Measuring the 3-30-300 rule to help cities meet nature access thresholds.

[1]  M. Beenackers,et al.  Preferred reporting items in green space health research. Guiding principles for an interdisciplinary field. , 2023, Environmental research.

[2]  A. Rigolon,et al.  Examining facilitators and challenges to implementing equitable green space policies: Lessons from Los Angeles County , 2023, Journal of Urban Affairs.

[3]  Bing Zhao,et al.  How to Systematically Evaluate the Greenspace Exposure of Residential Communities? A 3-D Novel Perspective Using UAV Photogrammetry , 2023, Remote. Sens..

[4]  Ruoyu Wang,et al.  Establishing a citywide street tree inventory with street view images and computer vision techniques , 2023, Comput. Environ. Urban Syst..

[5]  Won Hee Ko,et al.  View access index: The effects of geometric variables of window views on occupants’ satisfaction , 2023, Building and Environment.

[6]  T. Beatley,et al.  Denser and greener cities: Green interventions to achieve both urban density and nature , 2023, People and Nature.

[7]  D. Barton,et al.  Making trees visible: a GIS method and tool for modelling visibility in the valuation of urban trees , 2023, Urban Forestry & Urban Greening.

[8]  A. Gasparrini,et al.  Cooling cities through urban green infrastructure: a health impact assessment of European cities , 2023, The Lancet.

[9]  S. Ogletree,et al.  The PAD-US-AR dataset: Measuring accessible and recreational parks in the contiguous United States , 2022, Scientific data.

[10]  R. Remme,et al.  CUGIC: The Consolidated Urban Green Infrastructure Classification for assessing ecosystem services and biodiversity , 2022, bioRxiv.

[11]  P. Dadvand,et al.  Is indoor and outdoor greenery associated with fewer depressive symptoms during COVID-19 lockdowns? A mechanistic study in Shanghai, China , 2022, Building and Environment.

[12]  B. Jiang,et al.  How do computers see landscapes? comparisons of eye-level greenery assessments between computer and human perceptions , 2022, Landscape and Urban Planning.

[13]  Geoffrey H. Donovan,et al.  The association between tree planting and mortality: A natural experiment and cost-benefit analysis. , 2022, Environment international.

[14]  A. Dzhambov,et al.  Exposure to nature during the COVID-19 pandemic and the associated effect on mental health: a systematic review with meta-analysis , 2022, The Lancet Planetary Health.

[15]  Lincoln R. Larson,et al.  Beyond "bluespace" and "greenspace": A narrative review of possible health benefits from exposure to other natural landscapes. , 2022, The Science of the total environment.

[16]  Xavier Delclòs-Alió,et al.  A 10 m resolution urban green space map for major Latin American cities from Sentinel-2 remote sensing images and OpenStreetMap , 2022, Scientific Data.

[17]  M. Nieuwenhuijsen,et al.  The evaluation of the 3-30-300 green space rule and mental health. , 2022, Environmental Research.

[18]  C. Konijnendijk.  Evidence-based guidelines for greener, healthier, more resilient neighbourhoods: Introducing the 3–30–300 rule , 2022, Journal of Forestry Research.

[19]  Lara A. Roman,et al.  Why don’t people plant trees? Uncovering barriers to participation in urban tree planting initiatives , 2022, Urban Forestry & Urban Greening.

[20]  Alexander M. Tait,et al.  Dynamic World, Near real-time global 10 m land use land cover mapping , 2022, Scientific Data.

[21]  S. Blumentrath,et al.  Viewshed-based modelling of visual exposure to urban greenery – An efficient GIS tool for practical planning applications , 2022, Landscape and Urban Planning.

[22]  M. Adams,et al.  Using open data and open-source software to develop spatial indicators of urban design and transport features for achieving healthy and sustainable cities , 2022, The Lancet. Global health.

[23]  M. Plusquin,et al.  Residential Exposure to Urban Trees and Medication Sales for Mood Disorders and Cardiovascular Disease in Brussels, Belgium: An Ecological Study , 2022, Environmental health perspectives.

[24]  Samkelisiwe Khanyile,et al.  Interrogating park access and equity in Johannesburg, South Africa , 2022, Environment and Urbanization.

[25]  Y. Chan,et al.  Evaluation of window view preference using quantitative and qualitative factors of window view content , 2022, Building and Environment.

[26]  P. Jacobi,et al.  Editorial: Urban Greening in the Global South: Green Gentrification and Beyond , 2022, Frontiers in Sustainable Cities.

[27]  Q. Guo,et al.  Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based mobile lidar data , 2022, ISPRS Journal of Photogrammetry and Remote Sensing.

[28]  T. McPhearson,et al.  What is green infrastructure? A study of definitions in US city planning , 2022, Frontiers in Ecology and the Environment.

[29]  Naoyuki Furuya,et al.  ForestScanner: A mobile application for measuring and mapping trees with LiDAR-equipped iPhone and iPad , 2021, bioRxiv.

[30]  A. Tomao,et al.  Tree measurements in the urban environment: insights from traditional and digital field instruments to smartphone applications , 2021, Arboriculture & Urban Forestry.

[31]  Lincoln R. Larson,et al.  Greenspace and park use associated with less emotional distress among college students in the United States during the COVID-19 pandemic , 2021, Environmental Research.

[32]  Siqin Wang,et al.  Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches , 2021, Comput. Environ. Urban Syst..

[33]  F. Biljecki,et al.  Street view imagery in urban analytics and GIS: A review , 2021 .

[34]  Daniel L. Oberski,et al.  Can’t see the wood for the trees? An assessment of street view- and satellite-derived greenness measures in relation to mental health , 2021 .

[35]  Sara Meerow,et al.  A ‘green’ chameleon: Exploring the many disciplinary definitions, goals, and forms of “green infrastructure” , 2021 .

[36]  L. Knibbs,et al.  Greenspace and human health: An umbrella review , 2021, Innovation.

[37]  M. Nieuwenhuijsen.  New urban models for more sustainable, liveable and healthier cities post covid19; reducing air pollution, noise and heat island effects and increasing green space and physical activity , 2021, Environment International.

[38]  M. Helbich,et al.  Nature's contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID-19 , 2021, Science of The Total Environment.

[39]  D. D. de Souza,et al.  Greening and Just Cities: Elements for Fostering a South–North Dialogue Based on a Systematic Literature Review , 2021, Frontiers in Sustainable Cities.

[40]  S. Lindley,et al.  Estimating multiple greenspace exposure types and their associations with neighbourhood premature mortality: A socioecological study. , 2021, The Science of the total environment.

[41]  M. Alberti,et al.  The Benefits and Limits of Urban Tree Planting for Environmental and Human Health , 2021, Frontiers in Ecology and Evolution.

[42]  Jan Dirk Wegner,et al.  Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles , 2021, Remote Sensing of Environment.

[43]  Rafael H. M. Pereira,et al.  r5r: Rapid Realistic Routing on Multimodal Transport Networks with R5 in R , 2021 .

[44]  Alexander Zipf,et al.  Regional variations of context‐based association rules in OpenStreetMap , 2020, Trans. GIS.

[45]  Pablo Knobel,et al.  Development of the urban green space quality assessment tool (RECITAL) , 2020 .

[46]  S. Lindley,et al.  Modelling and mapping eye-level greenness visibility exposure using multi-source data at high spatial resolutions , 2020, Science of The Total Environment.

[47]  A. Loukaitou-Sideris,et al.  Promotores for Parks? The Potential of a Public Health Model to Improve Outreach and Community Engagement in Park Planning , 2020, Leisure Sciences.

[48]  M. Leishman,et al.  The Global Urban Tree Inventory: A database of the diverse tree flora that inhabits the world’s cities , 2020 .

[49]  Zhaowu Yu,et al.  Links between green space and public health: a bibliometric review of global research trends and future prospects from 1901 to 2019 , 2020, Environmental Research Letters.

[50]  M. Browning,et al.  The Role of Methodological Choices in the Effects of Experimental Exposure to Simulated Natural Landscapes on Human Health and Cognitive Performance: A Systematic Review , 2020, Environment and Behavior.

[51]  Ian Mell.  The impact of austerity on funding green infrastructure: A DPSIR evaluation of the Liverpool Green & Open Space Review (LG&OSR), UK , 2020 .

[52]  M. Dijst,et al.  Using structural equation modeling to examine pathways between perceived residential green space and mental health among internal migrants in China. , 2020, Environmental research.

[53]  Maria Immacolata Marzulli,et al.  Estimating tree stem diameters and volume from smartphone photogrammetric point clouds , 2019, Forestry: An International Journal of Forest Research.

[54]  M. Helbich,et al.  Relative importance of perceived physical and social neighborhood characteristics for depression: a machine learning approach , 2019, Social Psychiatry and Psychiatric Epidemiology.

[55]  S. Lindley,et al.  Spatial dimensions of the influence of urban green-blue spaces on human health: A systematic review. , 2019, Environmental research.

[56]  Pietro Perona,et al.  From Google Maps to a Fine-Grained Catalog of Street trees , 2019, ArXiv.

[57]  Pablo Knobel,et al.  A systematic review of multi-dimensional quality assessment tools for urban green spaces. , 2019, Health & place.

[58]  Lara A. Roman,et al.  Urban Tree Mortality: A Literature Review , 2019, Arboriculture & Urban Forestry.

[59]  Gail Hansen,et al.  Mobile Terrestrial Photogrammetry for Street Tree Mapping and Measurements , 2019, Forests.

[60]  G. Churkina,et al.  Urban trees, air quality, and asthma: An interdisciplinary review , 2019, Landscape and Urban Planning.

[61]  Lara A. Roman,et al.  Visual health assessments for palms , 2019, Urban Forestry & Urban Greening.

[62]  Jan Dirk Wegner,et al.  Country-wide high-resolution vegetation height mapping with Sentinel-2 , 2019, Remote Sensing of Environment.

[63]  M. Browning,et al.  Urban Green Spaces: Public Health and Sustainability in the United States , 2019, SpringerBriefs in Geography.

[64]  M. McDonough,et al.  Community Stories: Explaining Resistance to Street Tree-Planting Programs in Detroit, Michigan, USA , 2019, Society & Natural Resources.

[65]  A. Rigolon.  Nonprofits and park equity in Los Angeles: a promising way forward for environmental justice , 2018, Urban Geography.

[66]  M. Browning,et al.  Access to Urban Green Space in Cities of the Global South: A Systematic Literature Review , 2018, Urban Science.

[67]  Carlo Ratti,et al.  Treepedia 2.0: Applying Deep Learning for Large-Scale Quantification of Urban Tree Cover , 2018, 2018 IEEE International Congress on Big Data (BigData Congress).

[68]  T. Mattijssen,et al.  The benefits of self-governance for nature conservation: A study on active citizenship in the Netherlands , 2018, Journal for Nature Conservation.

[69]  Joseph Redmon,et al.  YOLOv3: An Incremental Improvement , 2018, ArXiv.

[70]  M. McDonough,et al.  The trouble with trees? Social and political dynamics of street tree-planting efforts in Detroit, Michigan, USA , 2018 .

[71]  Birgit H. M. Elands,et al.  The ‘green’ and ‘self’ in green self-governance – a study of 264 green space initiatives by citizens , 2018 .

[72]  S. M. Labib,et al.  The potentials of Sentinel-2 and LandSat-8 data in green infrastructure extraction, using object based image analysis (OBIA) method , 2018 .

[73]  Dexter H. Locke,et al.  Tree Canopy Change in Coastal Los Angeles, 2009 - 2014 , 2017 .

[74]  Edmund Seto,et al.  Natural outdoor environments and mental health: Stress as a possible mechanism , 2017, Environmental research.

[75]  M. Brauer,et al.  Exploring pathways linking greenspace to health: Theoretical and methodological guidance , 2017, Environmental research.

[76]  R. Gražulevičienė,et al.  Living Close to Natural Outdoor Environments in Four European Cities: Adults’ Contact with the Environments and Physical Activity , 2017, International journal of environmental research and public health.

[77]  Bolei Zhou,et al.  Scene Parsing through ADE20K Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[78]  Dexter H. Locke,et al.  Branching out to residential lands: Missions and strategies of five tree distribution programs in the U.S , 2017 .

[79]  D. Hochuli,et al.  Defining greenspace: Multiple uses across multiple disciplines , 2017 .

[80]  Geoff Boeing,et al.  OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks , 2016, Comput. Environ. Urban Syst..

[81]  Jianping Wu,et al.  View-based greenery: A three-dimensional assessment of city buildings' green visibility using Floor Green View Index , 2016 .

[82]  F. Götmark,et al.  Why Be a Shrub? A Basic Model and Hypotheses for the Adaptive Values of a Common Growth Form , 2016, Front. Plant Sci..

[83]  K. Lowe,et al.  Capacity and Equity: Federal Funding Competition between and Within Metropolitan Regions , 2016 .

[84]  C. Thompson,et al.  Green infrastructure and health , 2015 .

[85]  Juha Hyyppä,et al.  Evaluation of a Smartphone App for Forest Sample Plot Measurements , 2015 .

[86]  Jarlath O'Neil-Dunne,et al.  A Versatile, Production-Oriented Approach to High-Resolution Tree-Canopy Mapping in Urban and Suburban Landscapes Using GEOBIA and Data Fusion , 2014, Remote. Sens..

[87]  R. Reis,et al.  Are park proximity and park features related to park use and park-based physical activity among adults? Variations by multiple socio-demographic characteristics , 2014, International Journal of Behavioral Nutrition and Physical Activity.

[88]  Jolene D. Smyth,et al.  Internet, Phone, Mail, and Mixed‐Mode Surveys , 2014 .

[89]  T. Gillespie,et al.  Urban tree planting programs, function or fashion? Los Angeles and urban tree planting campaigns , 2013 .

[90]  Keith C. Pelletier,et al.  An object-based system for LiDAR data fusion and feature extraction , 2013 .

[91]  Chengquan Huang,et al.  Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error , 2013, Int. J. Digit. Earth.

[92]  G. Moisen,et al.  Modeling Percent Tree Canopy Cover: A Pilot Study , 2012 .

[93]  Dennis Luxen,et al.  Real-time routing with OpenStreetMap data , 2011, GIS.

[94]  D. Richardson,et al.  Trees and shrubs as invasive alien species – a global review , 2011 .

[95]  A. Hudak,et al.  A Comparison of Accuracy and Cost of LiDAR versus Stand Exam Data for Landscape Management on the Malheur National Forest , 2011, Journal of Forestry.

[96]  George Vosselman,et al.  Airborne and terrestrial laser scanning , 2011, Int. J. Digit. Earth.

[97]  David J. Nowak,et al.  Evaluating The National Land Cover Database Tree Canopy and Impervious Cover Estimates Across the Conterminous United States: A Comparison with Photo-Interpreted Estimates , 2010, Environmental management.

[98]  Athanasios Sideris,et al.  What Brings Children to the Park? Analysis and Measurement of the Variables Affecting Children's Use of Parks , 2009 .

[99]  B. Chaix,et al.  Neighbourhoods in eco-epidemiologic research: delimiting personal exposure areas. A response to Riva, Gauvin, Apparicio and Brodeur. , 2009, Social science & medicine.

[100]  Sandro Galea,et al.  Defining neighborhood boundaries for urban health research. , 2007, American journal of preventive medicine.

[101]  L. Eklund.  Summaries of selected publications from the Health Evidence Network of World Health Organization Regional Office for Europe , 2006, International Journal of Technology Assessment in Health Care.

[102]  J. Townshend,et al.  Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm , 2003 .

[103]  E. Talen.  Neighborhoods as Service Providers: A Methodology for Evaluating Pedestrian Access , 2003 .

[104]  B. Giles-Corti,et al.  Socioeconomic status differences in recreational physical activity levels and real and perceived access to a supportive physical environment. , 2002, Preventive medicine.

[105]  A. Gitelson,et al.  Novel algorithms for remote estimation of vegetation fraction , 2002 .

[106]  R. Tateishi,et al.  Relationships between percent vegetation cover and vegetation indices , 1998 .

[107]  Robert J. Chaskin,et al.  Perspectives on Neighborhood and Community: A Review of the Literature , 1997, Social Service Review.

[108]  A. Huete,et al.  A Modified Soil Adjusted Vegetation Index , 1994 .

[109]  John R. Collins,et al.  Perceived crowding in recreation settings: an urban case study. , 1987 .

[110]  J. Doran,et al.  Experiments with the Graph Traverser program , 1966, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[111]  Chongcheng Chen,et al.  Assessing the visibility of urban greenery using MLS LiDAR data , 2023, Landscape and Urban Planning.

[112]  Barcelona, Spain , 2019, The Statesman’s Yearbook Companion.

[113]  Adam Berland,et al.  Google Street View shows promise for virtual street tree surveys , 2017 .

[114]  D. Kendal,et al.  Global patterns of diversity in the urban forest: is there evidence to support the 10/20/30 rule? , 2014 .

[115]  P. Wiseman,et al.  Use of Urban Tree Canopy Assessments by Localities in the Chesapeake Bay Watershed , 2014 .

[116]  Jarlath O'Neil-Dunne,et al.  AN OBJECT-BASED APPROACH TO STATEWIDE LAND COVER MAPPING , 2014 .

[117]  United Nations Economic Commission for Europe EUROPE ’ S FORESTS IN A CHANGING ENVIRONMENT Twenty years of Monitoring Forest Condition by ICP Forests , 2005 .

[118]  F. Santamour,et al.  TREES FOR URBAN PLANTING : DIVERSITY UNIFORMITY , AND COMMON SENSE , 1999 .