cherry-blossoms-analysis's Introduction

Cherry blossoms data

This repo contains the data and map tile processing used in hrecht/cherry-blossoms for https://www.hrecht.com/cherry-blossoms/.

Data sources

2024 cherry blossom tree dataset from Casey Trees
Metro lines and Metro stations from Open Data DC. I made updates based on the latest rail map from WMATA.
- Note: These files had some incorrect and outdated information as of analysis time, mostly related to the Yellow Line changes in 2023. I emailed the Open Data DC team to flag this information and they were actively working on updating the files as of mid-March 2024.
- I manually edited the yellow line route in QGIS to end at Mt Vernon Square (since updated in the Open Data DC file.)
- I entered station rail line changes and station name splits into data/metro/metro-stations-corrections.csv and incorporated them with scripts/01-get-wmata-geo.R. Specifically, I updated the station rail line information and split out the long station names into name_short and name_subtitle for display purposes. For example, the U Street/African-Amer Civil War Memorial/Cardozo station has name_short: U Street and name_subtitle: African-Amer Civil War Memorial/Cardozo. The original file from DC still listed the green and yellow lines as serving this station, but it is now green line only.
State and water boundaries from Census TIGER/Line

Requirements

R for data analysis. Key packages used include some of the tidyverse for cleaning, sf for spatial analysis, and ggplot2 for mapping.

Building map tiles

Tiles for the interactive basemap are downloaded and built in scripts/00-make-basemap.sh. Install dependencies with homebrew:

brew install wget

Planetiler to build map tiles. Install Java 21+, necessary to run planetiler.

brew install --cask temurin

Save planetiler into the tiles subfolder (gitignored).

wget https://github.com/onthegomap/planetiler/releases/latest/download/planetiler.jar

Install tippecanoe for mbtiles merging.

brew install tippecanoe

Install pmtiles for clipping tiles to bounding box and converting into pmtiles format for the interactive map.

brew install pmtiles

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cherry-blossoms-analysis's Issues

{arcgislayers} in case you want to use arcgis hub data in the future :)

This analysis was super cool! I noticed you hand crafted and processed Feature Layer queries :)

In case you want to use data like this in the future you can make it a little bit easier by using the arcgislayers package!

library(arcgis)
#> Attaching core arcgis packages:
#> → arcgisutils v0.2.0.9000
#> → arcgislayers v0.2.0

# create a reference to the feature layer
cherry_blossoms <- arc_open(
  "https://services2.arcgis.com/j23KFYd23hRWewtZ/arcgis/rest/services/CHERRY_BLOSSOM_DATA_FINAL/FeatureServer/0"
)

# read all features as sf in parallel
all_trees <- arc_select(cherry_blossoms)

# preview
head(all_trees)
#> Simple feature collection with 6 features and 6 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -8577336 ymin: 4704984 xmax: -8572557 ymax: 4709696
#> Projected CRS: WGS 84 / Pseudo-Mercator
#>   FID                      SciName         CmmnName Species  Genus Cultivar
#> 1   1               Prunus species      Cherry Spp.  <Null> Prunus         
#> 2   2             Prunus yedoensis   Yoshino Cherry  <Null> Prunus         
#> 3   3 Prunus serrulata 'Snowgoose' Snowgoose Cherry  <Null> Prunus         
#> 4   4             Prunus yedoensis   Yoshino Cherry  <Null> Prunus         
#> 5   5               Prunus species      Cherry Spp.  <Null> Prunus         
#> 6   6               Prunus species      Cherry Spp.  <Null> Prunus         
#>                   geometry
#> 1 POINT (-8572557 4704984)
#> 2 POINT (-8572657 4705214)
#> 3 POINT (-8572620 4705181)
#> 4 POINT (-8572618 4705115)
#> 5 POINT (-8576760 4708402)
#> 6 POINT (-8577336 4709696)