CEFE-CNRS, sept 2019
The aim of this document is to list free spatial data and resources on the web for ecology and geography.
The data are identified by title, URL and keywords.
# select polygon feature example | |
# with leaflet & shiny | |
library(shiny) | |
library(leaflet) | |
data(gadmCHE) | |
ui <- bootstrapPage( | |
tags$style(type = "text/css", "html, body {width:100%;height:100%}"), |
snappy requiert la version 3.6 de Python (or la dernière version de Python est plutôt 3.10). L'utilisation de conda, qui permet d'utiliser plusieurs versions de python sur un même poste, prend tout son sens.
Pour créer et activer un environnement virtuel :
conda create -n snap_env -c conda-forge python=3.6 mamba
conda activate snap_env
# Effective Mesh Size (CBC) | |
library(vroom) | |
library(dplyr) | |
# pour surface en ha | |
divisurf <- 10000 | |
nom_colonnes <- c("id", "id_patch", "surf_m2", "nb_pixels") | |
tbl_stats_grass <- vroom("FR/stats_completes.txt", delim = "\t", col_names= nom_colonnes, col_types = "iidi") |
#library(openxlsx) | |
library(tidyverse) | |
library(readxl) | |
library(nominatimlite) | |
library(sf) | |
library(htmltools) | |
# lire fichier excel | |
f_xlsx <- "data/00_Ressources_propres_UMR_2021_2023_corrige.xlsx" |