Emergencia y Desastre República Dominicana

import matplotlib.pyplot as plt import geopandas as gpd from shapely.geometry import Point, LineString # Load a basic map of the Dominican Republic world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) dominican_republic = world[world.name == "Dominican Rep."] # Define points of interest: COEs, meteorological stations, key monitoring points points_of_interest = gpd.GeoDataFrame({ 'name': ['COE Santo Domingo', 'Meteorological Station Santiago', 'Monitoring Point Puerto Plata', 'COE Punta Cana', 'Meteorological Station La Romana'], 'geometry': [Point(-69.9312, 18.4861), Point(-70.7011, 19.4792), Point(-70.6876, 19.7934), Point(-68.3667, 18.5667), Point(-68.9667, 18.4333)] }) # Define key communication routes (simplified example) routes = gpd.GeoDataFrame({ 'name': ['Route 1', 'Route 2'], 'geometry': [LineString([(-69.9312, 18.4861), (-70.7011, 19.4792)]), LineString([(-69.9312, 18.4861), (-68.3667, 18.5667)])] }) # Plotting the map fig, ax = plt.subplots(1, 1, figsize=(10, 10)) dominican_republic.plot(ax=ax, color='lightgrey') # Plot points of interest points_of_interest.plot(ax=ax, color='red', markersize=100, alpha=0.6, edgecolor='k') # Plot routes routes.plot(ax=ax, color='blue', linewidth=2, linestyle='--') # Adding labels to points of interest for idx, row in points_of_interest.iterrows(): plt.text(row.geometry.x, row.geometry.y, row['name'], fontsize=12, ha='right') # Title and legend plt.title('Mapa de la República Dominicana con Red de Comunicaciones y Manejo de Equipos de Emergencia', fontsize=16) plt.legend(['Rutas de Comunicación', 'Centros y Estaciones'], loc='upper left') # Show the plot plt.show()