sesu_opgd {gdverse} | R Documentation |
comparison of size effects of spatial units based on OPGD
Description
Function for comparison of size effects of spatial units in spatial heterogeneity analysis based on optimal parameters geographical detector(OPGD) model.
Usage
sesu_opgd(
formula,
datalist,
su,
discvar,
discnum = NULL,
discmethod = NULL,
cores = 1,
increase_rate = 0.05,
alpha = 0.95,
...
)
Arguments
formula |
A formula of comparison of size effects of spatial units. |
datalist |
A list of |
su |
A vector of sizes of spatial units. |
discvar |
Name of continuous variable columns that need to be discretized.Noted that
when |
discnum |
(optional) A vector of number of classes for discretization. Default is |
discmethod |
(optional) A vector of methods for discretization,default is used
|
cores |
(optional) A positive integer(default is 1). If cores > 1, a 'parallel' package cluster with that many cores is created and used. You can also supply a cluster object. |
increase_rate |
(optional) The critical increase rate of the number of discretization.
Default is |
alpha |
(optional) Specifies the size of confidence level. Default is |
... |
(optional) Other arguments passed to |
Details
Firstly, the OPGD
model is executed for each data in the datalist (all significant
Q statistic of each data are averaged to represent the spatial connection strength under
this spatial unit), and then the loess_optscale
function is used to select the optimal
spatial analysis scale.
Value
A list with SESU OPGD results
sesu
a tibble representing size effects of spatial units
optsu
optimal spatial unit
Author(s)
Wenbo Lv lyu.geosocial@gmail.com
References
Song, Y., Wang, J., Ge, Y. & Xu, C. (2020) An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: Cases with different types of spatial data, GIScience & Remote Sensing, 57(5), 593-610. doi: 10.1080/15481603.2020.1760434.
Examples
## Not run:
## The following code takes a long time to run:
library(tidyverse)
fvcpath = "https://github.com/SpatLyu/rdevdata/raw/main/FVC.tif"
fvc = terra::rast(paste0("/vsicurl/",fvcpath))
fvc1000 = fvc %>%
terra::as.data.frame(na.rm = T) %>%
as_tibble()
fvc5000 = fvc %>%
terra::aggregate(fact = 5) %>%
terra::as.data.frame(na.rm = T) %>%
as_tibble()
sesu_opgd(fvc ~ .,
datalist = list(fvc1000,fvc5000),
su = c(1000,5000),
discvar = names(select(fvc5000,-c(fvc,lulc))),
cores = 6)
## End(Not run)