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Attempting to gather MODIS aerosol data for a number of different AERONET stations in the UK to plot against one another. However, due to the number of files (upwards of 2000), QGIS and ArcMap crash.

I have attempted to find a solution within RSGISLib, whereby I extract a raster to .csv via a defined vector but keep getting the following:

ERROR 1: Attempt to read shape with feature id (1) out of available range. Segmentation fault

I have seen a method to extract to a .csv using r, however, I would prefer for this to be done within Python. Is there a way?

import rsgislib
from rsgislib import zonalstats
import glob

inputimage = '/home/student/Desktop/Ben_Folder/Test2/test.kea'
inputvector = '/home/student/Desktop/Ben_Folder/AERONET_POINTS/Chilbolton.shp'
outputtxt = 'test.csv'
useBandNames = False
zonalstats.pointValue2TXT(inputimage, inputvector, outputtxt, useBandNames)
  • How are you attempting to do it with ArcGIS? Is it via scripting (arcpy)? If so, can you show an example of your code? I think you could easily get rid of the "out of memory" issues by simply release memory as you process each file. Also, it is probably better do it with 64bit python which in ArcGIS is available if you have installed the Background Porcessing and should be in C:\Ptyhon27\ArcGISx6410.x – umbe1987 Sep 10 '18 at 10:30
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I would do it with Rasterio and Fiona. In the following code snippet, I use pandas to create a Serie object and write the records to a CSV file in order to improve code readability ; however you could also use the csv module. Also, I am assuming that your shapefile contains points and not polygons.

import pandas as pd
import rasterio
import fiona

values = pd.Series()

# Read input shapefile with fiona and iterate over each feature
with fiona.open('stations.shp') as shp:
    for feature in shp:
        station_name = feature['properties']['name']
        coords = feature['geometry']['coordinates']
        # Read pixel value at the given coordinates using Rasterio
        # NB: `sample()` returns an iterable of ndarrays.
        with rasterio.open('test.kea') as src:
            value = [v for v in src.sample([coords])][0][0]
        # Update the pandas serie accordingly
        values.loc[station_name] = value

# Write records into a CSV file
values.to_csv('test.csv')

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