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3,709 results for “urbanicity”
Species and groundcover of understory herbaceous plants in a chronosequence of reforested urban sites, Lexington, KY USA
This dataset contains information on understory plant communities in across twenty urban reforestation sites planted as part of the Reforest the Bluegrass program in Lexington, KY. Urban reforested areas located in Lexington, Kentucky were evaluated over the course of summer 2020. At least three plots (and up to nine plots) were established in each site, with additional plots added if forested patches were sufficiently large. At each plot, we established a 0.008-ha (0.02-ac) circular sampling plot to survey understory plant species. Groundcover of all species, excepting tree- and shrub-forming species, was visually estimated in 10 grids, 0.6 m x 0.6 m. These data will contribute to understanding of understory plant community dynamics in developing urban forests.
Regional Heat Vulnerability Map and Cooling Solutions: A webtool of the Healthy Urban Environments Initiative
## Regional Heat Vulnerability Map and Cooling Solutions The regional heat vulnerability map and cooling solutions webtool offers two data sources for equitable heat mitigation. The dashboard layers vulnerability data onto land surface temperature regional rankings to identify areas with high and low heat exposure and vulnerability as well as the existing assets in each census block group. Additional layers can be added into the heat vulnerability map to highlight how heat affects critical infrastructures including schools, mobile home parks, parking lots, public transportation stops, pedestrian thoroughfares, and bikeways. The solutions tab showcases a variety of heat mitigation solutions and the research behind them. Heat-related solutions and resources from urban Maricopa County are included, including solutions funded through the Healthy Urban Environment Initiative. The data catalogued here are the underlying data that populate the webtool. ## Healthy Urban Environment (HUE) Initiative - Overview HUE is a solutions-focused research, policy and technology incubator to create healthier communities across Maricopa County (central Arizona, USA) through collaboration between researchers, practitioners and community members. As such, HUE funded rapid development, testing and deployment of heat-mitigation and air-quality improvement strategies and technologies. Heat emerged as the urgent focus, as urban centers across the desert Southwest continue to grow in size and density, aggravating existing challenges posed by the expansion of the built environment. In Phoenix, AZ, this expansion of the built environment creates conditions which magnify the intensity and duration of heat – making it difficult for residents to achieve thermal comfort throughout the day and night. Further, the legacies of urban sprawl and transportation planning in the Phoenix, Arizona metropolitan area have contributed to challenges with atmospheric pollutants. Importantly, urban heat and air qua
Atmospheric Wet Deposition in Urban and Suburban Sites Across the United States
These data are for the publication: Conrad-Rooney, E., J. Gewirtzman, Y. Pappas, V.J. Pasquarella, L.R. Hutyra, and P.H. Templer. 2023. Atmospheric Wet Deposition in Urban and Suburban Sites Across the United States. Atmospheric Environment, https://doi.org/10.1016/j.atmosenv.2023.119783 This study investigated long-term trends in atmospheric wet deposition of nitrogen (ammonium and nitrate), sulfate, cations, and chloride for urban and suburban sites in the U.S. using data from the National Atmospheric Deposition Program and assessed whether urban NADP sites are hotspots for atmospheric wet deposition. To examine potential impacts of urbanization on atmospheric wet deposition, percent impervious surface area and population density data were extracted from Google Earth Engine. The results of this study highlight that urban areas have greater rates of many forms of atmospheric deposition and that there should be more long-term monitoring of atmospheric deposition in cities and suburban sites throughout the U.S. Data sources: - Dewitz, J., and U.S. Geological Survey, 2021, National Land Cover Database (NLCD) 2019 Products (ver. 2.0, June 2021): U.S. Geological Survey data release, doi:10.5066/P9KZCM54 - National Atmospheric Deposition Program (NRSP-3). 2022. NADP Program Office, Wisconsin State Laboratory of Hygiene, 465 Henry Mall, Madison, WI 53706. https://nadp.slh.wisc.edu/networks/national-trends-network/ - United States Census Bureau, TIGER: US Census Blocks, 2010 United States Census. https://developers.google.com/earth-engine/datasets/catalog/TIGER_2010_Blocks#description
Water-soluble organic matter and nutrients from stormwater control measure and urban wetland soils
Water-soluble organic matter (WSOM) represents organic matter that has the potential to be readily released from soils. WSOM has been understudied in urban, engineered soils relative to natural soils. To understand the potential for organic matter and nutrient release, we extracted WSOM from the soils of stormwater control measures (SCM) and urban wetlands. In February 2022, we sampled soils from 20 SCMs and natural wetlands in the Rappahannock River watershed of the mid-Atlantic United States. The SCMs reflected a variety of design configurations including bioretention, rain gardens, wet ponds, and swales. We also sampled naturally occurring floodplain wetlands that are located in this urban watershed. Soils were sampled to a depth of approximately 40 cm. If there was standing water present in the SCMs and wetlands at the time of sampling, we also collected surface water samples. If present, grab samples of leaf litter or biomass were collected. Soil characteristics, such as pH, bulk density, soil moisture, soil organic matter, and cation exchange capacity were also determined for each site. WSOM was extracted from soils and biomass in the laboratory and analyzed for organic matter concentration (dissolved organic carbon) and composition (absorbance and fluorescence metrics), along with dissolved nutrient concentrations (total dissolved nitrogen, total dissolved phosphorus, nitrate, ammonium, and orthophosphate). In addition to the 20 sites in the Rappahannock watershed, soils from 2 additional bioretention SCMs on the Virginia Tech campus were sampled on a monthly basis from February 2022 to February 2023 to explore temporal variability in WSOM. To characterize changes in soil hydrologic conditions during monthly SCM sampling, we applied a Thornthwaite-type monthly water balance model. Finally, we performed a simple scaling exercise to WSOM results based on SCM area, sample depth, and soil bulk density to estimate potential SCM contributions of organic matter.
Dust geochemistry and lead isotopes along an urban-rural transect in central Ohio, 2021
This data package contains geochemical concentrations and stable lead isotope ratios for dust samples collected along an urban-rural land use gradient in central Ohio during 2021. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, to see how much dust varies across land use and by season. At four sites along an urban-rural transect in central Ohio, we collected weekly bulk deposition samples and analyzed the geochemical composition (47 elements including major elements, trace metals, and rare earth elements) and stable lead isotopes (208Pb, 207Pb, 206Pb, and 204Pb) of the particulate matter. This study demonstrates the tight connection between land use and anthropogenic dust composition in a region where land use is changing rapidly as development encroaches into farmland. This dataset is complete and will not be updated.
Air mass back-trajectory modeling output along an urban-rural transect in central Ohio, 2021
This data package contains modeled air parcel back-trajectories generated using the Stochastic Time-Inverted Lagrangian Transport model (STILT) via the R interface. The purpose of the study was to characterize the geochemical and isotopic signatures of dust in relation to different land uses, and to connect the geochemistry of deposited dust to air mass trajectories. Back-trajectories are three-dimensional paths of air parcels from a receptor site (the dust collection site) backwards in time and space for the duration of the tracking interval, calculated iteratively using wind fields from high-resolution gridded meteorological data. To calculate a probability of potential pathways, rather than a single back-trajectory, STILT introduces small random perturbations into the wind fields during each time step. For four sites along an urban-rural transect in central Ohio for June-July 2021, we generated weekly footprints of potential sources for the dust deposited at each site. These back-trajectories can be paired with geochemical data to establish a connection between land use and anthropogenic dust composition. This dataset is complete and will not be updated.
Baltimore Ecosystem Study: Soil moisture and temperature along an urban to rural gradient, 2011 - present
Soil temperature and soil moisture have been measured at multiple locations in and around Baltimore Maryland to provide data on these variables in forests and lawns across an urban to rural gradient. In July 2011, we installed one Decagon Em50 Datalogger with five 5TM VWC/Temperature probes at four established forested, upslope, 20 x 20-m plots, two rural (ORU1, ORU2) and two urban (LEA1, LEA2), at 2 forested riparian sites at two transects along a stream (ORUR, ORLR), and two lawn plots on the campus of the University of Maryland Baltimore County campus (UMBC1, UMBC 2). Probes were buried horizontally at 10cm depth (except UMBC1 and UMBC2 where the five probes are mounted horizontally at a single location at depths of 50, 40, 30, 20 and 10 cm depth). At the upslope forested plots, the five probes are replicates. At the two riparian sites, probes are deployed in either "hummocks (drier, higher)" or in "hollows (lower, wetter)". Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in July 2011. In March 2017, an additional data logger was installed at Hillsdale Park (HD1) in a forested urban area. The five probes at HD1 were buried horizontally at 10cm depth and are replicates. Earlier soil moisture data were collected monthly (1999-2011), and can be found in https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=417
Residential housing segregation and urban tree canopy in 37 US Cities; data in support of Locke et al 2021 in npj Urban Sustainability
Our goal in this paper is to examine whether there are similar patterns in the distribution of tree canopy by Home Owners’ Loan Corporation (HOLC) graded neighborhoods across 37 cities. A pre-print of the paper can be found here: https://osf.io/preprints/socarxiv/97zcs This data packages contains: 1. City-specific file geodatabases with features classes of the HOLC polygons obtained from the Mapping Inequality Project https://dsl.richmond.edu/panorama/redlining/, and tables summarizing tree canopy, and in some cases other land cover classes. 2. An *.R script that replicates all of the analyses, graphs, and tables in the paper. Other double checks, exploratory, and miscellaneous outputs are created by the script too as a bonus. Everything in the paper can be done with the script; additional work outputs are also created. 3. A *.csv file containing city, the HOLC grade, and the percent tree canopy cover. This can be used to create the main findings of the paper and this flat file is provided as an alternative to running the R script to extract information from the geodatabases, combine, and analyze them. The intention is that this file is more widely accessible; the underlying information is the same. Redlining was a racially discriminatory housing policy established by the federal government’s Home Owners’ Loan Corporation (HOLC) during the 1930s. For decades, redlining limited access to homeownership and wealth creation among racial minorities, contributing to a host of adverse social outcomes, including high unemployment, poverty, and residential vacancy, that persist today. While the multigenerational socioeconomic impacts of redlining are increasingly understood, the impacts on urban environments and ecosystems remains unclear. To begin to address this gap, we investigated how the HOLC policy administered 80 years ago may relate to present-day tree canopy at the neighborhood level. Urban trees provide many ecosystem services, mitigate the urban heat island effect
Sex-specific relationships between urbanization, parasitism, and plumage coloration in house finches
Historically, studies of condition-dependent signals in animals have been male-centric, but recent work suggests that female ornaments can also communicate individual quality (e.g., disease state, fecundity). There also has been a surge of interest in how urbanization alters signaling traits, but we know little about if and how cities affect signal expression in female animals. We present data of carotenoid-based plumage coloration and coccidian (Isospora spp.) parasite burden in desert and city populations of house finches Haemorhous mexicanus to examine links between urbanization, health state, and feather pigmentation in males and females. In earlier work, we showed that male house finches are less colorful and more parasitized in the city, and we again detected such patterns in this study for males; however, urban females were less colorful, but not more parasitized, than rural females. Moreover, contrary to rural populations, we found that urban birds (regardless of sex) with larger patches of carotenoid coloration were also more heavily infected with coccidia. These results show that urban environments can disrupt condition-dependent color expression and highlight the need for more studies on how cities affect disease and signaling traits in both male and female animals.
Urban-Rural Temperature Data-relation between land-cover and the Urban Heat Island in San Juan, Puerto Rico
Our objective in this study is to quantify the UHI created by the San Juan Metropolitan Area over space and time using temperature data collected by mobile and fixed-station measurements. We used the fixed-station measurements to examine the relation between average temperature at a given location and the density of vegetation located upwind. We then regressed temperatures against regional land-cover to predict future temperature with projected land-cover change. Our data show the existence of a nocturnal UHI, with average nighttime urban-rural temperature differences (ΔTU-R) of up to 3.02°C. Each of the stations listed in this excel file were used to calculate the urban heat island created by the San Juan Metropolitan Area. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Greenhouse gas and water chemistry data from urban ponds in Madison, Wisconsin during the summer and under-ice period of 2021-2022
Stormwater ponds are common features in urbanized landscapes and can suffer from rapid oxygen depletion when thermally stratified or ice-covered. To investigate under-ice oxygen dynamics and drivers of bottom water oxygen saturation, we sampled 20 stormwater ponds in Madison, Wisconsin, USA during the summer of 2021 and winter 2022. The urban ponds ranged in age, shape, size, and depth. We repeatedly took YSI profiles of water temperature, oxygen, and specific conductance 7 times in the summer and 3 times in the winter. Water chemistry variables were collected in the surface waters, habitat surveys were conducted in the summer, and ice/snow thickness was recorded in the winter. We also measured the concentration of greenhouse gases in the surface waters as a consequence to oxygen depletion using the headspace equilibrium method.
Impact of urban and shipping emissions on NASA-Unified Weather Research and Forecasting model results
<p>This dataset supports Huang et al. (2019, JGR-Atmospheres): "Impact of aerosols from urban and shipping emission sources on terrestrial carbon uptake and evapotranspiration: a case study in East Asia". The file named "NUWRFout.tar.gz" contains NUWRF base and sensitivity simulation results on 31 May 2016. The file named "LIS_soil_LAI.zip" contains model grid information, soil conditions and leaf area index (LAI) at NUWRF initialization times in late May 2016.</p>
Urbanization drives an early spring for plants but not for pollinators
<p>These files include data and code used in the article titled: "Urbanization drives an early spring for plants but not for pollinators". Data files are .txt with tab-separated values, and include abundances of pollinators captured and total floral cover estimated in each site (1-12) at each sampling event (6 events), in the three urban classes (low, medium, high).</p>
Modifications of the plant-pollinator network structure and species' roles along a gradient of urbanization
<p>This file includes data and codes used in the article titled: " Modifications of the plant-pollinator network structure and species’ roles along a gradient of urbanization".</p> <p>Data include plant-pollinator interactions sampled in each site (1-12) at each sampling event (6 events) in the three urbanization classes (low, medium, high). Each row is a single insect pollinator X plant interaction. Full species names and abbreviations used in figures in the Supplementary Information are reported.<br> The data file is .txt with tab-separated values.</p>
Dataset of Proportion of non-native plants in urban parks correlates with climate, socioeconomic factors and plant traits
<p>Full datasets for the research entitled 'Proportion of non-native plants in urban parks correlates with climate, socioeconomic factors and plant traits'.</p>
Land cover, landscape metrics and typology of European cities for Urban Forest Ecosystem Services (UFES) evaluation
<p>The data refers to the paper "<em>Urban Forests as Regulating Ecosystems: Types and Ranking of European Cities</em>"</p> <p>The datasets provide a typology for 689 European urban areas, the land cover metrics and landscape metrics used to create the typology and the Urban Forest Ecosystem Services (UFES) indexes created from them.</p> <p>The typology of Urban Forest Ecosystem Services (UFES) presents 10 clusters of cities aggregated into 4 groups: Forest cities, Anthropogenic cities, Herbaceous cities and Standard European cities. The data can be used to support urban planning policies at local and regional scales; in urban forestry, urban form and ecosystem services work related at different spatial scales. The metrics used capture the spatial integration of different layers of natural, semi-natural and artificial land within functional urban areas.</p> <p> </p> <p>The datasets are a csv file (<code>Metrics.csv</code>) and a shapefile (<code>UFES.shp</code>) of polygons with attributes.</p> <ul> <li> <p><code>UFES.shp</code> attributes' are the following: FUA codes, country name, main city name, clusters and groups of FUAs resulting from the hierarchical cluster analysis (HCA), the R color codes used in the article, the five UFES budget indexes as well as an aggregated global UFES index for each FUA.</p> </li> <li> <p><code>Metrics.csv</code> contains the FUA codes, the land cover and landscape metrics used in the HCA.</p> </li> </ul> <p> </p>
Dataset-AOB: urban sounds events classification
<p>The dataset Dataset-AOB is an audio dataset collected and manually edited for urban sounds events classification using Convolutional Neural Networks for the Master Thesis: </p> <p>Ospina, A. "Audio Event Classification using Deep Learning. Use case: Urban Sounds Events classification with Convolutional Neural Networks," M.Eng. thesis, Beuth University of Applied Sciences, Berlin, 2020.</p> <p>- 10 audio events: alarm-siren, children playing, dog bark, engine, footsteps, glass breaking, gun shot, metro train, rain and screams.</p> <p>- duration: < 4 seconds</p> <p>- format: (.wav)</p> <p>- sampling rate: 22KHz - 44KHz</p> <p>- files: Dataset-AOB: development dataset (4831 samples), DatasetEVAL-AOB: evaluation (218 samples)</p> <p>- metadata: (.csv)</p> <p>- sources per class: (.png)</p> <p>Contact: aospinab@gmail.com</p>
UWSCatCH: Urban Water Supply Catchment Contributions and Hydrological Statistics for large cities of the conterminous United States.
<p>UWSCatCH extends and enhances the Urban Water Blueprint (McDonald et al., 2014) for a selection of 116 cities (population > 150,000) and their associated surface water supply catchments in the conterminous United States. The two major enhancements to the Urban Water Blueprint are: [1] estimates of the relative contributions of each surface water catchment to each city's average water supply (as well as updated estimates of any contributions from groundwater); [2] NHDplusV2 reach codes for each water supply intake stream location and associated average flow estimates (regulated and unregulated) (local upstream USGS gage IDs are also provided). UWSCatCH also features a raster file with spatially distributed (1/24° grid) runoff (average of 1980 - 2012 reanalysis simulation) which is masked to watershed polygons (included as a shapefile) to explore spatial distribution of average runoff generation affecting each city. UWSCatCH is designed for use in the R package "gamut" (https://github.com/IMMM-SFA/gamut), and may be applied in a variety of regional and national scale research studies concerning drinking water supply to major US cities.</p>
Survey of open data and information seeking in Kenya's Urban Slums and Rural Settlements
<p>This dataset provides survey responses from 240 people surveyed as part of the "Investigating the Impact of Kenya’s Open Data Initiative on Marginalized Communities: Case Study of Urban Slums and Rural Settlements" project.</p> <p>The data, collected in mid-2013 looks at issues of where citizens look for data, and how successful they have been in getting government information from different sources, as well as their awareness of the Kenya open data portal, and their interest in getting information through different digital channels in future.</p> <p>Descriptive statistics have been analysed in the publication "Open Government Data for Effective Public Participation: Findings of a Case Study Research Investigating The Kenya's Open Data Initiative in Urban Slums and Rural Settlements", but no further analysis has yet been carried out.</p> <p><strong>Data descriptions</strong></p> <p>The Codebook.csv file lists variable names and the questions asked to elicit each response.</p> <p>JHC-Data.csv contains the results from the questionnaires collected through structured in-person interview in the three locations. The questionnaires were administered at chiefs centres, community resource centres, constituency development fund office and religious centres). The questionnaires were filled in by every 2nd these centres.</p> <p><strong>More information</strong></p> <p>More information on the research project can be found at http://opendataresearch.org/project/2013/jhc</p>
Social sensing of urban land use based on analysis of Twitter users' mobility patterns
<p>A companion dataset for the paper "Social sensing of urban land use based on analysis of Twitter users' mobility patterns". This dataset contains five files and one dictionary depicting the preferential return of Twitter users to their key locations and the urban land use types at these locations. More details can be found in the README file. </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.