The lockdown response to coronavirus disease 2019 (COVID-19) has caused an unprecedented reduction in global economic and transport activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations, using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find declines in the population-weighted concentration of ground-level nitrogen dioxide (NO ₂ : 60% with 95% CI 48 to 72%), and fine particulate matter (PM _2.5 : 31%; 95% CI: 17 to 45%), with marginal increases in ozone (O ₃ : 4%; 95% CI: −2 to 10%) in 34 countries during lockdown dates up until 15 May. Except for ozone, satellite measurements of the troposphere indicate much smaller reductions, highlighting the spatial variability of pollutant anomalies attributable to complex NO _x chemistry and long-distance transport of fine particulate matter with a diameter less than 2.5 µm (PM _2.5 ). By leveraging Google and Apple mobility data, we find empirical evidence for a link between global vehicle transportation declines and the reduction of ambient NO ₂ exposure. While the state of global lockdown is not sustainable, these findings allude to the potential for mitigating public health risk by reducing “business as usual” air pollutant emissions from economic activities. Explore trends here: https://nina.earthengine.app/view/lockdown-pollution .

The global response to the COVID-19 pandemic has brought with it significant changes to human mobility patterns and working environments. We aimed to explore how social distancing measures affected recreational use of urban green space during the partial lockdown in Oslo, Norway. Mobile tracking data from thousands of recreationists were used to analyze high resolution spatio-temporal changes in activity. We estimated that outdoor recreational activity increased by 291% during lockdown relative to a 3 yr average for the same days. This increase was significantly greater than expected after adjusting for the prevailing weather and time of year and equates to approx. 86 000 extra activities per day over the municipality (population of 690 000). Both pedestrians (walking, running, hiking) and cyclists appeared to intensify activity on trails with higher greenviews and tree canopy cover, but with differences in response modulated by trail accessibility and social distancing preferences. The magnitude of increase was positively associated with trail remoteness, suggesting that green spaces facilitated social distancing and indirectly mitigated the spread of COVID-19. Finally, pedestrian activity increased in city parks, peri-urban forest, as well as protected areas, highlighting the importance of access to green open spaces that are interwoven within the built-up matrix. These findings shed new light on the value of urban nature as resilience infrastructure during a time of crisis. The current pandemic also reveals some important dilemmas we might face regarding green justice on the path towards urban planning for future sustainable cities.

The European Space Agency’s Sentinel satellites have laid the foundation for global land use land cover (LULC) mapping with unprecedented detail at 10 m resolution. We present a cross-comparison and accuracy assessment of Google’s Dynamic World (DW), ESA’s World Cover (WC) and Esri’s Land Cover (Esri) products for the first time in order to inform the adoption and application of these maps going forward. For the year 2020, the three global LULC maps show strong spatial correspondence (i.e., near-equal area estimates) for water, built area, trees and crop LULC classes. However, relative to one another, WC is biased towards over-estimating grass cover, Esri towards shrub and scrub cover and DW towards snow and ice. Using global ground truth data with a minimum mapping unit of 250 m², we found that Esri had the highest overall accuracy (75%) compared to DW (72%) and WC (65%). Across all global maps, water was the most accurately mapped class (92%), followed by built area (83%), tree cover (81%) and crops (78%), particularly in biomes characterized by temperate and boreal forests. The classes with the lowest accuracies, particularly in the tundra biome, included shrub and scrub (47%), grass (34%), bare ground (57%) and flooded vegetation (53%). When using European ground truth data from LUCAS (Land Use/Cover Area Frame Survey) with a minimum mapping unit of <100 m², we found that WC had the highest accuracy (71%) compared to DW (66%) and Esri (63%), highlighting the ability of WC to resolve landscape elements with more detail compared to DW and Esri. Although not analyzed in our study, we discuss the relative advantages of DW due to its frequent and near real-time data delivery of both categorical predictions and class probability scores. We recommend that the use of global LULC products should involve critical evaluation of their suitability with respect to the application purpose, such as aggregate changes in ecosystem accounting versus site-specific change detection in monitoring, considering trade-offs between thematic resolution, global versus. local accuracy, class-specific biases and whether change analysis is necessary. We also emphasize the importance of not estimating areas from pixel-counting alone but adopting best practices in design-based inference and area estimation that quantify uncertainty for a given study area.

While global deforestation induced by human land use has been quantified, the drivers and extent of simultaneous woody plant encroachment (WPE) into open areas are only regionally known. WPE has important consequences for ecosystem functioning, global carbon balances and human economies. Here we report, using high-resolution satellite imagery, that woody vegetation cover over sub-Saharan Africa increased by 8% over the past three decades and that a diversity of drivers, other than CO₂, were able to explain 78% of the spatial variation in this trend. A decline in burned area along with warmer, wetter climates drove WPE, although this has been mitigated in areas with high population growth rates, and high and low extremes of herbivory, specifically browsers. These results confirm global greening trends, thereby bringing into question widely held theories about declining terrestrial carbon balances and desert expansion. Importantly, while global drivers such as climate and CO₂ may enhance the risk of WPE, managing fire and herbivory at the local scale provides tools to mitigate continental WPE.

Satellites overestimate urban heat islands.