Fine simulation of PM2.5 combined with NPP-VIIRS night light remote sensing and mobile monitoring data.

Human activity plays a crucial role in influencing PM2.5 concentration and can be assessed through nighttime light remote sensing. Therefore, it is important to investigate whether the nighttime light brightness can enhance the accuracy of PM2.5 simulation in different stages. Utilizing PM2.5 mobile monitoring data, this study introduces nighttime lighting brightness as an additional factor in the PM2.5 simulation model across various time periods. It compares the differences in simulation accuracy, explores the impact of nocturnal human activities on PM2.5 concentrations at different periods of the following day, and analyzes the spatial and temporal pollution pattern of PM2.5 in urban functional areas. The results show that (1) the incorporation of nighttime lighting brightness effectively enhances the model's accuracy (R2), with an improvement ranging from 0.04 to 0.12 for different periods ranges. (2) the model's accuracy improves more prominently during 8:00-12:00 on the following day, and less so during 12:00-18:00, as the PM2.5 from human activities during the night experiences a strong aggregation effect in the morning of the next day, with the effect on PM2.5 concentration declining after diffusion until the afternoon. (3) PM2.5 is primarily concentrated in urban functional areas including construction sites, roads, and industrial areas during each period. But in the period of 8:00-12:00, there is a significant level of PM2.5 pollution observed in commercial and residential areas, due to the human activities that occurred the previous night.

Spatiotemporal Evolution of West Africa's Urban Landscape Characteristics Applying Harmonized DMSP-OLS and NPP-VIIRS Nighttime Light (NTL) Data.

Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development. Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite (NPP-VIIRS) Nighttime Light (NTL) data, this paper investigated the characteristics of urban landscape in West Africa. Using the harmonized NTL data, spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018. We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas. In addition, we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa. The accuracy of urban area extraction based on NTL data were R 2 = 0.8314 in 2000, R 2 = 0.8809 in 2006, R 2 = 0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R 2 = 0.8426 in 2018, by using Google Earth images as validation. The results indicated that there was a high rate and acceleration of urban landscapes in West Africa, with rates of 0.016 0, 0.017 3, 0.018 9, and 0.068 6, and accelerations of 0.31, 0.42, 0.54, and 0.90 for the periods of 1998-2003, 2003-2008, 2008-2013, and 2013-2018, respectively. The expansion direction of urban agglomeration in West Africa during 1993-2018 was mainly from the coast to inland. However, cities located in the Sahel Region of Africa and in the middle zone expanded from north to south. Finally, the results showed that the urban landscape of West Africa was mainly in a scattered and disordered 'diffusion' process, whereas only a few cities located in coastal areas experiencing the process of 'coalescence' according to urban growth phase theory. This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.

Interaction and mediation effects of economic growth and innovation performance on carbon emissions: Insights from 282 Chinese cities.

China is under rapid urbanization and consequently facing increasing carbon emissions (CE). Economic growth (EG) and innovation performance (IP), as two critical indicators of urbanization, are considered the driving forces of CE. Although economy and innovation are entangled and can jointly affect CE in reality, the measured effects of economy and innovation on CE are often treated separately in traditional studies. We adopted a three-part research framework including the total, interaction and mediation effect tests to elucidate how EG and IP affected CE in China from 2005 to 2015 based on insights from 282 Chinese cities. The empirical results showed that both economy and innovation contributed to CE, although the contribution has reduced over the 11 years. In particular, the interaction effect between economy and innovation for North China, Northeast China, and Southwest China was -4.201, -8.442, and - 3.897, respectively, in 2015, meaning that these regions adversely affect CE. In addition, we found that the economy helps reduce CE via innovation. When considering the changes of economy and innovation, their mediation effect on CE changes varied in different regions, attributable to the level of economy and innovation as well as the stocks of energy resources. Therefore, future planning for low-carbon transition should regard the economy and innovation together. Based on this principle, we propose five detailed policies. Overall, this study is valuable not only for further understanding the triangle relationship among economy, innovation, and CE, but also for reaching low-carbon goals.

Dense canopies browning overshadowed by global greening dominant in sparse canopies.

Greening, an increase in photosynthetically active plant biomass, has been widely reported as period-related and region-specific. We hypothesized that vegetation trends were highly density-dependent with intensified browning in dense canopies and increased greening in sparse canopies. We exploited this insight by estimating vegetation trends in peak growth from dense to sparse canopies graded from 1 to 20 using the non-parametric Mann-Kendall trend test based on the 500 m 8-day composite MODIS Near Infrared Reflectance of terrestrial vegetation (NIRv) time series datasets in the past two decades (2001-2019) at the global scale. We found that global greening increased by 1.42% per grade with strong fit before grade 15 (R2 = 0.95): net browning (11% browning vs 9% greening) exhibited in high-density canopies (NIRv > 0.39) in contrast to 32% greening in low-density canopies (NIRv ≈ 0.15). While the density-dependent greening was evidenced across different biomes and ecosystems, the steepest gradient (changes per grade) in cropland highlighted the increasingly intensified agricultural activities globally. Greening gradients declined in the dryland, but enhanced in the High-latitude ecosystems driven by warming, especially in the shrubland. Density-dependent vegetation trends were accounted for by the disproportionately impacts from climate changes and the unequal contributions of Land Cover Changes (LCC) among dense and sparse canopies. Vegetation trends and greening gradients could be extensively facilitated by Wetting or Decreasing solar Radiation (WDR), especially in sparse grassland and shrubland. Browning was dominant in dense canopies, which was further aggravated by Drying and Increasing solar Radiation (DIR), especially woody vegetation. This study implied the widespread degradation or mortality of highly productive vegetation hidden among global greening dominant in open ecosystems, which might be further exacerbated by the predicted increasing drought under global warming.

Increasing fragmentation and squeezing of coastal wetlands: Status, drivers, and sustainable protection from the perspective of remote sensing.

Coastal wetlands are of great ecological and economic value but face significant degradation and losses because of human activities. Nevertheless, the changes in spatiotemporal landscape patterns, which have occurred as a result of coastal wetland losses, have not been well documented under the rapid urbanization in coastal zones. In this study, an algorithm based on periodic tidal inundations and full time-series indices was developed to map the detailed status and trends in the coastal wetlands in Fujian Province from 1994 to 2018 by using more than archived 5000 Landsat images. The results showed that in 2018, there were 1136.56 km2 of coastal wetlands along the coast of Fujian with an overall accuracy of 95.63%, which were mainly distributed in estuaries and bays. These coastal wetlands consisted of tidal flats, low marshes, and high marshes with proportions of 84.91%, 13.05%, and 2.04%, respectively. An unprecedented loss of coastal wetlands has occurred in Fujian Province, with an annual rate of 15.44 km2/a from 1994 to 2018. Many coastal wetlands were reclaimed, dredged, and converted into inland areas for aquaculture ponds, ports, and built-up areas in different urbanization periods, which has led to a great loss of coastal spaces with an area of 476.87 km2. The interplay between the loss of coastal wetlands and seaward urbanization will lead to severe fragmentation and squeezing effects in the coastal zone and will weaken the coastal protection from marine disasters that is provided by coastal wetlands. Therefore, we conceived two conceptional frameworks for sustainable coastal protection based on the current situations of the coastal communities to provide a trade-off between economic development and the protection of coastal developing countries in the world.

Exploring the relationship between 2D/3D landscape pattern and land surface temperature based on explainable eXtreme Gradient Boosting tree: A case study of Shanghai, China.

With more record-breaking skyscrapers built in big cities around the world, horizontal urban sprawl no longer dominates the research of urbanization rather than the vertical growth of cities. In such a context, the urban heat island problem cannot be understood by solely studying the impact of the horizontal urban expansion because the 3D structure of the urban landscape could severely alter the natural heat flux transport over the land surface and thus lead to bigger heat island problems. In addition to our current knowledge of impact of 2D landscape changes on urban thermal dynamics, it is crucial to understand the effects of 3D landscape pattern on the thermal environment, in order to maintain a sustainable and eco-friendly urban development. This study investigated the 2D/3D landscape pattern metrics and their association with the land surface temperature (LST) changes in a case study area of Shanghai City using the extreme gradient boosting (XGBoost) regression model and Sharpley Additive exPlanations (SHAP) interpretation method based on datasets of land cover and digital surface model (DSM). Major findings include, 1) 3D landscape pattern metrics could better describe the undulation and heterogeneity of urban surface and were essential when explaining the variation of LST compared with conventional 2D landscape pattern metrics, 2) Low-rise and high-rise buildings tend to alleviate LST while buildings with medium height heating the surroundings; 3) the cooling effect of vegetation was significantly strong; 4) different urban functional types impact the surface temperature in the way determined by their 3D urban landscape pattern. These findings may help urban planners and landscape designers achieve the goal of minimizing urban heat island using computer models of 3D urban structure.

Effects of urban forms on CO2 emissions in China from a multi-perspective analysis.

Effectively evaluating the effects of urban forms on CO2 emissions has become a hot topic in socioeconomic sustainable development; however, few studies have been able to explore the urban form-CO2 emission relationships from a multi-perspective view. Here, we attempted to analyze the relationships between urban forms and CO2 emissions in 264 Chinese cities, with explicit consideration of the government policies, urban area size, population size, and economic structure. First, urban forms were calculated using the urban land derived from multiple-source remote sensing data. Second, we collected and processed CO2 emissions and three control variables. Finally, a correlation analysis was implemented to explore whether and to what extent the spatial patterns of urban forms were associated with CO2 emissions. The results show that urban form irregularity had a more significant impact on CO2 emissions in low-carbon pilot cities than in non-pilot cities. The impact of the complexity of urban forms on CO2 emissions was relatively significant in the small- and large-sized cities than in the medium-sized cities. Moreover, urban form complexity had a significant correlation with CO2 emissions in all of the cities, the level of which basically increased with the population size. This study provides scientific bases for use in policy-making to prepare effective policies for developing a low-carbon economy with consideration of the associations between urban forms and CO2 emissions in different scenarios.

Nighttime Light Images Reveal Spatial-Temporal Dynamics of Global Anthropogenic Resources Accumulation above Ground.

Urbanization and industrialization represent largely a process of transforming materials from biosphere and lithosphere to anthroposphere. Understanding the patterns of such anthropogenic material stock accumulation is thus a fundamental prerequisite to assess and sustain how humans alter the biophysical movements of resources around Earth. Previous studies on these anthropogenic stocks, however, are often limited to the global and national scales, due to data gaps at higher spatial resolutions. Here, based on a new set of national materials stock data and nighttime light images, we developed a regression model to map the global anthropogenic stocks of three fundamental construction materials (steel, concrete, and aluminum) at a 1 × 1 km level from 1992 to 2008. We revealed an unevenly distributed pattern, with over 40% found in three belts: from England across the Channel to Western Europe; from eastern coast China to South Korea and Japan; and from Great Lakes along eastern coast of United States to Florida. The spatial-temporal dynamics of global anthropogenic stocks at smaller spatial scales reflect a combined effect of physical geography, architectural and construction specifications, and socioeconomic development. Our results provide useful data that can potentially support policy-makers and industry on resource efficiency, waste management, urban mining, spatial planning, and environmental sustainability at regional and urban scales.