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我经常在 Google Earth Pro 和 Mars 上用地标标记好位置，然后将它们导出为 kml 文件（然后转换为 CSV）。此时，kml 文件包含位置坐标，但不包含高程。

对于在地球上标记的位置，我可以通过使用 Python 的 Google Map Platform 的 Elevation API ( https://developers.google.com/maps/documentation/elevation/requests-elevation ) 获取它们的海拔，参考包含的坐标以公里为单位。

import requests
import xml.etree.ElementTree as ET
import csv
import unicodedata

# load KML
tree = ET.parse('placemarks.kml')
root = tree.getroot()

# CSV
placeDict = dict.fromkeys(["placemarks_name","latitude","longitude","altitude"],"")

outputFileName = "placemarks.csv"
f = open(outputFileName, "w")
w = csv.DictWriter(f, placeDict.keys())
w.writeheader()

for line in root.iter('*'):

    # placemarks_name
    if line.tag == '{http://www.opengis.net/kml/2.2}name':
        placeDict["placemarks_name"] =  line.text
        
    # coordinates
    if line.tag == '{http://www.opengis.net/kml/2.2}coordinates':
        coordArray = line.text.split(",")
        placeDict["longitude"] = coordArray[0]
        placeDict["latitude"] = coordArray[1]

        # Google API key
        YOUR_API_KEY = 'myapikey'
        latitude = coordArray[1]
        longitude = coordArray[0]

        # Output in xml style
        url = 'https://maps.googleapis.com/maps/api/elevation/xml?locations=' + latitude  + ',' + longitude + '&key=' + YOUR_API_KEY

        payload={}
        headers = {}

        response = requests.request("GET", url, headers=headers, data=payload)
        # Convert to xml
        root = ET.fromstring(response.text)
        # pick up elevation data
        for elevation in root.iter('elevation'):
            placeDict["altitude"] = elevation.text
   
        w.writerow(placeDict)  # to csv
        
f.close()

在火星上标记的位置的情况下，我可以获得与上述海拔请求方式相同的海拔吗？你能推荐这样做的方法吗？

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1 回答 1

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问题自行解决！

我将分享解决方案。

我决定参考Mars MGS MOLA - MEX HRSC Blended DEM (.tif)。

使用 QGIS，我将 .tif 文件转换为 ndarray：

from osgeo import gdal
import numpy as np

path = '/PATH/Mars_HRSC_MOLA_BlendDEM_Global_200mp_v2.tif'
src = gdal.Open(path, gdal.GA_ReadOnly)
elv = src.GetRasterBand(1)
elv_arr = elv.ReadAsArray()
print(elv_arr.shape)

np.save('/PATH/MOLA-HRSC_elevation_ndarray', elv_arr)

转换后，我使用 .kml 文件中的坐标引用了 ndarray 中的高程值，该文件基于 DEM 地理空间信息重新缩放：

import numpy as np
import xml.etree.ElementTree as ET
import csv
import unicodedata


# Load KML
tree = ET.parse('placemarks_mars.kml')
root = tree.getroot()

# CSV format
placeDict = dict.fromkeys(["placemarks_name","latitude","longitude","elevation"],"")

# Load MOLA-HRSC_DEM ndarray
elemap = np.load('PATH/MOLA-HRSC_elevation_ndarray.npy')
# Center of MOLA-HRSC_DEM ndarray as xy origin
pixel_origin = np.array([elemap.shape[0]//2, elemap.shape[1]//2])

f = open('placemarks_mars.csv', "w")
w = csv.DictWriter(f, placeDict.keys())
w.writeheader()

for line in root.iter('*'):

    ## placemarks_name
    if line.tag == '{http://www.opengis.net/kml/2.2}name':
        placeDict["placemarks_name"] =  line.text
        
    ## coordinates
    if line.tag == '{http://www.opengis.net/kml/2.2}coordinates':
        coordArray = line.text.split(",")
        placeDict["longitude"] = coordArray[0]
        placeDict["latitude"] = coordArray[1]

        ### ndarray of Lat&Lon at locations
        LatLon_coord = np.array([coordArray[1], coordArray[0]], dtype='float64')
        ### y-axis(Lat): Positive Down(Positive South) to y-axis(Lat): Positive Up(Positive North). *x-axis(Lon) is Positive Right(Positive East)
        np.put(LatLon_coord,[0],LatLon_coord[0] * -1)

        ### Lat&Lon at locations to xy
        ### Scale(pixels/degree) = 296.3735
        ### https://astrogeology.usgs.gov/search/map/Mars/Topography/HRSC_MOLA_Blend/Mars_HRSC_MOLA_BlendDEM_Global_200mp_v2
        datapoint = np.floor(pixel_origin + LatLon_coord * 296.3735)
        datapoint = np.array (datapoint, dtype='int64')

        ### See elevations
        placeDict["elevation"] = elemap[datapoint[0], datapoint[1]]
   
        w.writerow(placeDict)  ### to CSV
        
f.close()

谢谢！

于 2021-12-30T14:32:15.830 回答