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How to plot topographic station map in Python (codes included)

Utpal Kumar   1 minute read      

We read the station information from a file to plot the 1 arc-minute relief map

In this post, we read the station information stored in the text file statlist2.txt using the pandas library in Python and then plot it over the topographic map. The details on how to plot the topographic map in Python can be found here. The plot_topo_netcdf function can be used from here.

Taiwan station map using basemap
Taiwan station map using basemap

Requirements

You will need two files for the below script to run:

  1. statlist2.txt file with the format as: 
    TW NACB latval lonval eleval
TW YHNB latval lonval eleval

    Replace the latval, lonval and eleval with appropriate values.

  2. Set the path to the etopo_file downloaded from NOAA website.

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Code

from plotting_topo import plot_topo, plot_topo_netcdf
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

stn_df = pd.read_csv('statlist2.txt',header=None,sep='\s+',names=['net','sta','lat','lon','ele']) 

etopo_file = "/Users/utpalkumar50/Documents/bin/ETOPO1_Bed_g_gmt4.grd"

lonmin, lonmax = 119.5,122.5 # minimum and maximum of the longitudes
latmin, latmax = 21.5,25.5 # minimum and maximum of the latitudes

if stn_df['lat'].min()<latmin or stn_df['lat'].max()>latmax or stn_df['lon'].min()<lonmin or stn_df['lon'].max()>lonmax:
    print("GEOGRAPHICAL RANGE ERROR: Stations outside the range")

else:
    networkset = set([val for val in stn_df['net']]) #making unique set of network for legend
    stations = [val for val in stn_df['sta']] #list of stations for marking on map
    color=iter(plt.cm.jet(np.linspace(0,1,len(networkset)))) #unique set of colors based on "jet" colormap for legend
    netcolor = {net:c for net, c in zip(networkset, color)} #one legend for each network

    fig = plt.figure(figsize=(10,6))
    ax = fig.add_subplot(111)
    map = Basemap(projection='merc',resolution = 'f', area_thresh = 10000., llcrnrlon=lonmin, llcrnrlat=latmin,urcrnrlon=lonmax, urcrnrlat=latmax)
    cs = plot_topo_netcdf(map,etopo_file=etopo_file,cmap='terrain',lonextent=(lonmin, lonmax),latextent=(latmin, latmax),zorder=2)
    fig.colorbar(cs, ax=ax, shrink=0.8)
    map.drawcoastlines(color='k',linewidth=0.5)
    map.drawcountries(color='k',linewidth=0.1)

    parallelmin,parallelmax = int(latmin), int(latmax)+1
    map.drawparallels(np.arange(parallelmin, parallelmax+1,0.5).tolist(),labels=[1,0,0,0],linewidth=0,fontsize=6)
    meridianmin,meridianmax = int(lonmin),int(lonmax)+1
    map.drawmeridians(np.arange(meridianmin, meridianmax+1,0.5).tolist(),labels=[0,0,0,1],linewidth=0,fontsize=6)
    map.drawmapboundary(color='k', linewidth=2, zorder=1)

    for lon, lat, sta, net in zip(stn_df['lon'],stn_df['lat'],stn_df['sta'],stn_df['net']):
        x,y = map(lon, lat)
        plt.text(x+25000, y, sta, ha="center", va="center",fontsize=5)
        map.plot(x, y,'^',color=netcolor[net], markersize=7,markeredgecolor='k',linewidth=0.1,markeredgewidth=0.1)
    for net in networkset:
        map.plot(np.NaN,np.NaN,'^',color=netcolor[net],label=net, markersize=7,markeredgecolor='k',linewidth=0.1,markeredgewidth=0.1)
    plt.legend(loc=4,fontsize=8)
    plt.savefig('station_map.png',bbox_inches='tight',dpi=600)
    plt.close('all')

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