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27 results for “open space”
Built Open spaces
<p>ESM data subset, generated by extracting band 30 as buildings with the next information:</p> <p>gid integer geom geometry(Polygon,EPSG:3035) albedo real transmissivity real vegetation_shadow real run_off_coefficient real building_shadow smallint hillshade_building real</p> <p>This data is an input for local effects calculation.</p>
Level of Protection for Areas Designated Protected and Open Space - Ipswich Watershed - Idrisi Raster File.
This datalayer is part of a group of layers used for research in the Ipswich River Watershed. This datalayer shows the level of protection for areas that are defined as Protected and Recreational Open Space by MassGIS (www.state.ma.us/mgis). This layer is derived from the Protected and Recreational Open Space layer provided by for each town. The values are from the Level of Protection (lev_prot) field in the data table. To show the what level of protection open space areas in the Ipswich watered are under.
Primary Use of Open Space and Protected Land - Ipswich Watershed - Idrisi Raster File.
This datalayer is part of a group of layers used for research in the Ipswich River Watershed. This datalayer shows the primary use of land that is defined as protected by MassGIS. (http://state.ma.us/mgis/). This layer has information derived from the Protected and Recreational Open Space town coverages provided by MassGIS. To provide information about the use of open space.
Status and Custodianship of Designated Open Space - Ipswich Watershed - Idrisi Raster File.
This datalayer is part of a group of layers used for research in the Ipswich River Watershed. This datalayer shows the Status for areas that are defined as Protected and Recreational Open Space by MassGIS (www.state.ma.us/mgis). This layer is derived from the Protected and Recreational Open Space layer provided by for each town. The values are from the status field (status_fee) field in the data table.
Fig. 3 in Influence of plant direction, layer, and spacing on the infestation levels of Anthonomus eugenii (Coleoptera: Curculionidae) in open jalapeño pepper fields in North Florida
Fig. 3. Number of infested fruits and presence of weevil larvae in different jalapeño plant parts (means ± SE). Number of infested fruits in 5 directions (A), in 3 layers (C), and at 5 spacings (E). Number of larval A. eugenii within infested fruits in 5 directions (B), in 3 layers (D), and at 5 spacings (F). Different letters indicate significant differences among the treatments (means separated by Tukey's HSD, P <0.05).
Fig. 4 in Influence of plant direction, layer, and spacing on the infestation levels of Anthonomus eugenii (Coleoptera: Curculionidae) in open jalapeño pepper fields in North Florida
Fig. 4. Fruit wall thickness and single weight in different jalapeño plant parts (means ± SE). Fruit wall thickness (A) and single weight (B) in 5 directions, fruit wall thickness (C) and single weight (D) in 3 layers, fruit wall thickness (E) and single weight (F) at 5 spacings. Different letters indicate significant differences among the treatments (means separated by Tukey's HSD, P <0.05).
Fig. 2 in Influence of plant direction, layer, and spacing on the infestation levels of Anthonomus eugenii (Coleoptera: Curculionidae) in open jalapeño pepper fields in North Florida
Fig. 2. Infestation and larval density of pepper weevil in 2017. Vertical bars are standard errors of the means.
Fig. 5 in Influence of plant direction, layer, and spacing on the infestation levels of Anthonomus eugenii (Coleoptera: Curculionidae) in open jalapeño pepper fields in North Florida
Fig. 5. Relationship between the infestation level and the fruit wall thickness (A) and single weight (B). Each data point represents the number of infested fruits per plant in each fruit wall thickness or weight (means ± SE). Line was fitted using linear regression analysis.
Fig. 1 in Influence of plant direction, layer, and spacing on the infestation levels of Anthonomus eugenii (Coleoptera: Curculionidae) in open jalapeño pepper fields in North Florida
Fig. 1. (a) Adult pepper weevil feeding on the stalk of a pepper fruit; (b) young and full grown larvae inside a pepper fruit; (c) pupa inside the fruit; and (d) adult weevil exit holes in pepper fruits.
HeatResilientCity II - work package 2.3: Interactions between buildings and open space adaptation measures – Meteorological input data for building performance simulation
<p>This repository contains <strong>meteorological</strong> <strong>data</strong> from urban climate simulations that were carried out in districts of the cities of Dresden and Erfurt as part of the <a href="http://heatresilientcity.de/">HeatResilientCity II</a> project. The data was extracted at specific points (receptors) of the urban climate model. In addition to the data, a <strong>script </strong>is attached that can be utilized to generate a time series for IDA ICE building performance simulations using IceWeather.exe. Therefore, a Microsoft Windows operating system is required. To create a time series, simply use the function <em>createIdaIceInput()</em> at the end of the script <em>createTimeSeries.py</em>. Further explanations can be found at the beginning of the script. Information about the ENVI-met data used to create the IDA ICE input can be found in <em>README_RawENVImetOutput_DD.txt</em> and <em>README_RawENVImetOutput_EF.txt</em>.</p> <p>Some input <strong>data files have already been generated</strong><strong> </strong>and can be directly used for<strong> thermal building performance simulations with IDA ICE</strong>. These files can be found in the folder <em>0.3_Input_Timeseries (Climate) for IDA ICE</em>.</p> <p>The <strong>naming convention</strong> of the final input data files for IDA ICE is as follows:</p> <ul> <li>TOWN_SCENARIO_RECEPTOR_AVERAGING_INTERFACE_LATITUDE_LONGITUDE_VERSION</li> <li>TOWN: Choose between 'Erfurt' and 'Dresden'</li> <li>SCENARIO: See further information in <em>README_RawENVImetOutput_DD.txt</em> and <em>README_RawENVImetOutput_EF.txt</em></li> <li>RECEPTOR: Location in the modelled area (ENVI-met simulation) where data was extracted.</li> <li>AVERAGING: Information about averaging the hourly values of the urban climate simulation (see <em>createTimeSeries.py and READMEs)</em></li> <li>INTERFACE: Information on how single days were joined together (see <em>createTimeSeries.py</em>).</li> <li>LATITUDE: Default values for Dresden and Erfurt are set in the script. Add additional values in the function <em>setIceWeatherParams()</em> if you are using other cities/custom ENVI-met simulation data.</li> <li>LONGITUDE: Default values for Dresden and Erfurt are set in the script. Add additional values in the function <em>setIceWeatherParams()</em> if you are using other cities/custom ENVI-met simulation data.</li> <li>VERSION: The version number can be set in the script.</li> </ul> <p>Example: <em>Dresden_2y_A1_a_timeSeries_24-24_51.0468_13.6707_v11.prn</em></p> <p><strong>Folder overview:</strong></p> <ul> <li>The ENVI-met raw data is stored in <em>0.1_Input_RawENVImetOutput</em>.</li> <li>The script is stored in <em>0.2_Input_ScriptsToCreateTimeSeries</em>.</li> <li>The final datasets ready for simulation with IDA ICE are stored in <em>0.3_Input_Timeseries(Climate)ForIDAICE</em>. This folder also contains some weather data time series that have already been created and can be used for IDA ICE (subfolders Erfurt_v11 and Dresden_v11).</li> </ul>
Model generated open-closed field topology maps produced by ISSI team "Magnetic Open Flux And Solar Wind Structuring Of Interplanetary Space"
<p>Open and closed magnetic field topologies of the solar corona generated using four PFSS based coronal models (EUHFORIA, WSA, MULTI-VP, PSI-PFSS) and one full MHD coronal model (PSSI-MHD) using two different types of HMI-ADAPT magnetic field maps (with and without Active Regions (AR) added retrospectively). The magnetograms used are accessible here <a href="https://doi.org/10.5281/zenodo.10211762" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10211762</a> (Henney, Carl. ‘ADAPT Global Solar Magnetic Maps - 2010 Sep 18-20 (w/ & W/o Farside Active Region Input)’. Zenodo, 28 November 2023).</p> <p>These model outputs were generated by the ISSI team "Magnetic Open Flux And Solar Wind Structuring Of Interplanetary Space" and were used for the paper accessible on Arxiv via this link: https://arxiv.org/abs/2311.04024</p>
Corona Haikus - Poetics of compassion. Visual poetry and co-creation in virtual opening spaces as self-care and community-care
<p>The COVID-19 lockdowns and the maxim of social distancing have not only been accompanied by an upheaval of all so far assumed certainties and our complex socio-cultural infrastructures – they have also brought along deep permutation in our personal, intimate lives. As closeness and connectivity are essential in times of cataclysm, and as the preservation and negotiation of the effects of crises and its consequences is one element in deal with stress and anxieties, the impulse to document and reflect one's experiences, to reset one's focus and to regain agency through (co-)creative practices and mutual care have gained momentum. This might be one reason why during the lockdown many virtual communities emerged, e.g. social media initiatives with a documentary impetus, as well as collaborative web-projects. The motives for engaging in such networks are various – and often, one and the same project serves different needs at the same time for different user-participants. Apart from the impulse to document unprecedented times as a coping strategy to face personal uncertainties, and apart from the impetus to share one's experiences with others and thus to create a feeling of connectivity, these projects are also means for mediated self-care: they are spaces to self-reflexively cope with a slow-downed and often also isolated lifestyle and to make social distancing more bearable. This contribution examines the potentials of co-creative documentary poetry/poetic documentary in times of crises, taking the participatory project Corona Haikus as an example – a project, which launched during the first lockdown in March 2020 as an artistic experiment repurposing the facebook platform and which later metamorphosed into a curated website. I will investigate which community needs have existed during the crisis, and how the collaborative project Corona Haikus answered them. The focus of the presentation lies on co-creation as a form of self- and community-care, on the visual haiku as a poetic and therapeutic form and meditative practice of creation, as well as the use of networked media, to create 'open spaces' (sensu Zimmermann & De Michiel 2018), to foster communicative connectivity and to inspire creativity – thus making social media networks social in the proper sense of the word. Conceptualizations of co-creation, participation, mediated mindfulness and the healing potential of creativity – especially visual poetry – will be supplemented by reflections on community building, agency in co-creative projects and media ethics. In this sense, the contribution is meant as an analytic investigation of the status quo but also as a glimpse on the potential quo vadis of collaborative, interactive documentary and its (new) functions a means for self-care and community-care.</p> <p>Corona Haikus curated website: <a href="https://coronahaikus.com">https://coronahaikus.com</a></p> <p>Corona Haikus facebook group: <a href="https://www.facebook.com/groups/226094118756231">https://www.facebook.com/groups/226094118756231</a> </p> <p>Interview / Podcast with Sandra Gaudenzi and Sandra Tabares Duque on Kammerfilmmern & Mediales Rauschen: <a href="https://kammerflimmern.podigee.io/b10-corona-haikus">https://kammerflimmern.podigee.io/b10-corona-haikus</a></p> <p>Published in: <a href="https://trametrami.avinus.org/publikationen/8-2023">https://trametrami.avinus.org/publikationen/8-2023</a> </p>
Data from: Candelariella clarkii and Lecidea hoganii: two lichen species new to science from White Rocks Open Space, City of Boulder, Colorado
Two new species are described from vouchers collected as part of an intensive lichen inventory of Fox Hills Sandstone outcrops in an open space preserve within the city limits of Boulder, Colorado. Candelariella clarkii is characterized by its cryptolecanorine apothecia, chartreuse areolate thallus, and 8-spored asci. Lecidea hoganii is a member of the L. auriculata morphological group characterized by a thick white chalky thallus, pink pigments in the hymenium, and absence of secondary compounds. We provide IUCN conservation assessments for both new species, which should be considered critically endangered. The discovery of two species new to science in a relatively densely populated region of North America illustrates the ecological relevance of small of patches of native habitat, which are certain to become even more important in the future.
COS-1m: the first community-scale open space maps of 31 major cities in China created with the layered occlusion perception model
<p>Correspondence to:<br>Shihong Du<br>Peking University<br>Beijing 100871, China<br>E-mail: shdu@pku.edu.cn</p> <p>COS-1m (Community Open Spaces) offers detailed, high-resolution maps of community-level open spaces across 31 major cities in China. Developed using the latest very high-resolution satellite imagery and a novel Layered Occlusion Perception Model (LOPM), this dataset ensures precise representation with a spatial resolution of 1 meter. In total, the COS-1m dataset covers an area of 46727.46 square kilometers.</p> <p>The COS-1m dataset addresses the critical challenge of layered occlusions in remote sensing imagery by accurately modeling and reconstructing the intricate layered structures of COS. This approach allows for the detailed delineation of occluded ground elements, overcoming the limitations of traditional single-layer mapping methods. The dataset reveals that, on average, 60.51 km² of COS area per city is occluded, constituting 10.18% of the total COS area, which had previously been overlooked.</p> <p>Key features of the COS-1m dataset include:</p> <ul> <li><strong>Four Types of Public Open Space Elements</strong>: Green spaces (1), blue spaces (2), squares (4), and walkways (6).</li> <li><strong>Three Types of Coupled Open Spaces</strong>: waterfront woodlands (3), shaded squares (5), and shaded walkways (7).</li> </ul> <p>The dual-layer mapping technique used in COS-1m provides a comprehensive overview of urban open spaces, capturing the vertical overlaps of various elements such as trees, water bodies, squares, and walkways. This dataset is a significant advancement in COS monitoring technology, filling a critical gap in community-scale Sustainable Development Goal (SDG) assessments. It provides urban planners and policymakers with valuable insights to promote more effective and sustainable urban development.</p> <p>COS-1m achieved an overall accuracy of 86.39% and an average F1-score of 77.47% across the 31 cities, demonstrating its robustness and reliability as a tool for urban space analysis and planning.</p> <p>If you use this dataset, please cite: "Lei, Y., Zhang, X., Xiong, S., Tan, G., & Du, S. (2025). Developing Layered Occlusion Perception Model: Mapping community open spaces in 31 China cities. Remote Sensing of Environment, 316, 114498."</p> <p> </p>
North Campus Open Space (NCOS) Monthly Bird Survey Data (2017-2023)
<p>Bird surveys are completed once a month by Cheadle Center staff and associates. Each survey starts 45 minutes after sunrise and lasts about 2 hours. The survey has at least 4 experienced birders- 2 that survey the eastern side and 2 that survey the western route (exact routes can be found on ArcGIS online). Surveyors use a combination of binoculars, scopes, and listening for calls to identify species. A point is placed on the map to the best accuracy possible using the ArcGIS app field maps or collector. The survey is also set up to record the surveyors' location every 30 seconds as a way to track the survey route. When there are large groups of birds, 10 or more, an approximate number is decided between the two surveyors. If a bird is seen multiple times along the route, it is labeled a repeat. The two groups met up after the survey and discussed what was seen. Any birds that are expected to be a repeat were changed to note that they were a repeat within the dataset. Environmental data such as cloud cover, water level, and temperature are recorded at the beginning and end of the survey.</p> <p>This data is an aggregation that contains the number of each species spotted on site each month. If you are interested in the birds' exact location, you can download individual monthly data from ArcGIS Online.</p>
FIGURE 64. Syagrus pimentae. A. Habit. B. Palm with Ricardo Pimenta for scale. C. Palm showing Butia-like leaves with evenly spaced leaflets. D. Old inflorescences. E. Newly opened inflorescence. F. Infructescence. G in A revision of the genus Syagrus (Arecaceae)
FIGURE 64. Syagrus pimentae. A. Habit. B. Palm with Ricardo Pimenta for scale. C. Palm showing Butia-like leaves with evenly spaced leaflets. D. Old inflorescences. E. Newly opened inflorescence. F. Infructescence. G. Whole plant with infructescence. (Pimenta & Campos-Rocha s.n. [holotype HPL]).
Data accompanying "Calibrated microphone array recordings reveal that a gleaning bat emits low-intensity echolocation calls even in open-space habitat"
<p>Introduction to the dataset: </p> <p>In this manuscript, we analyse recordings of brown long-eared bats in the wild collected with a 4-microphone array, which we use to measure the distance between the bat and the microphone.<br> The distance is then used to correct the recordings for distance-dependent frequency and amplitude attenuation.<br> To ensure that our measurements and corrections are correct, we fully calibrated the microphone array and analysis set-up. <br> The calibration includes a comparison between real distances and calculated distances between a loudspeaker and the microphone array as well as comparisons between the real amplitude and the calculated amplitude of the loudspeaker.<br> To obtain the original amplitude of the calibration recording, we calibrated the loudspeaker as well</p> <p>In this folder, we provide the original bat recordings as well as the datasheet with all analysed call measurements, and the original data from the microphone calibration.</p> <p>DATA & FILE OVERVIEW</p> <p>Folder list: <br> - Bat data: folder containing the original Plecotus recordings and raw call parameters<br> - Calibration data : folder containing the array calibration raw data, as well as codes and recordings necessary to calibrate the loudspeaker. <br> </p>
HeatResilientCity II - work package 2.3: Interactions between buildings and open space adaptation measures – Results of building performance simulations
<p>This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.3: Interactions between buildings and open space adaptation measures of the project <a href="http://heatresilientcity.de/">HeatResilientCity II</a>. The buildings under consideration are a multi-residential so-called „Gründerzeithaus“ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms of each building on the top floor/attic and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoor and outdoor. Further information can be found in the README of this repository.</p> <p>In addition to the “plain” simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in <em>Calculate_Indicators_Dresden.txt </em>and<em> Calculate_Indicators_Erfurt.txt</em>. The calculated quantities include temperature weighted exceedance hours for the limits of 25, 26 and 27 °C, the maximum operative temperature occurring during the simulation and the operative indoor temperature and outdoor air temperatures at 4 am and 6 pm on the last day of the heat period/simulation.</p> <p>The used <strong>input data</strong> and <strong>building models</strong> can be found in the related identifiers.</p>
Data from: Candelariella clarkii and Lecidea hoganii: two lichen species new to science from White Rocks Open Space, City of Boulder, Colorado
Open the record for dataset details and reuse information.
North Campus Open Space (NCOS) Monthly Bird Survey Data (2017-2023)
Open the record for dataset details and reuse information.
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.