使用 Python 将纬度、经度、CSV 值转换为栅格地图 [英] Lat, Lon, Values CSV to Raster Map Using Python

问题描述

如果我有一个包含 Lat、Lon 和 Value 字段的 CSV 数据集，使用 python 生成栅格地图的最佳方法是什么?栅格 Z 字段可以是此表中的任何列..

If I have a CSV Dataset with Lat, Lon, and Value fields, what is the best approach on generating a raster map using python? The raster Z field can be any column within this table..

L5  L6  L7  L8  L9  L10 L11 L12 L13 L14 LAT LON
3.571732    1.338448    0   9.96921E+36 -3.482845   -1.42944    133.229919  141.246002  67.685631   5.059844    24.335797   -95.088764
3.571732    1.338448    0   9.96921E+36 -3.420345   -1.42944    132.749512  140.641464  67.318848   5.105563    24.335107   -95.060013
3.571732    1.338448    0   9.96921E+36 -3.420345   -1.42944    132.230164  140.047211  67.318848   5.063346    24.334408   -95.031263
3.571732    1.338448    0   9.96921E+36 -3.420345   -1.42944    132.230164  139.463104  67.318848   5.063346    24.333701   -95.002512
3.509232    1.369698    0   9.96921E+36 -3.357845   -1.42944    131.702133  137.82196   66.940475   5.021552    24.332986   -94.973763
3.509232    1.369698    0   9.96921E+36 -3.357845   -1.49194    131.702133  137.26651   66.043732   5.021552    24.332263   -94.945013
3.509232    1.369698    0   9.96921E+36 -3.357845   -1.49194    131.165268  136.72081   66.043732   4.980192    24.331531   -94.916265
3.509232    1.338448    0   9.96921E+36 -3.357845   -1.49194    131.165268  136.184738  66.043732   4.980192    24.330792   -94.887516

记住，这些是numpy数组

Keep in mind, These are numpy arrays

推荐答案

根据您的经纬度坐标，有两个选项.当 Lat、Lon 坐标形成等距网格时，您可以使用第一个选项，否则您可以使用下面的第二个选项.

There are two options depending on your Lat, Lon coordinates. When the Lat, Lon coordinates form an equidistant grid you can use this first option, otherwise you can use the second option below.

第一个选项

我使用第一列中的值和第二和第三列中的 Lat、Lon 创建了下面的数组:

I create the array below with values in the first column and Lat, Lon in the 2nd and 3rd column:

import numpy as np

lat = np.arange(0, 15, 5)
lon = np.arange(0, 10, 5)
val = np.random.randint(0,10, size =len(lat)*len(lon))
xx, yy = np.meshgrid(lon, lat)
array = np.array([val,  yy.ravel(), xx.ravel()]).T
print(array)

>>> array([[ 7,  0,  0],
           [ 8,  0,  5],
           [ 7,  5,  0],
           [ 3,  5,  5],
           [ 2, 10,  0],
           [ 8, 10,  5]])

当你的纬度、经度坐标被整齐地排序后，你可以重新调整值以获得这样的网格数组:

When your Lat, Lon coordinates are neatly sorted you can reshape the values to get a grid array like this:

no_lon = len(np.unique(array[:,-1]))
no_lat = len(np.unique(array[:,-2]))
grid_array = array[:,0].reshape((no_lat,no_lon))[::-1]
print(grid_array)
>>> array([[2, 8],
           [7, 3],
           [7, 8]])

<小时>

第二个选项

---

second option

当你有一堆随机的 Lat、Lon 与这里创建的值协调时:

When you have a bunch of random Lat, Lon coordinates with values like the one created here:

array = np.random.randint(0,10, size =(6,3))
print(array)
>>> array([[9 6 0]
           [7 8 8]
           [6 0 9]
           [7 7 4]
           [2 4 3]
           [0 2 9]])

您可以使用如下插值将其转换为网格:

you can convert this to a grid by using interpolation like this:

from scipy import interpolate

lon_list = np.arange(3, 6, 1)
lat_list = np.arange(4, 8, 1)

lon_2d, lat_2d = np.meshgrid(lon_list, lat_list)
grid_array = interpolate.griddata((array[:,-1], array[:,-2]), array[:,0],
                                  (lon_2d, lat_2d))[::-1]
print(grid_array)

>>> [[  nan  7.    6.72]
     [ 6.    5.4   5.6 ]
     [ 4.    3.8   4.  ]
     [ 2.    2.2   2.4 ]]

请注意，如果您的网格单元不在您的点的范围内，您将获得 nan 值.

Note that you get nan values if your grid cells are not within the bounds of your points.

您可以使用 plt.imshow 将结果可视化

You can visualize the results using plt.imshow

import matplotlib.pyplot as plt
plt.imshow(grid_array)

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