Leaflet

• leading open-source JavaScript library
• has been around for ~ 10 years
• usually when you see maps online, they are made with Leaflet

Deck.gl

• started ~ 4 years ago
• especially great for large data and 3D views
• R package to access deck.gl: mapdeck

plotting all + 80.000 cars in Friedrichshain-Kreuzberg

geocomputation made easy with the sf package

streets_in_xhain <- st::st_intersection(streets_berlin, xhain_outline) 

cars <- st::st_sample(streets_xhain,size= 80808)

Plot raster data with leaflet and leafem

• add raster data: leaflet::addRasterImage()
• add Mouseover for raster data: leafem::addImageQuery()

leaflet() %>% 
    addProviderTiles(providers$CartoDB.DarkMatter) %>%
    addRasterImage(hours_of_sunshine, group = "g") %>% 
    addImageQuery(hours_of_sunshine, layerId = "g")

Which boulder gym is closest to you?

Create a geospatial voronoi map mit dismo

gyms_voronoi <- dismo::voronoi(boulder_gyms[c("lon", "lat")])

How large is the area of in 2019 destroyed rain forest?

leafpm for editable polygons

• leafpm::addPmToolbar() to draw, cut, edit and move vectors

  leaflet(rainforest_area) %>%
    addTiles() %>%
    addPolygons(group = "p") %>% 
    leafpm::addPmToolbar(targetGroup = "p")

use stplanr for routing and aggregating lines

start_points <- st_sample(berlin,size=500) %>% st_as_sf
end_points <- st_sample(berlin,size=500) %>% st_as_sf

routes <- stplanr::route(from = start_points, 
                to = end_points, 
                route_fun = osrmRoute,
                returnclass = "sf")

routes["count"] <- 1

overlapping_segments <- stplanr::overline(routes, attrib = "count")

react to clicks on leaflet map with shiny

observeEvent(input$map_shape_click, {})

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Air traffic between German Airports

Origin destination with flowmap.blue

• Flowmap.blue
• fast and easy viz of origin destination data
• can be done entirely without coding (with Google Sheets)
• new: also available as R package

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get OSM data with osmdata

• OpenStreetMap overs a huge ressource on openly available geodata (streets, rivers, restaurants, stores, … )
• this data can be retrieved with the Overpass API which is accesible with the osmdata package in R

osmdata::opq(bbox = 'berlin germany') %>%
     add_osm_feature(key = 'amenity', 
                     value = c('fast_food', 'restaurant')) %>% 
     osmdata_sf ()

auto aggregated grids with mapdeck

• insert point data
• point counts are automatically aggregated to grids

mapdeck::mapdeck() %>% 
 mapdeck::add_screengrid(data = restaurants)

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All traffic accidents in Stuttgart

elevation and hexagons with mapdeck

• insert point data
• point counts are automatically aggregated to hexagons

mapdeck::mapdeck() %>% 
 mapdeck::add_hexagon(data = accidents_stuttgart)

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all U-Bahns in Berlin

moving lines with mapdeck

mapdeck::mapdeck() %>% 
 mapdeck::add_trips(data = ubahn)