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30 results for “south pole”
Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration
<p>Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration</p> <p>Data contains the georeferenced map plate of our geologic map that can be used in any geoinformation system (GIS).</p> <p><strong>If you use these data, please cite BOTH the Planetary Science Journal publication and the Zenodo dataset.</strong></p> <p>Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. <em>The Planetary Science Journal</em>, <em>5</em>(6), 147. <a href="https://iopscience.iop.org/article/10.3847/PSJ/ad2c04">https://iopscience.iop.org/article/10.3847/PSJ/ad2c04</a></p> <p>Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Supplementary Data for Wueller et al. (2024): Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. <em>Zenodo Dataset</em>. <a href="https://doi.org/10.5281/zenodo.10693820" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10693820</a></p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>Mapping Scale is 1:100,000</p> <p>Print Scale is 1:1,000,000</p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>For further questions contact lwueller@uni-muenster.de</p> <p>Lukas Wueller, Institut für Planetologie, Universität Münster, Germany, June 2024</p>
Supplementary material to: Highly resolved topography and illumination at Mercury south pole from MESSENGER MDIS-NAC
<p>We produced a new higher-resolution topographic map of Mercury’s south polar region (75°-90° South, covering ~1.3 million km<sup>2</sup>) by using data collected by the NASA MESSENGER spacecraft’s Mercury Dual Imaging System (MDIS; Hawkins et al, 2007) over the years 2011-2015. This new map enables, <em>e.g.</em>, the first detailed modeling of illumination and thermal conditions in these southern radar-bright locations and the first constraints on the nature and history of volatiles residing there, but it is also intended as a resource for other geophysical analyses and for the preparation of the BepiColombo mission, currently en-route to the planet.</p> <p>For more details, please visit <a href="https://pgda.gsfc.nasa.gov/products/88">https://pgda.gsfc.nasa.gov/products/88</a>.</p> <p><strong>Products:</strong></p> <p>DEM (interpolated), DEM (filled), Slopes, PSR masks</p> <p>All these files (except the PSR masks shapefile) are 250 m/pix GeoTiffs with south polar stereographic X/Y coords in meters.</p> <p><br> <em>If using these products, please cite:</em><br> Bertone, S., E. Mazarico, M.K. Barker, M. Siegler, J. M. Martinez Camacho, C. Hamill, A. Glatzenberg, N. L. Chabot, 2022: <em>Highly resolved topography and illumination at Mercury south pole from MESSENGER MDIS-NAC</em>. The Planetary Science Journal, 02/2023, <a href="http://dx.doi.org/10.3847/PSJ/acaddb">doi:10.3847/PSJ/acaddb</a></p>
Endmember spectra and classified maps derived from CRISM targeted data at the south pole of Mars
<p><strong>Overview</strong></p> <p>Current maps of compositional variation across south polar ice exposures on Mars do not resolve the meter-scales at which erosional processes are most active, ultimately limiting our understanding of how the deposits form and evolve and how they can be used to interpret long-term climate records. In this study, we use <em>k</em>-means clustering and random forest classification to identify and map a set of universal spectral endmembers across 167 high-resolution observations acquired during southern summer by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). The 21 endmembers show distinct combinations and strengths of key infrared absorption features reflecting diverse mixtures of CO<sub>2</sub> ice, H<sub>2</sub>O ice, and dust. The resulting compositional framework can be used to characterize the nature of both seasonal CO<sub>2</sub> frost and the residual ices it overlies across a variety of terrains. </p> <p> </p> <p><strong>Contents</strong></p> <p>The repository contains three .zip files, which can be expanded to access the files described below:</p> <ul> <li><strong>classified_maps.zip</strong> <ul> <li>lookup_files <ul> <li><em>SP_CRISM_RF_ColorMap.clr</em> : An ESRI-formatted color map file that can be used to apply the endmember color scheme to random forest-classified maps in ArcGIS (see Symbology settings).</li> <li><em>SP_CRISM_RF_ColorMap.txt</em> : A text file that can be loaded into Python as a numpy array and used to generate a matplotlib color ramp. Row indices correspond to endmember numbers (see below) and columns are red, green, and blue values scaled from 0 to 1.</li> <li><em>SP_CRISM_RF_Endmember_Lookup.csv</em> : A lookup table that can be used to cross-reference between endmember numbers (as stored in GeoTiffs or the indices of the colormaps above) and corresponding endmember names (C1, Dc2, etc.).</li> </ul> </li> <li>morphologic_reference <ul> <li>Contains GeoTiffs of the R1330 spectral parameter (reflectance at 1330 nm) for each processed CRISM observation. Filenames indicate the observation ID, Mars Year, and solar longitude (Ls) of acquisition ("Ls314-07" = Ls 314.07º). These images can be used as a reference for the surface morphology and albedo of each scene. Tie points used to georeference these images to other datasets can be applied to the random forest classification maps to properly align endmember mapping results.</li> </ul> </li> <li>random_forest_classification <ul> <li>Contains GeoTiffs of the random forest classification results for each processed CRISM observation. Filenames indicate the observation ID, Mars Year, and solar longitude (Ls) of acquisition ("Ls314-07" = Ls 314.07º). These images are not rendered to display colors consistent with the publication figures, but instead store the endmember classification for each pixel as a number from 0 to 21; use the contents of <em>lookup_files</em> to find the corresponding endmember name or render the image with the color scheme from the publication. To view rendered summary plots of each observation, see the contents of <em>observation_info</em>. To georeference these images to other datasets, use the corresponding morphologic reference (see above) to set tie points.</li> </ul> </li> </ul> </li> <li><strong>observation_info.zip</strong> <ul> <li>footprint_shapefile <ul> <li>Contains the components of an ESRI shapefile that outlines the surface footprint/coverage of each processed CRISM observation. The attributes associated with each observation are the same as those in <em>observation_lookup</em> below. Note that the polygons extend slightly beyond the area shown in maps in <em>random_forest_classification</em> due to the inclusion of border pixels.</li> </ul> </li> <li>observation_lookup <ul> <li><em>SP_CRISM_Classified_Obs_Info.csv</em> : Information on each processed CRISM observation; this is the same file as Table S1 in the publication. Includes the MY and Ls of acquisition and (where applicable) the figure panel where the observation appears in the publication. The location of each observation is indicated with Center Latitude/Longitude and the assigned Spatial Domain (see Figure 1 in the publication). The Observation ID can be used to locate the source Targeted Reduced Data Record (TRDRs, Version 3) on the Geosciences Node of the Planetary Data System. The spatial extent of each observation is provided in the <em>footprint_shapefile</em> described above. </li> </ul> </li> <li>summary_plots <ul> <li>Contains summary plots of the endmember map generated for each processed CRISM observation. Each plot notes the observation ID, Mars Year, and Ls and displays the morphologic reference map, random forest classification map, and a breakdown of the endmembers that are present. To access the maps rendered here, see the contents of <em>classified_maps.zip</em>.</li> <li>Also contains the full-resolution version of Figure S3 from the publication (<em>All_Obs_Unprojected.png</em>), which can be used to lookup observations of interest via small labels above each map. </li> </ul> </li> </ul> </li> <li><strong>spectral_library.zip</strong> <ul> <li>Contains spectral libraries with the median spectrum of each endmember as presented in Figure 3 in the publication. A basic text file listing the wavelength (WVL) and normalized reflectance values for each endmember is included (<em>SP_CRISM_EndmemberMedians.txt</em>) as well as an ENVI-formatted spectral library (S<em>P_CRISM_EndmemberMedians_ENVI.sli</em>). Note that a subset of the 438 wavelengths sampled in the source CRISM data were removed around the longest and shortest wavelengths and the filter boundary to avoid error-prone bands, leaving these spectral libraries with 404 bands.</li> </ul> </li> </ul>
Mini-RF S-band Radar Characterization of a Lunar South Pole-Crossing Tycho Ray: Implications for Sampling Strategies
<p>Data behind the figures for the publication in the Planetary Science Journal. Data is in .mat format, which is a Matlab save file which can also be read by open languages such as Python. The accompanying code, in .m format, is a Matlab code that will recreate the figures. The .m code can be read by any text editor application. All figures are also provided as pngs. Figures 7 and 8 are provided as GeoTiffs, where the first channel is S1, second channel S2, third channel S3, and the fourth channel S4 (i.e., the four Stokes parameters).<br>Figures.zip is a zip file with all of the figures in png format.<br>FiguresData.zip includes two files: MakeFigures.m, which is the matlab code that will recreate the figures, and RiveraValentinETAL_2024_PSJ_AccompanyingData.mat, which is that matlab data needed to recreate the figures. The .m file contains a header describing each variable in the .mat file. <br>GeoTiffs.zip contains two files, newton_stokes.tiff and haworth_stokes.tiff. These are GeoTiffs of Figures 7 and 8, respectively. </p>
Datasets for 'Multiple impact sources for light plains around the lunar south pole' research paper
<p>The attached datasets are the shapefiles (areas and crater measurements) for the article ' Multiple impact sources for light plains around the lunar south pole'.</p> <p>The shapefiles can be directly imported in ArcPRO. </p> <p>Also attached is a .png file (image) of the study region with the 22 dated light plains and smooth crater floors color-coded by age, Fig. 4 in the research paper.</p>
Moon South Pole Permanent Shadowed Regions
<p>File containing PSRs at the lunar south pole</p>
Endmember spectra and classified mosaics derived from CRISM mapping data at the south pole of Mars
<p><strong>Overview</strong></p> <p>Multispectral mapping data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provide a unique opportunity to characterize south polar ice deposits at higher spectral sampling, spatial resolution, or spatiotemporal coverage than previous work. This new perspective can help to constrain the nature and distribution of different mixtures of CO<sub>2</sub> ice, H<sub>2</sub>O ice, and dust that influence the formation, evolution, and preservation of Mars climate records. We processed 1103 CRISM observations spanning southern summer of six Mars Years through a combination of <em>k</em>-means clustering and random forest classification. Using a set of 12 spectral endmembers directly tied to previous work with high-resolution CRISM targeted data, we made a series of temporally restricted mosaics showing surface spectral variation over time. The endmember set and classified mosaics produced in this work can provide critical context for future studies of the dynamic processes that shape south polar ice deposits.</p> <p>This is follow-on work to a previous study that produced a series of classified maps and a spectral library from CRISM targeted data. That work can be accessed with the following links:</p> <ul> <li>Publication: <a href="https://doi.org/10.1029/2022JE007372">https://doi.org/10.1029/2022JE007372</a></li> <li>Repository: <a href="https://doi.org/10.5281/zenodo.6960943">https://doi.org/10.5281/zenodo.6960943</a></li> </ul> <p><strong>Contents</strong></p> <p>The repository contains two .zip files, which can be expanded to access the files described below:</p> <ul> <li><strong>classified_mosaics.zip</strong> <ul> <li>lookup_files <ul> <li><em>SP_CRISM_RF_ColorMap.clr</em> : An ESRI-formatted color map file that can be used to apply the endmember color scheme to random forest-classified maps in ArcGIS (see Symbology settings). Note that for continuity with <em>Cartwright (2022),</em> there are 21 colors in this file, though only endmembers associated with 12 of those colors are present in the classified mosaics.</li> <li><em>SP_CRISM_RF_ColorMap.txt</em> : A text file that can be loaded into Python as a numpy array and used to generate a matplotlib color ramp. Row indices correspond to endmember numbers (see below) and columns are red, green, and blue values scaled from 0 to 1. Note that for continuity with <em>Cartwright (2022),</em> there are 21 colors in this file, though only endmembers associated with 12 of those colors are present in the classified mosaics.</li> <li><em>SP_CRISM_RF_Mapping_Endmember_Lookup.csv</em> : A lookup table that can be used to cross-reference between endmember numbers (as stored in GeoTiffs or the indices of the colormaps above) and corresponding endmember names (C1m, Dc3m, etc.). Note that for continuity with <em>Cartwright (2022),</em> the endmember numbers are not sequential and instead correspond to the number of the original reference spectrum (e.g., C1m in this work has the same endmember number as C1 in <em>Cartwright (2022)</em>).</li> </ul> </li> <li>random_forest_classification <ul> <li>Contains GeoTiff mosaics of random forest classification results. Mosaics compile all observations falling in 10º bins of solar longitude (Ls) for a given year, provided that data was acquired in that range. Classified observations are stacked in ascending order of Ls. Mosaics of MSW data have a resolution of ~90 m/pixel while mosaics of MSP or combined MSP and MSW data have a resolution of ~180 m/pixel. Filenames indicate the observation type ("MSP", "MSW", or combined "MSP-MSW"), Mars Year ("MY28", "MY29", etc.) and Ls range ("Ls300-310" indicates all observations acquired between Ls 300º and Ls 310º). These images are not rendered to display colors consistent with the publication figures, but instead store the endmember classification for each pixel as a number from 0 to 21; use the contents of <em>lookup_files</em> to find the corresponding endmember name or render the image with the color scheme from the publication. To view rendered summary plots of each observation, see the contents of <em>summary_plots </em>below.</li> </ul> </li> <li>summary_plots <ul> <li>Contains summary plots of the endmember-classified mosaics provided in <em>random_forest_classification </em>above<em>.</em> Each plot presents the classified mosaic over a grey outline approximating the extent of high-albedo CO<sub>2</sub> ice in the south polar residual cap (SPRC). Note that the summary view focuses on the area in and around the SPRC, but the full mosaics may extend beyond these bounds. </li> </ul> </li> </ul> </li> <li><strong>spectral_library.zip</strong> <ul> <li>Contains spectral libraries with the median spectrum of each endmember as presented in Figure 3 in the publication. A basic text file listing the wavelength (WVL) and normalized reflectance values for each endmember is included (<em>SP_CRISM_MappingEndmemberMedians.txt</em>) as well as an ENVI-formatted spectral library (S<em>P_CRISM_MappingEndmemberMedians_ENVI.sli</em>). Note that a subset of the 55 wavelengths sampled in the source CRISM data were removed to avoid error-prone bands, leaving these spectral libraries with 51 bands. The spectra are normalized by the value at 1.330 µm.</li> </ul> </li> </ul>
Shallow subsurface water-ice distribution in the lunar south pole: Analysis based on Mini-RF and multi-metrics
Open the record for dataset details and reuse information.
Mantle melting conditions of mare lavas on South Pole–Aitken basin of lunar farside
<p>supplementary dataset for the paper submitted to GRL, titled 'Mantle melting conditions of mare lavas on South Pole–Aitken basin of lunar farside'</p>
The datasets for the paper "Spatial and temporal distribution of lobate scarps in the lunar south polar region: Evidence for latitudinal variation of scarp geometry, kinematics and formation ages, continuous tectonic activity in the last 100 million years and seismically safe south pole Artemis human landing site" Geophysical Research Letters.
<p>This dataset provides the original data that were used for preparing the illustrations, figures and tables.</p>
2019-Xunyu Zhang-Mafic minerals in the South Pole-Aitken basin
<p>It is the dataset of extracted spectra and their location used in the paper "Mafic minerals in the South Pole-Aitken basin".</p>
2020-Xunyu Zhang-Thickness of orthopyroxene-rich materials of ejecta deposits from the South Pole-Aitken basin
<p>This is the detailed information for the article "Thickness of orthopyroxene-rich materials of ejecta deposits from the South Pole-Aitken basin", including the names, diameters, central coordinates, and stratigraphic ages of craters and basins in the South Pole-Aitken basin region.</p>
Lunar heat flow constrained from Chang'E-2 Microwave Radiometer and Diviner observations at the Moon's south pole
<p>This data repository includes the Chang'E-2 microwave radiometer data which is provided by the Ground Research and Application System of Chinese Lunar Exploration Program.</p>
Data sets associated with "Deep structure of the lunar South Pole–Aitken basin"
<p>These grid files contain the data used in Figures 2 and 3 of the submitted manuscript, "Deep structure of the lunar South Pole–Aitken basin". Although the data are global, note that they are not meant to be used outside of the South Pole–Aitken basin.</p>
"RadioICE" McMurdo-South Pole HF sounder data from 2019
<p>Results of the 12-frequency sounding experiment described in Chartier et al. (2020). https://amt.copernicus.org/articles/13/3023/2020/amt-13-3023-2020.html</p> <p> </p>
Acetylene and ethane surface flask measurements from Cape Grim, Australia and South Pole, Antarctica
Open the record for dataset details and reuse information.
First ISCCP Regional Experiment (FIRE) Cirrus 1 Surface Radiation Budget (SRB) Data over the South Pole
Results from ISCCP analysis of B3 radiance data (sampled to 25 km). Unlike the standard ISCCP product, these data are reported at original pixel resolution and contain detailed information about the algorithm decision.Data covers the region from: 55 degrees South to 90 degrees South (-55 to -90), 180 degrees West to 180 degrees East (-180 to +180). (Polar projection covers 55S - 90S or 55N - 90N, maximum; Midlatitude maps cover 55S to 55N, maximum.)Spatially sampled imaging data. Nominal spatial resolution is 25 km. Pixel field of view is 4 km (NOAA data). Earth location (latitude +/- 90 degrees, longitude +/- 180 degrees) is obtained for each pixel from ancillary data.
Data files used in the paper " Multiple subglacial water bodies below the south pole of Mars unveiled by new MARSIS data "
<pre>Each file corresponds to a MARSIS radar acquisition on the Ultima Scopuli on Mars. The Data are in ASCII format and they organized as a follow: first row: operating frequency in MHz second row: longitude in degree third row: latitude in degree forth row: spacecraft height from fifth row to the end row: amplitude radar signal The name of the file corresponds to name of the MARSIS orbit</pre>
Gazetteer of Planetary Nomenclature: Moon: 1:10 million-scale Shaded Relief and Color-coded Topography: South Pole
These lunar maps display the four different areas of the moon with color-coded topography in low and high resolution approved by the International Astronomical Union (IAU).
Spitzer South Ecliptic Pole MIPS 24 micron Point Source Catalog
The Spitzer/MIPS 24 and 70 μm imaging of an 11.5 square degree region near the South Ecliptic Pole (SEP) has been carried out in order to complement sub-millimeter wavelength observations (250-500 μm) of the same region of sky taken with the Balloon-borne Large Aperture Sub-millimeter Telescope (BLAST), with the goal of better characterizing the nature of sub-millimeter selected galaxies and their role in galaxy evolution. This field has also been extensively mapped at other wavelengths, and will be imaged from 100-500 μm as part of the Herschel Multi-tiered Extragalactic Survey (HerMES). Source detection and photometry were performed using the APEX software within the MOPEX package. Source candidates with S/N > 5 and reduced chi-squared values less than or equal to three (97% of the sources) are considered reliable detections. The remaining source candidates were then inspected (see Scott et al. 2010 for details) and false positives were removed from the catalog. Some sources in the catalog are flagged as possible false positives; see the status field.
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International Brain Laboratory public data
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