grids

Spatial datasets of explanatory variables at a 500-m resolution.

Variables

Most of the current methods explore spatial association using
observations at sample locations, which are defined as the first
dimension of spatial association (FDA). The proposed concept of
the second dimension of spatial association (SDA),
as described in Yongze Song (2022)
<doi:10.1016/j.jag.2022.102834>, aims to extract
in-depth information about the geographical environment from
locations outside sample locations for exploring spatial
association.

Yongze Song 

SecDim

The Second Dimension of Spatial Association

grids function

<code>grids</code>: A data frame of explanatory variables with 68757 rows and 11 columns.

Format

Yongze Song <a href="/link/yongze.song%40curtin.edu.au?package=SecDim&version=3.2" data-mini-rdoc="SecDim::yongze.song@curtin.edu.au">yongze.song@curtin.edu.au</a>

Author

Spatial grid dataset. — grids

Yongze Song <a href='mailto:yongze.song@curtin.edu.au'>yongze.song@curtin.edu.au</a>

grids: Spatial grid dataset.

Description

Usage

Arguments

Format

Author