In this paper, we propose a novel approach to model spatial heterogeneity for epidemic
spreading, which combines the relevance of transport proximity in human movement and the …

Global warming is a serious threat to human survival and health. Facing increasing global
warming, the issue of CO 2 emissions has attracted more attention. China is a major …

Chlorophyll-a is one of the main indicators for water quality (WQ) analysis in environmental
monitoring of aquatic ecosystems. WQ degradation is mostly a result of the increase of the …

Geographically weighted regression (GWR) and geographically and temporally weighted
regression (GTWR) are classic methods for estimating non-stationary relationships …

Geographically weighted regression (GWR) is a classical method of modeling spatially non-
stationary relationships. The geographically neural network weighted regression (GNNWR) …

An appropriate management of the available resources within oceans and coastal regions is
vital to guarantee their sustainable development and preservation, where water quality is a …

Linear regression models are commonly used for estimating ground PM2. 5 concentrations,
but the global spatial autocorrelation and local spatial heterogeneity of PM2. 5 distribution …

In natural forest ecosystems, there is often abundant down dead wood (DDW) due to wind
disasters, which greatly changes the size and structure of forests. Accurately determining the …

Revealing the spatiotemporal variations of nutrients in coastal waters is crucial to the
understanding and evaluation of coastal environment, thereby providing efficient guidance …

Confronted with the spatial heterogeneity of the real estate market, some traditional research
has utilized geographically weighted regression (GWR) to estimate house prices. However …