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26 results for “Canary Islands La Palma”
Canary Islands La Palma: pinar canario change map (2003-2015)
<p>A change map for the land cover class "PINAR CANARIO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "PINAR CANARIO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from PINAR CANARIO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: cloud cover map (2015)
<p>A multi-temporal cloud cover map related to 10 Landsat 8 images in "La Palma" PA from August to December 2015.</p> <p>The 10 layers were related to the following dates: August 9<sup>th</sup>, August 25<sup>th</sup>, September 10<sup>th</sup>, September 26<sup>th</sup>, October 12<sup>nd</sup>, October 28<sup>th</sup>, November 13rd, November 29<sup>th</sup>, December 15<sup>th</sup>, December 31<sup>st</sup>.</p> <p>The maps was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates cloud cover pixels whereas value 0 indicates No cloud cover pixels.</p>
Canary Islands La Palma: pinar disperso change map (2003-2015)
<p>A change map for the land cover class "PINAR DISPERSO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "PINAR DISPERSO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from PINAR DISPERSO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: cloudiness timely presence (2016)
<p>A map representing the cloudiness timely presence on "La Palma" PA from December 2015 to April 2016.</p> <p>The map has 10 values related as follows:</p> <p>Value 1 = presence of cloudiness in 1 scene</p> <p>Value 2 = presence of cloudiness in 2 scene</p> <p>Value 3 = presence of cloudiness in 3 scene</p> <p>Value 4 = presence of cloudiness in 4 scene</p> <p>Value 5 = presence of cloudiness in 5 scene</p> <p>the higher values correspond to higher cloudiness timely presence.</p> <p>The map was produced from Sentinel-2A at 60 meters spatial resolution and projected in WGS84/UTM28N.</p>
Canary Islands La Palma: improductivo change map (2003-2015)
<p>A change map for the land cover class "IMPRODUCTIVO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "IMPRODUCTIVO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from IMPRODUCTIVO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, Remote Sensing of Environment, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: cloud cover map (2016)
<p>A multi-temporal cloud cover map related to 5 Sentinel-2A images in "La Palma" PA from December 2015to April 2016.</p> <p>The 5 layers representing the cloud cover (as OR among different temporal and spatial acquisitions in each month) were related to the following dates: December 2015, January 2016, February 2016, March 2016 and April 2016 .</p> <p>The maps was produced at 60 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates cloud cover pixels whereas value 0 indicates No cloud cover pixels.</p>
Canary Islands La Palma: cultivo change map (2003-2015)
<p>A change map for the land cover class "CULTIVO" in "La Palma" PA, obtained by the Cross Correlation Analysis algorithm (CCA) [1,2] considering at time T1 the layer "CULTIVO" from an existing land cover map dated 2003 and at time T2 a Landsat 8 image dated July 8th, 2015.</p> <p>The map was produced at 30 meters spatial resolution and projected in WGS84/UTM28N.</p> <p>The map has binary values where value 1 indicates pixels changed from CULTIVO to other whereas value 0 indicates No changed/Not considered pixels.</p> <p>[1] Koeln, G., & Bissonnette, J. (2000). Cross-correlation analysis: Mapping landcover changes with a historic landcover database and a recent, single-date, multispectral image. Proc. 2000 ASPRS Annual Convention, Washington, D.C. (8 pp.).</p> <p>[2] C. Tarantino, M. Adamo, R. Lucas, P. Blonda. (2016). “Detection of changes in semi-natural grasslands by cross correlation analysis with Worldview-2 images and new Landsat 8 data”, <em>Remote Sensing of Environment</em>, Vol. 175C, pp. 65-72, doi: 10.1016/j.rse.2015.12.031, ISSN 0034-4257</p>
Canary Islands La Palma: cloudiness timely presence (2015)
<p>A map representing the cloudiness timely presence on "La Palma" PA from August to December 2015.</p> <p>The map has 10 values related as follows:</p> <p>Value 1 = presence of cloudiness in 1 scene</p> <p>Value 2 = presence of cloudiness in 2 scene</p> <p>Value 3 = presence of cloudiness in 3 scene</p> <p>Value 4 = presence of cloudiness in 4 scene</p> <p>Value 5 = presence of cloudiness in 5 scene</p> <p>Value 6 = presence of cloudiness in 6 scene</p> <p>Value 7 = presence of cloudiness in 7 scene</p> <p>Value 8 = presence of cloudiness in 8 scene</p> <p>Value 9 = presence of cloudiness in 9 scene</p> <p>Value 10 = presence of cloudiness in 10 scene</p> <p>the higher values correspond to higher cloudiness timely presence.</p> <p>The map was produced from Landsat 8 at 30 meters spatial resolution and projected in WGS84/UTM28N.</p>
Landscape and biodiversity indicators for La Palma - Canary Island
<p>Landscape and biodiversity indicators have been identified as crucial for detecting changes in the Land Cover/Habitat map target classes and evaluating threats and intense impacts on certain areas of a site. This analysis is useful to prevent future ecosystem degradation, update the preservation strategies or take immediate mitigation actions.</p> <p>Regarding La Palma – Canary Island, Landscape and biodiversity indicators were generated for 2007. The Land Cover/Habitat map and Object-ID raster files were used as input to estimate the indicators. The outputs include a raster file of each indicator and a file “indValues.csv” containing the values of indicators per object.</p> <p>The calculated indicators are: (i) PLAND; (ii) PD; (iii) SHAPE_MN; (iv) CA; (v) MPS; (vi) MESH; (vii) AWMPFD. Indicator files are accompanied by INSPIRE metadata XML. Detailed information can be found in the “Readme.pdf” included in the zip containing the dataset.</p>
Insights into the Magmatic Feeding System of the 2021 Eruption at Cumbre Vieja (La Palma, Canary Islands) Inferred from Gravity Data Modeling. Remote Sens. 2023, 15, 1936. https://doi.org/10.3390/rs15071936
<p>Paper: Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling <br> F. G. Montesinos1,7, S. Sainz-Maza2,7, D. Gómez-Ortiz3, J. Arnoso4,7, I. Blanco-Montenegro5,7, M. Benavent1,7 E. Vélez4,7, N. Sánchez6 and T. Martín-Crespo3</p> <p>1 Facultad de CC. Matemáticas, Universidad Complutense de Madrid. Plaza de Ciencias 3, 28040 Madrid, Spain.<br> 2 Observatorio Geofísico Central (IGN). C/ Alfonso XII, 3. 28014 Madrid, Spain.<br> 3 Dpt. Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos. C/Tulipán s/n, 28933 Móstoles, Madrid, Spain.<br> 4 Instituto de Geociencias (IGEO), CSIC-UCM. C/ Doctor Severo Ochoa, 7. 28040 Madrid, Spain.<br> 5 Departamento de Física, Escuela Politécnica Superior, Universidad de Burgos. Avda. de Cantabria s/n, 09006 Burgos, Spain.<br> 6 Instituto Geológico y Minero de España (IGME, CSIC), Unidad Territorial de Canarias, Alonso Alvarado, 43, 2A, 35003 Las Palmas de Gran Canaria, Spain.<br> 7 Research Group ‘Geodesia’, Universidad Complutense de Madrid, Spain.</p> <p><br> Corresponding author: Fuensanta G. Montesinos (fuensant@ucm.es)</p> <p>This research is supported by the project PID2019-104726GB-I00/AEI/10.13039/501100011033 funded by the Spanish Research Agency. Further, the University Complutense of Madrid (grants Financiación Grupos 2021, UCM 2022-GRFN14/22) and the Spanish Ministry of Science and Innovation (RD 1078/2021, funding for research activities of the CSIC-PIE project CSIC-LAPALMA-07) supported this research.</p> <p>------------------------------------------------------------------------------------------------</p> <p>Responsible Researchers:<br> - Fuensanta González Montesinos, Facultad de CC. Matemáticas, Universidad Complutense de Madrid. Spain<br> fuensant@ucm.esResponsible Researchers: </p> <p>- José Arnoso Sampedro, Instituto de Geociencias (CSIC-UCM), Spain<br> jose_arnoso@csic.es</p> <p> </p> <p><br> >> The use of this data set is limited to academic or research purposes and it have to be referenced</p> <p><br> Zone:Cumbre Vieja (La Palma Island, Spain)<br> Geodetic Coordinates Datum WGS84<br> Gravity(mGal) and Bouguer Gravity anomaly GRS80 (mGal)(Terrain density 2450 kg/m3)</p> <p>The file GravityCumbreVieja_FGMontesinos_et_al.dat includes the values of gravity and complete Bouguer gravity anomaly (GRS80) calculated for the land gravity stations at the Cumbre Vieja area (La Palma Island, Spain). The gravity values were observed in 142 land gravity stations (Figure 3 in the manuscript) by our group in 2005 and 2021 surveys The positions of the stations were selected to cover most of the Cumbre Vieja area, and the coordinates were obtained by differential GPS (WGS84 Datum). The gravity observations were processed taking into account the usual corrections (instrument height, drift, jumps, etc.). The tidal correction was calculated from gravity tide measurements made in several islands of the Canary Archipelago. All the gravity values referred to absolute gravity stations (Table S1). The procedure to obtain the terrain correction and the Bouguer anomaly map is explained in the manuscript and in the supporting information.</p>
Geothermal and structural features of La Palma island (Canary Islands) imaged by ambient noise tomography
<p>These folders contain all the results obtained in the ambient noise tomography of La Palma for geothermal exploration. </p>
Supporting Data of Bonadonna et al. "Physical Characterization of Long-Lasting Hybrid Eruptions: the Tajogaite Eruption of Cumbre Vieja (La Palma, Canary Islands)"
<p>Data on plume height, volcanic tremor, deposit thinning and lava emissions of Bonadonna et al. "Physical Characterization of Long-Lasting Hybrid Eruptions: the Tajogaite Eruption of Cumbre Vieja (La Palma, Canary Islands)"</p>
Videos of lava flows on 16th November 2021 at the South Delta of the 2021 Cumbre Vieja eruption (La Palma, Canary Islands).
<p>Videos of field observations made on 16th November 2021 at 15:00 UTC from a point (UTM coordinates 28-R, 213992, 3167808 ) on the coastline of the South lava delta formed during the 2021 eruption of Cumbre Vieja volcanic rift at La Palma (Canary Islands).</p> <p>Video 1 shows a high-mobility lava flowed down the marine cliff over a well-developed ramp.</p> <p>Video 2 shows the ocean entrance of the lava flow, accompanied by the formation of a large gas plume in which vertical steam jets containing dark particulate matter. These jets, up to 10 m high, included lava fragments of diameter >10 cm that were projected to a maximum of 10–15 m away, following ballistic trajectories until falling into the sea and often leaving traces of white steam behind them. </p>
Gravity change data used in the paper "Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling"
<p>Gravity changes data observed in the network between July 2021 and January 2022 </p> <p>Reference:</p> <p>Insights into the magmatic feeding system of the 2021 eruption at Cumbre Vieja (La Palma, Canary Islands) inferred from gravity data modeling <br> F. G. Montesinos1,7, S. Sainz-Maza2,7, D. Gómez-Ortiz3, J. Arnoso4,7, I. Blanco-Montenegro5,7, M. Benavent1,7 E. Vélez4,7, N. Sánchez6 and T. Martín-Crespo3</p> <p>1 Facultad de CC. Matemáticas, Universidad Complutense de Madrid. Plaza de Ciencias 3, 28040 Madrid, Spain.<br> 2 Observatorio Geofísico Central (IGN). C/ Alfonso XII, 3. 28014 Madrid, Spain.<br> 3 Dpt. Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos. C/Tulipán s/n, 28933 Móstoles, Madrid, Spain.<br> 4 Instituto de Geociencias (IGEO), CSIC-UCM. C/ Doctor Severo Ochoa, 7. 28040 Madrid, Spain.<br> 5 Departamento de Física, Escuela Politécnica Superior, Universidad de Burgos. Avda. de Cantabria s/n, 09006 Burgos, Spain.<br> 6 Instituto Geológico y Minero de España (IGME, CSIC), Unidad Territorial de Canarias, Alonso Alvarado, 43, 2A, 35003 Las Palmas de Gran Canaria, Spain.<br> 7 Research Group ‘Geodesia’, Universidad Complutense de Madrid, Spain.</p> <p><br> Corresponding author: Fuensanta G. Montesinos (fuensant@ucm.es)</p> <p>This research is supported by the project PID2019-104726GB-I00/AEI/10.13039/501100011033 funded by the Spanish Research Agency. Further, the University Complutense of Madrid (grants Financiación Grupos 2021, UCM 2022-GRFN14/22) and the Spanish Ministry of Science and Innovation (RD 1078/2021, funding for research activities of the CSIC-PIE project CSIC-LAPALMA-07) supported this research.</p>
IDW interpolation dataset of ash and tephra deposition following the 2021 Tajogaite volcanic eruption on La Palma, Canary Islands, Spain
<p>The compiled dataset is the result of a field collection campaign to measure the depth of the ash and tephra layer in the aftermath of the 2021 volcanic eruption (Tajogaite) on the island of La Palma, Canary Islands, Spain.</p> <p>The dataset consists of two files: a shapefile and a GeoTIFF raster. The shapefile is a point layer file that displays the location of all ash depth measurements (415 points) taken in the field. To improve our sampling near the crater, where safety and time constraints prevented field collection, we manually sampled additional drone-based measurements (66 points). We combined these data into a single dataset ("ash_depth"; 481 total points) that was then used as input for a spatial interpolation using Inverse Distance Weighting (IDW).</p> <p>The IDW interpolation was performed using the Spatial Analyst toolbox in ArcMap 10.8.1 (Esri, 2021). As an exact deterministic interpolation, IDW estimates pixels values of unknown points by using average distance and a weight between sample points (Watson & Philip, 1985). This is ideal for a dataset that includes many field measurements since IDW interpolates between the minimum and maximum of the collected data. The model parameters were adjusted manually but the best results were yielded using the default settings, with the exception of the output cell size. The output cell size was calibrated to 2 m. The IDW parameters can be viewed in Table 1.</p> <p>The sample point locations were resampled from the raster file to estimate the Root Square Mean Error (RMSE) and were saved to the shapefile as "ash_idw". The RMSE of the dataset is 0.34 m. For further inquiries please contact Christopher Shatto (email: christopher.shatto@uni-bayreuth.de).</p> <p> </p> <p>Please cite the data paper link to this repository as: </p> <p><strong>C. Shatto, F. Weiser and A. Walentowitz et al., Volcanic tephra deposition dataset based on interpolated field measurements following the 2021 Tajogaite Eruption on La Palma, Canary Islands, Spain, Data in Brief, https://doi.org/10.1016/j.dib.2023.109949</strong></p> <p> </p> <table> <tbody> <tr> <td>Power</td> <td>2</td> </tr> <tr> <td>Output cell size</td> <td>2</td> </tr> <tr> <td>Search neighborhood type</td> <td>Standard (circular)</td> </tr> <tr> <td>Major/minor semiaxis</td> <td>12161.79/12161.79</td> </tr> <tr> <td>Max/minimum neighbors</td> <td>15/10</td> </tr> <tr> <td>Sector type</td> <td>1</td> </tr> <tr> <td>Angle</td> <td>0</td> </tr> <tr> <td>Weight field</td> <td>None</td> </tr> </tbody> </table> <p> </p>
FIGURE 4. Genital system. A in Hemicycla (Hemicycla) fuenterroquensis (Gastropoda: Helicoidea: Helicidae), a new species from La Palma, Canary Islands
FIGURE 4. Genital system. A, Hemicycla vermiplicata; B, H. fuenterroquensis sp. nov.; C, H. granomalleata; bc, bursa copulatrix; bd, bursa duct; cs, common stalk of the bursa copulatrix complex; d, diverticulum; ds, dart sac; e, epiphallus; f, flagellum; go, genital orifice; pp1, proximal penial papilla; pp2, distal penial papilla; pc, penial chamber; r, retractor muscle.
FIGURE 3. A in Hemicycla (Hemicycla) fuenterroquensis (Gastropoda: Helicoidea: Helicidae), a new species from La Palma, Canary Islands
FIGURE 3. A, Shell drawings of Hemicycla fuenterroquensis sp. nov., holotype, showing the placement of the measurements obtained for Table 1. B, Scatter plots of some shell measurements of the studied species. BH, body whorl height (at columella level); BP, body whorl frontal perimeter; BS, body whorl frontal surface (plane view); D1, maximum shell diameter; D2, shell diameter perpendicular to D1; FP, shell frontal perimeter; FS, shell frontal surface (plane view); SH, shell height; SP, shell perimeter (dorsal plane view); SS, shell surface (dorsal plane view).
FIGURE 2 in Hemicycla (Hemicycla) fuenterroquensis (Gastropoda: Helicoidea: Helicidae), a new species from La Palma, Canary Islands
FIGURE 2. Shells and details of the body whorl ornamentation of the three known Hemicycla species from La Palma Island. A, B, Hemicycla vermiplicata; C, D, H. fuenterroquensis sp. nov.; E, F, H. granomalleata. The arrows in Fig. 2 D highlight the weak microsculpture of the H. fuenterroquensis sp. nov. shell.
FIGURE 1 in Hemicycla (Hemicycla) fuenterroquensis (Gastropoda: Helicoidea: Helicidae), a new species from La Palma, Canary Islands
FIGURE 1. Geographical distribution of the known Hemicycla species from La Palma Island, and a detailed photograph of a Hemicycla fuenterroquensis sp. nov. specimen described in the present study.
Rock-magnetic, paleomagnetic and paleointensity data from a lava flow erupted on 4 December 2021 in La Palma (Canary Islands, Spain)
<p><span>The folder “1 Rock magnetic data VFTB La Palma” contains data in .txt format of IRM acquisition curves (extension .irm), hysteresis curves (extension .hys), backfield curves (extension .coe) and thermomagnetic curves (extension .rmp) obtained on a lava flow erupted on December 4<sup>th</sup>, 2021 in La Palma (Canary Islands, Spain). Extension .rmp files including Ms-T in their file name are for magnetisation vs. temperature measurements and those including k-T in their file name are for susceptibility vs. temperature measurements. Thermomagnetic and hysteresis measurements were first performed on original specimens and then again on the same specimens after having been heated. Files including “antes” in their filename are the original measurements and those including “despues” in their file name correspond to heated samples. All measurements were performed on a Variable Field Translation Balance (VFTB) in the paleomagnetic laboratory of the University of Burgos (Spain). Columns are separated by tabs. Data can be visualised and analysed with the </span><span>RockMagAnalyzer 1.0 software (Leonhardt, 2006).</span></p> <p><span> </span></p> <p><span>The folder “2 Rock magnetic data k_fd and IRM analysis” contains four files of IRM acquisition data for the analysis of coercivity spectra (CV2-4ir0.asc, CV2-4ir7.asc, CV2-17i0.asc, CV2-17i7.asc) and one file with low- and high-frequency (470 and 4750 Hz) susceptibility data (susceptibility.asc) </span><span>obtained on a lava flow erupted on December 4<sup>th</sup>, 2021, in La Palma (Canary Islands, Spain). All files have an .asc extension containing characters in ASCII format.<a name="_Hlk171719051"></a> </span></p> <p><span><span>IRM acquisition data: (i) </span></span><span><span>File CV2-4ir0.asc</span></span><span>: progressive IRM acquisition of sample CV02-04 with remanence measurement immediately after field application. (ii) File CV2-4ir7.asc: progressive IRM acquisition of sample CV02-04 with remanence measurement 7 minutes after field application. (iii) File CV2-17i0.asc: progressive IRM acquisition of sample CV02-17 with remanence measurement immediately after field application. (iv) </span><span>File CV2-17i7.asc:</span><span> progressive IRM acquisition of sample CV02-17 with remanence measurement 7 minutes after field application. Column 1: measurement number; column DEMAG: first step<span> </span>(100mT) is zero value after AF demagnetisation at 100 mT, following values are IRM acquisition field steps in mT; columns CD, CI, ISD, ISI, RD, RI are declination and inclination values in sample, field corrected and bedding corrected coordinates; column M: magnetic moment in emu; column J: magnetisation in emu/g; columns X, Y, Z display magnetic moment X, Y and Z coordinates. As in IRM acquisition experiments the applied field was directed towards the sample z-axis, IRM values can be obtained by dividing column Z by the sample mass value (given in g), which is found under the tag “SIZE”.<span> </span>Coercivity spectra analysis has been performed with the MAX UnMix software (Maxbauer et al., 2016).</span></p> <p><span>File susceptibility.asc includes data from three </span><span>low-frequency (LF) and three high-frequency (HF) susceptibility measurements performed on two samples.</span></p> <p><span> </span></p> <p><span>The folder “3 Rock magnetic data FORC” contains three files with first order reversal curves data data obtained on three samples from a lava flow erupted on December 4<sup>th</sup>, 2021, in La Palma (Canary Islands, Spain). Data can be analysed using the </span><span>FORCinel software (Harrison and Feinberg, 2008).</span></p> <p><span> </span></p> <p><span>The folder “4 Paleomagnetic data La Palma” contains two folders with paleomagnetic thermal and alternating field demagnetisation data obtained on a lava flow erupted on December 4<sup>th</sup>, 2021, in La Palma (Canary Islands, Spain). Measurements were performed with a cryogenic magnetometer in the paleomagnetic laboratory of the University of Burgos (Spain). Data are in .txt format with the extension .rs3. Columns are separated by empty spaces. In AF measurements, a value of 100 must be subtracted from all AF demagnetisation steps to obtain the real AF-step value (i.e., a demagnetisation step of 165 really means 65 mT). Data can be visualised and analysed with the </span><span>Remasoft software (Chadima and Hrouda, 2006).</span></p> <p><span> </span></p> <p><span>The folder “</span><span>5 Thellier-Coe paleointensity data</span><span>” contains paleointensity determination data obtained with the Thellier-Coe method on a lava flow erupted on December 4<sup>th</sup>, 2021 in La Palma (Canary Islands, Spain). Experiments were carried out at the paleomagnetic laboratory of the University of Burgos (Spain). Data are in .txt format with the extension .tdt separated by tabs. Data can be visualised and analysed with the </span><span>ThellierTool software (Leonhardt et al.,2004).</span></p> <p><span> </span></p> <p><span>The folder “6 Multispecimen paleointen</span><span>sity data” contains a file (CVC02_MSP_Am2.txt) with </span><span>data of 3 paleointensity determinations from the Tajogaite volcano eruption on December 4th, 2021, in the island of La Palma (Canary Islands, Spain). These data were obtained with the multispecimen method (Biggin and Poidras, 2006; Dekkers and Böhnel, 2006; Fabian and Leonhardt, 2010) at the paleomagnetic laboratory of the University of Burgos (Spain). The data are in the "MSP generic format" for the online application Paleoinetnsity.org (Béguin et al., 2020), Multispecimen Protocol option. Each determination consists of five different heating steps (m0, m1, m2, m3 and m4) applied to 8 different specimens.</span></p> <p><span> </span></p> <p><span>The folder “7 Tsunakawa-Shaw paleointensity” contains four folders with paleointensity determination data obtained with the Tsunakawa-Shaw method. The folder named “csv” contains the outcome of the best fit interpretation performed by the Jupyter notebook. The folder “d” contains the original demagnetization data obtained for each specimen. The folder “MagIC” contains the outcome compatible with MagIC software. The folder “plots” contains the outcome plots of the best fit interpretation in .pdf format. These experiments were carried out in the <em>Paleomagnetism Laboratory at the Kochi Core Centre in Kochi University, Japan</em>. Data can be visualised and analysed through Jupyter, using the “TS_analysis_G-cubed_r20230714_cvc02” available in the folder. </span></p> <p><strong><span> </span></strong></p> <p><strong><span>REFERENCES</span></strong></p> <p><span> </span></p> <p><span>Béguin, A., Paterson, G. A., Biggin, A. J., & de Groot, L. V. (2020).<span> </span>Paleointensity org: an online, open source, application for the interpretation of paleointensity data. Geochemistry, Geophysics, Geosystems, 21, e2019GC008791,</span> <span>https://doi.org/10.1029/2019GC008791<span> </span>.</span></p> <p><span>Biggin, A., Poidras, T., 2006. First-order symmetry of weak-field partial thermoremanence in multi-domain ferromagnetic grains. 1. Experimental evidence and physical implications. Earth Planet. Sci. Lett. 245, 438–453. doi:10.1016/j.epsl.2006.02.035</span></p> <p><span>Chadima, M. and Hrouda, F., 2006. Remasoft 3.0 a user friendly paleomagnetic data browser and analyzer. <em>Travaux Géophysiques</em>, XXVII, 20-21.</span></p> <p><span>Dekkers, M.J., Böhnel, H.N., 2006. Reliable absolute palaeointensities independent of magnetic domain state. Earth Planet. Sci. Lett. 248, 507–516. doi:10.1016/j.epsl.2006.05.040</span></p> <p><span>Fabian, K., Leonhardt, R., 2010. Multiple-specimen absolute paleointensity determination: An optimal protocol including pTRM normalization, domain-state correction, and alteration test. Earth Planet. Sci. Lett. 297, 84–94. doi:10.1016/j.epsl.2010.06.006</span></p> <p><span>Harrison, R.J. and Feinberg, J.M. (2008), FORCinel: An improved algorithm for calculating first-order reversal curve distributions using locally weighted regression smoothing. <em>Geochem. Geophys. Geosyst.</em>, 9, Q05016, doi:10.1029/2008GC001987.</span></p> <p><span>Leonhardt, R., Heunemann, C. and Krása, D., 2004. Analyzing absolute paleointensity determinations: Acceptance criteria and the software ThellierTool4.0. <em>Geochem. Geophys. Geosyst.</em>, Vol. 5, no. 12, doi.: 10.1029/2004GC000807.</span></p> <p><span>Leonhardt, R., 2006. Analyzing rock magnetic measurements; The RockMagAnalyzer 1.0 software. <em>Computers and Geosciences</em>, 32, 1420-1431.</span></p> <p><span><span> </span></span><span>Maxbauer, D.P., Feinberg, J.M., Fox, D.L., 2016. MAX UnMix: A web application for unmixing magnetic coercivity distributions. <em>Comput. Geosci.</em> 95, 140–145. https://doi.org/10.1016/j.cageo.2016.07.009</span></p>
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.