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51 results for “urban development”

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dryad36/100

Logistics of zoning, zoning for logistics: Toward healthy and equitable development for urban freight

Open the record for dataset details and reuse information.

publicJul 2025View details →
edi36/100

Spatial-temporal change of climate in relation to urban fringe development in central Arizona-Phoenix

Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds. Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims. In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear re

openOpenJan 2020View details →
zenodo32/100

TAU Urban Acoustic Scenes 2020 Mobile, Development dataset

<p>TUT Urban Acoustic Scenes 2020 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Traveling by a tram - <em>tram</em></li> <li>Traveling by a bus - <em>bus</em></li> <li>Traveling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>The dataset contains in total 64 hours of audio. Version 2 fixes synchronization between 118 segments from devices A, B, and C, and removes 5 incorrect audio segments.</p>

openother-ncFeb 2020View details →
zenodo32/100

TAU Urban Acoustic Scenes 2022 Mobile, Development dataset

<p>TAU Urban Acoustic Scenes 2022 Mobile development dataset consists of 1-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Traveling by a tram - <em>tram</em></li> <li>Traveling by a bus - <em>bus</em></li> <li>Traveling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>The dataset contains in total 64 hours of audio.&nbsp;</p>

openother-ncMar 2022View details →
zenodo32/100

TUT Urban Acoustic Scenes 2018 Mobile, Development dataset

<p>TUT Urban Acoustic Scenes 2018 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Recordings were made with three devices that captured audio simultaneously. Each acoustic scene has 864 segments (144 minutes of audio) recorded with device A (main device) and 72 segments of parallel audio (12 minutes) each recorded with devices B and C. The dataset contains in total 28 hours of audio.</p>

openother-ncApr 2018View details →
zenodo32/100

TUT Urban Acoustic Scenes 2018, Development dataset

<p>TUT Urban Acoustic Scenes 2018 development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Each acoustic scene has 864 segments (144 minutes of audio). The dataset contains in total 24 hours of audio.</p>

openother-ncApr 2018View details →
zenodo32/100

TAU Urban Acoustic Scenes 2019 Mobile, Development dataset

<p>TUT Urban Acoustic Scenes 2019 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Recordings were made with three devices that captured audio simultaneously. Each acoustic scene has 1440 segments (240 minutes of audio) recorded with device A (main device) and 108 segments of parallel audio (18 minutes) each recorded with devices B and C. The dataset contains in total 46 hours of audio.</p>

openother-ncMar 2019View details →
zenodo32/100

TAU Urban Acoustic Scenes 2019, Development dataset

<p>TAU Urban Acoustic Scenes 2019 development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Each acoustic scene has 1440 segments (240 minutes of audio). The dataset contains in total 40 hours of audio.</p>

openother-ncMar 2019View details →
zenodo32/100

TAU Urban Acoustic Scenes 2019 Openset, Development dataset

<p>TAU Urban Acoustic Scenes 2019 Openset development dataset is designed for researching open set classification problem in acoustic scene classification. In this problem, the test recording may be from a different environment than the 10 target classes. The dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>In addition, material for Unknown scene `unknown` is provided from 4 scenes:</p> <ul> <li>Beach - <em>beach</em>, extracted from TUT Acoustic scenes 2017 dataset</li> <li>Library - <em>library</em>, extracted from TUT Acoustic scenes 2017 dataset</li> <li>Office - <em>office</em>, extracted from TUT Acoustic scenes 2017 dataset</li> <li>Public event - <em>public_event</em></li> </ul>

openother-ncMar 2019View details →
dryad32/100

Tourism and urban development as drivers for invertebrate diversity loss on tropical islands

<p>Oceanic islands harbour a disproportionately high number of endemic and threatened species. Rapidly growing human populations and tourism are posing an increasing threat to island biota, yet the ecological consequences of these human land uses on small oceanic island systems have not been quantified. Here, we investigated and compared the impact of tourism and urban island development on ground-associated invertebrate biodiversity and habitat composition on oceanic islands. To disentangle tourism and urban land uses, we investigated Indo-Pacific atoll islands, which either exhibit only tourism or urban development, or remain uninhabited. Within the investigated system, we show that species richness, abundance, and Shannon diversity of the ground-associated invertebrate community are significantly decreased on islands used for tourism and on islands with urban development, relative to uninhabited islands. Remote-sensing-based spatial data suggests that habitat fragmentation and a reduction in vegetation density are having significant effects on biodiversity on urban islands, whereas land use/ cover changes could not be linked to the documented biodiversity loss on tourist islands. This offers first direct evidence for a major terrestrial invertebrate loss on remote oceanic islands due to different human land uses with yet unforeseeable long-term consequences for the stability and resilience of oceanic island ecosystems.</p>

opencc-zeroSep 2021View details →
dryad32/100

Data from: Urban development, land sharing and land sparing: the importance of considering restoration

Open the record for dataset details and reuse information.

publicMar 2018View details →
dryad32/100

Tourism and urban development as drivers for invertebrate diversity loss on tropical islands

Open the record for dataset details and reuse information.

publicSep 2021View details →
dryad32/100

Data from: Does urbanization cause stress in wild birds during development? insights from feather corticosterone levels in juvenile house sparrows (Passer domesticus)

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publicDec 2018View details →
dryad28/100

Data from: The Urban Heat Island and its spatial scale dependent impact on survival and development in butterflies of different thermal sensitivity

Climate alteration is one of the most cited ecological consequences of urbanization. However, the magnitude of this impact is likely to vary with spatial scale. We investigated how this alteration affects the biological fitness of insects, which are especially sensitive to ambient conditions and well-suited organisms to study urbanization-related changes in phenotypic traits. We monitored temperature and relative air humidity in wooded sites characterized by different levels of urbanization in the surroundings. Using a split-brood design experiment, we investigated the effect of urbanization at the local (i.e., 200 × 200 m) and landscape (i.e., 3 × 3 km) scale on two key traits of biological fitness in two closely related butterfly species that differ in thermal sensitivity. In line with the Urban Heat Island concept, urbanization led to a 1°C increase in daytime temperature and an 8% decrease in daytime relative humidity at the local scale. The thermophilous species Lasiommata megera responded at the local scale: larval survival increased twofold in urban compared to rural sites. Urbanized sites tended to produce bigger adults, although this was the case for males only. In the woodland species Pararge aegeria, which has recently expanded its ecological niche, we did not observe such a response, neither at the local, nor at the landscape scale. These results demonstrate interspecific differences in urbanization-related phenotypic plasticity and larval survival. We discuss larval pre-adaptations in species of different ecological profiles to urban conditions. Our results also highlight the significance of considering fine-grained spatial scales in urban ecology.

opencc-zeroDec 2015View details →
zenodo28/100

Data from: Habitat diversification associated with urban development has a little effect on genetic structure in the annual native plant Commelina communis in an East Asian megacity

<p>Basic statistics for each population and genetic and landscape data between populations.</p>

opencc-by-4.0Dec 2023View details →
zenodo28/100

Fig. 10. A–K, M, O. Eurytreta minor Biernat. A in Urban and Peri-urban small and medium-size Enterprise Development for sustainable Vegetable Production and Marketing Systems

Fig. 10. A–K, M, O. Eurytreta minor Biernat. A. Dorsal valve RM Br133819, exterior, × 55. B, G, K. Dorsal valve RM Br133820, interior (B, × 40), oblique lateral view (G, × 40), detail of pseudointerarea (K, × 40). C, F, J, O. Ventral valve RM Br133821, exterior (C, × 75), oblique lateral view (F, × 80), detail of larval shell (J, × 60), detail of larval pitting (O, × 500). D, M. Dorsal valve RM Br133822, interior (D, × 50) and detail of pseudointerarea (M, × 135). E. Dorsal valve RM Br133823, oblique lateral view, × 90. H. Dorsal valve RM Br133824, interior, × 38. I. Dorsal valve RM Br133825, interior, × 53. L, N. Eoconulus sp. L. Dorsal valve RM Br133826, oblique lateral view, × 60. N. Dorsal valve RM Br133827, interior, × 50. All specimens from the Tremadoc chalcedonites, Wysoczki.

opencc-by-4.0Dec 2002View details →
zenodo28/100

Fig. 1. A–L in Urban and Peri-urban small and medium-size Enterprise Development for sustainable Vegetable Production and Marketing Systems

Fig. 1. A–L. Leptembolon cf. lingulaeformis (Mickwitz). A, E. Ventral valve RM Br133755, interior (A, × 18) and oblique lateral view of interior (E, × 32). B. Ventral valve RM Br133756, exterior; × 23. C, G, J. Ventral valve RM Br133757, interior (C, × 15), oblique lateral view (G, × 23) and detail of pseudointerarea (J, × 54). D, I. Dorsal valve RM Br133758, oblique lateral view of interior (D, × 30) and detail of pseudointerarea (I, × 46). E. Ventral valve RM Br133759, oblique lateral view of exterior; × 30. H. Dorsal valve RM Br133760, oblique lateral view of interior; × 26. K. Ventral valve RM Br133761, interior; × 37. L. Ventral valve RM Br133762, oblique lateral view of umbo; × 92. M–O. Rowellella sp. M. Dorsal valve RM Br133763, oblique lateral view of juvenile dorsal valve; × 41. N, O. Indeterminate valve RM Br133764, oblique lateral view (N, × 84) and detail of ornamentation (O, × 110). P–R. Orbithele ceratopygarum (Brøgger). P, Q. Ventral valve RM Br133765, exterior (P, × 37) and detail of larval shell (Q, × 100). R. Ventral valve RM Br133766, oblique lateral view of ventral valve exterior; × 80. All specimens from the Tremadoc chalcedonites, Wysoczki.

opencc-by-4.0Dec 2002View details →
zenodo28/100

Narrowing the Gap Between Urban and Rural Fields: Trust in E-government Services as A Tool to Develop Sustainable Government-citizen Relationship – The Case in Chongqing, China.

<p>Data in research</p>

opencc-by-4.0Oct 2019View details →
zenodo28/100

Continental Mapping Of African Sand Mining Shows Contrasting Links To Urban Development

<p>Continental African sand mining detection data used in '<strong>Continental Mapping Of African Sand Mining Shows Contrasting Links To Urban Development'</strong></p>

openAug 2024View details →
zenodo28/100

The development and validation of an Inhomogeneous Wind Scheme for Urban Street, Part B: perpendicular CFD simulations

<p>The CFD simulation results of&nbsp; perpendicular scenerios.</p>

opencc-by-4.0Nov 2022View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record