Python遥感可视化—将地面观测站点进行空间插值.zip

# _*_ coding: utf-8 _*_ __author__ = 'xbr' __date__ = '2019/1/11 14:49' from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt import pandas as pd import numpy as np from scipy.interpolate import griddata import cmaps # 用来正常显示中文 plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示负号 plt.rcParams['axes.unicode_minus'] = False # 获取PM2.5数据 df = pd.read_excel(r'D:\data\20180101PM25-CHINA.xlsx') # 剔除无效值NAN df = df.dropna(axis=0, how='any') # 获取纬度 lat = np.array(df["lat"][:]) # 获取经度 lon = np.array(df["lon"][:]) # 获取PM2.5 PM25 = np.array(df["PM25"][:]) # 创建格网 grid_x, grid_y = np.mgrid[73.56:135.04, 18.2:53.56] # 插值方法：'nearest', 'linear', 'cubic' grid_z = griddata((lon, lat), PM25, (grid_x, grid_y), method='cubic') # 画图 fig = plt.figure(figsize=(16, 9)) plt.rc('font', size=15, weight='bold') ax = fig.add_subplot(111) # 添加标题,PM2.5下标设置 plt.title(u'2018年01月01日中国地区$\mathrm{PM}_{2.5}$质量浓度分布', size=25, weight='bold') # 创建底图,等经纬度投影 mp = Basemap(llcrnrlon=73., llcrnrlat=17., urcrnrlon=135., urcrnrlat=55, projection='cyl', resolution='h') # 添加海岸线 mp.drawcoastlines() # 添加国家行政边界 mp.drawcountries() # 设置colorbar中颜色间隔个数 levels = np.linspace(0, np.max(PM25), 20) cf = mp.contourf(grid_x, grid_y, grid_z, levels=levels, cmap=cmaps.GMT_panoply) cbar = mp.colorbar(cf, location='right', format='%d', size=0.3, ticks=np.linspace(0, np.max(PM25), 10), label='$\mathrm{PM}_{2.5}$($\mu$g/$\mathrm{m}^{3}$)') plt.show()