177,458 research outputs found
Assessing land surface phenology in Araucaria-Nothofagus forests in Chile with Landsat 8/Sentinel-2 time series - Data and Material
No full textThis dataset contains the Enhanced Vegetation Index (EVI) data used in our research work about land surface phenology of Andean Araucaria-Nothofagus forests as well as the phenology information derived from it.
Study area: Conguillío National Park, Chile
Study period: 2016-2020
Description of datasets:
conguillio.sen2.lnd8.evi.2016.2020.nc - A raster dataset (NetCDF) of EVI values (resolution 10m). EVI was calculated from Level-2 Sentinel-2 and Landsat 8 data. To ensure harmonization, the Landsat 8 data was resampled and reprojected to Sentinel-2 properties prior to the index calculation.
evi_gb_beck_white.tif - A raster dataset (GeoTiff) of phenological metrics per year (resolution 10m). Metrics were derived by fitting a double logistic function (see Beck et al., 2006) to the smoothed and interpolated EVI pixel time series. Subsequently, the main phenological variables SOS (start of season) and EOS (end of season) were extracted using a 50% threshold value. The dataset itself is a result of the R package "greenbrown" and the layers are named accordingly (see https://greenbrown.r-forge.r-project.org/phenology.php). It is available as GeoTIFF and as R rasterfile.
Details about the methodology and results describing this dataset can be found in the following publication:
Kosczor, E., Forkel, M., Hernández, J., Kinalczyk, D., Pirotti, F. & Kutchartt, E., 2022. Assessing land surface phenology in Araucaria-Nothofagus forests in Chile with Landsat 8/Sentinel-2 time series. Int. J. Appl. Earth Obs. Geoinf. 112, 102862. https://doi.org/10.1016/j.jag.2022.10286
CLDFBench. Give your Cross-Linguistic data a lift
No full textForkel R, List J-M. CLDFBench. Give your Cross-Linguistic data a lift. In: Calzolari N, ed. Proceedings of the Twelfth International Conference on Language Resources and Evaluation. Luxembourg: European Language Resources Association (ELRA); 2020: 6995‑7002
tupuni/polynesianoutliersvoyaging: Data for Artefact geochemistry demonstrates long-distance voyaging in the Polynesian Outliers
No full textThis repository contains the data and code for our paper:
A. Hermann, P. Gutiérrez, C. Chauvel, R. Maury, C. Liorzou, E. Willie, I. Phillip, R. Forkel, C. Rzymski, S. Bedford (in review). Artefact geochemistry demonstrates long-distance voyaging in the Polynesian Outliers
Cite this repository a
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Lexibank Analysed
No full textCite the source of the dataset as:
List, J.-M., R. Forkel, S. Greenhill, C. Rzymski, J. Englisch, and R. Gray (2022): Lexibank, A public repository of standardized wordlists with computed phonological and lexical features. Scientific Data 9.316. 1-31. https://doi.org/10.1038/s41597-022-01432-
cldf/cldf: CLDF 1.3
No full text<p>Cite as</p>
<blockquote>
<p>Robert Forkel, Michael Cysouw, Johann-Mattis List, Christoph Rzymski, Simon J Greenhill, Steven Moran, Arjan Mossel, Gereon Kaiping, & Tarik Havighorst. (2024). cldf/cldf: CLDF 1.3 (v1.3). Zenodo.</p>
</blockquote>
<p>Please also cite the paper introducing CLDF as</p>
<blockquote>
<p>Forkel, R. et al. Cross-Linguistic Data Formats, advancing data sharing and reuse in comparative linguistics. Sci. Data. 5:180205 doi: <a href="https://doi.org/10.1038/sdata.2018.205">10.1038/sdata.2018.205</a> (2018).</p>
</blockquote>
cldf/cldf: CLDF 1.3
No full text<p>Cite as</p>
<blockquote>
<p>Robert Forkel, Michael Cysouw, Johann-Mattis List, Christoph Rzymski, Simon J Greenhill, Steven Moran, Arjan Mossel, Gereon Kaiping, & Tarik Havighorst. (2024). cldf/cldf: CLDF 1.3 (v1.3). Zenodo.</p>
</blockquote>
<p>Please also cite the paper introducing CLDF as</p>
<blockquote>
<p>Forkel, R. et al. Cross-Linguistic Data Formats, advancing data sharing and reuse in comparative linguistics. Sci. Data. 5:180205 doi: <a href="https://doi.org/10.1038/sdata.2018.205">10.1038/sdata.2018.205</a> (2018).</p>
</blockquote>
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
clics/clics3: CLICS3
No full textCite as
Rzymski, C., T. Tresoldi, S. Greenhill, M. Wu, N. Schweikhard, M. Koptjevskaja-Tamm, V. Gast, T. Bodt, A. Hantgan, G. Kaiping, S. Chang, Y. Lai, N. Morozova, H. Arjava, N. Hübler, E. Koile, S. Pepper, M. Proos, B. Epps, I. Blanco, C. Hundt, S. Monakhov, K. Pianykh, S. Ramesh, R. Gray, R. Forkel, and J.-M. List. The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies. Sci Data 7, 13 (2020). https://doi.org/10.1038/s41597-019-0341-
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