sesu_gozh {gdverse} | R Documentation |
comparison of size effects of spatial units based on GOZH
Description
comparison of size effects of spatial units based on GOZH
Usage
sesu_gozh(
formula,
datalist,
su,
cores = 1,
strategy = 2L,
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. |
cores |
(optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing. |
strategy |
(optional) Calculation strategies of Q statistics at different scales. Default
is |
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
When strategy
is 1
, use the same process as sesu_opgd()
.If not, all explanatory
variables are used to generate a unique Q statistic corresponding to the data in the
datalist based on rpart_disc()
and gd()
, and then loess_optscale()
is used to
determine the optimal analysis scale.
Value
A list.
sesu
a tibble representing size effects of spatial units
optsu
optimal spatial unit
strategy
the optimal analytical scale selection strategy
increase_rate
the critical increase rate of q value
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.
Luo, P., Song, Y., Huang, X., Ma, H., Liu, J., Yao, Y., & Meng, L. (2022). Identifying determinants of spatio-temporal disparities in soil moisture of the Northern Hemisphere using a geographically optimal zones-based heterogeneity model. ISPRS Journal of Photogrammetry and Remote Sensing: Official Publication of the International Society for Photogrammetry and Remote Sensing (ISPRS), 185, 111–128. https://doi.org/10.1016/j.isprsjprs.2022.01.009
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_gozh(fvc ~ .,
datalist = list(fvc1000,fvc5000),
su = c(1000,5000),
cores = 6)
## End(Not run)