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DATE: 2018-04-18
AUTHOR: John L. Godlee
I made a website for my labgroup using Jekyll and Github-pages. It can be seen here at seosaw.github.io[1]. The bit I want to show off about is the interactive map I made for the page on data and sites, which can be seen here[2].
2: https://seosaw.github.io/data.html
The map is powered using leaflet[3], which is a Javascript library specifically for making maps.
This is how I got our data to run on the map.
First I have to generate the geoJSON files for the location of our sites as points, and also for a polygon layer showing the extent of savannas in Africa. I used R to generate these files because that is the platform I have the most experience with GIS stuff in. This is a stripped down version of the script I used to transform the original data .csv and .shp into geoJSON outputs:
For the plot data:
# Packages ---- library(dplyr) library(geojsonio) library(readr) # Read in plot data plots <- read.csv("plots.csv") # Create intermediate data frame ---- plots_export <- plots %>% filter(!is.na(longitude_of_centre) & !is.na(latitude_of_centre)) %>% mutate(name = paste(name, "-", plotcode), lon = as.numeric(as.character(longitude_of_centre)), lat = as.numeric(as.character(latitude_of_centre)), area_of_plot = round(as.numeric(area_of_plot) * 10000, digits = 2)) %>% select(name, country, area_of_plot, lon, lat) %>% filter(!is.na(lon), !is.na(lat)) # Export to json ---- geojson_write(input = plots_export, lat = "lat", lon = "lon", file = "plots_export")
And for the polygon data:
# Packages ---- library(rgdal) library(rgeos) library(geojsonio) # Read shapefile ---- white_veg <- readOGR(dsn="whitesveg", layer="Whites vegetation") # Attempting to transform CRS to wgs84 ---- ## No CRS given proj4string(white_veg) white_veg <- spTransform(white_veg, CRS("+proj=longlat +datum=WGS84")) white_veg_sub <- white_veg[which((white_veg$DESCRIPTIO == "Moist-infertile savanna") | (white_veg$DESCRIPTIO == "Mosaics of forest") | (white_veg$DESCRIPTIO == "Mopane savanna") | (white_veg$DESCRIPTIO == "Montane Forest") | (white_veg$DESCRIPTIO == "Hydropmorphic grassland") | (white_veg$DESCRIPTIO == "Arid-fertile savanna") | (white_veg$DESCRIPTIO == "Sedge and reed swamp")),] white_woodlands_poly <- gUnaryUnion(white_veg_sub) # Output to geojson ---- # Export to json ---- geojson_write(input = white_woodlands_poly, file = "miombo_po")
The polygon data comes from White's 1983 vegetation map of Africa, which remains the best approximation of the biomes of Africa, even though it was constructed in a very non-systematic fashion.
Next I have to convert these geoJSON files to .js files and name them as variables by adding a variable designation at the top of the files like this:
var miombo = [ {"type": "FeatureCollection", "features": [{ "type": "Feature", ...
var locations = [ { "type": "Feature", "id": 1, "properties": { "name": "Kruger Skukuza - SSM-001", "country": "South Africa", "area_of_plot": 40000.0, "lon": 31.4970563, "lat": -25.0197541 }, "geometry": { "type": "Point", "coordinates": [ 31.4970563, -25.0197541 ] } }, { "type": "Feature", "id": 2, "properties": { "name": "Hwange-Farm41 - ZHH-001", "country": "Zimbabwe", "area_of_plot": 1000.0, "lon": 27.90663333, "lat": -18.62653333 }, "geometry": { "type": "Point", "coordinates": [ 27.90663333, -18.62653333 ] } }, ...
Then, I need to construct the javascript file which makes the map, which calls the map tiles (L.tileLayer), and gives the plot locations and polygons various aesthetic attributes:
var mymap = L.map('leaf-map').setView([-16.5, 24.7], 4); L.tileLayer('https://api.tiles.mapbox.com/v4/{id}/{z}/{x}/{y}.png?access_token=pk.eyJ1IjoibWFwYm94IiwiYSI6ImNpejY4NXVycTA2emYycXBndHRqcmZ3N3gifQ.rJcFIG214AriISLbB6B5aw', { maxZoom: 18, id: 'mapbox.streets' }).addTo(mymap); var plotLocOptions = { fillOpacity: 0.5, weight: 0.2, radius: 5, fillColor: "#7A0099", color: "#7A0099" }; function miomboOptions(feature) { return { fillOpacity: 0.9, fillColor: "#179600", color: "#179600", weight: 0.1 }; } L.geoJSON(miombo, {style: miomboOptions}).addTo(mymap); L.geoJSON(locations, { pointToLayer: function(feature, latlng) { return L.circleMarker(latlng, plotLocOptions); }, onEachFeature: function(feature, layer){ layer.bindPopup("Name: " + feature.properties.name + "<br>" + "Country: " + feature.properties.country + "<br>" + "Plot Area: " + feature.properties.area_of_plot + " m<sup>2</sup>"); } }).addTo(mymap);
The only thing left to do is make sure all of these scripts are called in the right order in the HTML file:
<script src="/scripts/plot_loc.js"></script> <!plot locations> <script src="/scripts/miombo_po.js"></script> <!polygon locations> <script src="https://unpkg.com/leaflet@1.2.0/dist/leaflet.js" integrity="sha512-lInM/apFSqyy1o6s89K4iQUKg6ppXEgsVxT35HbzUupEVRh2Eu9Wdl4tHj7dZO0s1uvplcYGmt3498TtHq+log==" crossorigin=""> </script> <!leaflet script> <script src="/scripts/leaf-map.js"></script> <!map construction script>