如何使用 GDAL 加速从光栅文件中提取点数据 python

Question

我有 366 个包含雪数据的 tif 格式光栅图像文件（MODIS 卫星每日数据）和另一个包含 19,000 个位置（纬度和经度）的 csv 文件。我需要从光栅文件中收集雪数据。我尝试使用 GDAL python 库收集数据。但是，该程序从每个文件中收集数据大约需要 30 分钟。这意味着我必须运行该代码大约 180 个小时。以下是我正在使用的代码。请建议我是否可以提高程序执行的速度，或者是否有更好的方法可以实现相同的速度。

import gdal
import pandas
import numpy as np
import os,subprocess
def runCmdAndGetOutput(cmd) :
    outList = []
    proc = subprocess.Popen(cmd,stdout=subprocess.PIPE)
    while True:
        line = proc.stdout.readline()
        if not line:
            break
        #the real code does filtering here
        outList.append(line.rstrip())
        print(outList)
    # value = float(outList[2].decode("utf-8").replace("<Value>","").replace("</Value>",""))
    value = float(outList[0].decode("utf-8"))
    return value

# ndsiFile = "2016001.tif"
locs = "hkkhlocations.csv"
ndsFileLoc = r"D:\SrinivasaRao_Docs\MODIS_NDSI_V6_201600000499560\out"
# with open(locs) as f:
#     locData = f.readlines()
latLnginfo = pandas.read_csv(locs)
print(latLnginfo.columns)
print(latLnginfo.shape)

# outDf = pandas.DataFrame()


outDf = pandas.DataFrame(np.zeros([len(latLnginfo),370])*np.nan)
day =1
print(os.listdir(ndsFileLoc))
print(type(os.listdir(ndsFileLoc)))
datasetsList = os.listdir(ndsFileLoc)
for eFile in datasetsList:
    rCount = 0
    # print(eFile)
    cCount = int(eFile[4:7])
    # print(cCount)
    with open("output.csv") as f :
        for line in f :
            locData = line.split(",")
            cmdToRun = ["gdallocationinfo" ,"-valonly", "-wgs84", os.path.join(ndsFileLoc,eFile) ,str(latLnginfo.iloc[rCount,4]), str(latLnginfo.iloc[rCount,3])]# str(locData[0]), str(locData[1])]
            v = runCmdAndGetOutput(cmdToRun)
            outDf.iloc[rCount,cCount]= float(v)
            rCount = rCount + 1
            print("rowno: ", rCount, "Dayno :", cCount, "SCF value: ", v)


    day = day+1
outDf.to_csv('test.csv')

'''

Answer 1

def run_cmd_processor(efile):
    r_count = 0
    c_count = int(efile[4:7])
    with open("output.csv") as f :
        for line in f :
            loc_data = line.split(",")
            # ~

pool = multiprocessing.Pool(processes=2) # You can add more processes
pool.map(run_cmd_processor, datasetsList)
pool.close()
pool.join()

好像只有"for eFile in datasetsList:"可以多处理分支。可以改成upper.

如何使用 GDAL 加速从光栅文件中提取点数据 python

How to speed up extracting data from raster file for points using GDAL python

python

gis

multiprocessing

gdal

rasterio