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802 results for “urban data”
Data from: The influence of illumination regimes on the structure of ant (Hymenoptera, Formicidae) community composition in urban habitats
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Data from: Bee-mediated pollen transport across five urban landscape features: Buildings are important barriers
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Data from: Effects of microclimate on disease prevalence across an urbanization gradient
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Data from: Plant radiocarbon across an urban-rural CO2 gradient matches surface and column CO2 observations
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Data from: Mosquito derived ingested DNA as a tool for monitoring terrestrial vertebrates within a peri-urban environment
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Data from: Plant–moth community relationships at the degraded urban peat-bog in Central Europe
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Data for: DRD4 allele frequencies in greylag geese vary between urban and rural sites
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Data from: Current inequality and future potential of US urban tree cover for reducing heat-related health impacts
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Data for: Promoting beneficial arthropods in urban agroecosystems: Focus on flowers, maybe not native plants
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Nitrogen and Carbon cycling data in 10 urban afforestation sites in New York City 2018
The data includes soil microbial processes of carbon (C) and N in 10 afforestation sites in New York City as part of the MillionTreesNYC initiative (MTNYC) of the New York City Department of Parks and Recreation. Long-term research plots were established between 2009-2011 in municipal parks: Alley Pond, Canarsie, Ft. Totten, Clearview, Conference House, Clove Lakes, Marine Park (3 sites), and Pelham Bay. Sites were planted with low (two tree species) and high diversity (six tree species) treatments. More detailed description of sites and MTNYC project is provided by Downey et al. (2021). In 2018, 1 m soil cores were collected from plots at each site and analyzed for microbial biomass C and N, basal respiration, potential net N mineralization and nitrification, denitrification potential, soil inorganic N, and total soil N. Laboratory methods followed those used by Raciti et al. (2011a,b), and Groffman et al. (1999).
Urban Forest Effects Model (UFORE) to calculate forest structure and function from sample ground data. Two part set.
Within the City of Baltimore, 195 permanent 1/10 circular plots were established based on a stratified random sample among land uses in 1999. These plots were re-measured in 2004 and 2009 and will be re-measured again in 2014. On each plot, all trees (as defined as woody vegetation with a stem diameter at 4.5 ft (dbh) greater than one-inch) are recorded. For each tree, data are recorded on species, dbh, height, crown width, condition, crown competition, percent canopy missing and distance and direction to nearby residential buildings. These data are analyzed using the i-Tree model (www.itreetools.org) to assess ecosystem services and values. However, more importantly, these plots along with a comparable set of plots established in Syracuse, NY in 1999 are the first and most spatially comprehensive set of long-term urban forest monitoring data within cities globally. These data are being used to understand how urban forest structure and associated ecosystem services are changing through time in the City of Baltimore.
Data for L.R. Johnson and S.N. Handel - Restoration treatments in urban park forests drive long-term changes in vegetation trajectories - Ecological Applications doi:10.1890/14-2063.1
Initial data from long-term research plots in New York City Park forest patches invaded by exotic woody plant species. Half (n = 30) of the sites were restored 15-20 years prior to first sampling in 2009-2010. The same suite of invasive plants was recorded in the other half of the sites at the time of initial restoration in the late 1980s and early 1990s (n = 30), but they were not restored in 2009-2010.
Crowd and community sourcing to update authoritative LULC data in urban areas
<p>The French National Mapping Agency (Institut National de l'Information Géographique et Forestière - IGN) is responsible for producing and maintaining the spatial data sets for all of France. At the same time, they must satisfy the needs of different stakeholders who are responsible for decisions at multiple levels from local to national. IGN produces many different maps including detailed road networks and land cover/land use maps over time. The information contained in these maps is crucial for many of the decisions made about urban planning, resource management and landscape restoration as well as other environmental issues in France. Recently, IGN has started the process of creating a high-resolution land use land cover (LULC) maps, aimed at developing smart and accurate monitoring services of LULC over time. To help update and validate the French LULC database, citizens and interested stakeholders can contribute using the <a href="https://paysages.ign.fr/">Paysages</a> mobile and web applications. This approach presents an opportunity to evaluate the integration of citizens in the IGN process of updating and validating LULC data.</p> <p><strong>Dataset 1: Change detection validation 2019</strong></p> <p>This dataset contains web-based validations of changes detected by time series (2016 – 2019) analysis of Sentinel-2 satellite imagery. Validation was conducted using two high resolution orthophotos from respectively 2016 and 2019 as reference data. Two tools have been used: <a href="https://paysages.ign.fr/">Paysages</a> web application and <a href="https://laco-wiki.net/">LACO-Wiki</a>. Both tools used the same validation design: blind validation and the same options. For each detected change, contributors are asked to validate if there is a change and if it is the case then to choose a LU or LC class from a pre-defined list of classes.</p> <p>The dataset has the following characteristics:</p> <ul> <li>Time period of the change detection: 2016-2019.</li> <li>Time period of data collection: February 2019-December 2019</li> <li>Total number of contributors: 105</li> <li>Number of validated changes: 1048; each change was validated by between 1 to 6 contributors.</li> <li>Region of interest: Toulouse and surrounding areas</li> </ul> <p>Associated files: 1- Change validation locations.png, 1-Change validation 2019 – Attributes.csv, 1-Change validation 2019.csv, 1-Change validation 2019.geoJSON</p> <p>This dataset is licensed under a Creative Commons Attribution 4.0 International. It is attributed to the <a href="https://landsense.eu/">LandSense Citizen Observatory</a>, <a href="http://www.ign.fr/">IGN-France</a>, and <a href="https://www.geoville.com/">GeoVille</a>.</p> <p><strong>Dataset 2: Land use classification 2019</strong></p> <p>The aim of this data collection campaign was to improve the LU classification of authoritative LULC data (<a href="https://geoservices.ign.fr/documentation/diffusion/telechargement-donnees-libres.html#ocs-ge">OCS-GE 2016</a> ©IGN) for built-up area. Using the Paysages web platform, contributors are asked to choose a land use value among a list of pre-defined values for each location. </p> <p>The dataset has the following characteristics:</p> <ul> <li>Time period of data collection: August 2019</li> <li>Types of contributors: Surveyors from the production department of IGN</li> <li>Total number of contributors: 5</li> <li>Total number of observations: 2711</li> <li><a href="https://geoservices.ign.fr/ressources_documentaires/Espace_documentaire/BASES_VECTORIELLES/OCS_GE/DC_OCS_GE_1-1.pdf">Data specifications of the OCS-GE</a> ©IGN</li> <li>Region of interest: Toulouse and surrounding areas</li> </ul> <p>Associated files: 2- LU classification points.png, 2-LU classification 2019 – Attributes.csv, 2-LU classification 2019.csv, 2-LU classification 2019.geoJSON</p> <p>This dataset is licensed under a Creative Commons Attribution 4.0 International. It is attributed to the <a href="https://landsense.eu/">LandSense Citizen Observatory</a>, <a href="http://www.ign.fr/">IGN-France</a> and the <a href="https://iiasa.ac.at/">International Institute for Applied Systems Analysis</a>.</p> <p><strong>Dataset 3: In-situ validation 2018</strong></p> <p>The aim of this data collection campaign was to collect in-situ (ground-based) information, using the Paysages mobile application, to update authoritative LULC data. Contributors visit pre-determined locations, take photographs, of the point location and in the four cardinal directions away from the point and answer a few questions with respect with the task. Two tasks were defined: </p> <ul> <li>Classify the point by choosing a LU class between three classes: industrial (US2), commercial (US3) or residential (US5).</li> <li>Validate changes detected by the LandSense Change Detection Service: for each new detected change, the contributor was requested to validate the change and choose a LU and LC class from a pre-defined list of classes.</li> </ul> <p>The dataset has the following characteristics </p> <ul> <li>Time period of data collection: June 2018 – October 2018</li> <li>Types of contributors: students from the School of Agricultural and Life Sciences and citizens</li> <li>Total number of contributors: 26</li> <li>Total number of observations: 281</li> <li>Total number of photos: 421</li> <li>Region of interest: Toulouse and surrounding areas</li> </ul> <p>Associated files: 3- Insitu locations.png, 3- Insitu validation 2018 – Attributes.csv, 3- Insitu validation 2018.csv, 3- Insitu validation 2018.geoJSON</p> <p>This dataset is licensed under a Creative Commons Attribution 4.0 International. It is attributed to the <a href="https://landsense.eu/">LandSense Citizen Observatory</a>, <a href="http://www.ign.fr/">IGN-France</a>.</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 689812.</p>
Exploring and promoting green urban spaces in Vienna - can data about public perception help drive change?
<p>Citizen Science has become a vital source for data collection when the spatial and temporal extent of a project makes it too expensive to send experts into the field. However, involving citizens can go further than that – participatory projects focusing on subjective parameters can fill in the gap between local community needs and stakeholder approaches to tackle key social and environmental issues.</p> <p>The Horizon 2020 project, <a href="https://landsense.eu/">LandSense</a>, is building a modern citizen observatory for Land Use & Land Cover (LULC) monitoring, by engaging citizens to transform current approaches to environmental decision making. Citizen Observatories are community-driven mechanisms to complement existing environmental monitoring systems and can be fostered through mobile and web applications, allowing citizens to play a key role in environmental monitoring. Within this project, the City Oases mobile application, focused on the city of Vienna, has been developed that aims not only to stimulate civic engagement to monitor changes within the urban environment, but also to enable users to drive improvements by providing city planners with information about the public perception of urban spaces. <a href="https://play.google.com/store/apps/details?id=com.iiasa.cityoases">City Oases</a> was launched in March 2019.</p> <p>Where are the best places for a romantic date? Where can you skate? Where is it cool on a hot summer’s day? Open urban spaces can be used in many ways. Pick an activity in the CityOases app and we show the spots where you can do them, including the rating of previous users and pictures from the location. If you visit the spot you can rate it as well based on a few selected subjective criteria. If you know a cool spot that is openly accessible but not marked in our map yet? Just add it with a list of activities and some pictures. Additionally, you can input your perceptions including whether it is noisy, clean or if the infrastructure is attractive. The picture module within the application promotes you to take photos in the four cardinal directions. Users can search for specific activities, visit one of the points indicated on the map and then evaluate this point.</p> <p>Time period of data collection: 19/03/2019 - 10/11/2019</p> <p>Types of contributors: General Public, Students<br> Number of contributors: 50<br> Number of observations: 788<br> Number of photos: 1846</p> <p>Associated files: City Oases Vienna 2019.csv, City Oases Vienna 2019.geoJSON, City Oases Vienna 2019 Attributes.csv</p> <p>This dataset is licensed under a Creative Commons Attribution 4.0 International. It is attributed to the <a href="https://landsense.eu/">LandSense Citizen Observatory</a>, <a href="https://www.umweltbundesamt.at/en/">Umweltbundesamt</a> (Environment Agency Austria) and the <a href="https://iiasa.ac.at/">International Institute for Applied Systems Analysis</a>.</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 689812.</p>
Data from: Microplastic prevalence in 4 Oregon rivers along a rural to urban gradient applying a cost‐effective validation technique
<p>Microplastics are ubiquitous in our environment and are found in rivers, streams, oceans, and even tap water. Riverine microplastics are relatively understudied compared to those in marine ecosystems. In Oregon, we sampled eight sites along four freshwater rivers spanning rural to urban areas to quantify microplastics. Plankton tow samples from sites along the Columbia, Willamette, Deschutes, and Rogue Rivers were analyzed using traditional light microscopy for initial microplastic counts. Application of Nile Red dye to validate microplastics improved microplastic identification, particularly for particles (Wilcox Test; p-value=0.001). Nile Red-corrected microfiber abundance was correlated with human population within five kilometers of the sample site (R²=0.554), though no such relationship was observed between microparticles and population (R²=0.183). This study finds plastics present in all samples from all sites, despite the range from undeveloped, remote stretches of river in rural areas to metropolitan sites within Portland, demonstrating the pervasive presence of plastic pollution<span> </span><span><span>in freshwater environments.</span></span></p>
Rainfall-runoff data from an urban catchment in Luleå, Sweden.
<p>Description and map of the catchment:<br> Broekhuizen, Ico, Günther Leonhardt, Jiri Marsalek, and Maria Viklander. “Event Selection and Two-Stage Approach for Calibrating Models of Green Urban Drainage Systems.” Hydrology and Earth System Sciences 24, no. 2 (February 26, 2020): 869–85. https://doi.org/10.5194/hess-24-869-2020.</p> <p>Rain gauge: Geonor T200B weighing bucket . Alter-type wind shield.</p> <p>Flow gauge: Teledyne ISCO 2150 Area-Velocity: acoustic Doppler for flow velocity, pressure transducer for water level.</p> <p>Additional information on field calibration checks of the rain gauge and laboratory testing of the same type of flow sensor:<br> Broekhuizen, Ico. “Uncertainties in Rainfall-Runoff Modelling of Green Urban Drainage Systems: Measurements, Data Selection and Model Structure.” Licentiate thesis, Luleå University of Technology, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-73367.</p> <p>Notes:<br> - The observations in this data set cover the snow-free parts of 2016-2019.<br> - For flow data, only observations >= 1 l/s are provided.</p> <p> </p> <p>The authors would like to thank Helen Galfi, Ralf Rentz and Karolina Berggren for their work in the initial setup and maintenance of the field measurements.</p>
Data from: Metropolitan lizards? Urbanization gradient and the density of lagartixas (Tropidurus hispidus) in a tropical city
Urbanization, with its cohort of environmental stressors, has a dramatic effect on wildlife, causing loss of biodiversity and decline in population abundance customarily associated with increasing levels of impervious surface and fragmentation of native habitats. Some studies suggest that faunal species from open habitats, and with higher abundance in natural environments, seem more likely to tolerate and live in urban environments. Here I evaluate how the level of urbanization affects lagartixas (Tropidurus hispidus) one of the most common lizards found in open vegetation ecosystems in NE Brazil. I surveyed a total of 47 transects across sites that differed in proportion of impervious surface (high, mild, peri-urban and rural). I also collected specific biotic (herbaceous cover, tree and arthropod abundance) and abiotic (amount of shelters and impervious surfaces) factors that could affect lagartixas abundance. Ants were the most common arthropod both in the rural and urban environment. Lagartixas thrive in urban environments and trees and shelter were key predictors of their abundance. Lagartixas show a clear association with use of artificial structures. The low densities of lagartixas in rural areas and higher density in urbanized areas suggests that they colonized urban areas due to the hard surfaces and they probably are not exploiting a novel habitat, but somewhat responding to conditions resembling those in which they evolved. Finally, lagartixas are extremely common in tropical cities, they have a suite of features that are associated with selective pressures in cities and they might play a key functional role in urban ecosystems making this lizard an excellent system for the study of ecology and adaptation to the urban environments.
Data from: Evaluating the potential for bird-habitat models to support biodiversity-friendly urban planning
<ol> <li>Urban expansion poses a major threat to wildlife populations. Biodiversity-friendly urban landscapes could deliver benefits for both wildlife and people, by incorporating conservation and ecosystem services objectives. Well-designed urban developments could also soften the ecological impacts of urbanisation. However, delivering urban landscapes that integrate biodiversity requirements effectively remains challenging.</li> <li>Ecological models, designed to predict wildlife population responses to alternative urban designs, could prove effective in supporting the creation of biodiversity-friendly urban landscapes. Here, we combine national-scale bird abundance data with high resolution, spatially explicit habitat data to characterise relationships between bird densities and urban landscape form in Britain. From these analyses and cross-validation, we evaluate the potential for well-parameterised, species-specific models to be used to predict bird densities in novel or modified urban areas.</li> <li>Our analyses indicate that responses of bird abundance to urban habitat are species-specific and complex, with few variables consistently affecting a large proportion of species. However, contiguous areas of greenspace within urban sites are preferential for accommodating breeding birds, compared to a more fragmented arrangement of multiple, small greenspace patches. In combination, the bird-habitat relationships identified could successfully predict observed variation in abundance for most bird species considered.</li> <li>Further evaluation of habitat descriptor variables, spatial scales of species' habitat use and analytical modelling approaches may be needed to improve the predictive ability of bird-habitat models for certain species, particularly waterbirds and those observed less frequently in urban areas.</li> <li> <i>Synthesis and applications.</i> We modelled breeding bird abundance in built-up areas with respect to the characteristics and contexts of urban environments. While most variables were important for multiple species, responses overall were species-specific, so simple assemblage metrics, like diversity, will not describe the variation in bird communities well. However, the results illustrate the potential of an evidence-based, spatially explicit evaluation of urban development impacts on biodiversity, by predicting the consequences for bird numbers. Subject to verification of predictive ability, practitioners can apply the models to compare, for example, land-sparing and sharing within developments, or to quantify the biodiversity requirements for effective offsetting. This would be facilitated by incorporation into an online tool allowing user-determined input scenarios.</li> </ol>
Data from: Colonial history impacts urban tree species distribution in a tropical city
Urban forests associated with green infrastructure for sustainable outcomes are particularly critical in the Global South, where some of the world's fastest-growing cities are located. However, compared to temperate cities, the drivers of urban tree species distribution in tropical cities remain understudied. In this study, we quantify the spatial distribution and abundance of urban forests in the tropical city of Georgetown, Guyana. British colonialism has shaped this city, including forced movement of peoples under slavery from Africa and indentured servants from the Indian Subcontinent. We studied how this multicultural context has influenced tree species distributions in the capital city of the only Anglophone country in South America. We quantified the abundance of tree species using a stratified sampling design to distribute transects across fifteen neighborhoods that vary in distance to the colonial center of the city and ethnic composition. We recorded a total of 57 unique species, the majority of which (73%) were cultivated for their edible fruits. We identify tree species that likely represent Guyana's unique multicultural heritage by comparing our species list to flora in nine cities in neighboring countries (Venezuela and Brazil) with different colonial histories. This international comparison identified a set of tree species that occurred only in Guyana. Relationships between ethnic composition and colonial history and tree species distribution were weak at the neighborhood scale, where proportion of East Indian residents had little explanatory power and distance to colonial center was correlated with abundance of only some species groups. This apparent discrepancy between neighborhood and national scales may relate to the establishment of Guyanese food as a unifying national identifier across ethnicities. The prominence of edible fruit trees in our study suggests a set of species that could be incorporated into urban planning to strengthen biocultural linkages, foster cultural integration, and promote food security.
Data from: Urban forest fragments as unexpected sanctuaries for the rare endemic ghost butterfly from the Atlantic forest.
Anthropogenic land expansion, particularly urbanization, is pervasive, dramatically modifies the environment and is a major threat to wildlife with its associated environmental stressors. Urban remnant vegetation can help mitigate these impacts and could be vital for species unable to survive in harsh urban environments. Although resembling non-urban habitats, urban vegetation remnants are subject to additional environmental stresses. Here we evaluate the occurrence and density of the endemic ghost butterfly (Morpho epistrophus nikolajewna), that was once common, in the highly fragmented Atlantic forest of NE Brazil. We tested whether this butterfly would be found at lower densities in urban forest fragments of contrasting sizes as opposed to rural ones, given the number of environmental stressors found in urban areas. We surveyed 14 forest fragments (range 2.8 to over 3000 ha) of semi-deciduous Atlantic forest in rural and urban locations using transect based distance sampling. The ghost butterflies showed strong seasonality; flying only from April to June. They were only identified in an urban fragment (515 ha), with an estimate of 720 individuals and a density 1.4 ind/ha. All forest fragments had experienced some level of logging in the past, which might have had an effect in the butterfly population. Nevertheless, rural forest fragments were subject to increased particulate matter concentrations, associated to biomass burning, that we suggest might have had a more influential role driving the collapse of rural populations. Our findings show the importance of urban forest remnants to sustain population of this endangered species.
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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)
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.