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3,709 results for “urbanization.”
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>
Figure 3 in Population structure of a native and an alien species of snail in an urban area of the Atlantic Rainforest
Figure 3. Detectability probability (A), abundance (B) and recruitment (C) estimated for Achatina fulica during the study. The error bars show 90% confidence intervals.
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>
Spectral Library of Impervious Urban Materials
<p>The radiative response of impervious urban materials is a highly influential surface property, due to its impacts on the radiation balance of incoming and outgoing long- and short-wave fluxes. Information about the material composition can be determined with data resolved to the wavelength level. Spectral reflectance in the visible- to short-wave infrared (VIS-SWIR) region is widely used in remote sensing-based land cover classification and spectral long-wave infrared (LWIR) emissivity is required for the observation of surface temperatures. The Spectral Library of impervious Urban Materials (SLUM) available from the London Urban Micromet data Archive (LUMA) includes LWIR emissivity spectra of 74 samples of impervious surfaces derived using measurements made by a portable Fourier Transform InfraRed (FTIR) spectrometer and matching short-wave reflectance spectra observed for each urban sample.</p> <p>The documentation (<a href="http://www.met.reading.ac.uk/micromet/documents/LUMA_SLUM.pdf">pdf</a>) contains photos, meta information for all 74 samples and plots of the short-wave reflactance (300-2500 nm) and long-wave (8-14 um) emissivity spectra.</p> <p>Data are provided in csv format for short-wave reflectance (LUMA_SLUM_SW.csv) and long-wave emissivity (LUMA_SLUM_LW.csv).</p> <p>Further details (including integrated broadband values of emissivity and albedo), methods and data analysis are presented in</p> <p>Kotthaus, S, TEL Smith, MJ Wooster, and CSB Grimmond 2014: Derivation of an urban materials spectral library through emittance and reflectance spectroscopy, <em>ISPRS Journal of Photogrammetry and Remote Sensing</em>, 94, 194–212. doi:10.1016/j.isprsjprs.2014.05.005</p> <p><strong>Please cite both this site and the paper above if you use this data</strong></p>
Dataset of Invasion risks and social interest of non-native woody plants in urban parks of Spain
<p>Full datasets for the research entitled "Invasion risks and social interest of non-native woody plants in urban parks of Spain"</p>
[Database] Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets
<p>This file contains the complete catalog of datasets and publications reviewed in: Di Mauro A., Cominola A., Castelletti A., Di Nardo A.. <em>Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets.</em> Water 2021.The <strong>complete catalog</strong> contains:</p> <ul> <li>92 state-of-the-art water demand datasets identified at the district, household, and end use scales;</li> <li>120 related peer-reviewed publications;</li> <li>57 additional datasets with electricity demand data at the end use and household scales.</li> </ul> <p>The following <strong>metadata</strong> are reported, for each <strong>dataset</strong>:</p> <ul> <li>Authors</li> <li>Year</li> <li>Location</li> <li>Dataset Size</li> <li>Time Series Length</li> <li>Time Sampling Resolution</li> <li>Access Policy.</li> </ul> <p>The following <strong>metadata </strong>are reported, for each <strong>publication</strong>:</p> <ul> <li>Authors</li> <li>Year</li> <li>Journal</li> <li>Title</li> <li>Spatial Scale</li> <li>Type of Study: Survey (S) / Dataset (D)</li> <li>Domain: Water (W)/Electricity (E)</li> <li>Time Sampling Resolution</li> <li>Access Policy</li> <li>Dataset Size</li> <li>Time Series Length</li> <li>Location</li> </ul> <p><strong>Authors:</strong><br> Anna Di Mauro - Department of Engineering | Università degli studi della Campania Luigi Vanvitelli (Italy) | <a href="mailto:anna.dimauro@unicampania.it">anna.dimauro@unicampania.it</a>;<br> Andrea Cominola - Chair of Smart Water Networks | Technische Universität Berlin - Einstein Center Digital Future (Germany) | <a href="mailto:andrea.cominola@tu-berlin.de">andrea.cominola@tu-berlin.de</a>; <br> Andrea Castelletti - Department of Electronics, Information and Bioengineering | Politecnico di Milano (Italy) | <a href="mailto:andrea.castelletti@polimi.it">andrea.castelletti@polimi.it</a><br> Armando Di Nardo -Department of Engineering | Università degli studi della Campania Luigi Vanvitelli (Italy) | <a href="mailto:armando.dinardo@unicampania.it">armando.dinardo@unicampania.it</a></p> <p><strong>Citation and reference:</strong></p> <p>If you use this database, please consider citing <a href="https://www.mdpi.com/2073-4441/13/1/36">our paper</a> </p> <p>Di Mauro, A., Cominola, A., Castelletti, A., & Di Nardo, A. (2021). Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets. Water, 13(1), 36, https://doi.org/10.3390/w13010036</p> <p><strong>Updates and Contributions:</strong></p> <p>The catalogue stored in this public repository can be collaboratively updated as more datasets become available. The authors will periodically update it to a new version. </p> <p>New requests can be submitted to the authors, so that the dataset collection can be improved by different contributors. Contributors will be cited, step by step, in the updated versions of the dataset catalogue.</p> <p><strong>Updates history:</strong></p> <ol> <li>March 1st, 2021 - Pacheco, C.J.B., Horsburgh, J.S., Tracy, J.R. (Utah State University, Logan, UT - USA) --- The dataset associated with paper <a href="https://doi.org/10.3390/s20133655">Bastidas Pacheco, C.J.; Horsburgh, J.S.; Tracy, R.J.. A Low-Cost, Open Source Monitoring System for Collecting High Temporal Resolution Water Use Data on Magnetically Driven Residential Water Meters. Sensors 2020, 20, 3655.</a> is published in the HydroShare repository, where it is available as an OPEN dataset. Data can be found here: <a href="https://doi.org/10.4211/hs.4de42db6485f47b290bd9e17b017bb51">https://doi.org/10.4211/hs.4de42db6485f47b290bd9e17b017bb51</a></li> </ol>
Resilient and sustainable Permeable Pavements For urban Flood Mitigation
<p>Permeable pavements are more sustainable option towards climate change as they maintain the hydrological cycle. However, they suffer from problems such as lower strength and integrity. In this project, this issue is addressed in three main stages: a. development of high viscosity bitumen; b. evaluating different types of additives to be used in porous asphalt mixtures (surface course of permeable pavements); c. Development of a multi-criteria tool to implement the permeable pavement system using GIS software. </p>
ChengYu Urban Agglomeration Dataset
<p>This dataset contains a shapefile and an excel document. The shapefile data includes the spatial data of ChengYu Urban Agglomeration and its attributes such as population, GDP, transportation, education, and public health. The excel document contains the traffic cost between cities for different modes of travel, such as expressway, high-speed railway, and general speed railway.</p>
Figs 14–16 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 14–16. Mumetopia interfeles Roháček sp. nov., female paratypes (SMOC MIT076–MIT078). 14. Body of aberrant specimen, lateral view. 15. Right wing. 16. Posterior part of thorax and abdomen, dorsal view. Scale bars = 0.5 mm. Photos by P. Krásenský.
Figs 1–3 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 1–3. Mumetopia interfeles Roháček sp. nov., ♂. 1. Holotype (SMOC MIT001), lateral view. 2. Right wing, paratype (SMOC MIT003). 3. Head and thorax, paratype (SMOC MIT002), laterodorsal view. Scale bars = 0.5 mm. Photos by P. Krásenský.
Fig. 32 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Fig. 32. Bayesian hypothesis for relationships of 64 species of Anthomyzidae based on DNA sequence data (12S, 16S, 28S, COI, COII, CytB, ITS2) representing 4583 characters. Numbers above nodes = posterior probability values if> 0.5, and below nodes = bootstrap support values for RAxML.
Figs 17–21 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 17–21. Mumetopia interfeles Roháček sp. nov., female paratypes (SMOC MIT080–MIT083). 17. Abdomen, dorsal view. 18, 21. Spermatheca. 19. Genital chamber and S8, lateral view. 20. Same, ventral view (setosity of S8 omitted). Scale bars: 17 = 0.2 mm; 18, 21= 0.05 mm; 19–20 = 0.1 mm. For abbreviations see Material and methods.
Figs 9–13 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 9–13. Mumetopia interfeles Roháček sp. nov., male paratypes (SMOC MIT005, MIT006). 9. Gonostylus, posterolateroventral view (widest extension view). 10. Hypandrial complex, lateral view. 11. Transandrium, caudal view. 12. Filum of distiphallus, anteroventral view. 13. Aedeagal complex, lateral view. Scale bars: 9, 12 = 0.05 mm; 10–11, 13 = 0.1 mm. For abbreviations see Material and methods.
Figs 29–31. Maps and habitat. 29 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 29–31. Maps and habitat. 29. Map of Chile with position of type locality of Mumetopia interfeles Roháček sp. nov. (blue open square). 30. Satellite view of part of Valparaíso city, with collecting site indicated by red arrow. 31. Habitat of M. interfeles sp. nov., northern end of grassy area between houses visited by cats. Photo by J. von Tschirnhaus (31), other sources: Vemaps.com (29), Google Earth Pro (30).
Figs 4–8 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 4–8. Mumetopia interfeles Roháček sp. nov., male paratypes (SMOC MIT004–MIT007). 4. Postabdomen with fifth abdominal segment, dorsal view. 5. Same, ventral view. 6. External genitalia, caudal view. 7. Postabdomen with fifth abdominal segment, lateral view. 8. Genitalia, lateral view. Scale bars: 4–5, 7 = 0.2 mm; 6, 8 = 0.1 mm. For abbreviations see Material and methods.
Fig. 34 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Fig. 34. Most parsimonious tree (L = 34 steps, CI = 0.85, RI = 0.82) resulting from cladistic morphological analysis of the Chamaebosca clade, ACCTRAN optimization. Full circles = non-homoplasious character transformations; empty circles = homoplasious character transformations. Numbers below branches indicate change to apomorphic (1, 2) or plesiomorphic (0) states of characters (reversals in case of (0)). Adapted from Roháček & Barber (2009: fig. 38).
Fig. 33 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Fig. 33. RAxML hypothesis for relationships of Anthomyzidae based on DNA sequence data (12S, 16S, 28S, COI, COII, CytB, ITS2) representing 4583 characters, without the Anthomyza group of genera clade displayed. Numbers below nodes = bootstrap support values.
Figs 22–28 in Mumetopia interfeles sp. nov., a new species of Anthomyzidae (Diptera) occurring en masse in an urban grassy habitat in Chile: its taxonomy, phylogeny and biology
Figs 22–28. Mumetopia interfeles Roháček sp. nov., paratypes (SMOC MIT002–MIT006, MIT081– MIT083). 22. ♂, f 1, posterior view. 23. Female postabdomen, lateral view. 24. Same, dorsal view. 25. Same, ventral view. 26. Apex of male t2 and base of mid basitarsus, anterior view. 27. Apex of male t 3 and hind basitarsus with 3 thickened ventrobasal setulae (black arrow), anterior view. 28. Male f 3, anterior view. Scale bars: 22, 26–28 = 0.2 mm; 23–25 = 0.1 mm. For abbreviations see Material and methods.
Reply to comment on "High-resolution, multi-layer modelling of Singapore's urban climate incorporating local climate zones"
<p>This data is for the publication submitted to the Journal of Geophysical Research Atmospheres</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>
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)
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.