Type: | Package |
Title: | Population Downscaling Using Areal Interpolation |
Version: | 0.2.1 |
Author: | Marios Batsaris |
Maintainer: | Marios Batsaris <m.batsaris@aegean.gr> |
Description: | Given a set of source zone polygons such as census tracts or city blocks alongside with population counts and a target zone of incogruent yet superimposed polygon features (such as individual buildings) populR transforms population counts from the former to the latter using Areal Interpolation methods. |
License: | GPL-3 |
URL: | https://github.com/mbatsaris/populR/ |
BugReports: | https://github.com/mbatsaris/populR/issues/ |
Encoding: | UTF-8 |
LazyData: | true |
Imports: | sf, rlang, Metrics, usethis, osmdata, dplyr, units |
Depends: | R (≥ 3.3.0) |
RoxygenNote: | 7.2.3 |
Suggests: | rmarkdown, microbenchmark, areal, knitr, testthat (≥ 3.0.0) |
Config/testthat/edition: | 3 |
VignetteBuilder: | knitr |
NeedsCompilation: | no |
Packaged: | 2023-03-13 11:54:40 UTC; mb |
Repository: | CRAN |
Date/Publication: | 2023-03-13 13:10:02 UTC |
Ancillary Information from OSM Features
Description
Ancillary Information from OSM Features
Usage
pp_ancillary(x, volume = NULL, key)
Arguments
x |
an object of class |
volume |
x volume information (height or number of floors) useful for float ancillary information |
key |
OSM feature keys or values available in x |
Value
an object of class sf
including ancillary information either for
night or day estimates
Examples
## Not run:
data('trg')
# Download OSM amenities
dt <- pp_vgi(trg, key = amenity)
# create binary ancillary information
dt <- pp_ancillary(dt, 'amenity')
# create ancillary information both binary and float
dt <- pp_ancillary(dt, floors, 'amenity')
## End(Not run)
Comparison to Other Data
Description
Comparison to Other Data
Usage
pp_compare(x, estimated, actual, title)
Arguments
x |
An object of class |
estimated |
Population estimates using pp_estimate function |
actual |
Actual population values |
title |
Scatterplot title |
Value
A list including rmse, mae, linear model details and correlation coefficient
Examples
# read lib data
data('src')
data('trg')
# areal weighting interpolation - awi
awi <- pp_estimate(trg, src, sid = sid, spop = pop,
method = awi)
# volume weighting interpolation - vwi
vwi <- pp_estimate(trg, src, sid = sid, spop = pop,
method = vwi, volume = floors)
# awi - rmse
pp_compare(awi, estimated = pp_est, actual = rf,
title ='awi')
# vwi - rmse
pp_compare(vwi, estimated = pp_est, actual = rf,
title ='vwi')
Areal Interpolation of Population Data
Description
Areal Interpolation of Population Data
Usage
pp_estimate(
target,
source,
sid,
spop,
volume = NULL,
ancillary = NULL,
point = FALSE,
method
)
Arguments
target |
An object of class |
source |
An object of class |
sid |
Source identification number |
spop |
Source population values to be interpolated |
volume |
Target feature volume information (height or number of floors).
Required when |
ancillary |
ancillary information |
point |
Whether to return point geometries (FALSE by default) |
method |
Two methods provided: |
Value
An object of class sf
including estimated population
counts for target features using either awi
or vwi
methods. The estimated population counts are stored in a new column called
pp_est.
Examples
# read lib data
data('src')
data('trg')
# areal weighted interpolation - awi
pp_estimate(trg, src, sid = sid, spop = pop,
method = awi)
# areal weighted interpolation - awi using point geometries
pp_estimate(trg, src, sid = sid, spop = pop,
method = awi, point = TRUE)
# volume weighted interpolation - vwi
pp_estimate(trg, src, sid = sid, spop = pop,
method = vwi, volume = floors)
# volume weighted interpolation - vwi using point geometries
pp_estimate(trg, src, sid = sid, spop = pop,
method = vwi, volume = floors, point = TRUE)
Rounding Function
Description
Rounding Function
Usage
pp_round(x, tpop, spop, sid)
Arguments
x |
An object of class |
tpop |
Target population estimates obtained by the pp_estimate function |
spop |
Initial source population values (included after the implementation of the pp_estimate function) |
sid |
Source identification number |
Value
An object of class sf
including rounded population counts stored
in a new column called pp_int
Examples
# read lib data
data('src')
data('trg')
# areal weighted interpolation - awi
awi <- pp_estimate(trg, src, sid = sid, spop = pop,
method = awi)
# volume weighted interpolation - vwi
vwi <- pp_estimate(trg, src, sid = sid, spop = pop,
method = vwi, volume = floors)
# awi - round
pp_round(awi, tpop = pp_est, spop = pop, sid = sid)
# vwi - round
pp_round(vwi, tpop = pp_est, spop = pop, sid = sid)
Download and Count OSM Features Over Target
Description
Download and Count OSM Features Over Target
Usage
pp_vgi(x, key)
Arguments
x |
an object of class |
key |
osm feature key (quoted) see available_features |
Value
an object of class sf
including OSM features
Examples
## Not run:
data('trg')
# example using just a key
pp_vgi(trg, key = 'amenity')
# example using two keys
pp_vgi(trg, key = c('amenity', 'shop')
## End(Not run)
Source (src)
Description
object of sf
class representing the blocks of a fictional area
Usage
src
Format
object of sf
class with 9 rows and 3 columns:
sid
Source identification number
pop
Source population values to be interpolated
geometry
Geometry
Source
Target (trg)
Description
An object of sf
class representing the buildings of a subset
area of the city of Mytilini, Greece. The data set contains 179 building
units along with the number of floors and residential use in binary format
where 0 for non-residential floors and 1 for residential floors.
Usage
trg
Format
object of sf
class with 179 rows and 12 columns:
tid
Target identification number
floors
Number of floors
rf
Reference population estimates
geometry
Geometry