World提高数据为CSV

Question

HiLatLong值和alt值取Geotiff值时有问题, 并想知道这些数据是否以Excel或CSV文件格式公开提供?可惜我自己什么都没发现

my data:https://wetransfer.com/downloads/8e5ba7aa4cd8c406068a60543b353b0420220622084939/d3c744面向知道Python的人

import numpy as np import matplotlib.pyplot as plt from netCDF4 import Dataset import pandas as pd  data = Dataset("C:/Users/Oliver Weisser/Desktop/Bachelor/Programm/Daten/Daten/ETOPO1_Bed_g_gdal.grd",'r') print(data.variables.keys())  lon_range = data.variables['x_range'][:] lat_range = data.variables['y_range'][:] topo_range = data.variables['z_range'][:] spacing = data.variables['spacing'][:] dimension = data.variables['dimension'][:] z = data.variables['z'][:] lon_num =  dimension[0] lat_num =  dimension[1]  lon = np.linspace(lon_range[0],lon_range[1],dimension[0]) lat = np.linspace(lat_range[0],lat_range[1],dimension[1])  topo = np.reshape(z, (lat_num, lon_num))   dfl = pd.DataFrame({         'Latitude': lat.reshape(-1),         'Longitude': lon.reshape(-1),         'Altitude': topo.reshape(-1)         }) print(dfl)

源码 :ETOPO1区域选择

这是我至今所编解码 也许有人会发现那里有窃听器

Answer 1

所以我希望我终于理解你真正问题所在, 并由此从csv数据中提供高位信息

import numpy as np from netCDF4 import Dataset import matplotlib.pyplot as plt  csv_data = np.loadtxt('1994_12_O18grid.csv',skiprows=1,delimiter=',')  num_el = csv_data[:,0] lat = csv_data[:,1] lon = csv_data[:,2] value = csv_data[:,3]  data = Dataset("ETOPO1_Bed_g_gdal.grd",'r') lon_range = data.variables['x_range'][:] lat_range = data.variables['y_range'][:] topo_range = data.variables['z_range'][:] spacing = data.variables['spacing'][:] dimension = data.variables['dimension'][:] z = data.variables['z'][:] lon_num =  dimension[0] lat_num =  dimension[1]  etopo_lon = np.linspace(lon_range[0],lon_range[1],dimension[0]) etopo_lat = np.linspace(lat_range[0],lat_range[1],dimension[1]) topo = np.reshape(z, (lat_num, lon_num))  height = np.empty_like(num_el) for i in range(len(num_el)):  #in this loop we search for the height values for the specific lat and lon values from your csv     desired_lat_idx = np.abs(etopo_lat - lat[i]).argmin()     desired_lon_idx = np.abs(etopo_lon - lon[i]).argmin()     height[i] = topo[desired_lat_idx,desired_lon_idx]  plt.figure() height[height<0]=0 # if you want to disregard values below 0 plt.imshow(np.reshape(height,(180,360))) # if the resolution of your csv data changes from 1 degree to something different you need to chance the values in the reshape.简单化我硬码数

查找高度效率不高,但我没有时间做适当的numpy样式解法