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Package {lczexplore}

Title: Imports, Visualizes, Compares and Explores Maps of Local Climate Zones
Version: 0.1.1
Description: Easily import and visualize local climate zone maps with standard encoding. Compare two or more maps, and group some LCZ types according to user defined grouping vectors. Explore their differences through circular visualization and indicators. For more Details see Gousseff et al (2023) "lczexplore: an R package to explore Local Climate Zone classifications" <doi:10.21105/joss.05445>.
License: LGPL (≥ 3)
Encoding: UTF-8
Imports: circlize, collapse, data.table, dplyr, forcats, ggnewscale, ggplot2, grDevices, ggspatial, ggsankeyfier, jsonlite, magrittr, methods, patchwork, randomcoloR, RColorBrewer, sf, shades, terra, tidyr, units
Suggests: knitr, markdown, rmarkdown, tinytest, png
VignetteBuilder: knitr
LazyData: true
Depends: R (≥ 4.0.0)
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-10-19 08:44:34 UTC; gousseff
Author: Matthieu Gousseff ORCID iD [aut, cre, cph] (affiliation: Centre National de la Recherche Scientifique, Lab-STICC)
Maintainer: Matthieu Gousseff <matthieu.gousseff@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-10-28 12:30:02 UTC

Compute Cohen's Kappa Coefficient

Description

Compute Cohen's Kappa Coefficient

Usage

CohenKappa(
  x,
  y = NULL,
  weights = c("Unweighted", "Equal-Spacing", "Fleiss-Cohen"),
  conf.level = NA,
  ...
)

Arguments

x

can either be a numeric vector or a confusion matrix. In the latter case x must be a square matrix, in lczexplore, will take the matrix of agreement weighted by area for all intersected geometries

y

not used here, but allows to compute cross table of x and y as an entry

weights

either one out of "Unweighted" (default), "Equal-Spacing", "Fleiss-Cohen", which will calculate the weights accordingly, or a user-specified matrix having the same dimensions as x containing the weights for each cell.

conf.level

confidence level of the interval. If set to NA (which is the default) no confidence intervals will be calculated.

...

further arguments are passed to the function table, allowing i.e. to set useNA. This refers only to the vector interface.

Details

Taken from descTools who based it on Kappa from library(vcd) author: David Meyer see also: kappa in library(psych) Integrated here to reduce dependecy to descTools as it is the only function from DescTools we used Computes the agreement rates Cohen's kappa and weighted kappa and their confidence intervals.

Cohen's kappa is the diagonal sum of the (possibly weighted) relative frequencies, corrected for expected values and standardized by its maximum value.
The equal-spacing weights (see Cicchetti and Allison 1971) are defined by

1 - \frac{|i - j|}{r - 1}

r being the number of columns/rows, and the Fleiss-Cohen weights by

1 - \frac{(i - j)^2}{(r - 1)^2}

The latter attaches greater importance to closer disagreements

Value

the value of this pseudoKappa

Author(s)

David Meyer david.meyer@r-project.org, some changes and tweaks Andri Signorell andri@signorell.net and integrated for areas by Matthieu Gousseff

References

Cohen, J. (1960) A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46. Everitt, B.S. (1968), Moments of statistics kappa and weighted kappa. The British Journal of Mathematical and Statistical Psychology, 21, 97-103. Fleiss, J.L., Cohen, J., and Everitt, B.S. (1969), Large sample standard errors of kappa and weighted kappa. Psychological Bulletin, 72, 332-327. Cicchetti, D.V., Allison, T. (1971) A New Procedure for Assessing Reliability of Scoring EEG Sleep Recordings American Journal of EEG Technology, 11, 101-109.

Examples

# from Bortz et. al (1990) Verteilungsfreie Methoden in der Biostatistik, Springer, pp. 459
m <- matrix(c(53,  5, 2,
             11, 14, 5,
             1,  6, 3), nrow=3, byrow=TRUE,
           dimnames = list(rater1 = c("V","N","P"), rater2 = c("V","N","P")) )
# confusion matrix interface
CohenKappa(m, weight="Unweighted")

Computes the area of each level of a LCZ

Description

Computes the area of each level of a LCZ

Usage

LCZareas(sf, column, LCZlevels)

Arguments

sf

is the sf dataset containing the LCZ

column

allows to specify in which column are the LCZ

LCZlevels

is the vector of expected levels in column

Value

The percentage of the total area covered by each LCZ

Examples

#LCZareas is not to be used directly by user.

To make LCZ types appear in the proper order, it can be useful ton convert them into strings with added zeros

Description

To make LCZ types appear in the proper order, it can be useful ton convert them into strings with added zeros

Usage

LCZlevelToOrderedString(LCZlevels)

Arguments

LCZlevels

a vector containing LCZlevels from 1 to 10 and 101 to 107

Value

the input with leading zeros for standard LCZ types, in order to respect alphabetical order in graphs

adds missing Reference Spatial Units (geometries) from the difference with a reference zone file, and possibly add a value to the lcz column according to a reference workflow reference spatial units nor represented by their own geometries adding a column for location and workflow names

Description

adds missing Reference Spatial Units (geometries) from the difference with a reference zone file, and possibly add a value to the lcz column according to a reference workflow reference spatial units nor represented by their own geometries adding a column for location and workflow names

Usage

addMissingRSUs(
  sfList,
  missingGeomsWf = "osm",
  zoneSf,
  refWf = "bdt",
  refLCZ = "107",
  residualLCZvalue = "105",
  column = "lcz_primary"
)

Arguments

sfList

the list of LCZ sf objects

missingGeomsWf

is the name of the column where some geometries are missing

zoneSf

is an sf file containing one geometry defining the zone where some geometries must be added

refWf

in case one wants to give the added geometries the value of a workflow of reference,

refLCZ

the LCZ type to report from the reference workflow to the missing geometries

residualLCZvalue

the LCZ type to add when the reference workflow has a different value than refLCZ for the added geometries

column

is the name of the LCZ column (to be explained)

Value

returns graphics of comparison and an object called matConfOut which contains : matConfLong, a confusion matrix in a longer form, matConfPlot is a ggplot2 object showing the confusion matrix. percAgg is the general agreement between the two sets of LCZ, expressed as a percentage of the total area of the study zone pseudoK is a heuristic estimate of a Cohen's kappa coefficient of agreement between classifications If saveG is not an empty string, graphics are saved under "saveG.png"

Examples

sfList<-importMultipleLCZvect(dirPath = paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
 workflowNames = c("osm","bdt","wudapt"), location = "Arville"  )
zoneSf <- sf::read_sf(
  paste0(
   system.file("extdata", package = "lczexplore"),
   "/multipleWfs/Arville/zone.fgb")
)
sfList<-addMissingRSUs(
sfList, zoneSf = zoneSf, refWf = NULL,
 refLCZ = "Unclassified", residualLCZvalue = "Unclassified")

For an sf object containing LCZ types, aggregates touching geometries with same value of LCZ

Description

For an sf object containing LCZ types, aggregates touching geometries with same value of LCZ

Usage

aggregateRSUsByLCZ(
  sf,
  aggregateBufferSize = 0,
  column,
  wfColumn,
  locationColumn = "location"
)

Arguments

sf

contains the geometry and LCZ levels

aggregateBufferSize

is the size of a buffer you can add to the geometries before agregation. Useful when you suspect numeric precision to create false disjunction of geometries.

column

the name of the column containing LCZ types

wfColumn

is the column where the workflow used to produce LCZ classif is precised.

locationColumn

is the name of the column where the location is stored

Value

an sf object containing the agregated geometries, their LCZ types and the wf and location columns if present in the initial sf

Examples

dirPath<-paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs")
allLocAllWfs<-importConcatMultipleLocsLCZvect(
 dirPath = dirPath, locations = c("Redon", "Arville"),
workflowNames = c("osm","bdt","wudapt"),
 missingGeomsWf= "osm",
 refWf = NULL,
 refLCZ = "Unclassified",
 residualLCZvalue = "Unclassified",
 column = "lcz_primary"
)
ASUallLocAllWfs <- aggregateRSUsByLCZ(
allLocAllWfs,
column = "lcz_primary", wfColumn = "wf", locationColumn = "location", aggregateBufferSize = 0.5)

Checks if a string or a vector of strings define colors in R

Description

Checks if a string or a vector of strings define colors in R

Usage

areColors(x)

Arguments

x

is the input string

Value

a vector of booleans indicting if the elements of x define a color in R (TRUE) or don't (FALSE)

Examples

areColors(c(NA, "black", "blackk", "1", "#00", "#000000"))

in a given directory, if several LCZ files are present, plots the repartition of LCZ regarding of their source (workflow) NOTE: to represent the map of LCZ for a given file, use showLCZ function instead

Description

in a given directory, if several LCZ files are present, plots the repartition of LCZ regarding of their source (workflow) NOTE: to represent the map of LCZ for a given file, use showLCZ function instead

Usage

barplotLCZaLocation(
  dirPath,
  location,
  workflowNames = c("osm", "bdt", "wudapt"),
  refWf = NULL,
  refLCZ = NA,
  residualLCZvalue = NA,
  missingGeom = "osm",
  plotNow = FALSE,
  plotSave = "/tmp"
)

Arguments

dirPath

is the path where the datasets are stored

location

is the name of the locations for the plot is produced

workflowNames

is a vector of prefixes. The LCZ files must be named workflow_rsu.fgb where workflow is on of the values in workflowNames vector

refWf

is a reference workflow name, passed to the function addMissingRSUs when needed

refLCZ

is a reference LCZtype, passed to the function addMissingRSUs when needed

residualLCZvalue

a LCZ default type, passed to the function addMissingRSUs when needed

missingGeom

allows to indicate which workflow is supposed to have missing geometries (not used most of the time)

plotNow

If TRUE, the boxplot of the repartition will be printed

plotSave

If TRUE, the plot will be saved in the directory pointed by dirPath

Value

A barplot of LCZ area percentage by LCZ type and workflow

Examples

barplotLCZaLocation(
dirPath = paste0(system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
refWf = NULL, refLCZ = NA, residualLCZvalue = "Unclassified",
location = "Arville", plotSave = FALSE, plotNow = TRUE)

plots the repartition of LCZ types regarding of their source (map/workflow) from an sf object containing all spatial units and LCZ value, typically the output of createIntersect

Description

plots the repartition of LCZ types regarding of their source (map/workflow) from an sf object containing all spatial units and LCZ value, typically the output of createIntersect

Usage

barplotLCZfromIntersect(
  sfInt,
  workflowNames = NULL,
  columns = NULL,
  stat = "perc",
  plotNow = TRUE
)

Arguments

sfInt

is the file containing the spatial units and LCZ type per workflow

workflowNames

is a vector of prefixes. The LCZ files must be named workflow_rsu.fgb where workflow is on of the values in workflowNames vector

columns

is the vector of names of the columns containing the LCZ types. If not specified, the function will try to use the workflowNames instead

stat

can take the value "perc" to plot percentage of area for each LCZ type or "sum" for total area for each LCZ type

plotNow

If TRUE, the boxplot of the repartition will be printed

Value

A barplot of LCZ area percentage by LCZ type and workflow

Examples


# Two Locations
sfList2<-importMultipleLocsLCZvect(
 dirPath = paste0(
     system.file("extdata", package = "lczexplore"),
     "/multipleWfs"),
 workflowNames = c("osm","bdt","wudapt"))

twoLocsIntersect <- createIntersect(
 sfList = sfList2, columns = rep("lcz_primary", 3),
 workflowNames = c("osm","bdt","wudapt"))
example<-barplotLCZfromIntersect(sfInt = twoLocsIntersect,
                              columns = c("osm", "bdt", "wudapt"),
                            workflowNames = c("osm", "bdt", "wudapt"))

Checks if the columns entered by the user match the columns in the data source

Description

Checks if the columns entered by the user match the columns in the data source

Usage

checkColnameCase(userColNames, dataColNames)

Arguments

userColNames

a vector of column names entered by the user

dataColNames

a vector names presents in a dataset

Value

returns an error if on or several colum names in userColNames are not present in dataColNames, except if they are present but in lower case, then the correspondent lower case name is substituted

Examples

userColNames<-c("ID", "LCZ_PRIMARY")
dataColNames<-c("ID", "LCZ_PRIMARY")
checkColnameCase(userColNames, dataColNames)
dataColNames<-c("ID", "lcz_primary")

Simply adds a slash at then end of a directory path if there is none

Description

Simply adds a slash at then end of a directory path if there is none

Usage

checkDirSlash(dirPath)

Arguments

dirPath

is a directory pas as a string

Value

the same string if it ended with a slash, else the string with a slash at its end

Examples

dirPathTest<-"test"
checkDirSlash(dirPathTest)

Checks if a character string can be used as a workflow name and corrects it if it contains spaces or underscores

Description

Checks if a character string can be used as a workflow name and corrects it if it contains spaces or underscores

Usage

checkWorkflowName(wfName)

Arguments

wfName

contains the character string to

Value

the character string if suitable, or a modified one to comply to what is expected for a workflow name

Examples

checkWorkflowName("BDT UTRF_test")

Compares two sets of geographical classifications, especially Local Climate Zones classifications

Description

Compares two sets of geographical classifications, especially Local Climate Zones classifications

Usage

compareLCZ(
  sf1,
  geomID1 = "",
  column1 = "LCZ_PRIMARY",
  confid1 = "",
  wf1 = NULL,
  sf2,
  column2 = "LCZ_PRIMARY",
  geomID2 = "",
  confid2 = "",
  wf2 = NULL,
  ref = 1,
  repr = "standard",
  saveG = "",
  exwrite = FALSE,
  outDir = getwd(),
  location = "Your Place",
  plotNow = TRUE,
  confPlot = "matrix",
  tryGroup = FALSE,
  minZeroArea = 0,
  ...
)

Arguments

sf1

is the sf object that contains the first (LCZ) classification

geomID1

is the name of the optionnal column storing the ID of the geoms in sf1 By defautl it is set to an empty string and no ID is loaded.

column1

is the column of sf1 that contains the LCZ classification for each geom of sf1.

confid1

is an optionnal column that contains an indicator of confidence of the values in column1, e.g. a uniqueness value, or a probability of belonging to the class... By defautl it is set to an empty string and no confidence indicator is loaded.

wf1

is the workflow used to produce the first LCZ classification. It is used ti create titles or legends. When GeoClimate was used with BD_TOPO V2 data as input, use "bdtopo_2_2". When GeoClimate was used with Open Street Map data as input, use "osm". When the LCZ come from the wudapt Europe tiff, use "wudapt".

sf2

is the sf object that contains the second (LCZ) classification

column2

is the column of sf2 that contains the LCZ classification for each geom of sf2

geomID2

is the name of the column storing the ID of the geoms in sf2

confid2

is a column that contains an indicator of confidence

wf2

is the workflow used to produce the second LCZ classification.

ref

: If the coordinate reference systems (CRS) of sf1 and sf2 differ, ref indicates which CRS to choose for both files (1 or 2)

repr

"standard" means that standard values of LCZ are expected, "alter" means other values are expected, like grouped values of LCZ or other qualitative variable. In the latter case, the ... arguments can contain the expected levels and a color vector.

saveG

: when an empty character string, "", the plots are not saved. Else, the saveG string is used to produce the name of the saved png file.

exwrite

: when TRUE, the values of the LCZ on the intersected geoms are written down in a csv file

outDir

: when exwrite equals TRUE, outDir is the path to the folder where one wants to write the csv file containing the values of the LCZ on the intersected geoms

location

: the name of the study area, as chosen as the name of the directory on the GeoClimate team cloud. If the area you wish to analyse is not uploaded yet, please contact the GeoClimate Team.

plotNow

: when FALSE none of the graphics are plotted or saved

confPlot

default is "matrix", to plot the confusion matrix. "sankey" allows to replaace it with a sankey diagram.

tryGroup

: when TRUE, one can group and compare on-the-fly : if the specified level names don't match the data, but the specified levels do, a call to the groupLCZ function will be tried, and if it works, the resulting grouping columns wille be compared

minZeroArea

allows you to specify a minimal area under which intersected spatial units will be discarded. It avoids numerical error and can save computing time.

...

allow to pass optionnal arguments if repr is set to alter. The expected arguments are the name of each level of the variables contained in column1 and column2, and also a vector called colors.

Details

compareLCZ produces a map for each classification, a map of their agreement (and a pseudo Kappa coefficent), and a confusion matrix between them. All are stored in a list, easily reusable

Value

returns graphics of comparison and an object called matConfOut which contains : matConfLong, a confusion matrix in a longer form, matConfPlot is a ggplot2 object showing the confusion matrix. percAgg is the general agreement between the two sets of LCZ, expressed as a percentage of the total area of the study zone pseudoK is a heuristic estimate of a Cohen's kappa coefficient of agreement between classifications If saveG is not an empty string, graphics are saved under "saveG.png"

Examples

comparisonBDT_OSM<-compareLCZ(sf1=redonBDT, column1="LCZ_PRIMARY", geomID1 = "ID_RSU",
confid1="LCZ_UNIQUENESS_VALUE", wf1="bdtopo_2_2",
sf2=redonOSM, column2="LCZ_PRIMARY", geomID2 = "ID_RSU",
confid2="LCZ_UNIQUENESS_VALUE", wf2="osm",
repr="standard", saveG="", exwrite=FALSE, location="Redon", plotNow = TRUE)
# To get the summed area of each LCZ levels for both dataset :
comparisonBDT_OSM$areas
# The plots of each dataset can be produced with the showLCZ function.
# To get the value of the general percentage of agreement call :
comparisonBDT_OSM$percAgg
# The values of that confusion matrix is available in a wide form:
comparisonBDT_OSM$matConfLarge
# or in a long form :
comparisonBDT_OSM$matConf
 # Examples for non LCZ variables are available in the importQualVar function examples.

Compares several sets of geographical classifications, especially Local Climate Zones classifications

Description

Compares several sets of geographical classifications, especially Local Climate Zones classifications

Usage

compareMultipleLCZ(
  sfInt,
  columns,
  workflowNames = NULL,
  trimPerc = 0,
  labelMatch = NULL,
  ...
)

Arguments

sfInt

an sf objects with intersected geometries and the LCZ columns for each workflow LCZ

columns

a vector which contains, the name of the columns of the classification to compare

workflowNames

a vector of strings which contains the names of the workflows used to produce the sf objects

trimPerc

this parameters indicates which percentile to drop out of the smallest geometries resulting It allows to account for numeric precision errors and to speed up computations at the cost of not considering the smallest geometries.

labelMatch

feed matching between levels of the data and some labels from the intersection of the original sf geometries intersection.

...

areguments to be passed for groupint, in the form of groupLevel = levels to group to this group level, and a possible groupColors named vectors, which names are the grouped levels and values are the desired colors.

Value

returns graphics of comparison and an object called matConfOut which contains : matConfLong, a confusion matrix in a long form (each line has the percentage of LCZ type i from workflow j which is classified in LCZ type i' by workflow j'), matConfPlot is a ggplot2 object showing the confusion matrix. percAgg is the general agreement between the two sets of LCZ, expressed as a percentage of the total area of the study zone If saveG is not an empty string, graphics are saved under "saveG.png" agreements a dtaframe with the pairs of workflows, areas on which they agree, disagree, and the percentage of agreement

Examples

sfList<-importMultipleLCZvect(dirPath =
paste0(system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
workflowNames = c("osm","bdt","wudapt"), location = "Arville")
ArvilleIntersect <- createIntersect(
 sfList = sfList, columns = rep("lcz_primary", 4),  
 workflowNames = c("osm","bdt","wudapt"))
ArvilleMultipleComparison<-compareMultipleLCZ(
 sfInt = ArvilleIntersect,
 columns = c("osm","bdt","wudapt"),
 trimPerc = 0.5)

creates a complete data.table from the cross cases of the specified columns

Description

creates a complete data.table from the cross cases of the specified columns

Usage

completeDT(DT, cols, defs = NULL)

Arguments

DT

is the data table you want to complete

cols

are the columns whose values will be crossed to complete the data.table

defs

a function name to apply to the crossed value

Value

the completed data table

Examples

# No example as this function is not to be called by the user, only needed for the package.

compute agreements between several LCZ maps

Description

compute agreements between several LCZ maps

Usage

computeAgreements(intersec_sf, nbWfs)

Arguments

intersec_sf

is a special sf or data.frame object whose lines correspond to intersected spatial units, the same for all workflows, and whose first columns contain LCZ values for the studied workflows, followed by a column containing the area of the spatial units

nbWfs

is the number of studied workflows (and therefore LCZ columns)

Compute an indicator of consensus among workflows for each LCZ type

Description

Compute an indicator of consensus among workflows for each LCZ type

Usage

computeConsensus(inDf, wfNames)

Arguments

inDf

a data frame, a data table or even an sf object, typically the output of the function createMultipleIntersect. It must contain values of LCZ types for different workflows in columns names after wf names, a column area which contains the area of each spatial unit

wfNames

a vector of strings containing the name of the workflows. The columns containing the LCZ type for each workflow bare the same names.

Value

Returns the values of consensus indicator per LCZ types

Examples

dirList <- list.dirs(paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs"), recursive = FALSE)
allLocIntersected<-concatIntersectedLocations(
dirList = dirList, locations = c("Arville", "Redon"))
consensus <- computeConsensus(inDf = allLocIntersected,
wfNames = c("bdt","osm", "wudapt"= "wud"))

importConcatMultipleLocsLCZvect is recommended instead as it loadsand concatenate input files and can even fill missing geometries with "unclassified" type. But if maps are already loaded in a List, concatAllLocsWorkflows is the equivalent of concatenateAlocationWorkflows, but for several Locations Take a list of locations, each list contains a list of sf files with an lcz_primary column, and concatenates them into a single sf object, adding a column for location and workflow names

Description

importConcatMultipleLocsLCZvect is recommended instead as it loadsand concatenate input files and can even fill missing geometries with "unclassified" type. But if maps are already loaded in a List, concatAllLocsWorkflows is the equivalent of concatenateAlocationWorkflows, but for several Locations Take a list of locations, each list contains a list of sf files with an lcz_primary column, and concatenates them into a single sf object, adding a column for location and workflow names

Usage

concatAllLocsWorkflows(sfList, refCrs = 1)

Arguments

sfList

contains a list of locations containing list of sf for each workflow

refCrs

a number telling which sf of the sfList will be the reference in termes of Coordinate Reference System

Value

returns a single sf object containing all geometries for all locations and workflows, and the the lcz types in the column lcz_primary

Examples

sfListAll<-importMultipleLocsLCZvect(dirPath = paste0(
 system.file("extdata", package = "lczexplore"),"/multipleWfs/"),
                              workflowNames = c("osm","bdt","wudapt"),
                              location = c("Arville", "Redon"))
allLocsAllWfs <-  concatAllLocsWorkflows(
 sfList = sfListAll)

Take a list of sf files with lcz_primary and wf columns, and concatenates them in a single sf object, adding a column for location and workflow names

Description

Take a list of sf files with lcz_primary and wf columns, and concatenates them in a single sf object, adding a column for location and workflow names

Usage

concatAlocationWorkflows(
  sfList,
  location = NA,
  refCrs = 1,
  columns = "lcz_primary"
)

Arguments

sfList

the list of LCZ sf objects

location

the name of the location at which all LCZ are created

refCrs

a number telling which sf of the sfList will be the reference in termes of Coordinate Reference System

columns

contains the names of the columns where LCZ types are stored. If it contains only one string, it will be repeated for all workflows

Value

returns an sf with values of LCZ for all workflows for a given location

Examples

sfList<-importMultipleLCZvect(dirPath = paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
workflowNames = c("osm","bdt","wudapt"), location = "Arville"  )
zoneSf <- sf::read_sf(
paste0(system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville/zone.fgb")
)
ArvilleAllWfs <-  concatAlocationWorkflows(
sfList = sfList, location = "Arville")

In a given directory (or a list of directories) the function looks for LCZ datafiles, intersects them and return a dataset with intersected geometries and LCZ values for each workflow

Description

In a given directory (or a list of directories) the function looks for LCZ datafiles, intersects them and return a dataset with intersected geometries and LCZ values for each workflow

Usage

concatIntersectedLocations(
  dirList,
  workflowNames = c("osm", "bdt", "wudapt"),
  locations,
  columns = "lcz_primary"
)

Arguments

dirList

the list of directories for which the different LCZ files will be intersected

workflowNames

sets the names of workflows and define the name of the files which will be loaded and intersected

locations

: for each diretory from dirList, a location name must be fed to the function

columns

the name (string) of the column containing LCZ types. If the different workflows do no use the same column names, a vector of names is passed

Value

returns an sf object with all intersections

Examples

dirList<-list.dirs(paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs"), recursive = FALSE)
allLocIntersected<-concatIntersectedLocations(
 dirList = dirList, locations = c("Arville", "Redon"), columns = "lcz_primary")

Computes the agreement between geographical (LCZ) classifications on a range of values of an indicator of confidence granted to each LCZ classification. The input file or dataset must have been produced by compareLCZ function, or at least the columns must be in the same order

Description

Computes the agreement between geographical (LCZ) classifications on a range of values of an indicator of confidence granted to each LCZ classification. The input file or dataset must have been produced by compareLCZ function, or at least the columns must be in the same order

Usage

confidSensib(
  inputDf = "",
  filePath = "",
  nPoints = 5,
  wf1 = "bdtopo_2_2",
  wf2 = "osm",
  geomID1 = "ID_RSU",
  column1 = "LCZ_PRIMARY",
  confid1 = "LCZ_UNIQUENESS_VALUE",
  geomID2 = "ID_RSU.1",
  column2 = "LCZ_PRIMARY.1",
  confid2 = "LCZ_UNIQUENESS_VALUE.1",
  sep = ";",
  repr = "standard",
  plot = TRUE,
  saveG = ""
)

Arguments

inputDf

is an R file with geom IDs, (LCZ) classifications and a confidence value granted for the (LCZ) classifications values of each geom. Ignored if filePath is not empty.

filePath

is the path to a csv file containing geom IDs, LCZ classifications and a confidence value granted for the LCZ value of each geom. Set it to "" if inputDf is specified (recommanded)

nPoints

is the number of points (quantiles) of confidence for which the average agreement between classifications will be computed

wf1

is the name of the workflow used to produce the first LCZ

wf2

is the name of the workflow used to produce the second LCZ

geomID1

is the name of the column that contains the geom ID associated to the first workflow

column1

is the name of the column storing the first LCZ classification values

confid1

is the name of the column storing the first LCZ classification confidence value

geomID2

is the name of the column that contains the geom ID associated to the second workflow

column2

is the name of the column storing the second LCZ classification values

confid2

is the name of the column storing the second LCZ classification confidence value

sep

the separator used if filePath is not empty

repr

is standard when original LCZ values are expected, alter otherwise

plot

if TRUE the graph is plotted

saveG

if not an empty string, specifies where to save graphs

Value

returns an object called output, which contains the values of the thresholds for the confidence value and the agreement between classifications for the LCZ levels presents in the dataset

Examples

# creation of the comparison data on which to perform the analysis
redonCompare<-compareLCZ(sf1=redonBDT, wf1="bdt", geomID1 = "ID_RSU", column1 ="LCZ_PRIMARY",
                        confid1 = "LCZ_UNIQUENESS_VALUE",
                        sf2=redonOSM, wf2="osm",geomID2 = "ID_RSU", column2="LCZ_PRIMARY",
                        confid2 ="LCZ_UNIQUENESS_VALUE", exwrite=FALSE, plot=FALSE, saveG="")
confidSensib(inputDf=redonCompare$data,
nPoints=5, wf1="bdtopo_2_2", wf2="osm",
geomID1="ID_RSU", column1="bdt", confid1="LCZ_UNIQUENESS_VALUE",
geomID2="ID_RSU.1",column2="osm", confid2="LCZ_UNIQUENESS_VALUE.1",
sep=";", repr="standard", plot=TRUE, saveG="")

Intersects multiple sf files in which Local Climate Zones are set for polygon geometries

Description

Intersects multiple sf files in which Local Climate Zones are set for polygon geometries

Usage

createIntersect(
  sfList,
  columns,
  refCrs = NULL,
  workflowNames = NULL,
  minZeroArea = 0
)

Arguments

sfList

a list which contains the classifications to compare, as sf objects

columns

a vector which contains, for each sf of sfList, the name of the columns of the classification to compare

refCrs

a number which indicates which sf object from sfList will provide the CRS in which all the sf objects will be projected before comparison By defautl the first sf object CRs is applied to all sf objects.

workflowNames

a vector of strings which contains the names of the workflows used to produce the sf objects

minZeroArea

all geometries smaller than this value are discarded (avoids numeric precision problems)

Details

The input SfList can contain two levels, the first level being the locations, the second being the workflow. In this case, the output will still be a single sf object, concatenating the workflows and locations as columns

Value

a single sf file with values of LCZ from all the input are assigned to geometries resulting from intersection of all input geometries

Examples

sfList<-importMultipleLCZvect(
dirPath = paste0(
system.file("extdata", package = "lczexplore"),
"/multipleWfs/Arville"),
workflowNames = c("osm","bdt","wudapt"), location = "Arville")
ArvilleIntersect <- createIntersect(
 sfList = sfList, columns = rep("lcz_primary", 4),  
 workflowNames = c("osm","bdt","wudapt"))
# Two Locations
sfList2<-importMultipleLocsLCZvect(
 dirPath = paste0(
     system.file("extdata", package = "lczexplore"),
     "/multipleWfs"),
 workflowNames = c("osm","bdt","wudapt"))

TwoLocsIntersect <- createIntersect(
 sfList = sfList2, columns = rep("lcz_primary", 3),
 workflowNames = c("osm","bdt","wudapt"))

Takes an sf object with several workflow values, and creates all pairwise confusion matrices, then conatenates them in long form, usable to plot chord diagrams

Description

Takes an sf object with several workflow values, and creates all pairwise confusion matrices, then conatenates them in long form, usable to plot chord diagrams

Usage

createWeightedFlux(
  intersectSfWide,
  columns = NULL,
  wfNamesIn = NULL,
  typeLevelsDefaultIn = .lczenv$typeLevelsDefault
)

Arguments

intersectSfWide

is an sf object, containing the different lcz classification on already intersected geometries in wide format with a column wf for the workflow names, a column lcz_primary for the LCZ types.

columns

a vector containing the names of the LCZ type columns

wfNamesIn

the name of the input compared workflows. They will be the output columns for the LCZ types

typeLevelsDefaultIn

is a named vector of strings containing the LCZ levels. By default inherited from lczexplore

Value

a dataframe with columns orig, dest and weightedFlux, weighted flux the percentage of area from a given LCZ type of a given workflow (orig) to another LCZ type of another workflow (dest).

Examples

twoLocsDir<-paste0(
 system.file("extdata", package = "lczexplore"),"/multipleWfs")
twoLocsSfList<-importMultipleLocsLCZvect(
 dirPath = twoLocsDir, workflowNames = c("osm","bdt","wudapt"),
 location = c("Arville", "Redon"))

twoLocsSfIntersected <- createIntersect(
 sfList = twoLocsSfList, columns = rep("lcz_primary", 4),
 refCrs=NULL, workflowNames=c("osm", "bdt", "wudapt"), minZeroArea=0.001)

twoLocsWeightedFlux<-createWeightedFlux(
twoLocsSfIntersected, wfNamesIn = c("osm","bdt","wudapt"))

Draws how LCZ types from several workflows break up into LCZ types of one another

Description

Draws how LCZ types from several workflows break up into LCZ types of one another

Usage

drawChordDiagram(weightedFluxIn, colorMapIn = NULL, labelMatch = NULL, ...)

Arguments

weightedFluxIn

is typically the output of the function createWeightedFlux, and is expected to contain the following columns orig, dest and weightedFlux, whose names are quite self explanatory : orig is the origin LCZ type, dest is the destination LCZ type and weightedFlux is the percentage of area transfered from orig to dest

colorMapIn

is a named vector whose names are the unique values of orig and dest columns of weightedFluxIn and values are the associated colors. In cas of grouping, these values are overwritten by the groupCols argument, see the ... parameters

labelMatch

allox to match a level of dest or orig from weightedFluxIn and a label. It also allows to change the order in which they are visualized (default is alphabetical order). It is then possible to prefixe values of Levels by a letter to force this order and use LabelMatch to use original names. When using grouping vectors, they are visualized in the order they are specified.

...

allows the user to do on-the-fly grouping. These must be passed as groupName = groupValues where groupName is the name of a resulting group and groupValues a vector of the initial values it will regroup.

Value

a chord diagram of how LCZ types of a workflow break up into types of the other workflows

Examples

twoLocsDir<-paste0(
 system.file("extdata", package = "lczexplore"),"/multipleWfs")
twoLocsSfList<-importMultipleLocsLCZvect(
 dirPath = twoLocsDir, workflowNames = c("osm","bdt","wudapt"),
 location = c("Arville", "Redon"))
twoLocsSfIntersected <- createIntersect(
 sfList = twoLocsSfList, columns = rep("lcz_primary", 4),
 refCrs=NULL, workflowNames=c("osm", "bdt", "wudapt"), minZeroArea=0.001)
twoLocsWeightedFlux<-createWeightedFlux(
 twoLocsSfIntersected, wfNamesIn = c("osm","bdt","wudapt"))
# Subsetting and grouping allow further exploration.
# Playing on grouping names and alphabetical order allows
# to choose the order of the sectors
twoLocsWeightedFluxNo104no101<-subset(twoLocsWeightedFlux,
     !grepl("101", twoLocsWeightedFlux$orig) &
     !grepl("104", twoLocsWeightedFlux$orig) &
     !grepl("101", twoLocsWeightedFlux$dest) &
     !grepl("104", twoLocsWeightedFlux$dest))
aggregMatch<-c(
    "acompact"="Compact",
     "blessCompact" = "Less Compact",
    "cfewToNoBuild" = "Few to No Buildings",
    "dunclass" = "Unclassified")
drawChordDiagram(twoLocsWeightedFluxNo104no101, labelMatch = aggregMatch,
    acompact = c("1", "2", "3"),
    blessCompact = c("4", "5", "6", "7", "8", "10"),
    cfewToNoBuild = c("101", "102", "103", "104", "105", "106", "107", "9"),
    dunclass = "Unclassified",
    groupColors = c(
      "acompact" = "#8b0101",
      "blessCompact" = "#ff9856",
       "cfewToNoBuild" = "#bbdb7a","dunclass" = "grey"))

Draws how LCZ types from several workflows break up into LCZ types of one another when some grouping is precised in the arguments

Description

Draws how LCZ types from several workflows break up into LCZ types of one another when some grouping is precised in the arguments

Usage

drawChordDiagramWithGrouping(
  weightedFluxIn,
  colorMapIn = NULL,
  labelMatch = NULL,
  ...
)

Arguments

weightedFluxIn

is typically the output of the function createWeightedFlux, and is expected to contain the following columns orig, dest and weightedFlux, whose names are quite self explanatory : orig is the origin LCZ type, dest is the destination LCZ type and weightedFlux is the percentage of area transfered from orig to dest

colorMapIn

is a named vector whose names are the unique values of orig and dest columns of weightedFluxIn and values are the associated colors. In cas of grouping, these values are overwritten by the groupCols argument, see the ... parameters

labelMatch

allow to match a level of dest or orig from weightedFluxIn and a label. Remember to match labels with the grouping names you chose in the named grouping vectors passed to ... When using grouping vectors, they are visualized in the order they are specified.

...

allows the user to do on-the-fly grouping. These must be passed as groupName = groupValues where groupName is the name of a resulting group and groupValues a vector of the initial values it will regroup.

Value

a chord diagram after LCZ types are grouped according to ... arguments

Examples

twoLocsDir<-paste0(system.file("extdata", package = "lczexplore"),"/multipleWfs")
twoLocsSfList<-importMultipleLocsLCZvect(
dirPath = twoLocsDir, workflowNames = c("osm","bdt","wudapt"),
 location = c("Arville", "Redon"))
twoLocsSfIntersected <- createIntersect(
 sfList = twoLocsSfList, columns = rep("lcz_primary", 4),
 refCrs=NULL, workflowNames=c("osm", "bdt", "wudapt"), minZeroArea=0.001)
twoLocsWeightedFlux<-createWeightedFlux(
 twoLocsSfIntersected, wfNamesIn = c("osm","bdt","wudapt"))
# Subsetting and grouping allow further exploration.
# Playing on grouping names and alphabetical order allows
# to choose the order of the sectors
# Subsetting and grouping allow further exploration.
# Playing on grouping names and alphabetical order allows
# to choose the order of the sectors
twoLocsWeightedFluxNo104no101<-subset(twoLocsWeightedFlux,
     !grepl("101", twoLocsWeightedFlux$orig) &
     !grepl("104", twoLocsWeightedFlux$orig) &
     !grepl("101", twoLocsWeightedFlux$dest) &
     !grepl("104", twoLocsWeightedFlux$dest))
aggregMatch<-c("acompact"="Compact", "blessCompact" = "Less Compact",
"cfewToNoBuild" = "Few to No Buildings at All",
    "dunclass" = "Unclassified")
drawChordDiagram(twoLocsWeightedFluxNo104no101, labelMatch = aggregMatch,
    acompact = c("1", "2", "3"),
    blessCompact = c("4", "5", "6", "7", "8", "10"),
    cfewToNoBuild = c("101", "102", "103", "104", "105", "106", "107", "9"),
    dunclass = "Unclassified",
    groupColors = c(
      "acompact" = "#8b0101",
      "blessCompact" = "#ff9856",
       "cfewToNoBuild" = "#bbdb7a","dunclass" = "grey"))

Draws sectors and groups inside the drawChordDiagram function

Description

Draws sectors and groups inside the drawChordDiagram function

Usage

drawSectors(sectorID, sectorsIn = sectors, colorMapIn = colorMap, textMatch)

Arguments

sectorID

ar the identifiers of sectors as returned by the makeSectorsAndGroups function

sectorsIn

are the values of a sectors as returned by the makeSectorsAndGroups function

colorMapIn

is a named vector whose names must contain the values of sectorsIn and whose values are the desired colors see drawChorDiagram function for details

textMatch

is fed by drawChordDiagram to provide labels for sectors

Value

a list containing vectors and groups for a chord diagram

Deprecated DO NOT USE, kept in case some users might need it Fetches LCZ classification data, by default from the Geomanum cloud, for locations already uploaded there by the Geoclimate team

Description

Deprecated DO NOT USE, kept in case some users might need it Fetches LCZ classification data, by default from the Geomanum cloud, for locations already uploaded there by the Geoclimate team

Usage

fetchLCZ(
  location,
  outDir,
  wf = "bdtopo_2_2",
  refYear = "2022",
  baseURL = "https://cloud.geomanum.org/index.php/s/geoclimate/download?path=%2F",
  ...
)

Arguments

location

is the name of the place for which you want to get the GeoClimate data

outDir

is the path to the directory in which fetchLCZ will unpack the data

wf

workflow can be bdtopo_2_2, when GeoClimate used the BDTOPO data base, or osm when it used the open street map data.

refYear

this parameters is integrated in the name given to the data, in order to allow to re-run the function according to the reference year. At the moment only 2022 data have been tried

baseURL

is the adress of the server where the function fetches the data. The data must be organised in a bdtopo_2_2 and an osm/year directories. This function is intended to be used by Paendora project members, so the default is the Geomanum Foundation cloud.

...

allows to pass arguments from the produce analysis function to the groupLCZ and compareLCZ functions

Value

returns no R object. The data are uploaded from the GeoClimate cloud and locally unpacked in the outDir directory

Examples

# not run as the access is not open
# fetchLCZ(location="Allaire",
# outDir=system.file("extdata", package = "lczexplore"),
# wf="bdtopo_2_2",refYear="2022")

Calls GeoClimate jar file and feeds it a configuration file by building a command an using system (only tested on linux)

Description

Calls GeoClimate jar file and feeds it a configuration file by building a command an using system (only tested on linux)

Usage

geoClimateCall(jarFilePath, configFilePath, wf = "OSM")

Arguments

jarFilePath

tells where the geoclimate jar file is, default points to the embedded jar file, i.e. the latest snapshot version when the package was built. Versions can be downloaded from https://github.com/orbisgis/geoclimate/wiki/Download

configFilePath

points to the configuration JSON file for GeoClimate, typically a file created with the geoClimateConfigFile function

wf

is the workflow to use with GeoClimate, the default is OSM for OpenStreetMap. The other possible value is "BDTOPO_V2". Other values will be added (e.g. for BDTOPO_V3) when tested.

Value

returns nothing but executes GeoClimate in the folder specified in the JSON configuration file.

Examples

# not run as they write files
# test <- geoClimateConfigFile(
#     outConfigFile = "",
#     wf = "OSM", outFolder = "", locations = "Redon",
#     rsuIndics = c("LCZ", "TEB", "UTRF"),
#     gridIndics = c(
#         "BUILDING_FRACTION", "BUILDING_HEIGHT", "WATER_FRACTION",
#         "VEGETATION_FRACTION", "ROAD_FRACTION",
#         "IMPERVIOUS_FRACTION", "LCZ_PRIMARY", "LCZ_FRACTION", "UTRF"),
#        writeNow = FALSE)
# not run as geoclimate jar source needed
# geoClimateCall(
# jarFilePath = "path/to/Geoclimate/geoclimate-0.0.2-SNAPSHOT.jar",
# configFilePath = "/tmp/RedonOSM2022.json", wf = "OSM")
# rsuIndics = c("LCZ","TEB","UTRF"),
# gridIndics = c(
#        "BUILDING_FRACTION","BUILDING_HEIGHT",
#        "WATER_FRACTION","VEGETATION_FRACTION","ROAD_FRACTION",
#        "IMPERVIOUS_FRACTION","LCZ_PRIMARY","LCZ_FRACTION","UTRF"))

Builds a JSON configuration file for GeoClimate workflow.

Description

Builds a JSON configuration file for GeoClimate workflow.

Usage

geoClimateConfigFile(
  wf,
  locations,
  forceSRID = FALSE,
  outFolder = "/tmp",
  date = "2022-01-01T12:00:00Z",
  rsuIndics = c("LCZ", "TEB", "UTRF"),
  svfSimplified = TRUE,
  estimatedHeight = TRUE,
  grid_x_size = 0,
  grid_y_size = 0,
  rowCol = FALSE,
  outputType = "geojson",
  gridIndics = "",
  outConfigDir = "/tmp",
  outConfigFile = "configFile",
  BDTinFolder = "",
  writeNow = FALSE
)

Arguments

wf

is the workflow used by GeoClimate. For now, only OSM" is available, for OpenStreetMap, but "BDT" for BDTOPO of IGN should be added when an online database is available.

locations

is either the town or the coordinates of the bounding box of the area on which GeoClimate will run. If a town name, it will be fed to the Nominoe API, through the overpass API of OpenStreetMap.

forceSRID

some BD TOPO input file may not have an srid, this forces srid to be 2154

outFolder

indicates where the results of GeoClimate will be put

date

is the date of the data we extract from OpenStreetMap. The format is "yyyy:mm:ddThh:mm:ssZ" (for BDTOPO the version depends from the input data folder)

rsuIndics

is a vector with the indicators one wants to compute at the RSU scale. The default is c("LCZ","TEB","UTRF"),

svfSimplified

uses the simplified method to calculate skyview factor, default = TRUE

estimatedHeight

uses an algorithm to estimate the missing building height, default = TRUE

grid_x_size

is the x size for the grid if some grid indicators are to be computed, default=100

grid_y_size

is the x size for the grid if some grid indicators are to be computed, default=100

rowCol

if grid_x_size and grid_y_size are not set, one cal set the number of rows and cols throug rowCol, but the recommended and default is FALSE

outputType

is the format of GeoClimate outputs, default="geojson"

gridIndics

is a vector containing the indicators to compute at the grid scale. Default is c("BUILDING_FRACTION", "BUILDING_HEIGHT", "WATER_FRACTION", "VEGETATION_FRACTION", "ROAD_FRACTION", "IMPERVIOUS_FRACTION","LCZ_PRIMARY","LCZ_FRACTION","UTRF")

outConfigDir

is the folder were the resulting JSON file will be put, the folder where GeoClimate will read it from (different from out outFolder, where GeoClimates will put its geoJSON ouputs), default is "/tmp"

outConfigFile

is the name of your configuration file, if and empty string, a name will be created from location and workflow parameters.

BDTinFolder

the path of the folder where are the BDTOPO needed by geoclimate

writeNow

if TRUE, the resulting config file is written using the outConfigDir and outConfigFile parameters

Details

GeoClimate is not included in this package. The json configuration call can be fed to GeoClimate with the geoClimateCall function, provided that user has downloaded a version of the software from the official repository https://github.com/orbisgis/geoclimate

Value

Exports a json configuration file to be read by GeoClimate software

returns a JSON configuration file to be fed to GeoClimate

Examples

# not run as they write files
# test <- geoClimateConfigFile(
#     outConfigFile = "",
#     wf = "OSM", outFolder = "", locations = "Redon",
#     rsuIndics = c("LCZ", "TEB", "UTRF"),
#     gridIndics = c(
#         "BUILDING_FRACTION", "BUILDING_HEIGHT", "WATER_FRACTION",
#         "VEGETATION_FRACTION", "ROAD_FRACTION",
#         "IMPERVIOUS_FRACTION", "LCZ_PRIMARY", "LCZ_FRACTION", "UTRF"),
#        writeNow = FALSE)
# not run as geoclimate jar source needed
# geoClimateCall(
# jarFilePath = "path/to/Geoclimate/geoclimate-0.0.2-SNAPSHOT.jar",
# configFilePath = "/tmp/RedonOSM2022.json", wf = "OSM")
# rsuIndics = c("LCZ","TEB","UTRF"),
# gridIndics = c("BUILDING_FRACTION","BUILDING_HEIGHT",
# "WATER_FRACTION","VEGETATION_FRACTION","ROAD_FRACTION",
# "IMPERVIOUS_FRACTION","LCZ_PRIMARY","LCZ_FRACTION","UTRF"))

Allows to group (Local Climate Zone) geographical classification levels into broader categories to explore classification agreements

Description

Allows to group (Local Climate Zone) geographical classification levels into broader categories to explore classification agreements

Usage

groupLCZ(sf, column, outCol = "grouped", ...)

Arguments

sf

is the input files. It must be an sf file and contain an LCZ column (levels 1 to 10 and 101 to 107). It must contain the geom column.

column

is the name of the column containing the LCZ to be grouped

outCol

is the name of the colum in which the grouped LCZ will be put

...

the names of the groups followed by the levels the regrouped for instance urban=c("1","2","3","4","5","6","7","8","9")

Value

a file containing the original geom and lcz, and a new grouped column

Examples

redonBDTgrouped<-groupLCZ(redonBDT,column="LCZ_PRIMARY",
urban=c("1","2","3","4","5","6","7","8","9"),
industry="10", vegetation=c("101","102","103","104"),
impervious="105",pervious="106",water="107",
colors=c("red","black","green","grey","burlywood","blue"))

showLCZ(redonBDT,column="LCZ_PRIMARY", repr="standard")
showLCZ(redonBDTgrouped,column="grouped",repr="alter",
LCZlevels=c("urban","industry","vegetation","impervious","pervious","water"),
colors=c("red","black","green","grey","burlywood","blue"),wf="BD TOPO")

Regroups levels of origin and destination of a multiple confusion matrix in long form.

Description

Regroups levels of origin and destination of a multiple confusion matrix in long form.

Usage

groupLCZsuffix(weightedFluxIn, ...)

Arguments

weightedFluxIn

is typically the output of the function createWeightedFlux, and is expected to contain the following columns orig, dest and weightedFlux, whose names are quite self explanatory : orig is the origin LCZ type, dest is the destination LCZ type and weightedFlux is the percentage of area transfered from orig to dest

...

a set of argument passed as groupName = groupValues where groupName is the name of a resulting group and groupValues a vector of the initial values it will regroup.

Value

a list containing vectors and groups for a chord diagram

In a given list of directories the function looks for LCZ datafiles, return a datasets LCZ values for each geom and workflow

Description

In a given list of directories the function looks for LCZ datafiles, return a datasets LCZ values for each geom and workflow

Usage

importConcatMultipleLocsLCZvect(
  dirPath,
  locations = NA,
  workflowNames = c("osm", "bdt", "wud"),
  missingGeomsWf = "osm",
  refWf = NULL,
  refLCZ = NA,
  residualLCZvalue = NA,
  column = "lcz_primary"
)

Arguments

dirPath

is the path to the root directory where are the subdirectories containing different location LCZ files

locations

for each diretory from dirList, a location name must be fed to the function

workflowNames

sets the names of workflows and define the name of the files which will be loaded and intersected

missingGeomsWf

the name of the workflow where some areas were not classified

refWf

the name of the workflow one uses as a reference to complete the incomplete workflow. if NULL then the geometries added will get the level specified in residualLCZvalue, else, the level in refLCZ

refLCZ

the reference level the completed geometries will receive

residualLCZvalue

the value the completed geometries where the reference workflow does not classify the geometry with refLCZ level

column

a parameter to feed addMissingRSUs function

Value

an sf object conaining the LCZ types of all workflows for all locations

Examples

dirPath<-paste0(
system.file("extdata", package = "lczexplore"),
"/multipleWfs")
allLocAllWfs<-importConcatMultipleLocsLCZvect(
 dirPath = dirPath, locations = c("Redon", "Arville"),
workflowNames = c("osm","bdt","wudapt"),
 missingGeomsWf= "osm",
 refWf = NULL,
 refLCZ = "Unclassified",
 residualLCZvalue = "Unclassified",
 column = "lcz_primary"
)

Imports the wf_lcz fgb file produced by GeoClimate. Not recommended. Use the more generic importLCZvect function

Description

Imports the wf_lcz fgb file produced by GeoClimate. Not recommended. Use the more generic importLCZvect function

Usage

importLCZgc(dirPath, output = "sfFile", file = "rsu_lcz.fgb")

Arguments

dirPath

: the path where the rsu_lcz.geojson file is.

output

: if sfFile the rsu_lcz.geojson is imported as an sf file, if bBox, a bounding box of the area is returned

file

: name of the file to load. Default is rsu_lcz.fgb, as it is the output of GeoClimate when the the rsu indicators are specified (as opposed to grid indicators).

Value

: if output is set to sfFile, the function returns an sf objects containing all the colums of the rsu_lcz.geojson found in the dirPath directory. If output is bBox a bounding box (seef sf package) of the area contained in the rsu_lcz file in the dirPath directory is returned. This is useful to select geoms analysed in other sf objects.

Examples

# not run
# bdtTest <- importLCZgc(dirPath = system.file("extdata/multipleWfs/Redon", package = "lczexplore"),
# file = "bdt_lcz.fgb")

Imports the LCZ classifications produced on raster maps. For now, the european tif map produced by WUDAP is used as a reference example. Users can DOWNLOAD the WUDAPT tif file at the following url : https://figshare.com/articles/dataset/European_LCZ_map/13322450

Description

Imports the LCZ classifications produced on raster maps. For now, the european tif map produced by WUDAP is used as a reference example. Users can DOWNLOAD the WUDAPT tif file at the following url : https://figshare.com/articles/dataset/European_LCZ_map/13322450

Usage

importLCZraster(
  dirPath,
  bBox,
  fileName = "EU_LCZ_map.tif",
  LCZband = 1,
  LCZcolumn = "EU_LCZ_map",
  confidenceBand = "",
  confidenceColumn = "confidence",
  typeLevels = c(`1` = "1", `2` = "2", `3` = "3", `4` = "4", `5` = "5", `6` = "6", `7` =
    "7", `8` = "8", `9` = "9", `10` = "10", `101` = "11", `102` = "12", `103` = "13",
    `104` = "14", `105` = "15", `106` = "16", `107` = "17")
)

Arguments

dirPath

is the path to the directory where the

bBox

bBox is a mask to crop the raster file. It can be a bounding box or any single geometry which contains the desired zone. It can be produced by the importLCZvect function. It can either be of class bBox or of class sfc, like the geometry column of an sf object.

fileName

is the name of the raster file (tif or geotif), by default \'EU_LCZ_map.tif\'.

LCZband

defines the band of the raster file which contains the LCZ types. It can be a number or a band name (default = 1)

LCZcolumn

the name of the column of the output sf File in which the LCZ types will be stored (default = "LCZ")

confidenceBand

the band of the raster files which contains a measure of confidence. Can be a number or a band name (default = "", that is no measure of confidence provided)

confidenceColumn

the name of the column of the output sf File in which the confidence values will be stored (default = "", no confidence value specified)

typeLevels

indicates a named vector of the unique values contained in LCZcolumn,

Value

an sf file containing the geom and LCZ levels from theraster tiff within the bBox bounding box

Examples

redonBbox<-importLCZvect(dirPath=paste0(system.file("extdata", package = "lczexplore"),
"/multipleWfs/Redon"), file="bdt_lcz.fgb", column="LCZ_PRIMARY", output="bBox")

redonWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
fileName="redonWudapt.tif",bBox=redonBbox)

# Another way to get the bounding box when one explores a given city would be the use of the 
# getbb() function from the osmdata package. 
# This example requires the osmdata package and therefore is not executed here
# redonBbox<-osmdata::getbb("Redon")
# redonWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
# fileName="redonWudapt.tif",bBox=redonBbox)

# another way to get the bounding box when one doesn't want 
#to compare to a vector map is to enter it's coordinates 
# and feed them to st_bbox() of the sf package.

# imporLCZraster also allows to choose which band of a raster file to import
redonWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
fileName="redonWudapt.tif",bBox=redonBbox, LCZband=1, LCZcolumn='EU_LCZ_map')

Imports Local Climate Zone classifications from a vector source, a geographical file or an sf object from the current R session

Description

Imports Local Climate Zone classifications from a vector source, a geographical file or an sf object from the current R session

Usage

importLCZvect(
  dirPath,
  file = "bdt_lcz.fgb",
  output = "sfFile",
  column = "LCZ_PRIMARY",
  geomID = "",
  confid = "",
  typeLevels = .lczenv$typeLevelsConvert2,
  drop = TRUE,
  verbose = FALSE,
  sfIn = NULL,
  naAsUnclassified = TRUE
)

Arguments

dirPath

is the path of the directory of the file

file

is the name of the file from which the LCZ are imported

output

: if sfFile, the function returns an sfFile with the specified columns, if bBox, returns a bounding box one can use to crop a raster file or to intersect another sf file

column

indicates the name of the column containing LCZ values. LCZ values are expected to be of a standard LCZ format (1 to 17, or 1 to 10 and 101 to 107 or 1 to G), else, use the importQualVar function

geomID

is the name of the column containing the ID of each geom to load. If an empty string, no column is loaded.

confid

is the name of the column containing a confidence indicator to filter geoms, for instance the uniqueness of the LCZ level of each geom

typeLevels

the levels of the imported LCZ classification

drop

: the default is TRUE, which means all the column are dropped excepted those specified in previous parameters

verbose

if TRUE show the discrepancies between specified levels of LCZ and levels actually present in column

sfIn

allows you to import from an existing object of your session, not from an external file

naAsUnclassified

if TRUE allows NAs in the input file and assigns them the value "Unclassified"

Value

returns an sf object containing at least the geoms and the LCZ values, and if specified, columns for the IDs of the geoms and the confidence value of the LCZ levels.

Examples

redonBDTex<-importLCZvect(dirPath=paste0(system.file("extdata", package = "lczexplore"),
 "/multipleWfs/Redon"), file="bdt_lcz.fgb", column="LCZ_PRIMARY",
geomID="ID_RSU",confid="LCZ_UNIQUENESS_VALUE")
showLCZ(redonBDTex)

Imports Local Climate Zone classifications from a standard geographical file (tested : geojson, shp, more to come)

Description

Imports Local Climate Zone classifications from a standard geographical file (tested : geojson, shp, more to come)

Usage

importLCZvectFromFile(
  dirPath,
  file = "bdt_lcz.fgb",
  column,
  geomID = "",
  confid = "",
  verbose = TRUE,
  drop = TRUE
)

Arguments

dirPath

is the path of the directory of the file

file

is the name of the file from which the LCZ are imported

column

indicates the name of the column containing LCZ values. LCZ values are expected to be of a standard LCZ format (1 to 17, or 1 to 10 and 101 to 107 or 1 to G), else, use the importQualVar function

geomID

is the name of the column containing the ID of each geom to load. If an empty string, no column is loaded.

confid

is the name of the column containing a confidence indicator to filter geoms, for instance the uniqueness of the LCZ level of each geom

verbose

if TRUE show the discrepancies between specified levels of LCZ and levels actually present in column

drop

: the default is TRUE, which means all the column are dropped excepted those specified in previous parameters

Value

returns an sf object containing at least the geoms and the LCZ values, and if specified, columns for the IDs of the geoms and the confidence value of the LCZ levels.

Examples

redonBDTex<-importLCZvectFromFile(dirPath=paste0(system.file("extdata", package = "lczexplore"),
"/multipleWfs/Redon"), file="bdt_lcz.fgb", column="LCZ_PRIMARY",
geomID="ID_RSU",confid="LCZ_UNIQUENESS_VALUE")

Imports Local Climate Zone classifications from an existing sf object

Description

Imports Local Climate Zone classifications from an existing sf object

Usage

importLCZvectFromSf(sfIn, column, geomID = "", confid = "")

Arguments

sfIn

is the sf object containing the LCZ map

column

indicates the name of the column containing LCZ values. LCZ values are expected to be of a standard LCZ format (1 to 17, or 1 to 10 and 101 to 107 or 1 to G), else, use the importQualVar function

geomID

is the name of the column containing the ID of each geom to load. If an empty string, no column is loaded.

confid

is the name of the column containing a confidence indicator to filter geoms, for instance the uniqueness of the LCZ level of each geom

Value

returns an sf object containing at least the geoms and the LCZ values, and if specified, columns for the IDs of the geoms and the confidence value of the LCZ levels.

Examples

redonBDTex<-importLCZvect(dirPath=paste0(system.file("extdata", package = "lczexplore"),
"/multipleWfs/Redon"), file="bdt_lcz.fgb", column="LCZ_PRIMARY",
geomID="ID_RSU",confid="LCZ_UNIQUENESS_VALUE")
redonBDTex2<-importLCZvectFromSf(sfIn = redonBDTex , column="LCZ_PRIMARY",
                                 geomID="ID_RSU",confid="LCZ_UNIQUENESS_VALUE")

In a given directory (or a list of directories) the function looks for LCZ datafiles and load them in a list. In each directory, files must have names built as follow : wf_lcz.fileExtension, where wf are the values specified in workflowNames parameter and fileExtension is a file extension known by sf drivers, like fgb, geojson...

Description

In a given directory (or a list of directories) the function looks for LCZ datafiles and load them in a list. In each directory, files must have names built as follow : wf_lcz.fileExtension, where wf are the values specified in workflowNames parameter and fileExtension is a file extension known by sf drivers, like fgb, geojson...

Usage

importMultipleLCZvect(
  dirPath,
  workflowNames = c("osm", "bdt", "wudapt"),
  location = NA,
  fileExtension = ".fgb",
  columns = "lcz_primary",
  typeLevels = .lczenv$typeLevelsConvert2
)

Arguments

dirPath

is the place where the files are

workflowNames

sets the names of workflows

location

is the name of the location at which all LCZ are created

fileExtension

is the extensions of the files to load (.fgb is the recommended format)

columns

the name (string) of the column containing LCZ types. If the different workflows do no use the same column names, a vector of names is passed

typeLevels

allows to pass the expected levels of the lcz columns

Value

returns a list containing one sf by workflow for a given locations

Examples

sfList<-importMultipleLCZvect(dirPath = paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
workflowNames = c("osm","bdt","wudapt"), location = "Arville", columns = "lcz_primary")

Take a list of sf objects within the session and format them to allow the use of createIntersect and multipleCompare functions.

Description

Take a list of sf objects within the session and format them to allow the use of createIntersect and multipleCompare functions.

Usage

importMultipleLCZvectFromSession(
  sfList,
  workflowNames,
  columns,
  location,
  refCRS = 1
)

Arguments

sfList

the list of LCZ sf objects

workflowNames

a vector containing the workflow names of each sf object of sfList

columns

contain the names of the columns where the sf objects of sfList are stored

location

the name of the location, all files from sfList must regard the same location

refCRS

a number telling which sf of the sfList will be the reference in termes of Coordinate Reference System

Value

returns a list of sf objects, each of them has columns lcz_primary, wf and location

Examples

osm<-importLCZvect(dirPath = paste0(
     system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
     file = "osm_lcz.fgb")
bdt<-importLCZvect(dirPath = paste0(
     system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
 file = "bdt_lcz.fgb")
wudapt<-importLCZvect(dirPath = paste0(
     system.file("extdata", package = "lczexplore"),"/multipleWfs/Arville"),
 file = "wudapt_lcz.fgb", column = "lcz_primary")
sfList<-list(osm = osm, bdt = bdt, wudapt = wudapt)
sfListFormatted<- importMultipleLCZvectFromSession(sfList = sfList,
workflowNames = c("osm", "bdt", "wudapt"),location = "Arville",
columns = c("LCZ_PRIMARY", "LCZ_PRIMARY", "lcz_primary" ))
intersected<-createIntersect(sfList = sfListFormatted, columns = rep("lcz_primary", 3),
workflowNames = c("osm", "bdt", "wudapt"))
multicompare_test<-compareMultipleLCZ(intersected,
columns = c("osm","bdt","wudapt"),trimPerc = 0.5)

In a given directory the function looks different locations as subdirectories and LCZ datafiles in each subdirectory, and load them in a list In each directory, files must have names built as follow : wf_lcz.fileExtension, where wf are the values specified in workflowNames parameter and fileExtension is a file extension known by sf drivers, like fgb, geojson...

Description

In a given directory the function looks different locations as subdirectories and LCZ datafiles in each subdirectory, and load them in a list In each directory, files must have names built as follow : wf_lcz.fileExtension, where wf are the values specified in workflowNames parameter and fileExtension is a file extension known by sf drivers, like fgb, geojson...

Usage

importMultipleLocsLCZvect(
  dirPath = paste0(system.file("extdata", package = "lczexplore"), "/multipleWfs/"),
  workflowNames = c("osm", "bdt", "wudapt"),
  locations = c("Arville", "Redon"),
  fileExtension = ".fgb",
  columns = NULL
)

Arguments

dirPath

is the place where the files are

workflowNames

sets the names of workflows

locations

is the name of the location at which all LCZ are created

fileExtension

is the extensions of the files to load (.fgb is the recommended format)

columns

contains the names of the columns containing the LCZ types

Value

a list of sf, containing one element per location, each of which containing one sf per werkflow

Examples

sfList<-importMultipleLocsLCZvect(dirPath = paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs/"),
workflowNames = c("osm","bdt","wudapt"), location = c("Arville", "Redon"))

Imports a qualitative variable associated with polygons from a geographical dataset (tested : geojson, shp, more to come)

Description

Imports a qualitative variable associated with polygons from a geographical dataset (tested : geojson, shp, more to come)

Usage

importQualVar(
  dirPath = paste0(system.file("extdata", package = "lczexplore"), "/utrfFiles"),
  file = "bdt_utrf_area.fgb",
  output = "sfFile",
  column = "TYPO_MAJ",
  geomID = "ID_RSU",
  confid = "UNIQUENESS_VALUE",
  typeLevels = "",
  drop = TRUE,
  verbose = TRUE
)

Arguments

dirPath

is the path of the directory of the file

file

is the name of the file from which the variable is imported

output

: if sfFile, the function returns an sfFile with the qualitative variable, if bBox, returns a bounding box one can use to crop a raster file or to intersect another sf file

column

indicates the name of the column containing the qualitative variable is imported

geomID

is the name of the column containing the ID of each geom to load. If an empty string, no column is loaded.

confid

is the name of the column containing a confidence indicator, for instance the uniqueness of the LCZ level of each geom, in order to filter geoms,

typeLevels

the levels of the imported qualitative variable

drop

: the default is TRUE, which means all the column are dropped excepted those specified in previous parameters

verbose

allows to hide some messages when set to false.

Value

returns an sf object containing at least the geoms and the qualitative variable, and if specified, columns for the IDs of the geoms and the confidence value of thevalues of the variable.

Examples

utrfRedonBDT<-importQualVar(dirPath=paste0(
system.file("extdata", package = "lczexplore"), "/utrfFiles"),
file="bdt_utrf_area.fgb", column="TYPO_MAJ")
showLCZ(sf=utrfRedonBDT, column="TYPO_MAJ",repr="alter")
utrfRedonOSM<-importQualVar(dirPath=
paste0(system.file("extdata", package = "lczexplore"),"/utrfFiles"),
file="osm_utrf_area.fgb", column="TYPO_MAJ",geomID="ID_RSU",confid="UNIQUENESS_VALUE")
# One can now compare these 2 classifications and store the result in an object...
utrfComparison<-compareLCZ(
 sf1=utrfRedonBDT, column1="TYPO_MAJ", wf1="UTRF.BDT",
 sf2=utrfRedonOSM, column2="TYPO_MAJ", wf2 = "UTRF.OSM",
location = " Redon",exwrite=FALSE,repr="alter")
 # ... then plot the confusion matrix of these two classifications  
print(utrfComparison$matConfPlot)

DEPRECATED: use concatIntersectedLocations with the proper arguments Intersects several sf files for a given location identified by a given directory path and name

Description

DEPRECATED: use concatIntersectedLocations with the proper arguments Intersects several sf files for a given location identified by a given directory path and name

Usage

intersectAlocation(
  dirPath,
  workflowNames = c("osm", "bdt", "wudapt"),
  location,
  addMissingRSUs = TRUE,
  missingGeomsWf = "osm",
  refWf = NULL,
  refLCZ = "Unclassified",
  residualLCZvalue = "Unclassified",
  column = "lcz_primary"
)

Arguments

dirPath

is the directory where the original data are

workflowNames

are the names of the workflows : they are used to identify the files

location

is the name of the location (string)

addMissingRSUs

if TRUE calls the addMissingRSUs function to avoid areas with no geometries

missingGeomsWf

is passed to addMissingRSU function

refWf

is passed to addMissingRSU function

refLCZ

is passed to addMissingRSU function

residualLCZvalue

is passed to addMissingRSU function

column

the column name of the LCZ classification

Details

This function is not generic, it expects the data files to be named wf_rsu_lcz; wf varying among the values of workflownames, and the LCZ columns are expected to be lcz_primary (but lower and upper cases are accepted)

Value

an sf file with values of LCZ from all the input assigned to geometries resulting from intersection of all input geometries

Examples

# deprecated : use concatIntersectedLocations with the proper arguments

Manages the levels and the colors of the LCZ columns

Description

Manages the levels and the colors of the LCZ columns

Usage

levCol(sf, column, drop = FALSE, useStandCol = FALSE, ...)

Arguments

sf

is the input sf file

column

is the column that contains the data

drop

is set to TRUE if one wants to drop unused levels, in case column is a factor with unused levels

useStandCol

is set to TRUE if one wants recognized standard levels to be associated with standard colors. Default is FALSE

...

other parameters specified, expected a vector of levels and a vector of colors whose name must begin with colors. Other cases are handled to enhance usability.

Value

output is a list containing levelsColors, a named vector, which names are the levels present in the data and which values are the associated colors, and case, a string specifying what case was encountered when producing the levels and colors.

Examples

# levCol2 is not to be used directly by user. It deals with levels and colors provided by the user

Creates sectors and groups for the drawChordDiagram function

Description

Creates sectors and groups for the drawChordDiagram function

Usage

makeSectorsAndGroups(weightedFluxIn, groupOrder = NULL)

Arguments

weightedFluxIn

is typically the output of the function createWeightedFlux, and is expected to contain the following columns orig, dest and weightedFlux, whose names are quite self explanatory : orig is the origin LCZ type, dest is the destination LCZ type and weightedFlux is the percentage of area transfered from orig to dest

groupOrder

allows to specify in which order groups are visualized, usually the ones specified in labelMAtch argument of drawChordDiagram function

Value

a list containing vectors and groups for a chord diagram

Produces a confusion matrix between two sets of lcz on the same area (geoms do not need to be the same)

Description

Produces a confusion matrix between two sets of lcz on the same area (geoms do not need to be the same)

Usage

matConfLCZ(
  sf1,
  column1,
  sf2,
  column2,
  typeLevels = .lczenv$typeLevelsDefault,
  plotNow = FALSE,
  wf1 = "Reference",
  wf2 = "Alternative",
  sfInt = NULL,
  drop = FALSE,
  ...
)

Arguments

sf1

is the sf dataset containing the first lcz classification

column1

is the column of the first data set containing the lcz to be compared

sf2

is the sf dataset containing the second lcz classification

column2

is the column of the second data set containing the lcz to be compared

typeLevels

by default the levels of lcz incoded from 1 to 10 and 101 to 107.

plotNow

shows the graphical representation of the confusion matrix

wf1

the name of the workflow used to produce data from sf1

wf2

the name of the workflow used to produce data from sf2

sfInt

allows to produce the confusion matrix directly on the intersected sf object if it was produced before

drop

if TRUE the empty LCZ types are dropped When comparing othe variable, like grouped LCZ, the grouped levels have to be specified.

...

a set of unspecified arguments, for instance when the produceAnalysis function calls other functions

Details

Most of the time this function will not be called directly by the user but by the compareLCZ function

Value

returns an object called matConfOut which contains matConfLong, a confusion matrix in a longer form, which can be written in a file by the compareLCZ function and is used by the geom_tile function of the ggplot2 package. matConfPlot is a ggplot2 object showing the confusion matrix. If plot=TRUE, it is also directly plotted marginAreas contains the sums of each LCZ area percAgg is the general agreement between the two sets of LCZ, expressed as a percentage of the total area of the study zone

Examples

matConfRedonBDTOSM <- matConfLCZ(sf1=redonBDT, column1 = 'LCZ_PRIMARY',
sf2 = redonOSM, column2 = 'LCZ_PRIMARY', plotNow = TRUE)

Compares two LCZ classifications on several locations

Description

Compares two LCZ classifications on several locations

Usage

matConfLCZGlob(
  filePath = "",
  inputDf,
  wf1,
  wf2,
  geomID1 = "",
  column1,
  confid1 = "",
  geomID2 = "",
  column2,
  confid2 = "",
  sep = ";",
  typeLevels = "",
  plot = TRUE,
  ...
)

Arguments

filePath

: the full path to the inputDfto import

inputDf

: if filePath is an empty string inputDf is the name of an R dataframe containing the data

wf1

: a string indicating the origin of the LCZ classification 1

wf2

: a string indicating the origin of the LCZ classification 1

geomID1

is the name of the column containing the ID of each spatial units from the first type of datasets in \'inputDf\', it allows to post-treat some of the units

column1

is the name of the column containing the Local Climatic Zone of the first type of datasets in the \'file\' dump file be analyzed

confid1

is the name of the column measuring the confidence given to the LCZ level in column1

geomID2

is the name of the column containing the ID of each spatial units from the second type of datasets in \'inputDf\'

column2

see column1 but for the second type of datasets

confid2

is the name of the column measuring the confidence given to the LCZ level in column2

sep

: the seperator used in the csv file

typeLevels

: by default levels of the LCZ classification are built reading the data, but one can input a character string vector of levels, for instance to produce several graphs with the same levels or levels in a specific order

plot

if TRUE, then confusion matrix plot is shown, else it is just returned in the matConfOut object

...

other parameters that may be passed from a function calling matConfLCZGlob

Value

matConfOut is a list containing : matconf, the confusion matrix in its longer form ; matConfPlot, a ggplot2 plot of said matrix ; areas, the summed area per levels for both LCZ classification ; and pourcAcc, the general agreement between classifications expressed in percent of areas

Examples

matConfLCZGlob(filePath= paste0(
system.file("extdata", package = "lczexplore"),"/bdtopo_2_2_osm.csv"),
file="bdtopo_2_2_osm.csv", wf1="bdt", wf2="osm",
geomID1="ID_RSU", column1="LCZ_PRIMARY", confid1="LCZ_UNIQUENESS_VALUE",
geomID2="ID_RSU.1", column2="LCZ_PRIMARY.1", confid2="LCZ_UNIQUENESS_VALUE.1",
sep=";",
typeLevels="", plot=TRUE)
testSource<-read.csv(paste0(
system.file("extdata", package = "lczexplore"),
"/bdtopo_2_2_osm.csv"), sep=";",header=TRUE)
matConfLCZGlob(filePath="",
inputDf = testSource, wf1="bdt", wf2="osm",
geomID1="ID_RSU", column1="LCZ_PRIMARY", confid1="LCZ_UNIQUENESS_VALUE",
geomID2="ID_RSU.1", column2="LCZ_PRIMARY.1", confid2="LCZ_UNIQUENESS_VALUE.1",
sep=";",
typeLevels="", plot=TRUE)

Plots a tile graph of a confusion matrix between two sets of lcz on the same area

Description

Plots a tile graph of a confusion matrix between two sets of lcz on the same area

Usage

matConfPlot(
  matConfLong,
  column1 = "lcz_primary",
  column2 = "lcz_primary.1",
  marginAreas = NULL,
  agreeColumn = "agreePercArea",
  wf1 = "reference",
  wf2 = "alternative"
)

Arguments

matConfLong

is a dataframe for the matrice of confusion/agreement, in the longform : first column is the LCZ level of the first workflow, second the level of the second workflow and the third column the percentage of surface of the level of the first classification classified in the level of the second classification

column1

is the name of the first classification

column2

is the name of the second classification

marginAreas

are the percentage of areas for LCZ types for both workflows (an output of matConfLCZ)

agreeColumn

is the name where the agreement between classification is stored

wf1

is the name of the first workflow (for labels)

wf2

is the name of the second workflow (for labels)

Details

Most of the time this function will not be called directly by the user but by the compareLCZ function

Value

returns a plot of a matrice of confusion importFrom forcats fct_recode

Examples

matConfRedonBDTOSM <- matConfLCZ(sf1 = redonBDT, column1 = 'LCZ_PRIMARY',
                                sf2 = redonOSM, column2 = 'LCZ_PRIMARY', plot = TRUE)
matConfLong <- matConfRedonBDTOSM$matConf
marginAreas <- matConfRedonBDTOSM$areas
matConfPlot(matConfLong,
           column1 = "LCZ_PRIMARY", column2 = "LCZ_PRIMARY.1", agreeColumn = "agreePercArea",
           wf1 = "reference", wf2 = "alternative", marginAreas = marginAreas)

Plots a sankey graph between two LCZ workflows

Description

Plots a sankey graph between two LCZ workflows

Usage

plotSankeyfiedLCZ(
  sankeyfied,
  plotNow = TRUE,
  colorMap = NULL,
  v_space = "auto"
)

Arguments

sankeyfied

is the data as produced by the prepareSankeyLCZ function

plotNow

is set to TRUE by default, if set to FAULT the graph is not plotted.

colorMap

is a vector of colors whose names cover the valus of the nodes in sankeyfied

v_space

allows a separation between LCZ type bars

Value

returns a sankey plot of LCZ workflows on the same areas

Examples

dirList<-list.dirs(paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs"))[-1]
allLocIntersected<-concatIntersectedLocations(
dirList = dirList, locations = c("Redon", "Arville"))
testSankey<-prepareSankeyLCZ(intersectedDf = allLocIntersected
 , wf1 = "wudapt", wf2 = "osm")
testSankeyPlot<-plotSankeyfiedLCZ(
sankeyfied = testSankey, plotNow=TRUE)

For a given LCZ sf object, plots the number of geometries and an average area indicator per level of LCZ

Description

For a given LCZ sf object, plots the number of geometries and an average area indicator per level of LCZ

Usage

plotSummarisedRSUs(
  summarisedSfIn,
  workflowNames = c("wudapt", "osm", "bdt"),
  plotNow = TRUE,
  graphPath = ""
)

Arguments

summarisedSfIn

the output of summariseRSU function

workflowNames

contain the names of the workflows

plotNow

: if TRUE the plot will be displayed in the session

graphPath

: a valid directory path where th plot will be saved (for now an empty string to avoid saving in the working directory)

Value

the number of geometries (Reference Spatial units or RSUs) and their mean area per level of LCZ, and the same after agregatting geometries with same level of LCZ which touch each other

Examples

dirPath<-paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs")
allLocAllWfs<-importConcatMultipleLocsLCZvect(
 dirPath = dirPath,
    locations = c("Redon", "Arville"),
    workflowNames = c("osm","bdt","wudapt"),
 missingGeomsWf= "osm",
 refWf = NULL,
 refLCZ = "Unclassified",
 residualLCZvalue = "Unclassified",
 column = "lcz_primary"
 )
summarisedRSUs<-summariseRSUs(
     allLocAllWfs,
     aggregatingColumns = c("wf", "lcz_primary"))
plotSummarisedRSUs(
     summarisedSfIn = summarisedRSUs,
     workflowNames = c("wudapt"= "wud", "osm", "bdt"))

Prepares the data to produce a sankey graph between two LCZ workflows

Description

Prepares the data to produce a sankey graph between two LCZ workflows

Usage

prepareSankeyLCZ(intersectedDf, wf1, wf2, colorMap)

Arguments

intersectedDf

is an sf object or a data frame which contains lcz values for at least two workflows on the same geometries, and the area of the geometries

wf1

is the column name where the LCZ value of the first workflow are stored

wf2

wf1 is the column name where the LCZ value of the first workflow are stored

colorMap

a vector containing colors and whose names are the levels of the data to plot

Value

an object to feed plotSankeyLCZ

Examples

dirPath<-paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs")
allLocConcatenated<-importMultipleLocsLCZvect(
  dirPath = dirPath, locations = c("Arville", "Redon"))
allLocIntersected<-createIntersect(allLocConcatenated, columns = rep("lcz_primary", 4),
workflowNames = c("osm","bdt","wudapt"))
testSankey<-prepareSankeyLCZ(intersectedDf = allLocIntersected
 , wf1 = "wudapt", wf2 = "osm")

RedonBDT

Description

LCZ for Redon as produced by GeoClimate on BDTOPO data #'

Usage

redonBDT

Format

An sf object with 3 variables and a geometry :

ID_RSU

index identifying the Reference spatial unit

LCZ_PRIMARY

Local Climate Zone encoded according to Stewad and Oke approach, 1 to 10 then 101 to 107

LCZ_UNIQUENESS_VALUE

indicates how the LCZ_PRIMARY value was likely to be the only one suitable for this RSU, similar to a confidence value

geometry

containes the geometry of the RSU for all the spatial operations allowed by the sf class

Source

"https://github.com/orbisgis/geoclimate"

RedonOSM

Description

RedonOSM

Usage

redonOSM

Format

LCZ for Redon as produced by GeoClimate on OpenStreetMap data

ID_RSU

index identifying the Reference spatial unit

LCZ_PRIMARY

Local Climate Zone encoded according to Stewad and Oke approach, 1 to 10 then 101 to 107

LCZ_UNIQUENESS_VALUE

indicates how the LCZ_PRIMARY value was likely to be the only one suitable for this RSU, similar to a confidence value

geometry

containes the geometry of the RSU for all the spatial operations allowed by the sf class

Source

"https://github.com/orbisgis/geoclimate"

Produces a simple representation of the LCZ contained in an sf file with non standard LCZ type encoding

Description

Produces a simple representation of the LCZ contained in an sf file with non standard LCZ type encoding

Usage

showAlterLCZ(
  sf,
  title = "",
  wf = "",
  column = "LCZ_PRIMARY",
  drop = FALSE,
  useStandCol = FALSE,
  tryGroup = TRUE,
  plotNow = TRUE,
  labelType = "long",
  repr = "alter",
  naAsUnclassified = TRUE,
  noPercAlter = FALSE,
  addBorders = FALSE,
  ...
)

Arguments

sf

is the sf file which contains the LCZ column to be plotted.

title

allows the user to set the title of the plot

wf

is the workflow used to produced the LCZ. "bdt" and "osm" indicate that LCZ were produced by GeoClimate using the BD_TOPO_V2 or the Open Street Map data as input, respectively. If the LCZ were produced by WUDAPT, use "wudapt".

column

is the column that contains the LCZ.

drop

indicates if you want to show the levels present in no geometry.

useStandCol

is set to TRUE implies that any levels detected as a standard LCZ level will receive the standard associated color

tryGroup

is set to TRUE when one wants to group and plot on the fly

plotNow

is inherited from showLCZ, needs to be specified so it is not considered as part of ... arguments which contain grouping and color arguments

labelType

is inherited from showLCZ, same as previous argument

repr

is inherited from showLCZ, same as previous argument

naAsUnclassified

if TRUE, affects Unclassified value to NAs in the LCZ column

noPercAlter

allows to not show the percentage area in the alter representation

addBorders

if TRUE the borders of the geometries are visible

...

these dynamic dots allow you to pass arguments to specify levels expected in your dataset and colors associated to these levels when not in the standard representation. You can pas your levels through a vector and you colors through another vector called colors. For more details about this, read the "lcz_explore_alter" vignette.

Examples

# On grouped data, use the alter value for the repr argument.
redonBDTgrouped<-groupLCZ(redonBDT,column="LCZ_PRIMARY",
urban=c("1","2","3","4","5","6","7","8","9"),
industry="10", vegetation=c("101","102","103","104"),
impervious="105",pervious="106",water="107")
# For repr="alter", you can specify colors and levels this way :
showLCZ(redonBDTgrouped,column="grouped",repr="alter",
LCZlevels=c("urban","industry","vegetation","impervious","pervious","water"),
colors=c("red","black","green","grey","burlywood","blue"),wf="BD TOPO")

Produces a simple representation of the LCZ contained in an sf file

Description

Produces a simple representation of the LCZ contained in an sf file

Usage

showLCZ(
  sf,
  title = "",
  wf = "",
  column = "LCZ_PRIMARY",
  repr = "standard",
  drop = FALSE,
  useStandCol = FALSE,
  tryGroup = TRUE,
  naAsUnclassified = TRUE,
  noPercAlter = FALSE,
  plotNow = TRUE,
  addBorders = FALSE,
  labelType = "long",
  ...
)

Arguments

sf

is the sf file which contains the LCZ column to be plotted.

title

allows the user to set the title of the plot

wf

is the workflow used to produced the LCZ. "bdt" and "osm" indicate that LCZ were produced by GeoClimate using the BD_TOPO_V2 or the Open Street Map data as input, respectively. If the LCZ were produced by WUDAPT, use "wudapt".

column

is the column that contains the LCZ.

repr

indicates if the sf dataset contains standarde LCZ levels or grouped LCZ. If "standard" then an optimal set of colors is used to produce the plotted map. Else, colors can be specified with the colors argument.

drop

indicates if you want to show the levels present in no geometry.

useStandCol

is set to TRUE implies that any levels detected as a standard LCZ level will receive the standard associated color

tryGroup

is set to TRUE when one wants to group and plot on the fly

naAsUnclassified

if TRUE, affects Unclassified value to NAs in the LCZ column

noPercAlter

allows to not show the percentage area in the alter representation

plotNow

if FALSE the plot is generated but not shown (needs to be stored in an object)

addBorders

if TRUE the borders of the geometries are visible

labelType

in the standard representation, this value can take the values "long" (number, name and percentage area for each LCZ types), "short" (value and percentage), "very short" (only number and percentage), "no perc" (no area percentage).

...

these dynamic dots allow you to pass arguments to specify levels expected in your dataset and colors associated to these levels when not in the standard representation. You can pas your levels through a vector and you colors through another vector called colors. For more details about this, read the "lcz_explore_alter" vignette.

Value

return the plot of the LCZ levels

Examples

# On original LCZ levels, use the standard value for the repr argument.
showLCZ(redonBDT, column="LCZ_PRIMARY", repr="standard")
# On grouped data, use the alter value for the repr argument.
redonBDTgrouped<-groupLCZ(redonBDT,column="LCZ_PRIMARY",
urban=c("1","2","3","4","5","6","7","8","9"),
industry="10", vegetation=c("101","102","103","104"),
impervious="105",pervious="106",water="107")
# For repr="alter", you can specify colors and levels this way :
showLCZ(sf = redonBDTgrouped, column = "grouped", repr = "alter",
LCZlevels = c("urban","industry","vegetation","impervious","pervious","water"),
colors = c("red","black","green","grey","burlywood","blue"), wf="BD TOPO")

Produces a simple representation of the LCZ contained in an sf file when standard LCZ type format is used

Description

Produces a simple representation of the LCZ contained in an sf file when standard LCZ type format is used

Usage

showStandardLCZ(
  sf,
  title = "",
  wf = "",
  column = "LCZ_PRIMARY",
  repr = "standard",
  drop = FALSE,
  naAsUnclassified = TRUE,
  addBorders = FALSE,
  labelType = "long",
  ...
)

Arguments

sf

is the sf file which contains the LCZ column to be plotted.

title

allows the user to set the title of the plot

wf

is the workflow used to produced the LCZ. "bdt" and "osm" indicate that LCZ were produced by GeoClimate using the BD_TOPO_V2 or the Open Street Map data as input, respectively. If the LCZ were produced by WUDAPT, use "wudapt".

column

is the column that contains the LCZ.

repr

indicates if the sf dataset contains standarde LCZ levels or grouped LCZ. If "standard" then an optimal set of colors is used to produce the plotted map. Else, colors can be specified with the colors argument.

drop

indicates if you want to show the levels present in no geometry.

naAsUnclassified

if TRUE, affects Unclassified value to NAs in the LCZ column

addBorders

if TRUE the borders of the geometries are visible

labelType

in the standard representation, this value can take the values "long" (number, name and percentage area for each LCZ types), "short" (value and percentage), "very short" (only number and percentage), "no perc" (no area percentage).

...

these dynamic dots allow you to pass arguments to specify levels expected in your dataset and colors associated to these levels when not in the standard representation. You can pas your levels through a vector and you colors through another vector called colors. For more details about this, read the "lcz_explore_alter" vignette.

Value

return the plot of the LCZ levels

Examples

# On original LCZ levels, use the standard value for the repr argument.
showLCZ(redonBDT, column="LCZ_PRIMARY", repr="standard")

Detects standard LCZ levels and associate standard colors to them

Description

Detects standard LCZ levels and associate standard colors to them

Usage

standLevCol(levels, colors = "", useStandCol = FALSE)

Arguments

levels

is the vector of the LCZ levels present in a dataset

colors

is the vector of colors one intends to use to visualize the LCZ of the dataset

useStandCol

allows to say if standard colors should replace user specified colors when standard levels are detected.

Value

output is a list containing levelColors, a named vector, which names are the levels present in the data and which values are the associated colors, and case, a string spcifying what case was encountered when producing the levels and colors.

Examples

# standLevCol is not to be used directly by user. 
# It deals with levels and colors provided by the user and 
# tries to replace user color by standard color 
# when a standard level of LCZ is recognized

For a given LCZ sf object, returns the number of geometries and their mean area per LCZ type

Description

For a given LCZ sf object, returns the number of geometries and their mean area per LCZ type

Usage

summariseRSUs(sfIn, aggregatingColumns = "lcz_primary", trimValue = 0)

Arguments

sfIn

an sf objects that contains the geometry and LCZ levels

aggregatingColumns

should be the name of the LCZ types column, but can be any factor variable names

trimValue

a trim parameter to feed the mean function in order to avoid letting artificially small or big geometries to influence the average area results

Value

the number of geometries (Reference Spatial units or RSUs) and their mean area per level of LCZ, and the same after agregatting geometries with same level of LCZ which touch each other

Examples

dirPath<-paste0(
system.file("extdata", package = "lczexplore"),"/multipleWfs")
allLocAllWfs<-importConcatMultipleLocsLCZvect(
 dirPath = dirPath, locations = c("Redon", "Arville"),
workflowNames = c("osm","bdt","wudapt"),
 missingGeomsWf= "osm",
 refWf = NULL,
 refLCZ = "Unclassified",
 residualLCZvalue = "Unclassified",
 column = "lcz_primary"
)
summarisedRSUs<-summariseRSUs(allLocAllWfs, aggregatingColumns = c("wf", "lcz_primary"))

# After aggregating adjacent RSU of same LCZ type
ASUallLocAllWfs <- aggregateRSUsByLCZ(
     allLocAllWfs,
     column = "lcz_primary", wfColumn = "wf",
     locationColumn = "location", aggregateBufferSize = 0.5)
summarisedASUs<-summariseRSUs(ASUallLocAllWfs, aggregatingColumns = c("wf", "lcz_primary"))

plotSummarisedRSUs(
     summarisedSfIn = summarisedASUs,
     workflowNames = c("wud" = "wudapt", "osm", "bdt"))

From the output of compare multiple, cmputes which workflows agree the most regarding the area of agreement

Description

From the output of compare multiple, cmputes which workflows agree the most regarding the area of agreement

Usage

workflowAgreeAreas(sfMultiCompLong)

Arguments

sfMultiCompLong

the sfLong output of compareMultipleLCZ function

Value

the pairwise agreement between workflows, sorted by decreasing agreeing areas

Examples

sfList<-importMultipleLCZvect(dirPath = paste0(
system.file("extdata", package = "lczexplore"),
"/multipleWfs/Arville"),
workflowNames = c("osm","bdt","wudapt"), location = "Arville")
ArvilleIntersect <- createIntersect(
 sfList = sfList, columns = rep("lcz_primary", 4),  
 workflowNames = c("osm","bdt","wudapt"))
ArvilleMultipleComparison<-compareMultipleLCZ(
 sfInt = ArvilleIntersect,
 columns = c("osm","bdt","wudapt"),
 trimPerc = 0.5)
ArvilleWorkflowAgreement<-workflowAgreeAreas(ArvilleMultipleComparison$sfIntLong)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.