Geographical weighting as a further refinement to regression modelling: An example focused on the NDVI–rainfall relationship

By Giles M. Foody. 2003

355 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5551f59de9c9bf8556d81c0d4e85699590028e6d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. J. Ni
2. Quan Wang
3. John Tenhunen

In Environmental Engineering

1. J. Ni
2. Quan Wang
3. John Tenhunen

In Global and Planetary Change

1. J. Ni
2. Quan Wang
3. John Tenhunen

Citations in the corpus

• Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems (2005, methodology): “…model parameters derived, such as from the ordinary least squares (OLS) method, are assumed to apply globally over the entire region from which measured data have been taken, based on the assumption of spatial stationarity in the relationship between the variables under study (Foody, 2003).”