Oke, T. R. The heat island of the urban boundary layer: characteristics, causes and effects. In Wind climate in cities (eds Cermak, J. E. et al.) 81–107 (Springer, 1995). https://doi.org/10.1007/978-94-017-3686-2_5.
Wang, C., Wang, Z. H. & Yang, J. Cooling effect of urban trees on the built environment of contiguous United States. Earth’s Future 6, 1066–1081. https://doi.org/10.1029/2018EF000891 (2018).
Google Scholar
Pauleit, S. Urban street tree plantings: identifying the key requirements. Proc. Inst. Civ. Eng. Munic. Eng. 156, 43–50. https://doi.org/10.1680/muen.2003.156.1.43 (2003).
Google Scholar
Frantzeskaki, N. et al. Nature-based solutions for urban climate change adaptation: linking science, policy, and practice communities for evidence-based decision-making. BioScience 69, 455–466. https://doi.org/10.1093/biosci/biz042 (2019).
Google Scholar
Armson, D., Stringer, P. & Ennos, A. R. The effect of tree shade and grass on surface and globe temperatures in an urban area. Urban For. Urban Green. 11, 245–255. https://doi.org/10.1016/j.ufug.2012.05.002 (2012).
Google Scholar
Oke, T. R. The micrometeorology of the urban forest. Philos. Trans. R. Soc. Lond. B 324, 335–349. https://doi.org/10.1098/rstb.1989.0051 (1989).
Google Scholar
Chow, W. T. & Brazel, A. J. Assessing xeriscaping as a sustainable heat island mitigation approach for a desert city. Build. Environ. 47, 170–181. https://doi.org/10.1016/j.buildenv.2011.07.027 (2012).
Google Scholar
Wang, K., Ma, Q., Wang, X. & Wild, M. Urban impacts on mean and trend of surface incident solar radiation. Geophys. Res. Lett. 41, 4664–4668. https://doi.org/10.1002/2014GL060201 (2014).
Google Scholar
Bassuk, N. & Whitlow, T. Environmental stress in street trees. Arboricult. J. 12, 195–201. https://doi.org/10.1080/03071375.1988.9746788 (1988).
Google Scholar
Nowak, D. J., Kuroda, M. & Crane, D. E. Tree mortality rates and tree population projections in Baltimore, Maryland, USA. Urban For. Urban Green. 2, 139–147. https://doi.org/10.1078/1618-8667-00030 (2004).
Google Scholar
Monteith, J. . & Unsworth, M. . Principles of Environmental Physics: Plants, Animals, and the Atmosphere 4th edn. (Elsevier Ltd., 2013).
Simon, H. et al. Modeling transpiration and leaf temperature of urban trees—a case study evaluating the microclimate model ENVI-met against measurement data. Landsc. Urban Plan. 174, 33–40. https://doi.org/10.1016/j.landurbplan.2018.03.003 (2018).
Google Scholar
González-Dugo, M. P., Moran, M. S., Mateos, L. & Bryant, R. Canopy temperature variability as an indicator of crop water stress severity. Irrig. Sci. 24, 1–8. https://doi.org/10.1007/s00271-005-0023-7 (2006).
Google Scholar
Han, M., Zhang, H., DeJonge, K. C., Comas, L. H. & Trout, T. J. Estimating maize water stress by standard deviation of canopy temperature in thermal imagery. Agricult. Water Manag. 177, 400–409. https://doi.org/10.1016/j.agwat.2016.08.031 (2016).
Google Scholar
Hou, M., Tian, F., Zhang, T. & Huang, M. Evaluation of canopy temperature depression, transpiration, and canopy greenness in relation to yield of soybean at reproductive stage based on remote sensing imagery. Agricult. Water Manag. 222, 182–192. https://doi.org/10.1016/j.agwat.2019.06.005 (2019).
Google Scholar
Heilman, J. L., Brittin, C. L. & Zajicek, J. M. Water use by shrubs as affected by energy exchange with building walls. Agricult. For. Meteorol. 48, 345–357. https://doi.org/10.1016/0168-1923(89)90078-6 (1989).
Google Scholar
Perini, K. & Magliocco, A. Effects of vegetation, urban density, building height, and atmospheric conditions on local temperatures and thermal comfort. Urban For. Urban Green. 13, 495–506. https://doi.org/10.1016/j.ufug.2014.03.003 (2014).
Google Scholar
Soer, G. J. Estimation of regional evapotranspiration and soil moisture conditions using remotely sensed crop surface temperatures. Remote Sens. Environ. 9, 27–45. https://doi.org/10.1016/0034-4257(80)90045-0 (1980).
Google Scholar
Spronken-Smith, R. A. & Oke, T. R. The thermal regime of urban parks in two cities with different summer climates. Int. J. Remote Sens. 19, 2085–2104. https://doi.org/10.1080/014311698214884 (1998).
Google Scholar
Rahman, M. A. et al. Traits of trees for cooling urban heat islands: a meta-analysis. Build. Environ. 170, 106606. https://doi.org/10.1016/j.buildenv.2019.106606 (2020).
Google Scholar
Leuzinger, S., Vogt, R. & Körner, C. Tree surface temperature in an urban environment. Agricult. For. Meteorol. 150, 56–62. https://doi.org/10.1016/j.agrformet.2009.08.006 (2010).
Google Scholar
Meier, F. & Scherer, D. Spatial and temporal variability of urban tree canopy temperature during summer 2010 in Berlin, Germany. Theor. Appl. Climatol. 110, 373–384. https://doi.org/10.1007/s00704-012-0631-0 (2012).
Google Scholar
Ballester, C., Jiménez-Bello, M. A., Castel, J. R. & Intrigliolo, D. S. Usefulness of thermography for plant water stress detection in citrus and persimmon trees. Agric. For. Meteorol. 168, 120–129. https://doi.org/10.1016/j.agrformet.2012.08.005 (2013).
Google Scholar
Jones, H. G. Application of thermal imaging and infrared sensing in plant physiology and ecophysiology. Adv. Botan. Res. 41, 107–163. https://doi.org/10.1016/s0065-2296(04)41003-9 (2004).
Google Scholar
Givoni, B. Impact of planted areas on urban environmental quality: a review. Atmos. Environ. Part B Urban Atmos. 25, 289–299. https://doi.org/10.1016/0957-1272(91)90001-U (1991).
Google Scholar
Kalnay, E. & Cai, M. Impact of urbanization and land-use change on climate. Nature 423, 528–531. https://doi.org/10.1038/nature01675 (2003).
Google Scholar
A. Coutts, A. et al. Impacts of water sensitive urban design solutions on human thermal comfort. p. 20 (online link: https://watersensitivecities.org.au/wp-content/uploads/2016/07/TMR_B3-1_WSUD_thermal_comfort_no2.pdf) (2014).
Coutts1, A. et al. The Impacts of WSUD Solutions on Human Thermal Comfort Green Cities and Micro-climate-B3.1-2-2014 Contributing Authors. Tech. Rep. (1968).
Gunawardena, K. R., Wells, M. J. & Kershaw, T. Utilising green and bluespace to mitigate urban heat island intensity. Sci. Total Environ. 584–585, 1040–1055. https://doi.org/10.1016/j.scitotenv.2017.01.158 (2017).
Google Scholar
Völker, S., Baumeister, H., Classen, T., Hornberg, C. & Kistemann, T. Evidence for the temperature-mitigating capacity of urban blue space—a health geographic perspective. Erdkunde 67, 355–371. https://doi.org/10.3112/erdkunde.2013.04.05 (2013).
Google Scholar
Hu, L. & Li, Q. Greenspace, bluespace, and their interactive influence on urban thermal environments. Environ. Res. Lett. 15, 034041. https://doi.org/10.1088/1748-9326/ab6c30 (2020).
Google Scholar
Theeuwes, N. E., Solcerová, A. & Steeneveld, G. J. Modeling the influence of open water surfaces on the summertime temperature and thermal comfort in the city. J. Geophys. Res. Atmos. 118, 8881–8896. https://doi.org/10.1002/jgrd.50704 (2013).
Google Scholar
Ziter, C. D., Pedersen, E. J., Kucharik, C. J. & Turner, M. G. Scale-dependent interactions between tree canopy cover and impervious surfaces reduce daytime urban heat during summer. Proc. Natl. Acad. Sci. U. S. A. 116, 7575–7580. https://doi.org/10.1073/pnas.1817561116 (2019).
Google Scholar
Johnson, S., Ross, Z., Kheirbek, I. & Ito, K. Characterization of intra-urban spatial variation in observed summer ambient temperature from the New York City Community Air Survey. Urban Clim. 31, 100583. https://doi.org/10.1016/j.uclim.2020.100583 (2020).
Google Scholar
Wetherley, E. B., McFadden, J. P. & Roberts, D. A. Megacity-scale analysis of urban vegetation temperatures. Remote Sens. Environ. 213, 18–33. https://doi.org/10.1016/j.rse.2018.04.051 (2018).
Google Scholar
Zhou, W., Wang, J. & Cadenasso, M. L. Effects of the spatial configuration of trees on urban heat mitigation: a comparative study. Remote Sens. Environ. 195, 1–12. https://doi.org/10.1016/j.rse.2017.03.043 (2017).
Google Scholar
Weng, Q., Lu, D. & Schubring, J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sens. Environ. 89, 467–483. https://doi.org/10.1016/j.rse.2003.11.005 (2004).
Google Scholar
Hulley, G., Hook, S., Fisher, J. & Lee, C. ECOSTRESS, A NASA Earth-Ventures Instrument for studying links between the water cycle and plant health over the diurnal cycle. In International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2017-July, 5494–5496 (Institute of Electrical and Electronics Engineers Inc., 2017). https://doi.org/10.1109/IGARSS.2017.8128248.
Wood, S. N. Low-rank scale-invariant tensor product smooths for generalized additive mixed models. Biometrics 62, 1025–1036. https://doi.org/10.1111/j.1541-0420.2006.00574.x (2006).
Google Scholar
Duan, S.-B. et al. Estimation of diurnal cycle of land surface temperature at high temporal and spatial resolution from clear-sky MODIS data. Remote Sens. 6, 3247–3262. https://doi.org/10.3390/rs6043247 (2014).
Google Scholar
Hu, L., Sun, Y., Collins, G. & Fu, P. Improved estimates of monthly land surface temperature from MODIS using a diurnal temperature cycle (DTC) model. ISPRS J. Photogramm. Remote Sens. 168, 131–140. https://doi.org/10.1016/j.isprsjprs.2020.08.007 (2020).
Google Scholar
New York City Department of Information Technology and Telecommunications (NYC DoITT). Land Cover Raster Data 6-inch Resolution (2017).
New York City Department of Information Technology and Telecommunications (NYC DoITT). New York City Building Footprint (2017).
Wood, S. N. Generalized Additive Models: An Introduction with R 2nd edn. (CRC Press, 2017).
Google Scholar
Cârlan, I., Mihai, B. A., Nistor, C. & Große-Stoltenberg, A. Identifying urban vegetation stress factors based on open access remote sensing imagery and field observations. Ecol. Inform. 55, 101032. https://doi.org/10.1016/j.ecoinf.2019.101032 (2020).
Google Scholar
Cregg, B. & Dix, M. E. Tree moisture stress and insect damage in urban areas in relation to heat island effects. J. Arboricult. 27, 8–17 (2001).
Novem, D. & Falxa, N. United States Department of Agriculture The Urban Forest of New York City. Tech. Rep. https://doi.org/10.2737/NRS-RB-117 (2018).
Shaker, R. R., Altman, Y., Deng, C., Vaz, E. & Forsythe, K. W. Investigating urban heat island through spatial analysis of New York City streetscapes. J. Clean. Prod. 233, 972–992. https://doi.org/10.1016/j.jclepro.2019.05.389 (2019).
Google Scholar
Meir, T., Orton, P. M., Pullen, J., Holt, T. & Thompson, W. T. Forecasting the New York City urban heat island and sea breeze during extreme heat events. Weather Forecast. 28, 1460–1477. https://doi.org/10.1175/WAF-D-13-00012.1 (2013).
Google Scholar
Ramamurthy, P., González, J., Ortiz, L., Arend, M. & Moshary, F. Impact of heatwave on a megacity: an observational analysis of New York City during July 2016. Environ. Res. Lett. 12, 054011. https://doi.org/10.1088/1748-9326/aa6e59 (2017).
Google Scholar
Gedzelman, S. D. et al. Mesoscale aspects of the Urban Heat Island around New York City. Theor. Appl. Climatol. 75, 29–42. https://doi.org/10.1007/s00704-002-0724-2 (2003).
Google Scholar
Cavender, N. & Donnelly, G. Intersecting urban forestry and botanical gardens to address big challenges for healthier trees, people, and cities. Plants People Planet 1, 315–322. https://doi.org/10.1002/ppp3.38 (2019).
Google Scholar
Marias, D. E., Meinzer, F. C. & Still, C. Impacts of leaf age and heat stress duration on photosynthetic gas exchange and foliar nonstructural carbohydrates in Coffea arabica. Ecol. Evol. 7, 1297–1310. https://doi.org/10.1002/ece3.2681 (2017).
Google Scholar
Brune, M. Urban trees under climate change. Potential impacts of dry spells and heat waves in three Germany regions in the 1950s. Report 20, Climate Service Center Germany, Hamburg 123 (2016).
Jim, C. Y. Green-space preservation and allocation for sustainable greening of compact cities. Cities 21, 311–320. https://doi.org/10.1016/j.cities.2004.04.004 (2004).
Google Scholar
Santamouris, M. Cooling the cities—a review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environments. Sol. Energy 103, 682–703. https://doi.org/10.1016/j.solener.2012.07.003 (2014).
Google Scholar
Drescher, M. Urban heating and canopy cover need to be considered as matters of environmental justice. Proc. Natl. Acad. Sci. U. S. A. 116, 26153–26154. https://doi.org/10.1073/pnas.1917213116 (2019).
Google Scholar
Roloff, A. . Bäume in der Stadt (Ulmer, E, 2013).
Bruse, M. ENVI-met 3.0: Updated Model Overview. Tech. Rep. (2004).
US Census Bureau. State and County Quick Facts https://www.census.gov/quickfacts/fact/table/US/PST045219 (2019).
Shorris, A. Cool Neighborhoods NYC: A Comprehensive Approach to Keep Communities Safe in Extreme Heat. Tech. Rep.
Hulley, G. ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) Mission Level 2 Product Specification Document. Tech. Rep. (2018).
Stark, P. & Parker, R. Bounded-Variable Least-squares: An Algorithm and Applications. Tech. Rep. 394, (1995).
Source: Ecology - nature.com
