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300 results for “Urban area”
Enhancement of cloud-to-ground lightning activity caused by the urban effect: a case study in the Beijing metropolitan area
<p>The dataset here includes land-surface temperature, wind field, precipitation, UV aerosol index, and lightning information analyzed in the paper "<strong>Enhancement of cloud-to-ground lightning activity </strong><strong>caused by the urban effect: a case study in</strong> <strong>the Beijing metropolitan area</strong>".</p>
Data for publication "COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas"
<p>Data to accompany the "COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas" paper published in Atmospheric Chemistry and Physics. This repository contains metadata for the ambient air quality and surface meteorological sites used for the analysis.</p> <p>The observations have not been included due to licencing issues, but can be shared by reasonable request to the author. </p> <p>All files are .csv files, with UTF-8 encoding, and are self describing.</p> <p> </p>
Urban area age and coefficient of variation of spatial area extent
<p>The dataset contains an proxy for the age of urban area and the coefficient of variation of its spatial extent as proxy for spatial dynamics. Both variables are studied as key to conceptualize the process of urbanization by means of clusters of local spatial autocorrelation. The analysis is based on the HYDE 3.1 database, cf. Klein Goldewijk et al. (2010), Klein Goldewijk et al. (2011).</p>
Figure 7. from Inventory of the Heteroptera (Insecta: Hemiptera) in Komaba Campus of the University of Tokyo, a highly urbanized area in Japan - Biodiversity Data Journal 3: e4981 (24 April 2015) https://doi.org/10.3897/BDJ.3.e4981
Figure 7. - Cluster analysis of Heteroptera assemblages in Komaba Campus and the six reference sites based on Jaccard distances.
Figure 2. from Inventory of the Heteroptera (Insecta: Hemiptera) in Komaba Campus of the University of Tokyo, a highly urbanized area in Japan - Biodiversity Data Journal 3: e4981 (24 April 2015) https://doi.org/10.3897/BDJ.3.e4981
Figure 2. - The aerial photograph of the Komaba Campus (taken in 2009 by the Geospatial Information Authority of Japan).
WRF-Chem output- concentrations for the 4 simulations: reference, urbanization, extension of agricultural areas and more urban parks
<p>We use the WRF-Chem air-quality model with an urban canopy scheme to investigate how land use (urban, agriculture, parks) affects the urban climate and chemical processes (dry deposition, biogenic emissions), resulting in changes in air quality for scenarios proposed by the Urban Master Plan of the Metropolitan Area of Barcelona. We selected a heatwave period, 4th-7th July 2015, with maximum temperatures reaching 40 °C in the interior of the AMB and 35 °C on the coast. Here we provide averaged model output for the heatwave period for the different pollutants, surface temperature, wind speed, PBLH, deposition, and biogenic emissions under different urban scenarios: reference (REF), urbanization (URB), extension of agriculture (AGR), and increase in urban parks (PARK).<br><br>The results for a period before the heatwave (1-3 July 2015), with temperatures 3-4 degrees lower than during the heatwave, are also provided. <br><br>Land-use and irrigation is also provided for each scenaio. </p>
Reassessing the climate mitigation potential of Chinese ecological restoration: the undiscovered potential of urban areas
<p>The dataset includes urban climate mitigation benefit data for all 371 cities and 1,721 clusters in China, as well as aggregate data of different ecological restoration projects and climate backgrounds. Combining multi-source high-resolution remote sensing data sets and the reanalysis dataset, the absolute value standard deviation method of multiple linear regression is used to extract the largest dominant factor (pixel-by-pixel calculation) of daytime surface temperature in each city except NDVI (as a greening indicator). Then, the time trends of surface temperature, NDVI, and dominant factors were calculated based on the Theil-Sen Median slope estimation method. Finally, based on the linear statistical relationship of the three indicators, the surface temperature trend under the no-greening scenario was constructed, and the difference between the simulated and observed surface temperature trends was used to characterize the urban climate mitigation benefits of the ecological restoration project. The data details are as follows: </p> <p>If you have any questions or comments, please feel free to contact Mr. Dong Xu via <a href="mailto:zhangh573@mail2.sysu.edu.cn">xu.dong@u.nus.edu.</a></p> <table> <tbody> <tr> <td> <p><strong>Data name</strong></p> </td> <td> <p><strong>Spatial resolution</strong></p> </td> <td> <p><strong>Time resolution</strong></p> </td> <td> <p><strong>Source</strong></p> </td> <td> <p><strong>Unit</strong></p> </td> <td> <p><strong>Note</strong></p> </td> </tr> <tr> <td> <p>MOD13A2</p> </td> <td> <p>1000 m</p> </td> <td> <p>16-Day</p> </td> <td> <p>USGS.a</p> </td> <td> <p>/</p> </td> <td> <p>UG index</p> </td> </tr> <tr> <td> <p>MOD11A1</p> </td> <td> <p>1000 m</p> </td> <td> <p>Daily</p> </td> <td> <p>USGS.a</p> </td> <td> <p>Kelvin</p> </td> <td> <p>UST index</p> </td> </tr> <tr> <td> <p>MOD09A1</p> </td> <td> <p>500 m</p> </td> <td> <p>8-Day</p> </td> <td> <p>USGS.a</p> </td> <td> <p>/</p> </td> <td> <p>Calculate IBI index</p> </td> </tr> <tr> <td> <p>ERA5-Land reanalysis dataset</p> </td> <td> <p>10000 m</p> </td> <td> <p>Day</p> </td> <td> <p>ECMWF.b</p> </td> <td> <p>/</p> </td> <td> <p>Sensitivity analysis</p> </td> </tr> <tr> <td> <p>Population density datasets</p> </td> <td> <p>1000 m</p> </td> <td> <p>Annual</p> </td> <td> <p>WorldPop.c</p> </td> <td> <p>/</p> <p> </p> </td> <td> <p>Sensitivity analysis</p> </td> </tr> <tr> <td> <p>Global Urban Boundaries</p> </td> <td> <p>30 m</p> </td> <td> <p>Annual</p> </td> <td> <p>Li et al.</p> </td> <td> <p>/</p> </td> <td> <p>Delineate LUBs</p> </td> </tr> <tr> <td> <p><em>Note:</em> a, United States Geological Survey (https://earthexplorer.usgs.gov/). b, European Centre for Medium-Range Weather Forecasts (https://www.ecmwf.int/). c, WordPop (https://www.worldpop.org/). </p> <p><span>1. </span>Li X, Gong P, Zhou Y, et al. Mapping global urban boundaries from the global artificial impervious area (GAIA) data[J]. Environmental Research Letters, 2020, 15(9): 094044.</p> </td> </tr> </tbody> </table>
Interviewing users of services of selected urban areas (Granada)
<p>As part of the EU project SAFE (https://eusafe.fa.uni-lj.si/), University of Granada investigated living conditions and infrastructure offers in Granada (Spain) in order to work out possible suggestions for improvement. Students of University of Granada conducted a survey in Granada in March 2024. The dataset is a compilation of the raw data.</p>
Interviewing users of services of selected urban areas (Bydgoszcz)
<p>As part of the EU project SAFE (https://eusafe.fa.uni-lj.si/), WSG University investigated living conditions and infrastructure offers in Bydgoszcz (Poland) in order to work out possible suggestions for improvement. Students of WSG University conducted an oral survey of passers-by in Bydgoszcz in January 2024. The dataset is a compilation of the raw data.</p>
Data used in manuscript Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing
<p>This dataset provides the data used in the manuscript "<em>Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing</em>".</p> <p>The folders are:</p> <p><strong>1. Modelled_CO2_Flux</strong><br> This folder contains a portion of modelled CO2 fluxes generated by SUEWS. Fc is the net CO2 flux, FcPhoto the CO2 uptake by vegetation, FcRespi the CO2 release from soil and vegetation respiration, FcMetab the CO2 emissions from human metabolism, FcBuild the CO2 emissions from the local fuel combustion in buildings. Longitudes and latitudes denote the centroid of grid.<br> <strong>1.1 Fc_annual_2016_g_C_m-2_yr-1.nc</strong> is the annual CO2 fluxes in g C m-2 year-1.<br> <strong> 1.2 Fc_monthly_2016_g_C_m-2_mon-1.nc</strong> is the monthly CO2 fluxes in g C m-2 month-1.<br> <strong>1.3 Fc_annual_2016_g_C_m-2_yr-1.tiff</strong> is the annual Fc (g C m-2 year-1) provided in GeoTiff format.<br> <strong>1.4 6_ring_EPSG4326</strong> contains the ESRI Shapefile defining the study area (with the 6th Ring Road in Beijing as the boundary).</p> <p><strong>2. ModelRun</strong><br> This folder includes SUEWS source code (Järvi et al., 2011; Ward et al., 2016; Järvi et al., 2019) and a model run sample.<br> <strong>2.1 SUEWS_SourceCode</strong> is a folder including SUEWS V2020b source Fortran codes. For detailed descriptions, readers are referred to SUEWS webpage (https://suews.readthedocs.io/en/latest/). Enter "make" through the command line and a SUEWS executive will be built under ".../ModelRun/Release".<br> <strong>2.2 EvaluationRun</strong> is a folder including the SUEWS run for model performance evaluation. To conduct a quick model run to reproduce the results demonstrated in the manuscript, use command line "./SUEWS_V2020b". </p> <p><strong>3. Observations</strong><br> The unit for CO2 flux (Fc) is μmol m-2 s-1 under this folder.<br> <strong>3.1 co2_flux_140m_2016_rm_QC.csv</strong> is the Fc observations after quality control and resampled to hourly resolution.<br> <strong>3.2 Fc_gapfilled_with_MeanDC.csv</strong> is the Fc time series for the year 2016 gap-filled with the Mean Diurnal Cycle method on a seasonal basis.</p> <p> </p> <p>Contact information: zhengyingqi@mail.iap.ac.cn</p> <p><br><strong>[References]</strong><br>Järvi, L., Grimmond, C. S. B., & Christen, A. (2011). The surface urban energy and water balance scheme (SUEWS): Evaluation in Los Angeles and Vancouver. Journal of Hydrology, 411(3-4), 219-237.<br>Ward, H. C., Kotthaus, S., Järvi, L., & Grimmond, C. S. B. (2016). Surface Urban Energy and Water Balance Scheme (SUEWS): development and evaluation at two UK sites. Urban Climate, 18, 1-32.<br>Järvi, L., Havu, M., Ward, H. C., Bellucco, V., McFadden, J. P., Toivonen, T., ... & Grimmond, C. S. B. (2019). Spatial modeling of local‐scale biogenic and anthropogenic carbon dioxide emissions in Helsinki. Journal of Geophysical Research: Atmospheres, 124(15), 8363-8384.</p>
Interviewing users of services of selected urban areas (Vantaa)
<p>As part of the EU project SAFE (https://eusafe.fa.uni-lj.si/), Laurea Unversity of Applied Sciences investigated living conditions and infrastructure offers in Vantaa (Finland) in order to work out possible suggestions for improvement. Students of Laurea Unversity of Applied Sciences conducted a survey in Vantaa in November 2023. The dataset is a compilation of the raw data.</p>
Data for 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'
<p>This dataset supports Odériz et al. (2024). 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'</p>
TXRF and TXRF-XANES data for characterization of unique aerosol pollution episodes in urban areas
<p>The dataset contains the raw data for elemental composition and copper/bromine speciation determined in size-fractionated aerosol particles sampled by a May-type cascade impactor. </p> <p>These data are related to the journal article <strong>Characterization of unique aerosol pollution episodes in urban areas using TXRF and TXRF-XANES </strong>by Otto Czömpöly, Endre Börcsök, Veronika Groma, Simone Pollastri and Janos Osan, published in Atmospheric Pollution Research Volume 12, Issue 11, November 2021, 101214. <a href="https://doi.org/10.1016/j.apr.2021.101214">https://doi.org/10.1016/j.apr.2021.101214</a></p> <p>The elemental composition data were produced by total-reflection X-ray Spectrometry (TXRF) at Centre for Energy Research, Budapest, Hungary. </p> <p>The file "TXRF.zip" contains raw spectra as "*.spe", fitting results as "*.asr", calibration file "aer_mo.cal" and calculated elemental masses along the 20-mm stripe samples as "*.apr", all as text files in AXIL/QXAS format.</p> <p>The copper and bromine speciation data were produced by X-ray absorption near-edge structure (XANES) recorded in the TXRF detection mode at the XRF beamline of Elettra Sincrotrone Trieste, Italy.</p> <p>The file "XANES.zip" contains average XANES spectra of several energy scans for each sample as "*.xmu" and linear combination fitting results as "*.lcf", all as text files in Athena/Ifeffit format.</p> <p>The files are grouped in folders related to aerosol particles collected during the five pollution episodes (A-E) and near pollution sources as presented in the publication. The digit following the sample number denotes the impactor stage number (3-9), numbered from large (4.5-8.9 um) to small (70-180 nm) particle fractions. </p>
Survey Data Results for Project Strategies for Mitigating Congestion in Small Urban and Rural Areas
<p>File contains the Survey Data Results for Project Strategies for Mitigating Congestion in Small Urban and Rural Areas.</p> <p>Row 1 is the question number.</p> <p>Row 2 is the question.</p> <p>Remaining Rows are individual survey responses.</p>
Data from the paper "Learning to clusterize urban areas: two competitive approaches and an empirical validation"
<p>Data for urban clustering used in the paper "Learning to clusterize urban areas: two competitive approaches and an empirical validation". We release two datasets for urban clustering based on data acquired in Santiago de Chile. The first dataset is computed at the level of urban blocks. The second dataset is computed at the level of individuals using a uniform sample of Santiago inhabitants. Both datasets comprises features based on social characteristics (e.g., SES), land use, and aesthetic visual perception of the city. The features of each data unit (blocks or individuals) are provided using row packing (each row is a data unit) in CSV files. We release PCA (Principal Components Analysis) features for both datasets.</p>
Fig. 6 in Occurrence And Abundance Of Invasive And Native Arion Slugs In Three Types Of Habitats In Urban Area Of Wrocław (Sw Poland)
Fig. 6. Number and proportion of A. vulgaris, A. rufus and hybrids found in sites studied
Fig. 7 in Urban Green Areas, Recreational Use And Health Impact Of Victory Gardens (Córdoba - Spain)
Fig. 7. Principal pollination pediod for ornamental flora in the studied gardens.
Fig. 3 in Urban Green Areas, Recreational Use And Health Impact Of Victory Gardens (Córdoba - Spain)
Fig. 3. Origin for ornamental flora in the studied gardens.
Fig. 4 in Urban Green Areas, Recreational Use And Health Impact Of Victory Gardens (Córdoba - Spain)
Fig. 4. Pollination strategy for ornamental flora in the studied gardens.
Fig. 1 in Urban Green Areas, Recreational Use And Health Impact Of Victory Gardens (Córdoba - Spain)
Fig. 1. Map showing the location of Córdoba city.
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)
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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.