Wednesday, 1 June 2016

A clear day for Sentinel 2 satellite image of Cornwall

The ESA Copernicus programme includes the twin satellites Sentinel 2A and Sentinel 2B which have a multiband sensor. Details can be found here: https://sentinel.esa.int/web/sentinel/missions/sentinel-2.

Sentinel 2A has already been launched and is taking data, and Sentinel 2B will be launched later in 2016.

The Scientific Data Hub provides access to the data, although there is also access via an API, and via Amazon Web Services, and USGS Earth Explorer (currently some time behind).

Until recently, the images of Cornwall had been mostly heavily affected by cloud, although there was a better one taken on 30th May 2016.

A composite of bands 2, 3, and 4 (not atmospherically corrected) showing west Cornwall.

A composite of bands 2, 3 and 4 (not atmospherically corrected) around Aberystwyth in mid-Wales.
A Python script, using RSGISlib to stack Sentinel2 images into a band-stacked .kea file:

# David Trethewey 01-06-2016
#
# Sentinel2 Bands Stacker
# Uses visible, NIR, SWIR bands
# 
# Assumptions:
#
# the .jp2 files are in the current directory
# that this script is being run from
#
# there is only one Sentinel2 scene in the directory
# and no other jp2 files
#  
# Converts jp2 files of each band to single stacked file
#  
# imports
import rsgislib
import rsgislib.imageutils
import os.path
import sys

# image list
# find all *.jp2 files in the current directory
directory = os.getcwd()
dirFileList = os.listdir(directory)
# print dirFileList

jp2FileList = [f for f in dirFileList if (f[-4:].lower()=='.jp2')]

bands = ['01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '11', '12', '8A']
# bands that are already at 10m resolution
bands_10m = ['02', '03', '04', '08']

# resample other bands to resolution of blue image (B02)
bands_toberesam = [b for b in bands if b not in bands_10m]

# identify the band number by counting backwards from the end in the filename
Bands_VIS_NIR_SWIR_FileList = [f for f in jp2FileList if (f[-6:-4] in bands)and(f[-7]=='B')]

# list of bands to be resampled
Bands_resam_FileList = [f for f in jp2FileList if (f[-6:-4] in bands_toberesam)and(f[-7]=='B')]

# find the filename of the blue image
blue_image = [f for f in jp2FileList if (f[-6:-4] == '02')and(f[-7]=='B')][0]

# bands to be resampled 20m --> 10m
# 05, 06, 07, 8b, 11, 12
# bands to be resampled 60m --> 10m
# 01, 09, 10

for b in Bands_resam_FileList:
    print("resampling band {q} to 10m".format(q=b[-6:-4]))
    outFile = b[:-4]+'_10m.kea'
    rsgislib.imageutils.resampleImage2Match(blue_image, b, outFile, 'KEA', 'cubic')
    Bands_VIS_NIR_SWIR_FileList.remove(b)
    Bands_VIS_NIR_SWIR_FileList.append(outFile)

Bands_VIS_NIR_SWIR_FileList = sorted(Bands_VIS_NIR_SWIR_FileList)

fileNameBase = blue_image[:-7]

# Sentinel2 bands
bandNamesList = ["B1Coastal443nm", "B2Blue490nm", "B3Green560nm", "B4Red665nm", "B5NIR705nm", "B6NIR740nm",
                 "B7NIR783nm", "B8NIR_broad842nm", "B9NIR940nm", "B10_1375nm", "B11_SWIR1610nm",
                 "B12_SWIR2190nm", "B8A_NIR865nm"]

#output file name
outputImage = fileNameBase + 'B'+''.join(bands)+'_stack.kea'

#output format (GDAL code)
outFormat = 'KEA'
outType = rsgislib.TYPE_32UINT

# stack bands using rsgislib 
rsgislib.imageutils.stackImageBands(Bands_VIS_NIR_SWIR_FileList, bandNamesList, outputImage, None, 0, outFormat, outType)
# stats and pyramids
rsgislib.imageutils.popImageStats(outputImage,True,0.,True)

# remove individual resampled 10m files
print("removing intermediate resampled files")
for b in Bands_resam_FileList:
    outFile = b[:-4]+'_10m.kea'
    os.remove(outFile)


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