Category Archives: Geographic Information Science

Generalized Least Squares regression: regression models with spatial autocorrelation

This is the R code for performing Generalized Least Squares regression without (mod0) and with spatial autocorrelation (mod1), using the gls function in the library nlme: # first load the nlme library library(nlme) # read data (forest recovery after forest fire) # 30000 cells from satellite imagery datos

Towards the implementation of a vector data type in GIS

In contrast to scalars, which only have magnitude, vectors are geometrical objects defined by a magnitude and a direction. They play an important role in physics, since they can represent the forces acting on a body, velocities and accelerations, etc. In Geographic Information Science (GIS) analysis we are used to work with scalar fields, h(x,y), […]