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300 results for “Urban area”
Figure 1 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)
Figure 1. Satellite image showing nesting site of the T. furcata couple and the surrounding area in Campos dos Goytacazes, Rio de Janeiro. Adapted from Google Earth®.
Рис. 1. Карта-схема р. Амазар. Цифрами обозначены: I — места Αобычи россыпного зоΛота; II — участки иссΛеΑования в 2018–2019 гг.: 1 — реки Амазар и БоΛьшая Чичатка в районе пгт. Амазар, 2 — воΑохраниΛище, 3 — р. Крестовая, 4 — р. Амазар в нижнем течении Fig. 1. Schematic map of the Amazar River. Legend: I — placer gold mining areas; II — survey areas in 2018–2019: 1 — the Amazar and the Bolshaya Chichatka Rivers in the area of Amazar urban-type settlement, 2 — water storage reservoir, 3 — the Krestovaya River, 4 — the lower reaches of the Amazar River in Dynamics and current status of the Amazar River ichthyofauna after the construction of the PPM «Polyarnaya» hydroelectric complex
Рис. 1. Карта-схема р. Амазар. Цифрами обозначены: I — места Αобычи россыпного зоΛота; II — участки иссΛеΑования в 2018–2019 гг.: 1 — реки Амазар и БоΛьшая Чичатка в районе пгт. Амазар, 2 — воΑохраниΛище, 3 — р. Крестовая, 4 — р. Амазар в нижнем течении Fig. 1. Schematic map of the Amazar River. Legend: I — placer gold mining areas; II — survey areas in 2018–2019: 1 — the Amazar and the Bolshaya Chichatka Rivers in the area of Amazar urban-type settlement, 2 — water storage reservoir, 3 — the Krestovaya River, 4 — the lower reaches of the Amazar River
Fig. 2 in Not only pond sliders: freshwater turtles in the water bodies of the Milan northern urban area (Italy)
Fig. 2 - Distribution maps of the species found in the study area. Circled letters: species records; when the position is approximated, the circle is dashed. P. subrufa records are omitted because the species was recovered far from the wetlands; also T. scripta is not shown, because the species was excluded from the study. Letters indicate the wetlands as in Fig. 1 (modified from https://d-maps.com/ and GeoPortale Regione Lombardia). / Mappa di distribuzione delle specie rinvenute nell'area di studio. Lettera cerchiata: specie presente; quando la posizione è approssimativa, il cerchio è tratteggiato. Il dato per P. subrufa è omesso in quanto la specie è stata rinvenuta lontano dalle zone umide; la distribuzione di T. scripta non è indicata poiché la specie non è oggetto del presente studio. Le aree umide sono indicate da lettere secondo la nomenclatura usata in Fig. 1 (modificato da https://d-maps.com/ e GeoPortale Regione Lombardia).
Fig. 1 in Not only pond sliders: freshwater turtles in the water bodies of the Milan northern urban area (Italy)
Fig. 1 - Study area (Lombardy region, Northern Italy). Letters indicate each studied wetland (modified from www.d-maps.com and GeoPortale Regione Lombardia). / Area di studio (Lombardia, Italia Settentrionale). Ogni lettera identifica un'area umida indagata (modificato da https://d-maps.com/ e GeoPortale Regione Lombardia).
Everyday risks and access to water and sanitation in Lilongwe urban and peri-urban areas
<p>The household survey INHAbIT Cities - UNHIDE (Investigating Natural, Historical and Institutional Transformations in Cities and Uncovering Hidden Dynamics in Slum Environments) focuses on urban risks and sanitation in Lilongwe. The aim was to assess access to basic services and risks perception of urban dwellers living in areas characterised by different conditions of access to water and sanitation and other basic services. Lilongwe was a small town of less than 20,000 inhabitants in 1966 and only started growing after it became the capital in 1975. Its population has reached approximately 1 million inhabitants, living in 58 administrative units, called areas. Infrastructures and service provision is concentrated in the central areas – where parliament, ministries, government offices, embassies, hotels and the commercial area were located - while low income areas suffer the most from infrastructure and basic services deficits. To illustrate, while some areas access water through in-house connections, others are served through water kiosks, characterised (in some areas) by high rates of discontinuity. Similarly, everyday risks are unevenly distributed across urban spaces: as shown in the survey perception of risks varies drastically from neighbourhood to neighbourhood and depending on the quality and availability of services provided. Data for this survey were collected between February and April 2015 by a team of local researchers, who administered the questionnaire in local language.</p> <p>Publications linked to this survey are:</p> <p>Rusca M., Alda Vidal C., Hordijk M., Kral N., (2017) Bathing without water, and other stories of everyday hygiene practices and risk perception in urban low-income areas: the case of Lilongwe, Malawi, Environment and Urbanisation Vol 29, Issue 2, pp. 533 – 550. </p> <p>Tiwale S., Rusca M<strong>.</strong>, Zwarteveen M., The power of pipes: mapping urban water inequities through the material properties of networked water infrastructures. The case of Lilongwe, Malawi, Water Alternatives, Water Alternatives 11(2): 314-335.</p> <p>Rusca M. (2018): Visualising urban inequalities: the ethics of videography and documentary filmmaking in water research, <em>Wires Water</em>, <a href="https://doi.org/10.1002/wat2.1292">https://doi.org/10.1002/wat2.1292</a></p>
Monitoring of urban areas on Sentinel-1
<p>Data from Sentinel-1 SLC product was used to determine the extent of the urbanised area. Such a solution is necessary in the case of rapidly developing cities, as in the case of the capital of India - New Dehli.</p> <p>Links to the presentation:</p> <p>http://fabspace.pl/wp-content/uploads/2017/11/Urban-area-on-S-1.pdf</p> <p> </p>
Urban Fabric Types in Osaka-Kobe Metropolitan Area
<p>This upload provides the processed results of Multiple Fabric Assessment (Araldi and Fusco, 2019) performed on a hyper-urbanized region of 2,500 km<sup>2</sup> in Japan and including Osaka and Kobe municipalities. The scale of analysis are the areas surrounding urban streets at close distance, which are named proximity bands. Outputs are made available using a geospatial vector data format (GeoPackage - WGS 84/UTM zone 53N) in order to be visualized in a geographic information system software. Attribute data contain the Bayesian probability assignment of each proximity band for the nine urban fabric types that have been identified in the Osaka-Kobe metropolitan area, namely, (1) High-rise and discontinuous modern fabric (2) Discontinuous mid-to-high-rise fabric of mixed land use (3-4) Peripheral low-to-mid-rise discontinuous mixed fabric (5) Industrial and logistic techno-fabrics (6) Residential hyper-compact continuous fabric (7) Residential compact continuous fabric (8) suburban planned single-house residential fabric (9) ex-urban irregular fabric with natural spaces. “MostProb” variable provides the higher probability of each proximity band, which is the main output cross analyzed with field observations in Perez <em>et al.,</em> 2019. Results are based upon the processing of morphological indicators calculated using the following datasets: 2013/14 Zmap-TOWN II (ZENRIN Residential Maps) for building coverage and Digital Road Map Database extended version 2015.</p> <p>Perez J., Araldi A., Fusco G., Fuse T. (2019) “The Character of Urban Japan: Overview of Osaka-Kobe’s Cityscapes”, <em>Urban Science</em>, 3(105), pp 1-22. https://www.mdpi.com/2413-8851/3/4/105</p> <p>Araldi A., Fusco G. (2019) “From the built environment along the street to the metropolitan region. Human perspective approach in urban fabric analysis<em>”. Environment and Planning B: Urban Analytics and City Science</em>, 46(7), pp. 1243-1263.</p>
Fig. 4 in A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and Echinococcus multilocularis in an urban area in North America
Fig. 4. Map showing the geographic distribution of three small mammal assemblage types predicted for the City of Calgary area by a multinomial logistic regression (MLR) model associating the environmental variables to assemblage types, developed from data collected in 2012 and 2013 (Liccioli et al., 2014). Note how large portion of BWM and NHP were classified as assemblage 1 as expected, but also large portion of FCPP, where it was not expected.
Fig. 1 in A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and Echinococcus multilocularis in an urban area in North America
Fig. 1. Study sites for the characterization of the small mammal assemblages in urban Calgary, AB, Canada in 2012–2013, showing the location of five areas in Urban Calgary and detailed map of Bowmont, Southland Lowlands, and Weaselhead. Bowmont (BM), Fishcreek Provincial Park (FCPP), Nose Hill Park (NHP), Southland Lowlands (SL), and Weaselhead (WSH).
Fig. 2 in A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and Echinococcus multilocularis in an urban area in North America
Fig. 2. Dendrograms derived from the Bray-Curtis similarity of small mammal assemblages in five parks and natural areas in urban Calgary, AB, Canada, 2012–2013. a) Dendrogram using abundance data and group-average clustering algorithm. The dashed line indicates the cluster cut-off line of 45% similarity. Symbols for each site indicate the prevalence of definitive hosts (EmDH) and presence (1) or absence (0) of infected small mammals (EmIH). b) Dendrogram using abundance data and complete-linkage clustering algorithm. Note how it is similar to the dendrogram using group-average algorithm. c) Dendrogram using proportion data and group-average clustering algorithm. Note how all BM sites are in single cluster and all NHP sites and most sites are in another cluster, similar to the dendrogram using abundance data.
Figure 2 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 2. Daily average temperature in Kharkiv during 2013. Division of the year by phenological periods (blue – winter, green – spring, yellow – summer, orange – autumn), and periods of the bat life cycle; total number of bat records in a day (red columns). I-XII - months of the year.
Figure 12 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 12. The body mass dynamics by month for all E. serotinus during 2013 in Kharkiv. F – ♀♀, M – ♂♂ (red dot – mean value, line – median value, whiskers – min and max values, open dot – outlier).
Figure 8 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 8. Relationship between the number of recorded bats and the percentage of those that were dead or significantly injured, as shown using k-mean clustering.
Figure 11 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 11. The body mass dynamics by month of first-year individuals of N. noctula during 2013 in Kharkiv. F – ♀♀, M – ♂♂ (black dot – mean value, line – median value, whiskers – min and max values, open dot – outlier).
Figure 4 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 4. Spatial distributions of records of E. serotinus in Kharkiv. (a) The records in periods from 1 August to 2 December; (b) the records in winter, 1 January to 29 March and from 3 December to 31 December.
Figure 3 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 3. Spatial distributions of four bat species records throughout the year in Kharkiv. NNOC: N. noctula; PKUH: P. kuhlii; VMUR: V. murinus; PAUR: P.auritus.
Figure 10 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 10. The body mass dynamics by month of adult individuals of N. noctula during 2013 in Kharkiv. F – ♀♀, M – ♂♂ (black dot – mean value, line – median value, whiskers – min and max values, open dot – outlier).
Figure 9 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 9. Comparative ratios of the causes of death or significant injury during 2013 in Kharkiv: dir. people – directly killed or injured by people; cas. people – indirectly/casually killed or injured by people; attenuation – death after exhaustion; oil – death after fouling by oil products; cat – killed or injured by a cat; window trap – death as a result of becoming trapped in a window; un – uncertain.
Figure 3 in Bacterial community associated with Culex quinquefasciatus Say, 1823 (Diptera: Culicidae) from an urban area in the Amazon, Brazil
Figure 3 Phylogenetic tree based on maximum likelihood method using MEGA 11. The numbers shown next to the branches correspond to the percentage of replicate trees that the taxa were clustered together in the bootstrap test (1000 replicates).
Figure 2 in Bacterial community associated with Culex quinquefasciatus Say, 1823 (Diptera: Culicidae) from an urban area in the Amazon, Brazil
Figure 2 Heatmap of sequences with taxonomic assignment to genus level. The color gradient (yellow to purple) represents abundance. Yellow: higher bacterial abundance. Purple: lowest bacterial abundance. Abundance legend corresponds log10(%).
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.