Although two years have passed since the coronavirus disease 2019 (COVID-19) outbreak, various variants are still rampant across the globe. The Omicron variant, in particular, is rapidly gained dominance through its ability to spread. In this study, …
Rapid urbanization generates substantial demand, use, and demolition waste of construction materials. However, the existing top-down or bottom-up frameworks combining material flow analysis (MFA) and geographic information system (GIS) tend to …
Estimating the aboveground biomass (AGB) at the plot level plays a major role in connecting accurate single-tree AGB measurements to relatively difficult regional AGB estimates. The goal of this study is to determine whether combining machine learning with spatial statistics reduces the uncertainty of plot-level AGB estimates.
High-resolution mapping of steel resources accumulated above ground (referred to as steel stocks) is critical for exploring urban mining and circular economy opportunities. Prior studies have attempted to approximate steel stocks using nighttime …
Using Tencent location based service data and machine learning mapping produced by multi-sources geospatial data to investigate the health risk of short-term exposure to PM2.5..
Cities play an essential role in low-carbon development. However, Estimating CO$_2$ emissions at the urban scale, including both un-gridded (i.e., administrative unit maps) and gridded maps, cannot avoid the propagation of uncertainties from input to result, which highlights the importance of being aware of uncertainty estimation, especially in gridded maps due to its implications for the precision mitigation of CO$_2$ emissions. We proposed an analytic workflow to analyze the propagated uncertainties caused by the gridded model and the input for gridded CO$_2$ emission maps.
Using Tencent location based service data and machine learning mapping produced by multi-sources geospatial data to investigate the health risk of short-term exposure to PM2.5.
This paper presented the spatial database collected in 2013 for mitigating the urban carbon emissions of Jinjiang city, China. The database included the high-resolution $CO_2$ emissions gridded maps, urban form fragmentation evaluation maps, and …