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802 results for “urban data”
Urban Traffic Simulation Data from Real Fusion Estimates
<p>The datasets contain vehicle data from the simulation of the city center of Guimarães. The simulation was created using data collected from real sensor data, thus, providing an accurate view of the traffic flows. The data contains route information, fuel consumption, emissions, driving distance, and the amount of time each vehicle is stopped.</p>
Data in Support of Effects of Urbanization and Forest Fragmentation on Atmospheric Nitrogen Inputs and Ambient Nitrogen Oxide and Ozone Concentrations in Mixed Temperate Forests.
Urban ecosystems around the globe experience greater atmospheric nitrogen (N) deposition compared to rural areas and are particularly vulnerable to fragmentation due to land-use change. However, while the influences of urbanization and forest fragmentation on atmospheric inputs to temperate forests have been determined separately, the combined effects of the two changes on temperate forest ecosystems have yet to be assessed. To investigate these combined effects, we deployed throughfall collectors to measure atmospheric N inputs and passive samplers to measure nitrogen oxides (NOx) and ozone (O3) throughout the 2018 and 2019 growing seasons in seven temperate forest sites along an urbanization gradient from Boston to central Massachusetts. We found a positive relationship between the amount of impervious surface area surrounding each site (% ISA) and throughfall nitrate (NO3-) inputs at the forest edge, with urban edge NO3- inputs nearly double the rate at rural edge sites. There were higher rates of NO3- inputs in the rural forest interior than edge sites. Urban sites experienced significantly higher concentrations of NOx and O3 both in the interior and at the edge compared to rural sites. Atmospheric N inputs were significantly elevated in the early (May-July) compared to the late (August-November) growing season and concentrations of NOx and O3 were also elevated in the mid-growing season (June-September). Our results demonstrate that together, urbanization and forest fragmentation lead to greater rates of atmospheric N inputs and ambient pollutant concentrations of NOx and O3 in temperate forests of the northeastern U.S.
Field data for seasonal synoptic sampling of 100 urban streams in Boston, Massachusetts (USA) from 2021-2022
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Boston, Massachusetts (USA) metropolitan area. Field collection took place during four synoptic sampling events (September 2021, November 2021, April 2022, and July 2022) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
High-frequency water quality data for three urban streams in Boston, MA (USA), 2021-2022
This dataset contains high-frequency water quality data for three urban stream locations in the great Boston, Massachusetts metropolitan area. Multiparameter sondes with sensors to measure temperature, pH, specific conductivity, optical dissolved oxygen (DO), turbidity, colored dissolved organic matter (CDOM), and optical brighteners (OB) were deployed from 23 November 2021 to 20 December 2022. Data were collected at 15-minute intervals.
Field data for seasonal synoptic sampling of 100 urban streams in Miami, Florida (USA), 2021-2022
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Miami, Florida metropolitan area. Field collection took place during five synoptic sampling events: Summer 2021 (Wet; July 8 to July 27), Fall 2021 (Wet; September 27 to October 7), Winter 2022 (Dry; January 3 to January 13), Spring 2022 (Dry; April 7 to April 23), and Summer 2022 (Wet; June 1 to June 13) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Field data for seasonal synoptic sampling of 100 urban streams in Portland, Oregon (USA), 2023-2024
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Portland, Oregon (USA) metropolitan area. Field collection took place during four synoptic sampling events (July 2023, October 2023, January/February 2024, and May 2024) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Field data for seasonal synoptic sampling of 100 urban streams in Salt Lake City, Utah (USA), 2023-2024
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Salt Lake City, Utah (USA) metropolitan area. Field collection took place during four synoptic sampling events (July 2022, October 2022, February 2023, and May 2023) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Field data for seasonal synoptic sampling of 93 urban streams in Atlanta, Georgia (USA), 2021-2022
This dataset contains field measurements taken during water sampling from 93 first- to fifth-order streams in the Altamaha, Chattahoochee, and Flint Watersheds draining a gradient of urban land use in the greater Atlanta, Georgia metropolitan area. Field collection took place during four synoptic sampling events(September 2021, December 2021, March 2022, and July 2022) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in separate datasets. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
R code and data to reproduce figures from the "Multivariate autoregressive modelling and conditional simulation for temporal uncertainty analysis of an urban water system in Luxembourg" paper
<p>This repository contains the R code and data to reproduce figures from the "Multivariate autoregressive modelling and conditional simulation for temporal uncertainty analysis of an urban water system in Luxembourg" paper.</p>
Data from: Using genetic relatedness to understand heterogeneous distributions of urban rat-associated pathogens
<p>Urban Norway rats (<i>Rattus norvegicus</i>) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape, and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada and used 1,495 genome-wide single nucleotide polymorphisms to identify parent-offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens <i>Leptospira interrogans</i>, <i>Bartonella tribocorum</i>, and <i>Clostridium difficile</i>, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. <span>Our findings also highlight the utility of evolutionary tools to understand movement and rat-associated health risks in urban landscapes.</span></p>
Analyzing and predicting urban land use forms in East Africa using OpenStreetMap data, satellite imagery, and Convolutional Networks
<p>This multi-spectral satellite image data set is associated with our recent work on analyzing and predicting urban land use forms in East Africa using OpenStreetMap data, satellite imagery, and Convolutional Neural Networks.</p> <p>The images were extracted using an automated Python script from Google Maps Static API, based on sample locations in four East African capital cities namely Kampala, Nairobi, Dar es Salaam, and Kigali.</p> <p>Other data sets associated with this work, that is, ESRI shapefiles for administrative level 1 and OpenStreetMap data for the named cities may be downloaded directly from the respective URLs provided in the manuscript.</p>
Data from: Quantifying nectar production by flowering plants in urban and rural landscapes
<p>Floral resources (nectar and pollen) provide food for insect pollinators but have declined in the countryside due to land use change. Given widespread pollinator loss, it is important that we quantify their food supply to help develop conservation actions. While nectar resources have been measured in rural landscapes, equivalent data are lacking for urban areas, an important knowledge gap as towns and cities often host diverse pollinator populations.</p> <p>We quantified the nectar supply of urban areas, farmland and nature reserves in the UK by combining floral abundance and nectar sugar production data for 536 flowering plant taxa, allowing us to compare landscape types and assess the spatial distribution of nectar sugar among land uses within cities.</p> <p>The magnitude of nectar sugar production did not differ significantly among the three landscapes. In urban areas the nectar supply was more diverse in origin and predominantly delivered by non-native flowering plants. Within cities, urban land uses varied greatly in nectar sugar production. Gardens provided the most nectar sugar per unit area and 85% of all nectar at a city scale, while gardens and allotments produced the most diverse supplies of nectar sugar. Floral abundance, commonly used as a proxy for pollinators' food supply, correlated strongly with nectar resources, but left a substantial proportion of the variation in nectar supply unexplained.</p> <p>Synthesis. We show that urban areas are hotspots of floral resource diversity rather than quantity and their nectar supply is underpinned by the contribution of residential gardens. Individual gardeners have an important role to play in pollinator conservation as ornamental plants, usually non-native in origin, are a key source of nectar in towns and cities.</p>
Data from: Urban trees reduce nutrient leaching to groundwater
Many urban waterways suffer from excess nitrogen (N) and phosphorus (P) feeding algal blooms, which cause lower water clarity and oxygen levels, bad odor and taste, and the loss of desirable species. Nutrient movement from land to water is likely to be influenced by urban vegetation, but there are few empirical studies addressing this. In this study, we examined whether or not urban trees can reduce nutrient leaching to groundwater, an important nutrient export pathway that has received less attention than stormwater. We characterized leaching beneath thirty-three trees of fourteen species, and seven open turfgrass areas, across three city parks in Saint Paul, Minnesota. We installed lysimeters at 60 cm depth to collect soil water approximately biweekly from July 2011 through October 2013, except during winter and drought periods, measured dissolved organic carbon (C), N, and P in soil water, and modeled water fluxes using the BROOK90 hydrologic model. We also measured soil nutrient pools (bulk C and N, KCl-extractable inorganic N, Brays-P), tree tissue nutrient concentrations (C, N, and P of green leaves, leaf litter, and roots), and canopy size parameters (leaf biomass, leaf area index) to explore correlations with nutrient leaching. Trees had similar or lower N leaching than turfgrass in 2012 but higher N leaching in 2013; trees reduced P leaching compared with turfgrass in both 2012 and 2013, with lower leaching under deciduous than evergreen trees. Scaling up our measurements to an urban subwatershed of the Mississippi River (~17,400 ha, containing roughly 1.5 million trees), we estimated that trees reduced P leaching to groundwater by 533 kg in 2012 (0.031 kg/ha or 3.1 kg/km2) and 1201 kg in 2013 (0.069 kg/ha or 6.9 kg/km2). Removing these same amounts of P using stormwater infrastructure would cost $2.2 million and $5.0 million per year (2012 and 2013 removal amounts, respectively).
Data from: Assessing the contributions of intraspecific and environmental sources of infection in urban wildlife: Salmonella enterica and white ibis as a case study
Conversion of natural habitats into urban landscapes can expose wildlife to novel pathogens and alter pathogen transmission pathways. Because transmission is difficult to quantify for many wildlife pathogens, mathematical models paired with field observations can help select among competing transmission pathways that might operate in urban landscapes. Here we develop a mathematical model for the enteric bacteria Salmonella enterica in urban-foraging white ibis (Eudocimus albus) in south Florida as a case study to determine (i) the relative importance of contact-based versus environmental transmission among ibis and (ii) whether transmission can be supported by ibis alone or requires external sources of infection. We use biannual field prevalence data to restrict model outputs generated from a Latin hypercube sample of parameter space and select among competing transmission scenarios. We find the most support for transmission from environmental uptake rather than between-host contact and that ibis–ibis transmission alone could maintain low infection prevalence. Our analysis provides the first parameter estimates for Salmonella shedding and uptake in a wild bird and provides a key starting point for predicting how ibis response to urbanization alters their exposure to a multi-host zoonotic enteric pathogen. More broadly, our study provides an analytical roadmap to assess transmission pathways of multi-host wildlife pathogens in the face of scarce infection data.
Dataset and full R script used in the data analysis of the paper "Overlooked and undervalued: Peripheral pollinators in an urban network"
<p>Dataset and full R script used in the data analysis of the paper "<strong>Overlooked and undervalued: Peripheral pollinators in an urban network</strong>".</p> <p>Summary:</p> <p>Since insect pollinators are essential for their ecological and agricultural roles, their conservation should be a priority, particularly in the remnant green spaces within highly urbanised cities. To gain insight into the occurrence of interactions between plants and often overlooked pollinators, and into their requirements for persistence over time in urban green spaces, we studied flower visitor diversity associated with a remnant of native vegetation in Cordoba (Argentina), one of the largest cities in South America. We recorded 198 insect species from six orders (Hymenoptera, Diptera, Lepidoptera, Coleoptera, Thysanoptera, and Hemiptera) interacting with the flowers of 94 plant species. The plant-pollinator interaction network was significantly modular, with 178 pollinators playing a peripheral role (i.e., it has a few links inside its own module and rarely any to other modules). We focused on the life history traits of these peripheral pollinators, which are often neglected in ecological studies. We classified their requirements to complete the life cycle and to persist over time into three broad categories: floral rewards, places to reproduce, and additional resources for food and nests. The life cycle requirements of peripheral pollinators differ significantly across insect orders. Hymenoptera and Lepidoptera have distinct life history requirements while Diptera and Coleoptera overlap in resource use. The three life history categories highlight how pollinators displayed different foraging behaviour, reproductive strategies of immature and adult stages, and the requirement of additional food resources used by larvae and adults beyond flower rewards to complete their life cycles. Knowledge about the requirements of neglected pollinators is a benchmark that can help to identify where efforts need to be made to conserve and maintain their biodiversity, even in small urban green spaces.</p>
Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment
<p>The first Twin Test (TW1) of the TWEET-IE project (<a href="http://www.tweet-ie.eu">www.tweet-ie.eu</a>) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements. </p>
Species‑specific influence of powdery mildew mycelium on the efficiency of PM accumulation by urban greenery - Data
<p>Dataset of article: Przybysz, A., Nawrocki, A., Mirzwa-Mróz, E. <em>et al.</em> Species-specific influence of powdery mildew mycelium on the efficiency of PM accumulation by urban greenery. <em>Environ Sci Pollut Res</em> (2023). https://doi.org/10.1007/s11356-023-28371-6</p>
Data for: Assessing hydrology, biogeochemistry and organic micropollutants in an urban stream-aquifer system: an interdisciplinary dataset
<p>Accompanying data for data article "Assessing hydrology, biogeochemistry and organic micropollutants in an urban stream-aquifer system: a comprehensive dataset" of Popp et al., JGR:Biogeosciences.</p> <p><br>In this repository, all data described in Table 1 of the manuscript can be found, except for the data already published by Popp et al., 2020, ES&T, doi: 10.1021/acs.est.9b05393. These data can be freely accessed in ERIC (Eawag Research Data Institutional Collection): doi.org/10.25678/0001JD. </p> <p>Data are structured the following way:<br>1_logger-data: time series of logger data (water temperature, water levels, electrical conductivity and pH [the latter only for the stream]) obtained at the stream Chriesbach and piezometers P1 and P4;<br>2_tracer-data: time series of nutrients, ions, and other tracer data obtained at the stream Chriesbach, the piezometers (P1, P4, P5) and the regional groundwater well (reg-gw); <br>3_micropollutant_data: time series of organic micropolluntants obtained at the stream Chriesbach, P1, P4, P5 and the regional groundwater well (reg-gw);<br>4_R-script: R script used for statistical analysis and to create the plots shown in the manuscript.</p> <p>Units, estimated uncertainties or other measures of uncertainty such as limits of quantification are provided in the respective files. Each subfolder contains its own readme file with relevant metadata. </p> <p>Coordinates (WGS84): <br>Location Latitude Longitude<br>Stream logger monitoring 47.404613 8.6113<br>Stream sampling 47.404459 8.607777<br>Piezometer 1 (P1) 47.4044 8.6080<br>Piezometer 4 (P4) 47.4044 8.6078<br>Piezometer 5 (P5) 47.404392 8.607619<br>Regional groundwater 47.40501 8.60822</p>
Data for "Do electric vehicles mitigate urban heat? The case of a tropical city"
<p>This dataset contains the underlying data used in the publication "Do electric vehicles mitigate urban heat? The case of a tropical city", which is under review in <em>Front. Environ. Sci. .</em></p> <p>The dataset includes two folders:</p> <p>1. <strong>data</strong> <br> Include COSMO-DCEP-BEP model inputs and output needed to reproduce the results in the manuscript (NetCDF). </p> <p>2. <strong>script</strong><br> Include post-processing scripts used to generate the figures in the manuscript (Jupiter Python 3 Notebook).</p> <p><em> </em></p>
Dataset containing DTS-data used in Karttunen et al. "Quantifying coastal urban surface layer structure using distributed temperature sensing in Helsinki, Finland"
<p>This record contains DTS-data used in the following study:</p> <p>Karttunen et al. (2021): Quantifying coastal urban surface layer structure using distributed temperature sensing in Helsinki, Finland, submitted to AMTD</p> <p> </p> <p>DTS_highfreq_SMEARIII_Karttunen_et_al.zip contains continuous high frequency potential temperature profiles measured along the SMEAR III 31-metre tall mast. See more information on the data in the netCDF-file attributes and on the measurement setup in the related manuscript.</p> <p>DTS_statistics_SMEARIII_Karttunen_et_al.nc contains profiles for the turbulence temperature statistics calculated from the continuous DTS potential temperature profiles.See more information in the netCDF-file attributes and the related manuscript.</p> <p> </p>
ScienceDex guides
Understand access before you commit
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.