python工具——basemap使用二绘制中国地图

1.数据准备

下载中国shapefile格式的资料下载地址 https://gadm.org/download_country_v3.html

2.示例

绘制黑白地图

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt

# 绘制地图

m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            projection='lcc', lat_0 = 42.5,lon_0=120)
m.drawcoastlines()    # 海岸线
m.drawcountries(linewidth=1.5)    # 国界线

plt.show()

说明：

　　Basemap常用参数

llcrnrlon  左下角地理经度
llcrnrlat  左下角地理纬度
urcrnrlon  右上角地理经度
urcrnrlat  右上角地理纬度
width      地图的投影单位宽度
height     投影单位中地图的高度
lon_0      地图中心的经度
lat_0      地图中心的纬度
projection 设置要使用的地图投影

　　常用投影

 cyl              Cylindrical Equidistant  圆柱形等距投影               
 merc             Mercator     墨卡托投影                           
 tmerc            Transverse Mercator     横轴墨卡托投影                        
 cea              Cylindrical Equal Area     圆柱等面积投影             
 lcc              Lambert Conformal     兰伯特正形投影                  
 laea             Lambert Azimuthal Equal Area   兰勃特方位等积投影                           
 aeqd             Azimuthal Equidistant   等距方位离投影                                    
 poly             Polyconic      多圆锥投影                                       
 sinu             Sinusoidal       正弦曲线投影                       
 moll             Mollweide        默尔威得投影                                                
 mbtfpq           McBryde-Thomas Flat-Polar Quartic    麦克布赖德-托马斯平极四次投影

添加省界线

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt

# 绘制地图

m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            projection='lcc', lat_0 = 42.5,lon_0=120)
m.drawcoastlines()    # 海岸线
m.drawcountries(linewidth=1.5)    # 国界线
# CHN_adm1的数据是中国各省区域
m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)  
plt.show()

添加台湾，给各省上金色，北京红色

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
ax = plt.gca()
m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            projection='lcc', lat_0 = 42.5,lon_0=120)
m.drawcoastlines()    # 海岸线
m.drawcountries()    # 国界线
# CHN_adm1的数据是中国各省区域
m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)   
# 获取台湾省的 shp 信息
m.readshapefile('gadm36_TWN_shp/gadm36_TWN_0',
                'taiwan',
                drawbounds=True)
# 在形状上填充颜色——珊瑚色
for shp in m.states:
    poly = Polygon(xy=shp,
                   facecolor='gold',edgecolor='b'
                  )
    ax.add_patch(poly)

for shp in m.taiwan:
    poly = Polygon(shp,
                   facecolor='gold',edgecolor='b')
    ax.add_patch(poly)

# 用红色填充北京市
for info, shp in zip(m.states_info, m.states):
    proid = info['NAME_1']
    if proid == 'Beijing':
        poly = Polygon(shp,
                       facecolor='r',
                       lw=3)
        ax.add_patch(poly)

plt.show()

带各省轮廓的阴暗的浮雕图

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
fig = plt.figure()
ax1 = fig.add_axes([0.1,0.1,0.8,0.8])
m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            resolution='h', projection='cass', lat_0 = 42.5,lon_0=120,ax=ax1)

m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)  

for info, shp in zip(m.states_info, m.states):
    proid = info['NAME_1']
    if proid == 'Beijing':
        poly = Polygon(shp,facecolor='r',edgecolor='c')
        ax1.add_patch(poly)

m.shadedrelief()
m.drawcoastlines()
m.drawcountries()

plt.show()

绘制地形图

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import pandas as pd
import numpy as np
posi=pd.read_excel("2015Cities-CHINA.xlsx") #读取中国城市数据
lat = np.array(posi["lat"][0:120])          # 获取维度之维度值
lon = np.array(posi["lon"][0:120])          # 获取经度值
pop = np.array(posi["pop"][0:120],dtype=float) 
size=(pop/np.max(pop))*100 
m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            resolution='h', projection='cass', lat_0 = 42.5,lon_0=120)

m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)  

m.etopo() # 绘制地形图，浮雕样式
m.drawcoastlines()

plt.show()

绘制地形图和首都

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import pandas as pd
import numpy as np
posi=pd.read_excel("2015Cities-CHINA.xlsx") #读取中国城市数据
lat = np.array(posi["lat"][0:120])                        # 获取维度之维度值
lon = np.array(posi["lon"][0:120])                        # 获取经度值
pop = np.array(posi["pop"][0:120],dtype=float) 
size=(pop/np.max(pop))*100 
m = Basemap(llcrnrlon=80.33, 
            llcrnrlat=3.01, 
            urcrnrlon=138.16, 
            urcrnrlat=56.123,
            resolution='h', projection='cass', lat_0 = 42.5,lon_0=120)

m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)  

m.etopo() # 绘制地形图，浮雕样式
m.drawcoastlines()
x,y = m(lon[2],lat[2]) # 北京市坐标，经纬度坐标转换为该map的坐标
 
m.scatter(x,y,s=200,marker='*',facecolors='r',edgecolors='r') # 绘制首都

plt.show()

人口分布图

import urllib
import numpy as np
import matplotlib
matplotlib.rcParams['toolbar'] = 'None'
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from  matplotlib.animation import FuncAnimation
import pandas as pd
import seaborn as sns
 
posi=pd.read_excel("2015Cities-CHINA.xlsx")
 
lat = np.array(posi["lat"][0:120])                        # 获取维度之维度值
lon = np.array(posi["lon"][0:120])                        # 获取经度值
pop = np.array(posi["pop"][0:120],dtype=float)    # 获取人口数，转化为numpy浮点型
gdp = np.array(posi["GDP"][0:120],dtype=float)    # 获取人口数，转化为numpy浮点型
 
size=(pop/np.max(pop))*100    # 绘制散点图时图形的大小
 
m = Basemap(projection='stere', 
              lat_0=35, lon_0=110,
              llcrnrlon=82.33, 
              llcrnrlat=3.01, 
              urcrnrlon=138.16, 
              urcrnrlat=53.123,resolution='l',area_thresh=10000,rsphere=6371200.)
 
m.drawcoastlines()   
m.drawcountries(linewidth=1.5)    
m.readshapefile(shapefile='gadm36_CHN_shp/gadm36_CHN_1',
                name='states',
                drawbounds=True)  
m.drawmapboundary()
parallels = np.arange(0.,90,10.) 
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10) # 绘制纬线
meridians = np.arange(80.,140.,10.)
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10) # 绘制经线
x,y = m(lon,lat)
m.scatter(x,y,s=size)
plt.title("Population Distribution in China")
plt.show()