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78 results for “Green spaces”
# Replication code and data for: Tracking green space along streets of world cities
<p># Replication code and data for: Tracking green space along streets of world cities<br>Falchetta, G., & Hammad, A. T. (2025). Tracking green space along streets of world cities. Environmental Research: Infrastructure and Sustainability. https://doi.org/10.1088/2634-4505/add9c4 </p> <p>The file "gvi_358cities_2016_2023_yearly_falchetta_hammad.csv" contains<strong> output data</strong>, reporting sampling-point level data on the yearly (2016-2023) values of the Green View Index for the 190 cities covered in the paper AND an additional number of world cities (for a total of 358 cities). The "README_gvi_358cities_2016_2023_yearly_falchetta_hammad.txt" file contains a dictionary of each column name and units. </p> <p>____<br><br></p> <p>To replicate the analysis, the results, and the figures of the paper:</p> <ul> <li>Download input data from this Zenodo repository and code from Github https://github.com/giacfalk/urban_green_space_mapping_and_tracking</li> <li><em>*Optional data extraction steps* </em>(processed output data are already available in the Zenodo repository):<br> <ul> <li>Adjust your working directory</li> <li>Run [lines 4-11] of workflow/sourcer.R</li> <li>Run the Javascript scripts written by the string_generator_training.R and string_generator_prediction.R files in Google Earth Engine (https://code.earthengine.google.com) and complete the export to Drive tasks to generate the output .csv files</li> </ul> </li> <li>Run workflow/sourcer.R [lines 15-46] to train the ML model and make predictions (including figures and tables replication)</li> </ul> <div> <div> <div> </div> <div> <div> <div> </div> <div> <p dir="auto"> </p> <p dir="auto"> </p> </div> </div> </div> </div> </div> <div> <div> <div> </div> <div> <div> <div> </div> <div> <p dir="auto"> </p> <p dir="auto"> </p> </div> </div> </div> </div> </div>
Results: Predicted cooling effect, deaths prevented and associated economic value from public green spaces in Paris V2
<p>This dataset represents results predicting the cooling effect, deaths prevented and associated economic value for public green spaces in Paris for 40 hot days above the minimum mortality threshold in 2019. </p> <p>This is version 2. The value of a statistical life (VSL) has been corrcted and all values adjusted. </p> <p>The data format is a shapefile with coordinate reference system RGF93 v1 / Lambert-93 (EPSG:2154).</p> <p>Please see the Variable_name csv file for description of the variable names. </p> <p>The (non-reproducible) code is available at https://github.com/j-k-garrett/REGREEN_Paris_heat</p> <p>These results are from the submitted (September 2025) paper entitled:</p> <p><strong><span>Nature-Based Solutions for Urban Heat: Health and Economic Value of Paris’s Public Green Spaces</span></strong></p> <p>Authored by:</p> <p>Joanne K. Garrett<sup>1</sup>, David Neil Bird<sup>2</sup>, Timothy J. Taylor<sup>1</sup>, Elizabeth McCarthy<sup>3</sup>, David H. Fletcher<sup>4</sup>, Benedict W. Wheeler<sup>1</sup>, Marianne Zandersen<sup>5</sup>, Laurence Jones<sup>3</sup></p> <p><sup>1</sup>European Centre for Environment and Human Health, University of Exeter, Penryn, Cornwall, UK</p> <p><sup>2 </sup>Institute for Climate, Energy and Society, JOANNEUM RESEARCH, Graz, Austria</p> <p><sup>3</sup> Department of Environmental Studies, Schiller Institute for Integrated Science and Society, Boston College, USA</p> <p><sup>4</sup> UK Centre for Ecology & Hydrology, Environment Centre Wales, Bangor, Gwynedd, Wales, UK</p> <p><sup>5 </sup>Department of Environmental Science, iClimate Interdisciplinary Centre for Climate Change, Aarhus University, Denmark</p> <p> </p>
Identifying the mechanisms by which irrigation can cool urban green spaces in summer
<p>This dataset contains the measured soil moisture and microclimate data from two (2021 and 2022) urban green space irrigation experiments conducted in Burnley, Melbourne, Australia. The experiments consisted of two treatments, irrigated turf and unirrigated turf. The purpose of the experiments was to provide testing (2021) and evaluation (2022) data for an urban ecohydrological model, UT&C. </p> <p><br>After evaluating the performance of UT&C in modelling soil moisture and microclimate, UT&C was used to model the surface energy balance and evapotranspiration processes of the irrigated and unirrigated turf. This dataset also contains the modelled soil moisture, microclimate, surface energy balance and evapotranspiration data, as well as the measured background climate data at the reference climate station and the forcing data for the model.</p> <p><br>The aims of this study were to:<br>i) identify the proportional contribution of different evapotranspiration processes to irrigation cooling effect, and <br>ii) quantify the impacts of different irrigation amounts (from 2 to 30 mm/d) on the cooling effect of irrigating turfgrass in Melbourne, Australia during normal summer conditions.</p> <p>This study was published in:<br>Pui Kwan Cheung, Naika Meili, Kerry A. Nice, Stephen J. Livesley (2024). Identifying the mechanisms by which irrigation can cool urban green spaces in summer. Urban Climate. 55,101914. https://doi.org/10.1016/j.uclim.2024.101914.</p>
Data on different types of green spaces and their accessibility in the seven largest urban regions in Finland
<p>This repository contains data described in the article "Data on different types of green spaces and their accessibility in the seven largest urban regions in Finland" (Heikinheimo et al. 2023) and used in the research article "Associations of neighborhood-level socioeconomic status, accessibility, and quality of green spaces in Finnish urban regions" (Viinikka et al. 2023). <br> <br> This repository contains data on green space quality and path distances to different types of green spaces. The path distances represent green space accessibility using active travel modes (walking, cycling). The path distances were calculated using the pedestrian street network across the seven largest urban regions in Finland. We derived the green space typology from the Urban Atlas Data that is available across functional urban areas in Europe and enhanced it with national data on water bodies, conservation areas and recreational facilities and routes from Finland. We extracted the walkable street network from OpenStreetMap and calculated shortest paths to different types of green spaces using open-source Python programming tools. Network distances were calculated up to ten kilometers from each green space edge and the distances were aggregated into a 250 m x 250 m statistical grid that is interoperable with various statistical data from Finland. The geospatial data files representing the different types of green spaces, network distances across the seven urban regions, as well as the processing and analysis scripts are shared in an open repository. These data offer actionable information about green space accessibility in Finnish city regions and support the integration of green space quality and active travel modes into further research and planning activities.</p> <p> </p> <p><strong>Data description article: </strong></p> <p>Heikinheimo, V., Tiitu, M., & Viinikka, A. (2023). Data on different types of green spaces and their accessibility in the seven largest urban regions in Finland. <em>Data in Brief</em>, <em>50</em>, 109458. <a href="https://doi.org/10.1016/j.dib.2023.109458">https://doi.org/10.1016/j.dib.2023.109458</a></p> <p><strong>Related research article:</strong> </p> <p>Viinikka, A., Tiitu, M., Heikinheimo, V., Halonen, J. I., Nyberg, E., & Vierikko, K. (2023). Associations of neighborhood-level socioeconomic status, accessibility, and quality of green spaces in Finnish urban regions. <em>Applied Geography</em>, <em>157</em>, 102973. <a href="https://doi.org/10.1016/j.apgeog.2023.102973">https://doi.org/10.1016/j.apgeog.2023.102973</a></p>
Green Space Distribution m2 per capita in Valladolid city
<p>Urban green infrastructures are key part of the sustainable development in our cities. They can provide important Ecosystem Services in them, including provisioning, regulating, supporting and cultural services. The total surface of green areas needs to be relativized in terms of total area or per capita, in order to compare results with other cities or to observe the evolution within the same city.</p>
Questionnaire for surveys on Urban Green Space use and survey raw data for Brussels (Belgium), Luxembourg-city (Luxembourg) and Rouen (France)
<p>The repository contains the xml files of survey questionnaires on the use of urban green spaces. All survey files are translated into three languages (English, French and German).</p> <p>At the time of this publication, these questionnaires have already been used for conducting face-to-face surveys in 2016 in Brussels (Belgium), in 2017 in Luxembourg-city (Luxembourg) and in 2017 in Rouen (France).</p> <p>The results of these surveys are provided in raw data format (csv files), after anonymisation (home and workplace locations have been removed).</p> <p>Please feel free to contact us for any supplementary info.</p>
Expanding urban green space with superblocks
<p>The street geometries are processed geometries originating from OpenStreetMap. Map data<br> copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org.</p> <p>If you use this data, make sure to cite OpenStreetMap as outlined:<br> https://wiki.openstreetmap.org/wiki/Researcher_Information.</p> <p>All data is provided as GeoJSON files.</p> <p>The block files contain the following attributes:</p> <p> Attribute Explanation<br> --------- ------------<br> b_type Classification of either super- or miniblock<br> inter_id Random id<br> area area (m2)</p>
Mapping the Green Product-Space in Mexico: From Capabilities to Green Opportunities
<p>The aim of this paper is to examine the current and potential capability to promote the green economy in Mexico, simultaneously detecting new opportunities for diversification and “green” productive sophistication so that Mexican entities can move toward environmentally friendly ecological products. For this, we adopted a novel methodology to measure the productive capabilities of the green economy in Mexico, thereby discovering the green product space at a subnational scale. Economic complexity methods were used to estimate the Green Complexity Index (GCI) and the Green Complexity Potential (GCP) for 32 Mexican regions considering a time series from 2004 to 2018 and a set of data on international trade in ecological products. The main findings are reflected in a grid of the Green Adjacent Possible (GAP) and a heatmap that shows the “<span>grasslands</span>” (current green products by state). The results are likely to influence industrial policy and state innovation agendas. A limitation of this work is that it is based only on data from the formal, industrial, and regulated economy. The originality lies in the fact that there were no previous studies in the context analyzed, and the fecundity of the research reflects the need to expand the study with a focus on green business models.</p>
Data on learning about green space management by upper secondary school students
<p>A workshop survey -dataset detailing how upper secondary school students learn about green space management.</p>
Data for: Urban form and its impacts on air pollution and access to green space: A global analysis of 462 cities
Open the record for dataset details and reuse information.
Data from: A place-based participatory mapping approach for assessing cultural ecosystem services in urban green space
1. Cultural Ecosystem Services (CES) encompass a range of social, cultural and health benefits to local communities, for example recreation, spirituality, a sense of place and local identity. However, these complex and place-specific CES are often overlooked in rapid land management decisions and assessed using broad, top–down approaches. 2. We use the Toolkit for Ecosystem Service Site-based Assessment (TESSA) to examine a novel approach to rapid assessment of local CES provision using inductive, participatory methods. We combined free-listing and participatory geographic information systems (GIS) techniques to quantify and map perceptions of current CES provision of an urban green space. The results were then statistically compared with those of a proposed alternative scenario with the aim to inform future decision-making. 3. By identifying changes in the spatial hotspots of CES in our study area, we revealed a spatially-specific shift toward positive sentiment regarding several CES under the alternative state with variance across demographic and stakeholder groups. Response aggregations in areas of proposed development reveal previously unknown stakeholder preferences to local decision-makers and highlight potential trade-offs for conservation management. Free-listed responses revealed deeper insight into personal opinion and context. 4. This work serves as a useful case study on how the perceptions and opinions of local people regarding local CES could be accounted for in the future planning of an urban greenspace and how thorough analysis of CES provision is important to fully-inform local-scale conservation and planning for the mutual benefit of local communities and nature.
Data: Greater local cooling effects of trees across globally distributed urban green spaces
<p>The dataset used for hierarchical linear mixed effects models in the R code during the study. </p><p>The description of the column names is provided in the readme file.</p>
Dataset from publication "Predicting context-sensitive urban green space quality to support urban green infrastructure planning"
<p><strong>Data Description:</strong></p><p>This dataset presents the spatial outcome of an analysis modelling perceived green space quality across the city of Espoo, Finland. The analysis relies on data gathered through the My Espoo on the Map survey (<i>Mun Espoo kartalla</i>) in the autumn of 2020 as part of the NordForsk-funded research project NORDGREEN. A comprehensive account of the analytical process and potential applications of the dataset is available in the associated publication, "<i>Predicting context-sensitive urban green space quality to support urban green infrastructure planning</i>" (open access: <a href="https://doi.org/10.1016/j.landurbplan.2023.104952">https://doi.org/10.1016/j.landurbplan.2023.104952</a>).</p><p><strong>Data Processing:</strong></p><p>This dataset results from an analysis that integrates both primary and secondary sources of geospatial data. The primary data were collected with an online public participation GIS (PPGIS) survey directed for the adult inhabitants of Espoo. The data collection took place in September-October 2020 and was executed in collaboration with Aalto University and the City of Espoo. For a detailed overview of the data collection process, please refer to the related publication.</p><p><strong>Data characteristics:</strong></p><p>Format: Shapefile (50m x 50m grid)</p><p>Geographical area: Espoo, Finland</p><p>Spatial reference: EUREF FIN TM35FIN</p><p>Note: Only grid cells intersecting with greenspace have been included in the dataset. For the employed definition of green areas, please consult the related publication.</p><p><strong>Data attributes and their descriptions:</strong></p><p><strong>"</strong><i>P_PROB"</i>: Probability (P), positive perceived quality</p><p><i>"N_PROB"</i>: Probability (P), negative perceived quality</p><p><strong>Funding: </strong></p><p>This research was funded by NordForsk, Sustainable Urban Development and Smart Cities Programme, Project Smart Planning for Healthy and Green and Nordic Cities – NORDGREEN, under Grant Number: 95322.</p>
Data from: neglected puzzle pieces of urban green infrastructure: richness, cover, and composition of insect-pollinated plants in traffic-related green spaces
<p>Insect-pollinated vascular plants in spontaneous vegetation provide essential ecosystem services and benefit wildlife. However, floral communities associated with traffic-related green spaces are rarely considered valuable elements of urban green infrastructure (UGI). The dataset contains information on species-based floral communities of vascular insect-pollinated plants in traffic-related green spaces in three highly populated Finnish cities. Those are Helsinki (665 558 inhabitants), Tampere (244 029 inhabitants), and Turku (175 645 inhabitants). Data were collected during the mean flowering phenophase of vascular plants in July-August 2022 from two types of locations: (i) urban (city centers) and (ii) suburban (city outskirts), and from three types of traffic-related green spaces: (i) traffic islands, (ii) parking lots, (iii) road verges. The dataset contains information for the 93 vascular insect-pollinated plant species flowering during the survey. Sampling campaign was conducted in 90 sampling sites, and the dataset contains information on the location coordinates. In addition, the dataset possesses information on the amount of garbage pieces (cigarette filters, plastic boxes, or scraps) revealed for each sampling point in traffic-related green spaces.</p>
Effects of COVID-19 lockdown restrictions on parents' attitudes towards green space and time spent outside by children in Cambridgeshire and North London, United Kingdom
<p>1. In the United Kingdom, children are spending less time outdoors and are more disconnected from nature than previous generations. However, interaction with nature at a young age can benefit wellbeing and long-term support for conservation. Green space accessibility in the UK varies between rural and urban areas and is lower for children than for adults. It is possible that COVID-19 lockdown restrictions may have influenced these differences.</p> <p>2. In this study, we assessed parents' attitudes towards green space, as well as whether the COVID-19 lockdown restrictions had affected their attitudes or the amount of time spent outside by their children, via an online survey for parents of primary school-aged children in Cambridgeshire and North London, UK (n = 171). We assessed whether responses were affected by local environment (rural, suburban or urban), school type (state-funded or fee-paying) or garden access (with or without private garden access).</p> <p>3. Parents' attitudes towards green space were significantly different between local environments: 76.9% of rural parents reported being happy with the amount of green space to which their children had access, in contrast with only 40.5% of urban parents.</p> <p>4. COVID-19 lockdown restrictions also affected parents' attitudes to the importance of green space, and this differed between local environments: 75.7% of urban parents said their views had changed during lockdown, in contrast with 35.9% of rural parents. The change in amount of time spent outside by children during lockdown was also significantly different between local environments: most urban children spent more time inside during lockdown, whilst most rural children spent more time outside.</p> <p>5. Neither parents' attitudes towards green space nor the amount of time spent outside by their children varied with school type or garden access.</p> <p>6. Our results suggest that lockdown restrictions exacerbated pre-existing differences in access to nature between urban and rural children in our sampled population. We suggest that the current increased public and political awareness of the value of green space should be capitalised on to increase provision and access to green space and to reduce inequalities in accessibility and awareness of nature between children from different backgrounds.</p>
Nordic comparative study on green space use during COVID-19 – Case Helsinki (NCS-Helsinki)
<p>This dataset includes the data used in the Helsinki case study of an original research paper “<em>Pandemic urban resilience in the Nordic context - a cross-city analysis on associations between outdoor recreation and green infrastructure</em>” (Fagerholm et al., upcoming).</p> <p>The data were collected in the PLAN-Health (PLAN-H) research project (<a href="https://participatorymapping.org/project/health-promoting-urban-environment-plan-h/">https://participatorymapping.org/project/health-promoting-urban-environment-plan-h/</a>) and include point data of respondent-mapped outdoor locations visited in leisure time.</p>
Preliminary results: Predicted cooling effect, lives saved and associated economic value from public green spaces in Paris
<p><span>This dataset represents preliminary results predicting the cooling effect from public green spaces in Paris for the 10th, 22nd and 24th July 2019, the lives saved and associated economic valuation.</span></p> <p>The data format is a shapefile with coordinate reference system RGF93 v1 / Lambert-93 (EPSG:2154).</p> <p>Please see the README file for description of the variable names. </p> <p>Full results will be shared in due course, alongside all code and a detailed description of the method. If you would like to know more about the method or would like to be informed when the full results and method are published, please contact Jo Garrett at j.k.garrett@Exeter.ac.uk</p>
Dataset: Assessing Immediate and Lasting Impacts of COVID-19-Induced Isolation on Green Space Usage Patterns
<p>It includes the data for paper "Assessing Immediate and Lasting Impacts of COVID-19-Induced Isolation on Green Space Usage Patterns".</p> <p> </p>
Assessing Urban Green Space Accessibility in Amsterdam
<p>This is dataset is an ArcGIS Pro project was used to calculate walking distance from buildings to Urban Green Spaces (UGS) within the municipality of Amsterdam. This was made as part of an MSc Earth Sciences thesis aimed at assessing UGS and heat exposure in Amsterdam. The thesis is based on the idea that UGS function as cool spaces within the urban heat island of the city, and thus provides lower temperatures to urban residents, specifically during hot summer months, therefore reducing the risk of heat stress and heat-related illnesses and morbidity.</p>
Green Space Management - Urban Green as perceived by citizens
<p>This dataset contains the results, as csv file, of the monitoring surveys of green space management as perceived by citizens. The resources will be 1) results from first survey (summer 2021) and 2) results from the 2nd survey (TBD).</p> <p>Some of the most interesting columns in the results</p> <p>Column 9 ("Quartiere") is the residential area of the citizen.</p> <p>Column 10 ("Indirizzo"), when available, is the street where the citizen lives</p> <p>Column 11, ("Freq_parco"), when available, is the frequency with which the citizen visit a green area/park in the town</p> <p>Column 18, ("Distanza_parco"), when available, is the distance in minutes to reach a park</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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