rafapereirabr
commented
6 months ago Your map above only shows the result for walking. You're saying that the results for public transport look exactly the same. Correct?
This is likely related to question 6 in our FAQ.
on another point 1, you should run options(java.parameters = "-Xmx16G") before loading r5r with library(r5r)
on another point 2, your maps for 60 and 90 min. show a very clear discontinuity in accessibility levels, with a square shape. I supect that your OSM data does not cover the entire region of interest, which I assume includes all areas colored in blue
JideDanalyst
Hello @rafapereirabr Thanks for the other time on the accessibility exercise. In calculating accessibility, I followed the steps you outlined, which included merging the accessibility data with the study area boundary file with geometry, and then plotting an isochrone map to display accessible jobs based on cutoff times. Specifically, I analyzed accessibility on a weekday at 9:00 AM using two different travel modes: walking and taking the bus.
Despite changing the mode of transportation and analyzing different time slots (9:00 AM and 6:00 PM), the accessibility calculations and resultant maps remain identical. Based on my understanding, and as suggested in your book, variations in mode and time should yield different results. Could you please shed some light on this issue? Is it possible that I have overlooked a crucial step, or is it expected that the results remain consistent despite these changes? Your expert insights would be precious to me. Thank you for your time and assistance.
Codes: library(r5r) library(tidyverse) library(sf) library(data.table) library(ggplot2) library(mapview) library(rJava)
options(java.parameters = "-Xmx16G") path = "C:\Users\JUMIA-4237\Desktop\U_clean" r5r_core <- setup_r5(data_path = path) od_zones1 <- st_read(file.path(path,"Zone_3.gpkg")) od_zones1 %>% mapview() od_zones <- st_read(file.path(path,"zone_re.gpkg")) od_zones %>% mapview() od_points_sf <- st_read(file.path(path,"od_points_5.gpkg")) od_points_sf %>% mapview(zcol="Jobs") names(od_points_sf) transit <- transit_network_to_sf(r5r_core) transit$routes %>% mapview(zcol = "mode") access_walk_df <- accessibility(r5r_core, origins = od_zones, destinations = od_points_sf, mode = c("BUS","transit"), opportunities_colname = "Jobs", departure_datetime = as.POSIXct("23-05-2023 09:00:00", format = "%d-%m-%Y %H:%M:%S"), cutoffs = c(15, 30, 60, 90), verbose = FALSE)