I collect tree data sets and here are some links to open data from France. I will update the list when I find more!
You can find out more about my work on my github. To extract the trees from the files I needed to do a bit of data wrangling.
Guingamp
Typical lat/long in field.
guingamp <- sf::st_read("sources/Arbres de la Ville de Guingamp.csv")
guingamp <- sf::st_as_sf(guingamp, coords = c("longitude", "latitude"), crs = 4326)Ecoline
Isolated trees are only the ones with “Arbre isolé” in ele_txt field.
iau_ecoline <- sf::st_read("sources/elements-fixes-ponctuels-de-la-couche-ecoline-dile-de-france.json")
iau_ecoline <- iau_ecoline[iau_ecoline$ele_txt == "Arbre isolé",]Nancy metropolis
Nancy is a bit more tricky. Each city has a directory where you can found isolated trees (ARBRE_ISOLE.shp). Houdemont, one of the cities, has a file with a different number of columns so we needed to correct this.
nancy <- sapply(list.files(pattern = "ARBRE_ISOLE.shp$", recursive = T), sf::st_read) # read all the file
houdemont <- nancy[6] # we get Houdemont's data
houdemont$`sources/RESTITUTION_TOPO_3D_SHP/HOUDEMONT/ARBRE_ISOLE.shp`$Z <- NA # add the missing data
houdemont$`sources/RESTITUTION_TOPO_3D_SHP/HOUDEMONT/ARBRE_ISOLE.shp` <-
houdemont$`sources/RESTITUTION_TOPO_3D_SHP/HOUDEMONT/ARBRE_ISOLE.shp`[ # reorgonize it
,c("HAUTEUR", "DIAMETRE", "TYPE", "CCOCOM", "Z", "geometry")
]
nancy <- do.call(rbind, nancy[-6]) # one file from every cities except Houdemont
nancy <- rbind(nancy, houdemont$`sources/RESTITUTION_TOPO_3D_SHP/HOUDEMONT/ARBRE_ISOLE.shp`) # adding Houdemont