【Python基础绘图】rioxarray读取tif并可视化

rioxarray读取tif并可视化

01 引言：

python通过rioxarray轻松读取tif数据，并借助cartopy进行可视化，现记录在此分享给更多有需要的同学。

02 结果如下：

03 代码如下：

# -*- encoding: utf-8 -*-
'''
@File    :   GFHD.PY
@Time    :   2022/02/28 13:42:59
@Author  :   HMX 
@Version :   1.0
@Contact :   kzdhb8023@163.com
'''

# here put the import lib
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cmaps
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from cartopy.mpl.ticker import LatitudeFormatter, LongitudeFormatter
import rioxarray as rxr

def cm2inch(value): 
    return value/2.54


size1 = 10.5
fontdict = {'weight': 'bold','size':size1,'color':'k','family':'SimHei'}
mpl.rcParams.update(
    {
    'text.usetex': False,
    'font.family': 'stixgeneral',
    'mathtext.fontset': 'stix',
    "font.family":'serif',
    "font.size": size1,
    "mathtext.fontset":'stix',
    "font.serif": ['Times New Roman'],
    }
    )


proj=ccrs.PlateCarree()
fig,ax = plt.subplots(1, 1,figsize=(cm2inch(16),cm2inch(9)),dpi=100, subplot_kw={'projection': proj})
extent = [-180,180,-90,90]

ax.add_feature(cfeature.COASTLINE.with_scale('50m'), linewidth=0.5, zorder=2,color = 'k')# 添加海岸线
ax.add_feature(cfeature.LAND)#添加陆地

ax.set_xticks(np.arange(extent[0], extent[1] + 1, 60), crs = proj)
ax.set_yticks(np.arange(extent[-2], extent[-1] + 1,30), crs = proj)
ax.xaxis.set_major_formatter(LongitudeFormatter(zero_direction_label=False))
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.xaxis.set_major_formatter(LongitudeFormatter(zero_direction_label=False))
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.set_extent(extent, crs=ccrs.PlateCarree())
ax.minorticks_on()

filename=r'E:\Project\World\GFHD2005\GFHD2005_Resample.TIF'
ds = rxr.open_rasterio(filename)

lon,lat = np.meshgrid(ds['x'],ds['y'])
data = ds[0]

lev=np.arange(0,51,5)
cf=ax.contourf(lon,lat,data,levels=lev,extend='neither',transform=ccrs.PlateCarree(),cmap=cmaps.rainbow)
plt.subplots_adjust(right=0.86)
ax2 = fig.add_axes([0.875,0.17,0.02,0.654])
b=plt.colorbar(cf,shrink=0.93,orientation='vertical',extend='both',pad=0.035,aspect=30,ticks=lev,cax=ax2)
b.ax.set_ylabel(r'冠层高度/$\mathrm{m}$',fontdict = fontdict)

plt.savefig(r'E:\Project\Figure\GFHD2005.png',dpi = 600)
plt.show()
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