmi_enh.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/rarywl
title: Wegener_Halvo_vd1_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/x2soxs
title: Wegener_Halvo_tmi_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/t7ju5z
title: Klitdal_gradlong.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/c35uh6
title: Klitdal_gradlat.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/mxbatp
title: Wegener_Halvo_vd1.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/utn28l
title: Klitdal_gradlat.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/rtjlc1
title: dbview_readme.doc

description: :unav
DOI: 10.22008/fk2/ts7urv/jkbkkq
title: Klitdal_sheet1_tmi_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/lpotxd
title: Klitdal_vd1_2013.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/hkpium
title: Klitdal_tmi.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/4o4gcq
title: geosoft_dbviewer.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/c20osf
title: GRF23848_MiraGeoscience.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/2bpcuj
title: Wegener_Halvo_tmi_enh.GRD.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/tqrqa6
title: Klitdal_sheet1_vd1_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/vztwfn
title: Klitdal_gradlong.GRD.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/jpsreu
title: Klitdal_sheet2_vd1_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/ap4uyg
title: Wegener-Halvo.gdb

description: :unav
DOI: 10.22008/fk2/ts7urv/brwk6b
title: Thumbs.db

description: :unav
DOI: 10.22008/fk2/ts7urv/osl4rq
title: Klitdal.gdb.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/hkfti2
title: Klitdal_tmi.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/uihbfd
title: 13715 Logistics and Processing Report.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/wjkpcq
title: Klitdal_vd1.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/hvmvrh
title: Geotiff.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/hyms3c
title: Wegener_Halvo_tmi.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/j5lqtu
title: Klitdal_sheet1_vd1_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/zpbwye
title: Wegener_Halvo_vd1_enh.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/adimv4
title: East_Greenland_Copper.dbview

description: :unav
DOI: 10.22008/fk2/ts7urv/c4mzku
title: Wegener_Halvo_gradlat.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/gfbo5n
title: Klitdal_gradlong.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/ibwkou
title: Klitdal_vd1_2013.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/5ywdxq
title: Geosoft Grid Descriptor.doc

description: :unav
DOI: 10.22008/fk2/ts7urv/v2gvor
title: kmz_files.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/ihfcdn
title: Geosoft Archive Descriptor.doc

description: :unav
DOI: 10.22008/fk2/ts7urv/5p9u9f
title: Klitdal_tmi_2013.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/wso1hq
title: Klitdal_vd1-enh_2013.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/1esosk
title: Klitdal_gradlat.GRD.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/ifvj97
title: Klitdal_sheet1_fp.map

description: :unav
DOI: 10.22008/fk2/ts7urv/nbypgj
title: Klitdal_sheet2_fp.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/4k0ybe
title: Klitdal_tmi_enh.GRD.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/nmaepu
title: ASCII Archive Descriptor.doc

description: :unav
DOI: 10.22008/fk2/ts7urv/bunjmg
title: Klitdal_tmi_2013.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/zoxdps
title: Klitdal_sheet2_vd1_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/xbzika
title: Klitdal_sheet1_fp.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/gtnaj6
title: Klitdal_tmi_enh.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/ie37qh
title: Wegener-Halvo.gdb.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/jb1goe
title: Klitdal_vd1-enh_2013.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/mxkztn
title: Klitdal_vd1-enh_2013.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/wmpivi
title: Klitdal_tmi_2013.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/vc3di0
title: Wegener_Halvo_tmi.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/urjht6
title: Wegener_Halvo_vd1_enh.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/aehllc
title: Klitdal_tmi-enh_2013.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/mcpm7p
title: Klitdal_vd1.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/hpyjvi
title: Klitdal_tmi-enh_2013.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/dzyhvp
title: Wegener-Halvo_vd1_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/k2dblm
title: Wegener_Halvo_vd1.TAB

description: :unav
DOI: 10.22008/fk2/ts7urv/ljccjb
title: Wegener_Halvo_gradlat.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/c5sqx3
title: Klitdal_tmi-enh_2013.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/jgk6wb
title: Klitdal_sheet2_vd1_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/lam4ob
title: Klitdal_tmi.GRD.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/aosuh8
title: Wegener_Halvo_vd1.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/3orjim
title: Wegener_Halvo_tmi.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/ctc9ln
title: Wegener_Halvo_vd1.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/0wakyy
title: Klitdal_sheet1_vd1_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/1jwbkn
title: Klitdal_sheet2_tmi_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/s2zvad
title: Klitdal_sheet1_tmi_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/m6zdww
title: Klitdal_sheet2_tmi_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/evehzk
title: pdf_maps.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/mgiyrx
title: ascii_databases.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/9wggy6
title: Wegener_Halvo_tmi.tif

description: :unav
DOI: 10.22008/fk2/ts7urv/xffdka
title: Klitdal_vd1_2013.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/xtp1xo
title: East_Greenland_Copper.gpf

description: :unav
DOI: 10.22008/fk2/ts7urv/nro6ys
title: Wegener_Halvo_vd1.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/cznjc2
title: report.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/faz98q
title: Klitdal_sheet1_tmi_enh.kmz

description: :unav
DOI: 10.22008/fk2/ts7urv/sm6d9q
title: Wegener-Halvo_tmi_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/4xervk
title: geosoft_maps.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/9d0u7q
title: Wegener-Halvo_tmi_enh.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/s2jyun
title: Klitdal_sheet2_tmi_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/2e52wg
title: Wegener-Halvo_vd1_enh.map

description: :unav
DOI: 10.22008/fk2/ts7urv/8zyo4l
title: Klitdal_vd1_enh.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/zhg1uc
title: Klitdal_tmi_2013.tif.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/3uzrb7
title: Wegener_Halvo_gradlong.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/iv0om1
title: geosoft_databases.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/he8vhf
title: Wegener_Halvo_tmi.tif.xml

description: :unav
DOI: 10.22008/fk2/ts7urv/kwlegd
title: geosoft_grids.zip

description: :unav
DOI: 10.22008/fk2/ts7urv/rd9bhu
title: Klitdal_tmi_enh.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/8nndof
title: Wegener-Halvo_fp.pdf

description: :unav
DOI: 10.22008/fk2/ts7urv/vojfqt
title: Wegener_Halvo_gradlong.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/nc7ey5
title: Wegener_Halvo_tmi_enh.grd.gi

description: :unav
DOI: 10.22008/fk2/ts7urv/gjzhvd
title: Klitdal_vd1_enh.grd

description: :unav
DOI: 10.22008/fk2/ts7urv/za2gca
title: Wegener-Halvo_fp.map

description: :unav
DOI: 10.22008/fk2/ts7urv
title: Airborne gradient magnetic survey from Klitdal and Wegener Halvø, central East Greenland

description: For description of data set see: FUGRO Klitdal and Wegener Halvø surveys details.Size: 3.0 GB.
DOI: 10.22008/fk2/h106wl/p5upme
title: Base062510.stn

description: :unav
DOI: 10.22008/fk2/h106wl/yrdt32
title: Mag072610.bin

description: :unav
DOI: 10.22008/fk2/h106wl/kzuybl
title: GroundMag_Eqi_All.csv

description: :unav
DOI: 10.22008/fk2/h106wl/hox7tb
title: Mag071910(1).xyz

description: :unav
DOI: 10.22008/fk2/h106wl/mqv8yg
title: Mag072610.xyz

description: :unav
DOI: 10.22008/fk2/h106wl/ff8dnu
title: Base072610.stn

description: :unav
DOI: 10.22008/fk2/h106wl/kyq8xk
title: Mag072210.bin

description: :unav
DOI: 10.22008/fk2/h106wl/uwsjaf
title: Mag072210.xyz

description: :unav
DOI: 10.22008/fk2/h106wl/bwdmti
title: Eqi_Mag.gdb

description: :unav
DOI: 10.22008/fk2/h106wl/qvwca9
title: Base072110.stn

description: :unav
DOI: 10.22008/fk2/h106wl/t8bq6y
title: Base072410.stn

description: :unav
DOI: 10.22008/fk2/h106wl/txagv2
title: 22528_1.pdf

description: :unav
DOI: 10.22008/fk2/h106wl/h9qckj
title: Mag072410.bin

description: :unav
DOI: 10.22008/fk2/h106wl/yibwpx
title: Base062310.stn

description: :unav
DOI: 10.22008/fk2/h106wl/vgfs9v
title: Mag071810.bin

description: :unav
DOI: 10.22008/fk2/h106wl/zpzegs
title: Base072010.stn

description: :unav
DOI: 10.22008/fk2/h106wl/rammu5
title: Base071710.stn

description: :unav
DOI: 10.22008/fk2/h106wl/zxj3i0
title: Mag071910(2).xyz

description: :unav
DOI: 10.22008/fk2/h106wl/ripghx
title: Mag072110.bin

description: :unav