Processing residential buildings in BD Topo®

Introduction

This vignette provides a step-by-step guide to processing residential buildings in the BD-Topo® using the floodam.data package. The BD-Topo® is a comprehensive database of geographical information from France. This process involves downloading the data, extracting relevant residential building and dwelling information, analyzing it, summarizing the results, and generating reports.

Prerequisites

Before you begin, ensure that you have the following:

• Sufficient disk space to store the downloaded and processed data.
• A stable internet connection.

Step 1: Load Libraries

First, load the necessary libraries:

library(floodam.data)
library(sf)

Step 2: Define Paths

Define the paths to the directories where the data will be downloaded and processed. Important: Update these paths to match your local file system.

path_bd_topo = "~/data/data-local/original/bd-topo"
path_building = "~/data/data-local//adapted/bd-topo/building"
path_dwelling = "~/data/data-local//adapted/bd-topo/dwelling"
path_department = "~/data/data-local//adapted/admin-express"
path_eaip = "~/data/data-local//adapted/eaip"

Step 3: Get Latest Archive and Vintage

Download the BD Topo data for each department and extract the vintage information. Here we use department 34 (Hérault) as an example:

download_info = floodam.data::download_bd_topo(
    file.path(path_bd_topo, vintage), 
    department = 34, 
    type = "GPKG"
)
vintage = floodam.data::analyse_archive(download_info[["task"]][2])["vintage"]

This step downloads the data and stores it in the specified directory.

Step 4: Extract Building Data

Extract the building data from the downloaded archive:

extract_building(
  origin = file.path(path_bd_topo, vintage),
  destination = file.path(path_building, vintage),
  map = TRUE,
  path_eaip = path_eaip
)

Step 5: Extract Dwelling Data

Extract the dwelling data from the building data:

extract_dwelling(
  origin = file.path(path_building, vintage),
  destination = file.path(path_dwelling, vintage),
  department = path_department,
  map = TRUE
)

Step 6: Analyze Dwelling Data

Analyze the extracted dwelling data:

analyse_dwelling(
  file.path(path_building, vintage),
  retrieve = FALSE
)

Step 7: Summarize Dwelling Data

Summarize the analyzed dwelling data:

summarise_dwelling(file.path(path_dwelling, vintage))
summarise_dwelling(file.path(path_dwelling, vintage), flood = "eaip")

Step 8: Generate Report

Generate a report for each department:

generate_report(
  file.path(path_dwelling, vintage, "analysed"),
  quiet = TRUE,
  purge = TRUE,
  complete = TRUE
)