https://socictopen.socict.org/files/original/6db5287da788413c9c990dca54ea5da4.pdf 7f23c3cd81baf69519137d3d8dd383fe Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Tree Cover Is Unevenly Distributed Across Cities Globally, With Lowest Levels Near Highway Pollution Sources Creator An entity primarily responsible for making the resource Theodore Endreny, Francesco Sica, David Nowak Description An account of the resource Obtaining accurate tree cover maps within cities is a first step toward managing for equitable access to their ecosystem services. For example, by removing air pollutants trees contribute to fewer health impacts, and tree cover expansion could extend these benefits by targeting the most polluted areas and vulnerable populations. To support strategic tree expansion, this research created urban tree cover maps using the 2017 NASA MOD44B satellite 250 m pixel product for 35 megacities, areas with large levels of pollution and vulnerable populations. Estimates of tree cover from photo-interpretation (PI) were used to characterize map error, city-wide, and from low to high tree cover, using 21 bins from 0 to 100% tree cover. Map accuracy was highest when MOD44B percent tree cover was combined with its tree cover standard deviation product, with average difference of 1.8% compared with PI estimates of 19.9% city-wide tree cover. MOD44B estimates of tree cover spatial patterns had strong explanatory value. The maps explained the PI estimates of low to high tree cover at 5% tree cover intervals with an R2 = 0.97. The Getis Ord Gi* statistic determined a non-random spatial distribution of tree cover within the megacities, with significant clustering into hot spots of relatively high tree cover and cold spots of relatively low tree cover. Tree cover hot spots were most often furthest from downtown, at the rural-urban interface or within higher elevation terrain. Tree cover cold spots were most often in areas of concentrated development and along traffic corridors known for high levels of particulate matter and other air pollutants that could be reduced by trees. Given small increases in exposure to particulate matter are associated with significant increases in death rates from viruses, and that climate change and associated heat waves are forecast to exacerbate health risks to air pollution, we need to improve global urban tree cover. These map products can be used to expand tree cover that strategically contributes to pollutant abatement, human well-being, and sustainable cities. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource covid-19, air pollution, social justice, megacities, MOD44B, tree cover inequality Identifier An unambiguous reference to the resource within a given context 10.3389/frsc.2020.00016 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science (General), Social sciences (General)