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.
3,709
datasets available to search
ShareScore release 0.9.0
Dataset results
3,709 results for “urbanization.”
Map of the global wildland-urban interface
<p>The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human-environmental conflicts and risks are concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation, and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking.</p> <p>This dataset features a global, 10 m resolution map of the wildland-urban interface that was developed in a recent study by the authors of this dataset (see corresponding publication).</p> <p><strong>Temporal extent</strong></p> <p>The data contains data representative for ca. 2020.</p> <p><strong>Data format and units</strong></p> <p>The data are organized in tiles of 100 km x 100 km and follow the EQUI7 tiling grid and projection system. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Please consider the generation of image pyramids before using *.vrt files.</p> <p>The raster dataset contains Wildland-urban interface (WUI) data (one layer), 10 m spatial resolution, 8 discrete classes:</p> <p>1 - Forest/Shrubland/Wetland-dominated Intermix WU</p> <p>2 - Forest/Shrubland/Wetland-dominated Interface WUI</p> <p>3 - Grassland-dominated Intermix WUI</p> <p>4 - Grassland -dominated Interface WUI</p> <p>5 - Non-WUI: Forest/Shrub/Wetland-dominated</p> <p>6 - Non-WUI: Grassland-dominated</p> <p>7 - Non-WUI: Urban</p> <p>8 - Non-WUI: Other</p> <p>In addition, the data contain tabular data on WUI area, population and biomass in the WUI, as well as wildfire area and people affected by wildfire in the WUI per world region, country, subnational administrative unit and biome.</p> <p>The data also contain the key algorithm for WUI mapping (also accessible here: https://github.com/franzschug/global_wildland_urban_interface).</p> <p><strong>Further information</strong></p> <p>For further information, please see the publication or contact Franz Schug (fschug@wisc.edu). Visit the website of SILVIS lab, University of Wisconsin-Madison (http://silvis.forest.wisc.edu/globalwui) to learn more about the Wildland-Urban Interface.</p> <p>The data can be interactively visualizes in a web viewer <a href="https://geoserver.silvis.forest.wisc.edu/geodata/fast/globalwui/">here.</a></p> <p><strong>Corresponding publication</strong></p> <p>Schug, Franz<sup>*</sup>; Bar-Massada, Avi; Carlson, Amanda R.; Cox, Heather; Hawbaker, Todd J.; Helmers, David; Hostert, Patrick; Kaim, Dominik; Kasraee, Neda K.; Martinuzzi, Sebastián; Mockrin, Miranda H.; Pfoch, Kira A.; Radeloff, Volker C. The global wildland-urban interface, DOI: 10.1038/s41586-023-06320-0</p> <p><strong>Funding</strong></p> <p>This research was funded by the NASA Land Cover and Land Use Change Program under agreement 80NSSC21K0310.</p>
The variability of mass concentrations and source apportionment analysis of equivalent black carbon across urban Europe
<p>This study analyzed the variability of equivalent black carbon (eBC) mass concentrations and their sources in urban Europe to provide insights into the use of eBC as an advanced air quality (AQ) parameter for AQ standards. This study compiled eBC mass concentration datasets covering the period between 2006 to 2022 from 50 measurement stations, including 23 urban background (UB), 18 traffic (TR), 7 suburban (SUB), and 2 regional background (RB) sites. The results highlighted the need for the harmonization of eBC measurements to allow for direct comparisons between eBC mass concentrations measured across urban Europe. The eBC mass concentrations exhibited a decreasing trend as follows: TR > UB > SUB > RB. Furthermore, a clear decreasing trend in eBC concentrations was observed in the UB sites moving from Southern to Northern Europe. The eBC mass concentrations exhibited significant spatiotemporal heterogeneity, including marked differences in eBC mass concentration and variable contributions of pollution sources to bulk eBC between different cities. Seasonal patterns in eBC concentrations were also evident, with higher winter concentrations observed in a large proportion of cities, especially at UB and SUB sites. The contribution of eBC from liquid fossil fuel combustion, mostly traffic (eBC<sub>T</sub>) was higher than that of residential and commercial sources (eBC<sub>RC</sub>) in all European sites studied. Nevertheless, eBC<sub>RC</sub> still had a substantial contribution to total eBC mass concentrations at a majority of the sites. eBC trend analysis revealed decreasing trends for eBC<sub>T</sub> over the last decade, while eBC<sub>RC</sub> remained relatively constant or even increased slightly in some cities.</p>
Figure 1 in Where the rare species hide: a new record of Parachironomus monochromus (van der Wulp, 1874) for Slovakia from artificial urban waterbodies
Figure 1. View of the urban pond (left) and city fountain (right) in Banská Bystrica, where Parachironomus monochromus exuviae were collected. Photo: S Bartóková and L Hamerlík.
Figure 2 in Where the rare species hide: a new record of Parachironomus monochromus (van der Wulp, 1874) for Slovakia from artificial urban waterbodies
Figure 2. Number of Parachironomus monochromus exuviae recorded in the urban pond during the study period. Dates on x-axis refer to sampling dates. Dates after 17. 9. 2021 are not shown due to the absence of the species in the samples.
Figure 3 in New range extensions for the Canadian Chironomidae fauna from two urban streams
Figure 3. Sublettea coffmani (Roback, 1975) pupa. a) Thoracic horn, b) Abdominal tergite I-V, c) Spine patches on segment IV, d) Spine patches on ventral side of sternite VIII (arrows), e) Anal lobe and genital sac.
Figure 2 in New range extensions for the Canadian Chironomidae fauna from two urban streams
Figure 2. Rheosmittia spinicornis (Brundin, 1956) pharate male a-b, pupa c-d. a) Thorax, arrow indicates the location of scutal tubercle, b) Hypopygium, arrows indicate the inferior volsella, c) Cephalothorax, d) Anal lobes and genital sacs.
Figure 1 in New range extensions for the Canadian Chironomidae fauna from two urban streams
Figure 1. Odontomesa fulva (Kieffer, 1919) larva. a) Antenna, b) Labrum, SIV A (black arrow) and premandibles (white arrows), c) Mentum, d) Ventromental plate, e) Mandible, arrow points to basal external seta with 2 branches at the base, f) Variation of basal external seta with several branches, g) Posterior portion of the larva.
Abb. 4 in Die Allmend in Luzern: Urbaner Lebensraum einer artenreichen Fauna xylobionter Käfer (Coleoptera)
Abb. 4. Der Mohren-Pflanzenkäfer Allecula morio (Fabricius, 1787) gehört zu den Mulmbewohnern. Seine Larve entwickelt sich in trockenem, mit Detritus angereichertem Mulm, vorzugsweise in Stammhöhlen. (Foto: J. Reibnitz)
Abb. 2 in Die Allmend in Luzern: Urbaner Lebensraum einer artenreichen Fauna xylobionter Käfer (Coleoptera)
Abb. 2. Der Efeu-Borkenkäfer Kissophagus he- derae (Schmitt, 1843) ist ein Frischholzbewoh- ner. Seine Larven leben ausschliesslich unter der Rinde von austrocknenden starken Ästen des Efeu Hedera helix. (Foto: J. Reibnitz)
Abb. 3 in Die Allmend in Luzern: Urbaner Lebensraum einer artenreichen Fauna xylobionter Käfer (Coleoptera)
Abb. 3. Der Krainische Scheinbockkäfer Nacerdes carniolica (Gistl, 1832) ist ein Altholzbewohner. Die Larven entwickeln sich im morschen Nadel- holz, besonders von Kiefern und Fichten. (Foto: J. Reibnitz)
Urban Agriculture and Health in Africa. A Review
<p>The Excel table is raw data containing publications from the systematic literature review on urban agriculture's impacts on health and urban planning research.</p> <p>This work was totally funded by the Swiss National Science Foundation (SNF#18357) Sinergia Project – African Contribution to Global Health: Circulating Knowledge and Innovations.</p>
Large positive ecological changes of small urban greening actions
<p><strong>Updated data and R codes associated with our article <em>Large positive ecological changes of small urban greening actions</em>:</strong></p> <p><strong>Ecological Solutions and Evidence</strong></p> <p><strong>Abstract</strong></p> <p>The detrimental effects of human-induced environmental change on people and other species are acutely manifested in urban environments. While urban greenspaces are known to mitigate these effects and support functionally diverse ecological communities, evidence of the ecological outcomes of urban greening remains scarce. We use a longitudinal observational design to provide empirical evidence of the ecological benefits of greening actions. We show how a small greening action quickly led to large positive changes in the richness, demographic dynamics, and network structure of a depauperate insect community. We demonstrate how large ecological benefits may be derived from investing in small greening actions and how these contribute to bring indigenous species back to greenspaces where they have become rare or locally extinct. Our findings provide crucial evidence that support best practice in greenspace design and contribute to re-invigorate policies aimed at mitigating the negative impacts of urbanisation on people and other species. </p>
Data from: Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape
<p>Cities can have profound impacts on ecosystems, yet our understanding of these impacts is currently limited. First, the effects of socioeconomic dimensions of human society are often overlooked. Second, correlative analyses are common, limiting our causal understanding of mechanisms. Third, most research has focused on terrestrial systems, ignoring aquatic systems that also provide important ecosystem services. Here we compare the effects of human population density and low-income prevalence on the macroinvertebrate communities and ecosystem processes within water-filled artificial tree holes. We hypothesized that these human demographic variables would affect tree holes in different ways via changes in temperature, water nutrients, and the local tree hole environment. We recruited community scientists across Greater Vancouver (Canada) to provide host trees and tend 50 tree holes over 14 weeks of colonization. We quantified tree hole ecosystems in terms of aquatic invertebrates, litter decomposition, and chlorophyll-a. We compiled potential explanatory variables from field measurements, satellite images, or census databases. Using structural equation models, we showed that invertebrate abundance was affected by low-income prevalence but not human population density. This was driven by cosmopolitan species of Ceratopogonidae (Diptera) with known associations to anthropogenic containers. Invertebrate diversity and abundance were also affected by environmental factors, such as temperature, elevation, water nutrients, litter quantity, and exposure. By contrast, invertebrate biomass, chlorophyll-a, and litter decomposition were not affected by any measured variables. In summary, this study shows that some urban ecosystems can be largely unaffected by human population density. Our study also demonstrates the potential of using artificial tree holes as a standardized, replicated habitat for studying urbanization. Finally, by combining community science and urban ecology, we were able to involve our local community in this pandemic research pivot. </p> <p>This abstract is quoted from the original article "Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape" in Ecology (2023) by DS Srivastava et al.</p>
Urban Land Use Dataset (1964-2001) of Maputo city, Mozambique
<p>This dataset comprises land use maps of Maputo city, with exception of the KaTembe urban district, for the years 1964, 1973, 1982, 1991 and 2001. It is the digital version of the land use maps published by Henriques [1] and revised under the <a href="https://luco.fa.ulisboa.pt/index.php/en/">LUCO</a> research project.</p> <p>The land use of Maputo city was identified from: i) aerial photographs (1964, 1982, 1991), orthophoto maps (1973) and IKONOS images (2001); ii) documentary sources, such as the Urbanization Master Plan (1969) and the Maputo City Addressing (1997); iii) the recognition made during several field survey campaigns. The methodology is described in Henriques [1].</p> <p>Land use was classified into three levels, resulting from a hierarchical classification system, including descriptive and parametric classes. Levels I and II are available in this repository.</p> <p>Level I, composed by 10 classes, contains the main forms of occupation: built-up areas (residential, economic activity, equipment, and infrastructure) and non-built-up areas (vacant or "natural"). It is geared towards analyses that serve policymaking and resource management at the regional or national scale [1].</p> <p>Level II, composed by 31 classes, discriminates the higher hierarchical level according to its functional land use to become useful for municipal planning and management in municipal master plans, for example [1].</p> <p>Maps are available in shapefile format and include predefined symbology-legend files, for QGIS and ArcGIS (v.10.7 or higher). The urban land use classes are described in Portuguese and English, and their meaning is provided as an accompanying document (ULU_Maputo_Nomenclatura_PT.pdf / ULU_Maputo_Nomenclature_EN.pdf).</p> <p>Data format: vector (shapefile, polygon)</p> <p>Reference system: WGS84, UTM 36S (EPSG:32736)</p> <p>Original minimum mapping unit: 25 m2</p> <p>Urban Land Use dataset attributes:</p> <p>[N_I_C] – code of level I</p> <p>[N_I_D_PT] – name of level I, in Portuguese</p> <p>[N_I_D_EN] - name of level I, in English</p> <p>[N_II_C] – code of level II</p> <p>[N_II_D_PT] - name of level II, in Portuguese</p> <p>[N_II_D_EN] - name of level II, in English</p> <p>Funding: this research was supported by national funds through FCT – Fundação para a Ciência e Tecnologia, I.P. Project number: FCT AGA-KHAN/ 541731809 / 2019</p> <p>[1] Henriques, C.D. (2008). <em>Maputo. Cinco décadas de mudança territorial. </em><em>O uso do solo observado por tecnologias de informação geográfica</em> [<em>Maputo. </em><em>Five decades of territorial transformation. Land use assessed by geographical information technologies</em>]. Lisboa, Instituto Português de Apoio ao Desenvolvimento (ISBN: 978-972-8975-22-7).</p>
Dataset of AI4ER MRes titled "Improving Urban Tree Management Using High-Resolution Satellite Data"
<p>This repository contains the data used in the Master's thesis titled "Improving Urban Tree Management Using High-Resolution Satellite Data" by Andrés C. Zúñiga-González as part of the AI4ER MRes 1st year project at the University of Cambridge.</p> <p>The folders are split into large and small training and testing datasets. These folders contain the tiles (in png and tif formats) used in the models. In addition, it includes the crowns in ESRI Shapefile format for the training and testing datasets. Finally, it contains the best model from the project (named urban_trees_Cambridge_20230630.pth).</p>
Data used in the PhD dissertation entitled "Hidden beneath the surface: Microbial methane cycling in Dutch urban canals"
<p>Data used for the figures presented in the PhD dissertation of KAJ Pelsma, entitled "Hidden beneath the surface: Microbial methane cycling in Dutch urban canals". The chapters to which each file corresponds is indicated in each file name.</p>
Fig. 4A-D in The impact of urban warfare on the structure of ant assemblages on trees (Hymenoptera: Formicidae)
Fig. 4A-D – Multivariate linear regression (1 independent, n dependent) for different parameters: A – between degree of damage and number of ants; B – between number of ants and tree diameter; C – between dendrobiont (nesting in trees) ants and degree of damage; D – between herpetobiont (nesting in soil) ants and degree of damage.
Fig. 2A-F in The impact of urban warfare on the structure of ant assemblages on trees (Hymenoptera: Formicidae)
Fig. 2A-F – Degrees of damaged trees. A – undamaged trees, B – 1st degree of damage, C – 2nd degree, D – 3rd degree; E – 4th degree; F – 5th degree. Black arrows indicate superficial damage to the tree bark, red arrows indicate deep damage to conductive tissues, yellow arrows - destruction of the upper part of the tree trunk, blue arrows - irreparable damage to the tree (destruction of the trunk).
Fig. 1A-B in The impact of urban warfare on the structure of ant assemblages on trees (Hymenoptera: Formicidae)
Fig. 1A-B – Investigated locations in the Kyiv region: A – Bucha; B – Irpin. Areas of cities affected by military operations are highlighted in red. Data by UN Satellite Center.
Exploring the Relationship Between Land Cover Classifications and Urban Heat Island Intensity
<p>This dataset is a collection of data and results from a research project conducted by NASA SEES Interns. The research project aimed to study urban heat islands and their relationship with land cover observations. This dataset upload consists of 12 files. One file is a poster pdf that includes all the information needed about the project. The other 11 files are png images of heatmaps, bar graphs, scatter plots, and tables used in the analysis of our project. For quick reference, the abstract to this project is below:</p> <p><strong>The urban heat island (UHI) effect refers to the phenomenon in which urban areas experience higher temperatures compared to their rural counterparts. This research aims to quantify and examine the UHI effect within three areas of interest (AOIs) by utilizing LANDSAT imagery. In addition, this study seeks to explore the relationship between land cover classifications, which represent the most green (rural) and the most urban areas, and the intensity of the UHI effect. To achieve this, temperature data from local weather stations are analyzed, and statistical methods are employed to determine whether a correlation exists between the difference in land cover classifications and the intensity of the UHI effect, as determined by the average temperature difference between urban and rural areas. Google Earth Engine is used to visualize LANDSAT data from 2013 to 2022 in the months of July and August for each AOI. Subsequently, the data is compared with the land cover classifications from Collect Earth Online using statistical models in Microsoft Excel. These tools were used to take data from three pre-selected areas of interest in GLOBE Observer. The data findings from this analysis suggest that the more tree cover and rural an area is according to our classification method, the lower the UHI intensity. On the other hand, the higher the urban area, the higher the UHI intensity. By beginning this research, we have reinforced the validity of land cover classifications, and we now have the capability to generally predict the UHI intensity of locations based on their classifications. Overall, this investigation aims to contribute to a better understanding of the GLOBE land cover classifications and their potential indications of UHI intensity.</strong></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.