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ShareScore release 0.9.0
Dataset results
6 results for “Beijing-Tianjin-Hebei region”
ChinaHighPM2.5: MODIS/Terra+Aqua 1 km Ground-level PM2.5 Dataset for the Beijing-Tianjin-Hebei Region
<p>ChinaHighPM<sub>2.5</sub> is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). This dataset is generated from MODIS/Terra+Aqua MAIAC AOD products together with other auxiliary data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using the linear mixed effect (LME) model. </p> <p>This is the MODIS/Terra+Aqua monthly 1 km ground-level PM<sub>2.5</sub> dataset in the Beijing-Tianjin-Hebei region from 2000 to 2018, and this dataset yields a high quality with a cross-validation coefficient of determination (CV-R<sup>2</sup>) reaching 0.85 and a root-mean-square error (RMSE) of 21.49 µg m<sup>-3</sup> on a daily basis.</p> <p>If you use this dataset for related scientific research, please cite the corresponding reference (Xue et al., 2021, JCP):</p> <p>Xue, W., Zhang, J., Zhong, C., Li, X., and Wei, J. Spatiotemporal PM<sub>2.5</sub> variations and its response to the industrial structure from 2000 to 2018 in the Beijing-Tianjin-Hebei region, <em>Journal of Cleaner Production</em>, 2021, 279, 123742. https://doi.org/10.1016/j.jclepro.2020.123742</p> <p><strong>More CHAP datasets of different air pollutants can be found at: <a href="https://weijing-rs.github.io/product.html">https://weijing-rs.github.io/product.html</a></strong></p>
Dataset for the manuscript "Comparison of Spatiotemporal Distribution and Occurrence Conditions of Large and Small Hail Events in Beijing-Tianjin-Hebei Region"
<p>This data set is a supplement to the journal article " Comparison of Spatiotemporal Distribution and Occurrence Conditions of Large and Small Hail Events in Beijing-Tianjin-Hebei Region".</p> <p>The data set consists of</p> <ul> <li>Hail disaster information included the station NO., hail frequency and the maximum size of hailstone.</li> <li>The atmospheric environment data from ERA-interim data associated with the hail events in this study. </li> <li>VIL and meso-scale rotation parameters correspond to hailstorms. </li> </ul>
Temperature data for the Beijing-Tianjin-Hebei region from 1991 to 2020
Open the record for dataset details and reuse information.
Research on the Impact of Environmental Protection Tax Law on Corporate Technological Innovation: A Beijing-Tianjin-Hebei Regional Analysis
<p><span>Qi Wang: 写作 - 原稿,形式分析。</span></p> <p><span>Xin'e Li: 调查、写作 - 审查与编辑。</span></p> <p><span>毛龙丹:调查,数据管理。</span></p> <p><span>Meiling Yang:数据管理。</span></p>
Annual maps of rural settlements in Beijing-Tianjin-Hebei region, China (1990 to 2020)
<p>Using the Landsat-derived impervious surface area (ISA) data, the prolonged artificial Nighttime-light (NTL) data, and the Point of Interest (POI) data on the Google Earth Engine, we built the first annual maps of rural settlements (RUS) in the rapid urbanization region of Beijing-Tianjin-Hebei (BTH) in North China during 1990-2020. The RUS mapping model proposed in this study on the basis of referring to similar studies consisted of three basic steps, including kernel density estimation, initial boundary delineation, and post-processing. The location-based and the area-based comparison verified the effectiveness of our results, with a mean overall accuracy of 85% and a mean correlation value of 0.88, respectively.</p>
The CNOPs for PM2.5 forecasts in the Beijing-Tianjin-Hebei region.
<p>This is the analyzed data in the research titeld " An approach to refining the ground meteorological observation stations for improving PM<sub>2.5</sub> forecasts in Beijing-Tianjin-Hebei region ".</p>
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DANDI Archive for NWB datasets
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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.