Spatial Statistics

Improving Plot-Level Model of Forest Biomass: A Combined Approach Using Machine Learning with Spatial Statistics

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 spatial resolution mapping of steel resources accumulated above ground in mainland China: Past trends and future prospects

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 …

The direct and interactive impacts of hydrological factors on bacillary dysentery across different geographical regions in central China

Previous studies found non-linear mutual interactions among hydrometeorological factors on diarrheal disease. However, the complex interactions of the hydrometeorological, topographical and human activity factors need to be further explored. This …

The Evaluation of Health Effect of Short-term Exposure to PM2.5 during Spring Festival: A Case Study of 25 Cities in the Yangtze River Delta(Chinese)

To introduce our study on the health risk of short-term PM2.5 exposure during the Spring Festival, using Tencent location-based service data and machine learning mapping.

Investigating the Uncertainties Propagation Analysis of CO₂ Emissions Gridded Maps at the Urban Scale: A Case Study of Jinjiang City, China

Cities play an essential role in low-carbon development. However, Estimating CO₂ 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 CO₂ emissions. We proposed an analytic workflow to analyze the propagated uncertainties caused by the gridded model and the input for gridded CO₂ emission maps.

The Evaluation of Health Effect of Short-term Exposure to PM2.5 during Spring Festival: A Case Study of 25 Cities in the Yangtze River Delta(Chinese)

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.

What is geography? From coronavirus disease 2019 to Bei Dou Systems

To introduce what geography is and the three laws of geography to high school students.

A spatial database of CO₂ emissions, urban form fragmentation and city-scale effect related impact factors for the low carbon urban system in Jinjiang city, China

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 CO₂ emissions gridded maps, urban form fragmentation evaluation maps, and …

More fragmentized urban form more CO₂ emissions? A comprehensive relationship from the combination analysis across different scales

The “Scale effect” has always been the hot topic in landscape ecology research. Although, there are many studies on the driving force of urban environmental problems by using landscape metrics. Most studies are carried out in regional, continental and global scales. However, in this study, we explored the relationship between the urban form fragmentation and CO₂ emissions in the city scale from the perspective of dual resolution sizes and summarized the research conclusions that can be used in urban internal management based on the analysis results of small towns.

Creating a Carbon Source and Sink Map by Coupling an Ecological Process Model with an Emission Inventory to Study a Carbon Balance

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-carbon emission cities under the carbon-emission reduction target of the 2016 Paris …