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.
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..
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, …