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9 results for “intensity mapping”
21 cm intensity mapping: a 900 - 1300 MHz full-sky simulation
<p>This HDF5 file stores the simulation used and described in <a href="http://dx.doi.org/10.1093/mnras/staa2854">Recovery of 21 cm intensity maps with sparse component separation</a> (<a href="https://arxiv.org/abs/2006.05996">arXiv:2006.05996</a>). It is a collection of intensity maps in units of mK, full-sky, in HEALPIX format with nside=256. There are 5 components: 1. 21cm cosmological signal, 2. galactic free-free diffuse emission, 3. galactic synchrotron diffuse emission, 4. extragalactic point sources and background and 5. instrumental polarization leakage. For each component, there are 400 maps, corresponding to 400 channels of 1 MHz from 900 to 1300 MHz. In <a href="https://doi.org/10.1093/mnras/staa2854">the main paper</a> the simulation is used to test the algorithm GMCA as a foreground removal method for 21cm intensity mapping. A practical example of how to use these data and apply GMCA on them is shown at this GitHub <a href="https://github.com/isab3lla/gmca4im">repository</a>.</p> <p>If you are using this dataset or the tools developed to work with it, please do not forget to cite the dataset itself as well as the relevant publication.</p>
Cropping intensity maps for Vojvodina, Serbia
<p>This dataset represents cropping intensity maps in Vojvodina (Serbia) for 2022 and 2023, characterized by different weather conditions. These maps have a resolution of 10 meters and were created using machine learning techniques applied to Sentinel-2 data, along with on-site collected ground truth data.<br>The maps are in .tiff format and include the following classes:</p> <ul> <li>single summer cropping (0)</li> <li>single winter cropping (1)</li> <li>double-cropping (2)</li> <li>clover (3)</li> <li>other (4).</li> </ul>
Open-SEA-Rice-10: Open Access High-Resolution Maps of Rice Harvested Area and Cropping Intensity in Southeast Asia
<h2>Cite this article</h2> <p>Ginting, F.I., Rudiyanto, R., Fatchurrachman, F., Mohd Shah, R., Che Soh, N., Goh Eng Giap, S., Fiantis, D., Setiawan, B.I., Schiller, S., Davitt, A., Minasny, B. High-resolution maps of rice cropping intensity across Southeast Asia. Scientific Data [12, 1408] (2025). <a href="https://www.nature.com/articles/s41597-025-05722-1">https://doi.org/10.1038/s41597-025-05722-1</a></p> <p> </p> <h2>Data Description</h2> <p>The datasets are high-resolution mapping of rice cropping intensity across Southeast Asia using the integration of Sentinel-1 and Sentinel-2 data</p> <ul> <li>The data file is in “.tif" format</li> <li>Spatial extent: Southeast Asia</li> <li>Pixel size: 10 m</li> <li>Projection information: EPSG: 4326</li> <li>CropType: Paddy rice.</li> <li>Year: Values from 2021</li> <li>Raster class:<br>-1 is single rice cropping area; <br>-2 is double rice cropping area and<br>-3 is triple rice cropping area</li> <li>The data also can be viewed on the GEE App (<a href="https://ee-rudiyanto.projects.earthengine.app/view/open-sea-rice-10">https://ee-rudiyanto.projects.earthengine.app/view/open-sea-rice-10</a>) and the Climate TRACE platform (<a href="https://climatetrace.org/">https://climatetrace.org/</a>) </li> <li>Correspondence to: Rudiyanto (rudiyanto@umt.edu.my) and Budiman Minasny (budiman.minasny@sydney.edu.au)</li> </ul> <p> </p> <p> </p>
Companion data of a Systematic Mapping Study of Programming Languages for Data-Intensive HPC Applications
<p>As the current existing literature on the topic of HPC is very dispersed, we performed a Systematic Mapping Study (SMS) in the context of the European COST Action cHiPSet. This literature study maps characteristics of various programming languages for data-intensive HPC applications, including category, typical user profiles, effectiveness, and type of articles.</p> <p>We organised the SMS in two phases. In the first phase, relevant articles are identified employing an automated keyword-based search in eight digital libraries. This lead to an initial sample of 420 papers, which was then narrowed down in a second phase by human inspection of article abstracts, titles and keywords to 152 relevant articles published in the period 2006--2018. The analysis of these articles enabled us to identify 26 programming languages referred to in 33 of relevant articles. This document is the data companion for a paper published elsewhere and presents a detailed list of the selected papers. Besides, the document also presents the form of our questionnaire-based survey. </p> <p>We also include the filled in questionnaires and raw data of the referred survey. To validate the SMS results we conducted a survey (in November 2018) with 28 HPC experts involved in the cHiPSet COST action to which we added, in October 2019, 29 HPC experts which were not involved in that COST action. Participants were recruited through convenience sampling, and contacted directly by the authors. In total, we received 57 filled survey forms.</p>
Companion data of a Systematic Mapping Study of Programming Languages for Data-Intensive HPC Applications
<p>As the current existing literature on the topic of HPC is very dispersed, we performed a Systematic Mapping Study (SMS) in the context of the European COST Action cHiPSet. This literature study maps characteristics of various programming languages for data-intensive HPC applications, including category, typical user profiles, effectiveness, and type of articles.</p> <p>We organised the SMS in two phases. In the first phase, relevant articles are identified employing an automated keyword-based search in eight digital libraries. This lead to an initial sample of 420 papers, which was then narrowed down in a second phase by human inspection of article abstracts, titles and keywords to 152 relevant articles published in the period 2006--2018. The analysis of these articles enabled us to identify 26 programming languages referred to in 33 of relevant articles. This document is the data companion for a paper published elsewhere and presents a detailed list of the selected papers. Besides, the document also presents the form of our questionnaire-based survey. </p> <p>We also include the filled in questionnaires and raw data of the referred survey. To validate the SMS results we conducted a survey (in November 2018) with 28 HPC experts involved in the cHiPSet COST action to which we added, in October 2019, 29 HPC experts which were not involved in that COST action. Participants were recruited through convenience sampling, and contacted directly by the authors. In total, we received 57 filled survey forms.</p>
Data from: Genome-wide association mapping of phenotypic traits subject to a range of intensities of natural selection in Timema cristinae
The genetic architecture of adaptive traits can reflect the evolutionary history of populations and also shape divergence among populations. Despite this central role in evolution, relatively little is known regarding the genetic architecture of adaptive traits in nature, particularly for traits subject to known selection intensities. Here we quantitatively describe the genetic architecture of traits that are subject to known intensities of differential selection between host plant species in Timema cristinae stick insects. Specifically, we used phenotypic measurements of 10 traits and 211,004 single-nucleotide polymorphisms (SNPs) to conduct multilocus genome-wide association mapping. We identified a modest number of SNPs that were associated with traits and sometimes explained a large proportion of trait variation. These SNPs varied in their strength of association with traits, and both major and minor effect loci were discovered. However, we found no relationship between variation in levels of divergence among traits in nature and variation in parameters describing the genetic architecture of those same traits. Our results provide a first step toward identifying loci underlying adaptation in T. cristinae. Future studies will examine the genomic location, population differentiation, and response to selection of the trait-associated SNPs described here.
Subspecies and Distribution. T.n.napuF.Cuvier,1822—SMyanmar,Thai/MalayPeninsula,islandsoffWMalayPeninsula(Langkawi&Pangkor),Borneo,SSumatra,BangkaI,islandsoffBorneo(Laut&Serasan). T.n.bangue:Chasen&Kloss,1931—BanggiIandBalembanganI,offNBorneo. T.n.bunguranensisMiller,1901—NatunaIs(=Bunguran),oftWBorneo. T.n.neubronneriSody,1931—NSumatra. T.n.nmiasisLyon,1916—NiasI,offWSumatra. T.n.rufulusMiller,1900—TiomanI,offEMalayPeninsula,RiauandLinggaArchipelagos. T. n. terutus Thomas & Wroughton, 1909 — Terutau I, off W Malay Peninsula. The species was recently reconfirmed for Singapore. Maps that include Vietnam, Cambodia, and Laos in the distribution range are based on the earlier assumption that 7. versicolor was a subspecies of 1. napu. Subsequent studies have indicated that 7. versicolor is a distinct species, and that the range of 1. napu therefore does not extend into Cambodia, Laos, and Vietnam. The northern limit on the Thai-Malay peninsula is not well defined. Specimens of 1. napu have been collected from as far north as Bankachon in southern Myanmar (10° 08" N), but despite fairly intensive camera-trapping in Kui Buri National Park, Thailand (12° N), 7. napu has not been photographed there. At the northern margin ofits range, it is generally rare. It has been reported, for example, that during the flooding of the Chiew Larn Reservoir (Surat Thani Province; about 9° N, 98° 45' E), only six 7. napu were rescued compared with 172 71. kanchil. This area is the transition zone from wetter evergreen forest to drier deciduous types, and it might be that 7° napu is not well adapted to the drier forest types towards the northern limit ofits range. There are unconfirmed reports of the species on Java, where it may have been confused with one of the two color morphs of 7. javanicus. As explained in the Taxonomy section, the subspecific status of the populations of several islands remains unclear. in Tragulidae
Subspecies and Distribution. T.n.napuF.Cuvier,1822—SMyanmar,Thai/MalayPeninsula,islandsoffWMalayPeninsula(Langkawi&Pangkor),Borneo,SSumatra,BangkaI,islandsoffBorneo(Laut&Serasan). T.n.bangue:Chasen&Kloss,1931—BanggiIandBalembanganI,offNBorneo. T.n.bunguranensisMiller,1901—NatunaIs(=Bunguran),oftWBorneo. T.n.neubronneriSody,1931—NSumatra. T.n.nmiasisLyon,1916—NiasI,offWSumatra. T.n.rufulusMiller,1900—TiomanI,offEMalayPeninsula,RiauandLinggaArchipelagos. T. n. terutus Thomas & Wroughton, 1909 — Terutau I, off W Malay Peninsula. The species was recently reconfirmed for Singapore. Maps that include Vietnam, Cambodia, and Laos in the distribution range are based on the earlier assumption that 7. versicolor was a subspecies of 1. napu. Subsequent studies have indicated that 7. versicolor is a distinct species, and that the range of 1. napu therefore does not extend into Cambodia, Laos, and Vietnam. The northern limit on the Thai-Malay peninsula is not well defined. Specimens of 1. napu have been collected from as far north as Bankachon in southern Myanmar (10° 08" N), but despite fairly intensive camera-trapping in Kui Buri National Park, Thailand (12° N), 7. napu has not been photographed there. At the northern margin ofits range, it is generally rare. It has been reported, for example, that during the flooding of the Chiew Larn Reservoir (Surat Thani Province; about 9° N, 98° 45' E), only six 7. napu were rescued compared with 172 71. kanchil. This area is the transition zone from wetter evergreen forest to drier deciduous types, and it might be that 7° napu is not well adapted to the drier forest types towards the northern limit ofits range. There are unconfirmed reports of the species on Java, where it may have been confused with one of the two color morphs of 7. javanicus. As explained in the Taxonomy section, the subspecific status of the populations of several islands remains unclear.
Data from: Genome-wide association mapping of phenotypic traits subject to a range of intensities of natural selection in Timema cristinae
Open the record for dataset details and reuse information.
Figure. Map of Georgia with main administrative divisions delimited. Shade intensity indicates the richness of mayfly species for respective administrative unit. Dots indicate localities sampled for mayflies prior to this study. in The first annotated checklist of mayflies (Ephemeroptera: Insecta) of Georgia with new distribution data and a new record for the country
Figure. Map of Georgia with main administrative divisions delimited. Shade intensity indicates the richness of mayfly species for respective administrative unit. Dots indicate localities sampled for mayflies prior to this study.
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