knn_street_segments.Rmd

---
title: "Chapel Hill Crash Model R Code"
author: "Jason A. Jones"
date: "April 1, 2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


```{r}
library(tidyverse)
library(sf)
library(RANN)
```


```{r}
pedestrian_crashes <- read_sf("https://www.chapelhillopendata.org/explore/dataset/pedestrian-crashes-chapel-hill-region/download/?format=geojson&timezone=America/New_York")

bicycle_crashes <- read_sf("https://www.chapelhillopendata.org/explore/dataset/bicycle-crash-data-chapel-hill-region/download/?format=geojson&timezone=America/New_York")

chapel_hill_streets <- read_sf("https://www.chapelhillopendata.org/explore/dataset/streets/download/?format=geojson&timezone=America/New_York")
```


```{r}

street_nodes_sf <- chapel_hill_streets %>%
  group_by(objectid) %>%
  st_cast("POINT")


street_nodes_df <- data.frame(st_coordinates(street_nodes_sf), street_nodes_sf$objectid) %>%
  rename(objectid = street_nodes_sf.objectid) %>%
  mutate(seg = 1:nrow(.))


closest <- data.frame(nn2(street_nodes_df[,1:2], st_coordinates(pedestrian_crashes), k = 1))


merged <- closest %>%
  left_join(street_nodes_df, by = c("nn.idx" = "seg")) %>%
  group_by(objectid) %>%
  summarise(count = n()) %>%
  ungroup() %>%
  right_join(chapel_hill_streets)

merged$count[is.na(merged$count)] <- 0



st_write(merged, dsn = "geojson/street_counts.geojson")


merged %>%
  ggplot() +
  geom_sf(data = chapel_hill_streets, color = "grey") +
  geom_sf(color = "red") +
  theme(panel.background = element_blank())


```