.Rhistory

library(sf)
library(sp)
library(tidyverse)
library(leaflet)
library(mapview)
hotspots <- read_sf(dsn = "Data", layer = "CUCI_hotspots")
hotspots <- read_sf(dsn = "Data", layer = "CUCI_hotspots") %>%
filter(city == "Lilongwe")
hotspots
st_write(hotspots, "Data/enumeration_areas.shp")
st_crs(hotspots)
hotspots_meters <- st_transform(hotspots, 20936)
head(hotspots_meters)
str(hotspots)
head(hotspots)
hotspots_meters
read.csv("data/survey.csv")
class(survey)
survey <- read.csv("data/survey.csv")
head(survey)
class(survey)
survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326, remove = TRUE)
survey_sf <- survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326, remove = TRUE)
survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326)
survey_sf <- survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326)
extent <- st_bbox(hotspots) # the x and y axis limits to the graphs
print(extent)
extent <- st_bbox(hotspots) # the x and y axis limits to the graphs
print(extent)
m <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]]) %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
weight = 2,
radius = 10)
m
#--------#
# set up #
#--------#
# load packages
library(sf)
library(sp)
library(tidyverse)
library(leaflet)
library(mapview)
#' tidyverse = includes dplyr primary data processing packages in R
#' sf = simple features; basically just a dataframe with a geometry column, can use all dplyr functions on it
#' sfc = column of geometries
#' sfg = simple feature geometry (simple geometry)
#' types of sfg = points, polygons, etc.
#' crs = coordinate reference system (each geometry needs a CRS)
#' https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/coordinate_reference_systems.html
#' #' https://r-spatial.github.io/sf/articles/sf1.html
#' leaflet = a javascript interactive mapping "program"
#' https://rstudio.github.io/leaflet/
#' import EAs
#' read_sf = read in simple features - works with shapefiles, csvs, etc.
hotspots <- read_sf(dsn = "Data", layer = "enumeration_areas")
str(hotspots)
head(hotspots)
#' look at CRS
st_crs(hotspots)
st_set_crs(hotspots, 4326) # example of estting to lat lon CRS
#' import survey data and convert it to a sf object
survey <- read.csv("data/survey.csv")
head(survey)
class(survey)
#' convert survey to sf
survey_sf <- survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326)
# create basic map
extent <- st_bbox(hotspots) # the x and y axis limits to the graphs
print(extent)
leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]]) %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
weight = 2,
radius = 10)
m <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]]) %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
color = "red",
weight = 2,
radius = 10)
print(m)
survey %>%
st_join(hotspots, left = TRUE)
survey_sf %>%
st_join(hotspots, left = TRUE)
#--------#
# set up #
#--------#
# load packages
library(sf)
library(sp)
library(tidyverse)
library(leaflet)
library(mapview)
#' tidyverse = includes dplyr primary data processing packages in R
#' sf = simple features; basically just a dataframe with a geometry column, can use all dplyr functions on it
#' sfc = column of geometries
#' sfg = simple feature geometry (simple geometry)
#' types of sfg = points, polygons, etc.
#' crs = coordinate reference system (each geometry needs a CRS)
#' https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/coordinate_reference_systems.html
#' #' https://r-spatial.github.io/sf/articles/sf1.html
#' leaflet = a javascript interactive mapping "program"
#' https://rstudio.github.io/leaflet/
#' import EAs
#' read_sf = read in simple features - works with shapefiles, csvs, etc.
hotspots <- read_sf(dsn = "Data", layer = "enumeration_areas")
str(hotspots)
head(hotspots)
#' look at CRS
st_crs(hotspots)
st_set_crs(hotspots, 4326) # example of estting to lat lon CRS
#' import survey data and convert it to a sf object
survey <- read.csv("data/survey.csv")
head(survey)
class(survey)
#' convert survey to sf
survey_sf <- survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326)
# create basic map
extent <- st_bbox(hotspots) # the x and y axis limits to the graphs
print(extent)
m <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]]) %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
color = "red",
weight = 2,
radius = 10)
print(m)
survey_sf
hotspots
survey_sf %>%
st_join(hotspots, left = TRUE)
survey_sf %>%
st_join(hotspots, left = TRUE) %>%
mutate(in_ea = if_else(is.na(hs_name), "No", "Yes"))
survey_color <- colorFactor(c("Red", "Green"), domain = c("No", "Yes"))
# create map for each city and save
m <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent_city[[1]],
lat1 = extent_city[[2]],
lng2 = extent_city[[3]],
lat2 =  extent_city[[4]]) %>%
addPolygons(
data = hotspots_city,
color = ~survey_color(in_ea),
weight = 1)
basemap <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]])
print(basemap)
# chack that things look ok
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
color = "red",
weight = 2,
radius = 10)
basemap %>%
addPolygons(
data = hotspots_city,
color = ~survey_color(in_ea),
weight = 1) %>%
addCircles(
data = survey_city,
color = ~survey_color(in_hs),
weight = 2,
radius = 10)
basemap %>%
addPolygons(
data = hotspot,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_hs),
weight = 2,
radius = 10)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_hs),
weight = 2,
radius = 10)
#--------#
# set up #
#--------#
# load packages
library(sf)
library(sp)
library(tidyverse)
library(leaflet)
library(mapview)
#' tidyverse = includes dplyr primary data processing packages in R
#' sf = simple features; basically just a dataframe with a geometry column, can use all dplyr functions on it
#' sfc = column of geometries
#' sfg = simple feature geometry (simple geometry)
#' types of sfg = points, polygons, etc.
#' crs = coordinate reference system (each geometry needs a CRS)
#' https://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/coordinate_reference_systems.html
#' #' https://r-spatial.github.io/sf/articles/sf1.html
#' leaflet = a javascript interactive mapping "program"
#' https://rstudio.github.io/leaflet/
#' import EAs
#' read_sf = read in simple features - works with shapefiles, csvs, etc.
hotspots <- read_sf(dsn = "Data", layer = "enumeration_areas")
str(hotspots)
head(hotspots)
#' look at CRS
st_crs(hotspots)
st_set_crs(hotspots, 4326) # example of estting to lat lon CRS
#' import survey data and convert it to a sf object
survey <- read.csv("data/survey.csv")
head(survey)
class(survey)
#' convert survey to sf
survey_sf <- survey %>%
st_as_sf(coords = c("gps_lat", "gps_lon"), crs = 4326)
# create basemap
extent <- st_bbox(hotspots) # the x and y axis limits to the graphs
print(extent)
basemap <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
fitBounds(
lng1 = extent[[1]],
lat1 = extent[[2]],
lng2 = extent[[3]],
lat2 =  extent[[4]])
print(basemap)
# chack that things look ok
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_sf,
color = "red",
weight = 2,
radius = 10)
#---------------------------------#
# check if survey is in a hotspot #
#---------------------------------#
# join the survey data with the hotspots; if hotspot info is NA then the survey is outside of a hotspot
survey_hs <- survey_sf %>%
st_join(hotspots, left = TRUE) %>%
mutate(in_ea = if_else(is.na(hs_name), "No", "Yes"))
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_hs),
weight = 2,
radius = 10)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 10)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 20)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 50)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 1000)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 100)
mapshot(
m_final,
"output/map.html")
m_final <- basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 300)
# save maps
mapshot(
m_final,
"output/map.html")
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 300) %>%
addLegend(
data = survey_hs,
color = survey_color
)
basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 300) %>%
addLegend(
data = survey_hs,
pal = survey_color,
values = c("No", "Yes")
)
m_final <- basemap %>%
addPolygons(
data = hotspots,
weight = 1) %>%
addCircles(
data = survey_hs,
color = ~survey_color(in_ea),
weight = 2,
radius = 300,
fillOpacity = 1) %>%
addLegend(
data = survey_hs,
pal = survey_color,
values = c("No", "Yes"),
title = "In EA?")
m_final
mapshot(
m_final,
"output/map.html")