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.
Cities are typical sources of carbon and a focus of climate-change mitigation. Although there is great potential for reducing emissions in cities, constructing low-carbonemission cities under the carbon-emission reduction target of the 2016 Paris …
We present a low-cost method to create high-precision, spatially explicit reference maps of large-scale forest aboveground biomass (AGB) to provide a scientific basis for quantitative assessment of forest management decisions involving, for example, …