如何将多份VNP46A1 H5格式夜光数据拼接为欧洲全域夜光地图？

我需要制作欧洲区域的夜光地图，数据源为NASA的VNP46A1数据集（2022年3月27日），下载整个欧盟区域时得到了约14个独立的分块文件（tile）。我已实现单份文件的读取与绘制，但无法将这些分块数据拼接为完整的欧洲全域夜光地图。尝试过循环绘制，但耗时极长且结果错误。由于对该文件格式及此类绘图操作不熟悉，不清楚应搜索哪些关键词。

以下是用于绘制单份文件的可运行Python代码：

import numpy as np
import matplotlib.pyplot as plt
import h5py
import cartopy.crs as ccrs
import os
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.ticker as mticker
import glob

indir = 'D:/PYTHON/NASA/VNP46A1.A2023058.h17v03.001.2023060025350.h5'
data = h5py.File(indir)
list(data.keys())
dnb = data['HDFEOS/GRIDS/VNP_Grid_DNB/Data Fields/DNB_At_Sensor_Radiance_500m']
dnb = np.array(dnb)
dnb = np.where(dnb==65535, np.nan, dnb)
# np.nanmax(dnb)

lat_max = data['HDFEOS/GRIDS/VNP_Grid_DNB'].attrs['NorthBoundingCoord']
lat_min = data['HDFEOS/GRIDS/VNP_Grid_DNB'].attrs['SouthBoundingCoord']
lon_min = data['HDFEOS/GRIDS/VNP_Grid_DNB'].attrs['WestBoundingCoord']
lon_max = data['HDFEOS/GRIDS/VNP_Grid_DNB'].attrs['EastBoundingCoord']

lats = np.linspace(lat_max, lat_min, dnb.shape[1])
lons = np.linspace(lon_min, lon_max, dnb.shape[0])
x, y = np.meshgrid(lons, lats)

cmap = plt.get_cmap('cividis')
crs = ccrs.PlateCarree()

fig =  plt.figure(figsize=(6,6))
ax = plt.axes(projection=crs)
ax.coastlines(resolution='10m', color='white',alpha=0.5)
ax.pcolormesh(x, y, dnb, cmap = cmap, vmin = 0, vmax = 100)

plt.xlim()

gl = ax.gridlines(crs=crs, draw_labels=True, alpha=0.5)
gl.xlabels_top = None
gl.ylabels_left = None
xgrid = np.arange(lon_min-2, lon_max+2, 2.)
ygrid = np.arange(lat_min-2, lat_max+2, 2.)
gl.xlocator = mticker.FixedLocator(xgrid.tolist())
gl.ylocator = mticker.FixedLocator(ygrid.tolist())
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
gl.xlabel_style = {'size': 10, 'color': 'black'}
gl.ylabel_style = {'size': 10, 'color': 'black'}

plt.xlim((lon_min,lon_max))
plt.ylim((lat_min,lat_max))

plt.show()

运行上述代码可得到单块夜光数据的可视化结果，预期效果为覆盖欧洲全域的夜光地图（类似NASA Worldview平台展示的VIIRS夜间灯光影像）。

内容的提问来源于stack exchange，提问作者confused student