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30 results for “Built environment”
Social Innovations for Circularity in the Built Environment – a Scoping Review and Classification. Supplementary Data to the Bibliometric Review.
<p>To transition the built environment (BE) towards circularity, i.e., maximizing the time resources spend in the BE, thus minimizing negative environmental impacts of resource usage, social innovations (SI) – understood as new ways of doing, organizing, framing, and knowing – are just as important as technological advancements. This article provides an overview of the state of the knowledge regarding SI that contribute to circularity in the BE, and proposes a framework for coherently classifying such SI in terms of their main categories and effects.</p> <p>To identify and understand the current knowledge regarding social innovations (SI) that contribute to circularity in the built environment (BE), a bibliometric review of scientific literature is conducted. It shows that the term social innovation is not frequently used in this contexts although the buzzwords circularity and circular economy are themselves often framed as SI. To assess the characteristics and contribution of SI to circularity in the BE, a scoping review that includes grey literature into the context was conducted and a framework developed to classify predominant SI using concepts from transition studies as well as the systems thinking approach. The framework is designed to help assess the potential of SI and to identify research and/or action gaps. Key findings are (1) There is a broad diversity of SIs that contribute to circularity in the BE already in the focus of research, although they are not always identified as such; (2) Most SI focus on either the design or the demolition phase (i.e., market related phases), whereas user-centered SI are less frequently discussed; and (3) It is crucial to also consider potential sustainability goal conflicts in order to guide policies that address SI as a solution.</p> <p>These datasets are the basis to the bibliometric literature review.</p>
Unmanned Aerial Vehicle Image Dataset of the Built Environment for 3D reconstruction (UAVID3D)
<p>Unmanned Aerial Vehicles (UAV) provide increased access to unique types of urban imagery traditionally not available. Advanced machine learning and computer vision techniques when applied to UAV RGB image data can be used for automated extraction of building asset information and if applied to UAV thermal imagery data can detect potential thermal anomalies. However, these UAV datasets are not easily available to researchers, thereby creating a barrier to accelerating research in this area. </p> <p>To assist researchers with added data to develop machine learning algorithms, we present UAVID3D (Unmanned Aerial Vehicle (UAV) Image Dataset of the Built Environment for 3D reconstruction). The raw images for our dataset were recorded with a Zenmuse XT2 visual (RGB) and a FLIR Tau 2 (thermal, https://flir.netx.net/file/asset/15598/original/) camera on a DJI Mavic 2 pro drone (https://www.dji.com/matrice-200-series). The thermal camera is factory calibrated. All data is organized and structured to comply with FAIR principles, i.e. being findable, accessible, interoperable, and reusable. It is publicly available and can be downloaded from the Zenodo data repository. </p> <p>RGB images were recorded during UAV fly-overs of two different commercial buildings in Northern California. In addition, thermographic images were recorded during 2 subsequent UAV fly-overs of the same two buildings. UAV flights were recorded at flight heights between 60–80 m above ground with a flight speed of 1 m s and contain GPS information. All images were recorded during drone flights on May 10, 2021 between 8:45 am and 10:30 am and on May 19, 2021 between 2:15 pm and 4:30 pm. Outdoor air temperatures on these two days during the flights were between 78 and 83 degree fahrenheit and between 58 and 65 degree fahrenheit respectively. </p> <p>For the RGB flights, UAV path was planned and captured using an orbital flight plan in PIX4D capture at normal flight speed and overlap angle of 10 degree. Thermal images were captured by manual flights approximately 5 m away from each building facade. Due to the high overlap of images, similarities from feature points identified in each image can be extracted to conduct photogrammetry. Photogrammetry allows estimation of the three-dimensional coordinates of points on an object in a generated 3D space involving measurements made on images taken with a high overlap rate. Photogrammetry can be used to create a 3D point cloud model of the recorded region. UAVID3D dataset is a series of compressed archive files totaling 21GB. Useful pipelines to process these images can be found at these two repositories <a href="https://github.com/LBNL-ETA/a3dbr">https://github.com/LBNL-ETA/a3dbr</a>, and <a href="https://github.com/LBNL-ETA/AutoBFE">https://github.com/LBNL-ETA/AutoBFE</a></p> <p>This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies Program, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. </p> <p> </p> <p> </p>
Code and data to support 'Street view imagery for built environment auditing: a systematic review'
<p>Code and data to support the manuscript entitled 'Street view imagery for built environment auditing: a systematic review'</p>
Mixed salt systems in the built environment - charge balance calculations
<p>A large database of salt mixtures found in the built environment and a charge balance calculations toolkit. Output of the <a href="http://predict.kikirpa.be/">PREDICT</a> project predominantly including measurements of Belgian historic sites collected by KIK-IRPA Monuments Lab.</p> <p>Contents:</p> <ul> <li>Full integrated database and charge balance calculation sheet, including raw ion concentrations and balanced outputs (.xlsx)</li> <li>Sample integrated database (25 mixtures) and charge balance calculation sheet, including raw ion concentrations and balanced outputs (.xlsx)</li> <li>R scripts for charge balance calculations (.R)</li> <li>Full set of raw ion concentrations for the R scripts (.txt)</li> <li>Sample of 25 raw ion concentrations for the R scripts (.txt)</li> <li>Full set of balanced outputs from the R script (.txt)</li> <li>Sample of 25 balanced outputs from the R script (.txt)</li> </ul>
Data set for "Understanding Older Adults' Needs: Psychosocial Wellbeing in Context of Perceived and Objective Built Environment"
<p>This entry contains datasets for the article "Understanding Older Adults' Needs: Psychosocial Wellbeing in Context of Perceived and Objective Built Environment".</p>
Paper dataset of "ARAMIS: a Martian radiative environment model built from GEANT4 simulations"
<p>Supplementary materila dataset concerning the article : <a href="https://doi.org/10.1051/swsc/2024032">https://doi.org/10.1051/swsc/2024032 .</a></p> <p>In the version v1, the proton flux where not giving for both cone and total view which is corrected here. Beside there was a wrong upload file for proton_aramis_2015_2016.dat, which has been corrected as well.</p>
Pilot building dataset - "Portal for heritage buildings integration into the contemporary built environment" (URBAN PERISCOPE)
<p>LIM_411</p> <p>Address: Agkiras 147</p> <p>The building, located in the heart of the Turkish Cypriot quarter and very close to the Cami Cedit Mosque, was originally a school for Turkish Cypriot girls. It is unclear when it was built. The buildings surrounding it provided accommodation for the students. At some point it was used as a police station. Today, it functions as the Bi-communal Multi-functional Centre of the Municipality of Limassol.</p> <p>The building’s typology is very simple. It is a single-storey building, consisting of two large rooms and a smaller one between them. All three rooms have entrances on both the front and the back of the building. A covered exterior area is created on both sides.</p> <p>The appearance of the building is dominated by visible stone which is used in structural elements and decorative details. The main south entrance is surrounded by a carved stone arc and columns with engraved details. Visible stone can also be found on the frame of the small room’s south door, the frames of the windows, the niches, the corners and the base of the building and on its top part under the roof.</p> <p>The walls of the building are made of stone. The floor consists of painted tiles in the covered exterior areas, tiles in the two big rooms and newer wooden parquet in the small room. All the doors and windows are made of wood while the ceilings are made of wooden planks. The roof structure is composed of timber beams and tiles.</p> <p>Newer additions include the plasterboard walls that partly separate the space in the big rooms and the structure at the back of the west room that is used as a sanitary space.</p> <p>The building was included in the catalogue of listed buildings in 2000 for its significance as a Turkish school building with traditional and neo-classical characteristics.</p> <p>"Portal for heritage buildings integration into the contemporary built environment" (URBAN PERISCOPE), is funded by the Cyprus Research & Innovation Foundation Restart Programs 2016-2020 "Integrated Projects". Project Coordinator: The Cyprus Institute; Partners: Cyprus University of Technology (Cyprus), Frederic Research Center (Cyprus), Fondazione Bruno Kessler (Italy), University of Catania (Italy), Department of Urban Planning and Housing, Municipality of Strovolos, Municipality of Limassol, HIT- Hypertech Innovations, NetU Consultations and Talos RTD. The project [Grant number: INTEGRATED/0918/0034] is co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Innovation Foundation.</p> <p> </p>
Satellite Analysis (2013-2020) dataset - "Portal for heritage buildings integration into the contemporary built environment" (URBAN PERISCOPE)
<p>For the needs of the “Portal for heritage buildings integration into the contemporary built environment”, in short, PERIsCOPE project, satellite observations were applied. This repository includes the results from the macro-scale analysis, for which thermal data, optical satellite images, and ready satellite products were exploited to provide multi-temporal information.</p> <p>Satellite-based products estimate the temperature variations in a broader area for the selected urban testbeds (Limassol and Strovolos municipalities, Cyprus). Landsat 7 and 8 archives were downloaded through the EarthExplorer platform (“Landsat Collection 1 Level-1” for both “Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Level-1” and “Landsat 8 OLI/TIRS C1 Level-1”). The Level-1 data downloaded from the platform were rescaled to the top of atmosphere (TOA) reflectance and radiance using radiometric rescaling coefficients provided in the metadata file delivered with the Level-1 product (metadata—MTL file).</p> <p>More than 140 satellite images were selected (a cloud coverage filter was applied), downloaded, and processed, covering the period between 2013 and 2020. Specifically, 16 images during the Winter season, 30 images over Spring, 57 images for Summer, and 38 during Autumn were finally gathered for both case studies.</p> <p>The Google Earth Engine cloud platform infrastructure was used to extract optical products, namely the Normalised Difference Vegetation Index (NDVI) and the Normalised Difference Built-up Index (NDBI), which characterise vegetated and built-up areas, respectively.</p> <p>This repository concerns: (1) the mean Land Surface Temperature (LST) for both test sites (from 2013-2020), their standard deviation, and the maximum and minimum values. In addition, the (2) NDVI and (3) NDBI products per year (2013-2020) are provided. Lastly, (4) the seasonal variations are included.</p> <p>The data are structured in both forms of ArcGIS Pro Geodatabase (.gdb), while individual .tiff formats are provided in each folder.</p> <p>Further details can be found in the following references:</p> <p>1. Agapiou, A.; Lysandrou, V. Observing Thermal Conditions of Historic Buildings through Earth Observation Data and Big Data Engine. <em>Sensors</em> 2021, <em>21</em>, 4557. <a href="https://doi.org/10.3390/s21134557">https://doi.org/10.3390/s21134557</a></p> <p>2. Agapiou A., Lysandrou V., Cuca B., Copernicus earth observations for cultural heritage, Proceedings of the joint international event, 9th ARQUEOLÓGICA 2.0 & 3rd GEORES, Valencia (Spain). 26–28 April 2021, DOI: <a href="https://doi.org/10.4995/Arqueologica9.2021.12512">https://doi.org/10.4995/Arqueologica9.2021.12512</a></p>
Children's Use of the Built Environment for Physical Activity
ClinicalTrials.gov study NCT01939405. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Heat Death Associations with the built environment, social vulnerability and their interactions with rising temperature
The occurrence of extreme heat events in the American Southwest are expected to become more frequent and severe and it is more important to understand which neighborhoods and populations are at risk of negative heat-health outcomes. Vulnerability to heat is a function of its heat exposure, population characteristics, and adaptive capacity. This study focuses on underlying socioeconomic and demographic characteristics that contribute to this vulnerability. The contributions of these factors to heat mortality in Maricopa County, AZ were explored and used to identify areas where vulnerable populations exist.
Supplementary material 3 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Krona chart : Explanation note: Interactive Krona chart for visualizing the taxonomic distribution of annotated BMS sequences down to order level. Sequences classified as Fungi sp. (36.4%) or non-fungal (0.9%) were excluded from this dataset.
Supplementary material 1 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Keywords used to identify fungal sequences from the built environment in the INSDC : Explanation note: Keywords used to identify fungal sequences from the built environment in the INSDC.
Supplementary material 2 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Annotations made during the workshop : Explanation note: The annotations made during the workshop shown with original INSDC data. For the BMS, we targeted nine MIxS-BE items plus country of collection, host of collection, host association, and a general "Comment" field. For the OMS, we targeted country of collection, host of collection, host association, and a general "Comment" field.
Supplementary material 1 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The sequences renamed during the workshop. The INSDC accession number, the original INSDC name, and the new UNITE name are shown :
Supplementary material 3 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The metadata annotations for the sequences that were found in the same SHs as sequences from the built environment :
The Change Club Study: Evaluation of Civic Engagement for Built Environment Change and Health Improvement
ClinicalTrials.gov study NCT05002660. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Figure 3 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 3 - Analysis of the MIxS-BE "building occupancy type" (type of building where the underlying sample was taken).
Figure 2 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 2 - Krona chart of the taxonomic affiliation of the BMS sequences down to order level. The Krona chart lists all annotated BMS sequences except those classified as Fungi sp. (36.4%) and those of non-fungal origin (0.9%). An interactive version of the Krona chart is provided as Suppl. material 3. The figure includes pre-existing data plus the data added during the workshop, such that these charts indicate the scientific state of ITS-based Sanger-derived sequencing of the built mycobiome as of spring 2016. Sequences that were not annotated with a single built environment-related term in the INSDC were not included in this effort, and are not represented in these charts.
Figure 1 from: Abarenkov K, Adams RI, Irinyi L, Agan A, Ambrosio E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Unterseher M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH (2016) Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys 16: 1-15. https://doi.org/10.3897/mycokeys.16.10000
Figure 1 - Analysis of the BMS sequences for country of collection. Country centroids marked with bubbles of different size on the global map indicate the number of BMS sequences originating from these countries (54 distinct countries, sequence count ranging from 1 to 2,914). For an additional 2.9% of the sequences, country information could not be restored during the workshop. The figure includes pre-existing data plus the data added during the workshop, such that these charts indicate the scientific state of ITS-based Sanger-derived sequencing of the built mycobiome as of spring 2016. Sequences that were not annotated with a single built environment-related term in the INSDC were not included in this effort, and are not represented in these charts.
Supplementary material 4 from: Nilsson RH, Taylor AFS, Adams RI, Baschien C, Bengtsson-Palme J, Cangren P, Coleine C, Daniel H-M, Glassman SI, Hirooka Y, Irinyi L, Iršėnaitė R, Martin-Sanchez PM, Meyer W, Oh S-Y, Sampaio JP, Seifert KA, Sklenář F, Stubbe D, Suh S-O, Summerbell R, Svantesson S, Unterseher M, Visagie CM, Weiss M, Woudenberg JHC, Wurzbacher C, den Wyngaert SV, Yilmaz N, Yurkov A, Kõljalg U, Abarenkov K (2018) Taxonomic annotation of public fungal ITS sequences from the built environment – a report from an April 10–11, 2017 workshop (Aberdeen, UK). MycoKeys 28: 65-82. https://doi.org/10.3897/mycokeys.28.20887
The interactive Krona chart associated with Figure 2 :
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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.