Jiangbo Gao

TL;DR: Wang et al. as discussed by the authors used geographically weighted regression (GWR) with a case study in Shenzhen City, Guangdong Province, China, to examine spatially varying and scale-dependent relationships between effective mesh size, an indicator of landscape fragmentation, and related factors.

TL;DR: It can be found that the reduced temperature and solar radiation, caused by the increase in cloud cover and precipitation, may play important roles in the vegetation cover change in the Karst region.

TL;DR: In this article, the authors used geographically weighted regression (GWR) to investigate the spatially nonstationary relationships between NDVI and climatic factors at multiple scales in North China, and showed that all GWR models with appropriate bandwidth represented significant improvements of model performance over the ordinary least squares (OLS) models.

TL;DR: A global meta‐analysis of ANPP and the four variables (610 observations from 78 studies) for drought duration, intensity and their combination finds forest‐ANPP shows high sensitivity to long‐term moderate drought, whereas grass‐AN PP is more responsive to short‐term drought.

TL;DR: In this article, the spatial scale-dependency of the relationship between NDVI and environmental factors was identified by scaling the bandwidth of the GWR model, and the appropriate bandwidth for each variable was determined.