Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
21
datasets available to search
ShareScore release 0.9.0
Dataset results
21 results for “urban expansion”
Mapping and Modeling Clandestine Drivers of Urban Expansion in Mexico City (2016-2019)
This dataset incorporates Mexico City related essential data files associated with Beth Tellman's dissertation: Mapping and Modeling Illicit and Clandestine Drivers of Land Use Change: Urban Expansion in Mexico City and Deforestation in Central America. It contains spatio-temporal datasets covering three domains; i) urban expansion from 1992-2015, ii) district and section electoral records for 6 elections from 2000-2015, iii) land titling (regularization) data for informal settlements from 1997-2012 on private and ejido land. The urban expansion data includes 30m resolution urban land cover for 1992 and 2013 (methods published in Goldblatt et al 2018), and a shapefile of digitized urban informal expansion in conservation land from 2000-2015 using the Worldview-2 satellite. The electoral records include shapefiles with the geospatial boundaries of electoral districts and sections for each election, and .csv files of the number of votes per party for mayoral, delegate, and legislature candidates. The private land titling data includes the approximate (in coordinates) location and date of titles given by the city government (DGRT) extracted from public records (Diario Oficial) from 1997-2012. The titling data on ejido land includes a shapefile of georeferenced polygons taken from photos in the CORETT office or ejido land that has been expropriated by the government, and including an accompany .csv from the National Agrarian Registry detailing the date and reason for expropriation from 1987-2007. Further details are provided in the dissertation and subsequent article publication (Tellman et al 2021). The Mexico City portion of these data were generated via a National Science Foundation sponsored project (No. 1657773, DDRI: Mapping and Modeling Clandestine Drivers of Urban Expansion in Mexico City). The project P.I. is Beth Tellman with collaborators at ASU (B.L Turner II and Hallie Eakin). Other collaborators include the National Autonomous University of Mexico (UNAM),
Urban land expansion in area with decreased urban sprawl at global, national, and city scales during 2000 to 2020
<p>I used calibrated population density thresholds from the year 2000 and 2020 Worldpop population model to measure area and densities for urban and suburban density classes (≥ 250 humans per km<sup>2</sup>) at global and national scales and both broad multi-city agglomerations and fine city cores.</p>
FIGURE 7 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 7 Enlarged section of the Maximum-likelihood phylogenetic reconstruction of fig. 6, with all COI sequences shown for the sericatus group, i.e., P. thebeatles, P. medius, and P. sericatus. Colours match those in fig. 5.
FIGURE 4 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 4 Dorsal (perpendicular to the surface of the aedeagus between the orifice and the apex) and lateral views of the apices of the aedeagi of members of the Ptomaphagus sericatus complex. a: P. medius from Oegstgeest, the Netherlands, dorsal (a) and lateral (b) views. b: P. sericatus from Les Arnoulats, France, dorsal (c) and lateral (b) views. c: P. thebeatles from Amsterdam, the Netherlands, dorsal (e) and lateral (f) views. (Images derived from topotypical material, not from the holotype itself.).
FIGURE 2 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 2 Neotype of P. sericatus from Kiev, Ukraine: a, habitus; b, aedeagus, dorsal view (angle of view somewhat more rostral than in fig. 4); c, aedeagus, lateral view; d, genital segment; e, labels.
FIGURE 3 Antennomeres 1-7 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 3 Antennomeres 1-7 for members of the Ptomaphagus sericatus complex. a: P. sericatus, female (a) and male (b) from Les Arnoulats, France. b: P. thebeatles, female (c) from Middelburg, the Netherlands, and male (d) from Schiedam, the Netherlands. After Schilthuizen, 1989. c: P. medius, female (e) from Nieuw & St. Joostland, the Netherlands, and male (f) from Oostvoorne, the Netherlands. After Schilthuizen, 1989.
FIGURE 5 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 5 Distribution map of the specimens studied for this paper (the extralimital specimens of P. medius in Canada have not been included). The white arrows point at records that we interpret as recent range expansions.
FIGURE 6 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 6 Maximum-likelihood phylogenetic reconstruction, based on COI sequences, of P. thebeatles, P. medius, P. sericatus, and other members of the subgenus Ptomaphagus s. str., rooted with P. (Adelops) hatchi. Multiple sequences per species have been collapsed. Support values are given only for branches with>80% bootstrap percentage.
Data from: Were bed bugs the first urban pest insect? Genome-wide patterns of bed bug demography mirror global human expansion
Open the record for dataset details and reuse information.
Dataset of 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions'
<p>This dataset is an integral component of the research presented in 'Unequal Impacts of Urban Industrial Land Expansion on Economic Growth and Carbon Dioxide Emissions' by Yoo et al., 2024. It encompasses:</p> <p><strong>1. Links to two publicly accessible datasets:</strong></p> <ul> <li>Industrial land mapping data derived from Google Earth Engine.</li> <li>Data employed in a longitudinal analysis to evaluate the effects of urban industrial land expansion on CO2 emissions and economic growth.</li> </ul> <p><strong>2. Comprehensive input data </strong>utilized in Mixed Effects Random Forest (MERF) longitudinal modeling to assess the separate impacts on CO2 emissions and economic growth in developing and developed regions.</p> <p><strong>3. Python scripts provided for:</strong></p> <ul> <li>Executing MERF longitudinal modeling.</li> <li>Computing SHAP (SHapley Additive exPlanations) values to interpret the contributions of each predictor variable.</li> <li>Generating figures that visually summarize the findings for both developing and developed regions.</li> </ul> <p> </p> <p><strong>The manuscript is available</strong> at: <a href="https://doi.org/10.1038/s43247-024-01375-x"><span>https://doi.org/10.1038/s43247-024-01375-x</span></a></p> <div> <div> </div> </div>
MAUPP: 20 Years of Urban Expansion in Sub-Saharan Africa
<p>This dataset contains 20 years of urban expansion data for 46 case studies located in Sub-Saharan Africa. For more information, see <a href="https://maupp.ulb.ac.be">the MAUPP website</a>. The dataset can also be explored from your browser in an <a href="https://maupp.ulb.ac.be/page/wp1results/">interactive web map</a>. For each case study, the following files are provided:</p> <pre>Filename: builtup_<year>.tif Format: GeoTIFF [UINT8] Description: Binary built-up data for each year. Legend: 0=Not built-up; 1=Built-up. Filename: builtup_history.tif Format: GeoTIFF [UINT8] Description: Age of the built environment. Legend: 0=Not built-up; 1=Before 1995; 2=1995-2000; 3=2000-2005; 4=2005-2010; 5=2010-2015. Filename: expansion_<year1>_<year2>.tif Format: GeoTIFF [UINT8] Description: Characterization of urban expansion between <year1> and <year2>. Legend: 1=Existing built-up; 2=Infill; 3=Expansion; 4=Leapfrog. Filename: training_samples.tif Format: GeoTIFF [UINT8] Description: Training samples extracted from OpenStreetMap. Legend: 1=Built-up; 2=Not built-up. Filename: aoi.geojson Format: GeoJSON Description: Area of interest (EPSG:4326). Filename: validation.json Format: JSON Description: Validation metrics. Filename: metadata.json Format: JSON Description: Creation date, source data, CRS, country, city.</pre>
Replication materials for "Regional Warming from Urbanization is Disproportionate to Urban Expansion Rate"
<p>The datasets are replication materials for the research "Regional Warming from Urbanization is Disproportionate to Urban Expansion Rate". They show simulated global near-surface air temperature (TSA), specific humidity (Q2M), sensible heat flux (FSH), and latent heat flux (LHFLX) during the warm season over 50 years for four experiments: URB1985, URB2018, URB2018_0, and URB2018_×2. </p>
FIGURE 1 Ptomaphagus thebeatles n in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 1 Ptomaphagus thebeatles n. sp., habitus. Drawing by Erik-Jan Bosch.
Spatial impact of urban expansion on lake surface water temperature based on the perspective of watershed scale
<p>This is the original data from the article "Spatial impact of urban expansion on lake surface water temperature based on the perspective of watershed-scale"</p>
Urban Vegetation Carbon Sink Response to Urbanization Depends on Urban Expansion Rate
Open the record for dataset details and reuse information.
Forecasting the Potential Impact of Urban Expansion on Ecological Networks in Urban Clusters
Open the record for dataset details and reuse information.
Urban impervious surface expansion intensifies heavy rainfall in Beijing's rainy season
Open the record for dataset details and reuse information.
Data from: Niches in the Anthropocene: passerine assemblages show niche expansion from natural to urban habitats
Open the record for dataset details and reuse information.
GIS integration for spatial analysis of urban expansion in Tisaleo canton (Ecuador).
<p><span>Political or economic interests have led to an empirical zonal delimitation, and the deficient use of Geographic Information Systems does not allow the specific characterisation of the territories. This article aims to determine the spatial analysis of the urban expansion areas of the canton of Tisaleo by integrating Geographic Information Systems, using a quantitative research method. The main components analysed are: the situational diagnosis of the canton through the characterisation of its biophysical component, its human settlements and the public system of facilities and social services that support it. Based on this information, an interrelation of the data collected is carried out to complement a spatial analysis with GIS software. The results show that in the canton of Tisaleo there are areas suitable for urban growth, but their limits are overdimensioned, i.e. they include areas that do not have the aptitude to be urbanised, as well as rural areas that have the characteristics to be considered urban.</span></p>
Global Grid of Probabilities of Urban Expansion to 2030
The Global Grid of Probabilities of Urban Expansion to 2030 presents spatially explicit probabilistic forecasts of global urban land cover change from 2000 to 2030 at a 2.5 arc-minute resolution. For each grid cell that is non-urban in 2000, a Monte-Carlo model assigned a probability of becoming urban by the year 2030. The authors first extracted urban extent circa 2000 from the NASA MODIS Land Cover Type Product Version 5, which provides a conservative estimate of global urban land cover. The authors then used population densities from the Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) to create the population density driver map. They estimated the amount of new urban land in each United Nations region by 2030 in a Monte-Carlo fashion based on present empirical distribution of regional urban population densities and probability density functions of projected regional population and GDP values for 2030. To facilitate integration with other data products, CIESIN reprojected the data from Goode's Homolosine to Geographic WGS84 projection.
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.