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isce_utils.py
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isce_utils.py
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"""Utilities wrapped around ISCE."""
############################################################
# Program is part of MintPy #
# Copyright (c) 2013, Zhang Yunjun, Heresh Fattahi #
# Author: Zhang Yunjun, Heresh Fattahi, Apr 2020 #
############################################################
# 2020-07: Talib Oliver-Cabrera, add UAVSAR support
# 2020-10: Cunren Liang, add alosStack support
# 2022-06: Yujie Zheng, add standard processing from isce2
# Group contents:
# metadata
# geometry
# baseline
# multilook
# miscellaneous
# Recommend import:
# from mintpy.utils import isce_utils
import datetime
import glob
import logging
import os
import shelve
import time
import numpy as np
from scipy import ndimage
from mintpy.constants import EARTH_RADIUS, SPEED_OF_LIGHT
from mintpy.objects import sensor
from mintpy.utils import (
attribute as attr,
ptime,
readfile,
utils1 as ut,
writefile,
)
# suppress matplotlib DEBUG message
mpl_logger = logging.getLogger('matplotlib')
mpl_logger.setLevel(logging.WARNING)
def get_processor(meta_file):
"""
Get the name of ISCE processor (imaging mode)
"""
meta_dir = os.path.dirname(meta_file)
tops_meta_file = os.path.join(meta_dir, 'IW*.xml')
alos_meta_file = os.path.join(meta_dir, '*.track.xml')
stripmap_meta_files = [os.path.join(meta_dir, i) for i in ['data.db', 'data.dat', 'data']]
processor = None
if len(glob.glob(tops_meta_file)) > 0:
# topsStack
processor = 'tops'
elif len(glob.glob(alos_meta_file)) > 0:
# alosStack / alos2App
processor = 'alosStack'
elif any(os.path.isfile(i) for i in stripmap_meta_files):
# stripmapStack
processor = 'stripmap'
elif meta_file.endswith('.xml'):
# stripmapApp
processor = 'stripmap'
else:
raise ValueError(f'Un-recognized ISCE processor for metadata file: {meta_file}')
return processor
##################################### metadata #######################################
def load_product(xml_name):
"""Load the product using Product Manager."""
import isce
from iscesys.Component.ProductManager import ProductManager
pm = ProductManager()
pm.configure()
return pm.loadProduct(xml_name)
def extract_isce_metadata(meta_file, geom_dir=None, rsc_file=None, update_mode=True):
"""Extract metadata from ISCE stack products
Parameters: meta_file : str, path of metadata file, reference/IW1.xml or referenceShelve/data.dat
geom_dir : str, path of geometry directory.
rsc_file : str, output file name of ROIPAC format rsc file. None for not write to disk.
Returns: meta : dict
frame : object, isceobj.Scene.Frame.Frame / isceobj.Scene.Burst.Burst
"""
# check existing rsc_file
if update_mode and ut.run_or_skip(rsc_file, in_file=meta_file, readable=False) == 'skip':
return readfile.read_roipac_rsc(rsc_file), None
# 1. read/extract metadata from XML / shelve file
processor = get_processor(meta_file)
if processor == 'tops':
print('extract metadata from ISCE/topsStack xml file:', meta_file)
meta, frame = extract_tops_metadata(meta_file)
elif processor == 'alosStack':
print('extract metadata from ISCE/alosStack xml file:', meta_file)
meta, frame = extract_alosStack_metadata(meta_file, geom_dir)
else:
print('extract metadata from ISCE/stripmapStack shelve file:', meta_file)
meta, frame = extract_stripmap_metadata(meta_file)
# 2. extract metadata from geometry file
if geom_dir:
if processor != 'alosStack':
meta = extract_geometry_metadata(geom_dir, meta)
# 3. common metadata
meta['PROCESSOR'] = 'isce'
if 'ANTENNA_SIDE' not in meta.keys():
meta['ANTENNA_SIDE'] = '-1'
# convert all value to string format
for key, value in meta.items():
meta[key] = str(value)
# write to .rsc file
meta = readfile.standardize_metadata(meta)
if rsc_file:
print('writing ', rsc_file)
writefile.write_roipac_rsc(meta, rsc_file)
return meta, frame
def extract_tops_metadata(xml_file):
"""Read metadata from xml file for Sentinel-1/TOPS
Parameters: xml_file : str, path of the .xml file, i.e. reference/IW1.xml
Returns: meta : dict, metadata
burst : isceobj.Sensor.TOPS.BurstSLC.BurstSLC object
"""
import isce
import isceobj
from isceobj.Planet.Planet import Planet
obj = load_product(xml_file)
burst = obj.bursts[0]
burstEnd = obj.bursts[-1]
meta = {}
meta['prf'] = burst.prf
meta['startUTC'] = burst.burstStartUTC
meta['stopUTC'] = burstEnd.burstStopUTC
meta['radarWavelength'] = burst.radarWavelength
meta['startingRange'] = burst.startingRange
meta['passDirection'] = burst.passDirection
meta['polarization'] = burst.polarization
meta['trackNumber'] = burst.trackNumber
meta['orbitNumber'] = burst.orbitNumber
try:
meta['PLATFORM'] = sensor.standardize_sensor_name(obj.spacecraftName)
except:
if os.path.basename(xml_file).startswith('IW'):
meta['PLATFORM'] = 'sen'
time_seconds = (burst.sensingMid.hour * 3600.0 +
burst.sensingMid.minute * 60.0 +
burst.sensingMid.second)
meta['CENTER_LINE_UTC'] = time_seconds
orbit = burst.orbit
peg = orbit.interpolateOrbit(burst.sensingMid, method='hermite')
# Sentinel-1 TOPS pixel spacing
Vs = np.linalg.norm(peg.getVelocity()) #satellite speed
meta['satelliteSpeed'] = Vs
meta['azimuthPixelSize'] = Vs * burst.azimuthTimeInterval
meta['rangePixelSize'] = burst.rangePixelSize
# Sentinel-1 TOPS spatial resolution
iw_str = 'IW2'
if os.path.basename(xml_file).startswith('IW'):
iw_str = os.path.splitext(os.path.basename(xml_file))[0]
meta['azimuthResolution'] = sensor.SENSOR_DICT['sen'][iw_str]['azimuth_resolution']
meta['rangeResolution'] = sensor.SENSOR_DICT['sen'][iw_str]['range_resolution']
elp = Planet(pname='Earth').ellipsoid
llh = elp.xyz_to_llh(peg.getPosition())
elp.setSCH(llh[0], llh[1], orbit.getENUHeading(burst.sensingMid))
meta['HEADING'] = orbit.getENUHeading(burst.sensingMid)
meta['earthRadius'] = elp.pegRadCur
meta['altitude'] = llh[2]
# for Sentinel-1
meta['beam_mode'] = 'IW'
meta['swathNumber'] = burst.swathNumber
# 1. multipel subswaths
xml_files = glob.glob(os.path.join(os.path.dirname(xml_file), 'IW*.xml'))
if len(xml_files) > 1:
swath_num = [load_product(fname).bursts[0].swathNumber for fname in xml_files]
meta['swathNumber'] = ''.join(str(i) for i in sorted(swath_num))
# 2. calculate ASF frame number for Sentinel-1
meta['firstFrameNumber'] = int(0.2 * (burst.burstStartUTC - obj.ascendingNodeTime).total_seconds())
meta['lastFrameNumber'] = int(0.2 * (burstEnd.burstStopUTC - obj.ascendingNodeTime).total_seconds())
return meta, burst
def extract_stripmap_metadata(meta_file):
"""Read metadata from shelve file for StripMap stack from ISCE
Parameters: meta_file : str, path of the shelve file, i.e. referenceShelve/data.dat
Returns: meta : dict, metadata
frame : isceobj.Scene.Frame.Frame object
"""
import isce
import isceobj
from isceobj.Planet.Planet import Planet
if os.path.basename(meta_file).startswith('data'):
# shelve file from stripmapStack
# referenceShelve/data for uavsar
# referenceShelve/data.dat for all the others
fbase = os.path.splitext(meta_file)[0]
with shelve.open(fbase, flag='r') as mdb:
frame = mdb['frame']
elif meta_file.endswith(".xml"): #XML file from stripmapApp
frame = load_product(meta_file)
else:
raise ValueError(f'un-recognized isce/stripmap metadata file: {meta_file}')
meta = {}
meta['prf'] = frame.PRF
meta['startUTC'] = frame.sensingStart
meta['stopUTC'] = frame.sensingStop
meta['radarWavelength'] = frame.radarWavelegth
meta['startingRange'] = frame.startingRange
meta['trackNumber'] = frame.trackNumber
meta['orbitNumber'] = frame.orbitNumber
meta['PLATFORM'] = sensor.standardize_sensor_name(frame.platform.getSpacecraftName())
meta['polarization'] = str(frame.polarization).replace('/', '')
if meta['polarization'].startswith("b'"):
meta['polarization'] = meta['polarization'][2:4]
time_seconds = (frame.sensingMid.hour * 3600.0 +
frame.sensingMid.minute * 60.0 +
frame.sensingMid.second)
meta['CENTER_LINE_UTC'] = time_seconds
orbit = frame.orbit
peg = orbit.interpolateOrbit(frame.sensingMid, method='hermite')
Vs = np.linalg.norm(peg.getVelocity()) #satellite speed
meta['satelliteSpeed'] = Vs
meta['azimuthResolution'] = frame.platform.antennaLength / 2.0
meta['azimuthPixelSize'] = Vs / frame.PRF
frame.getInstrument()
rgBandwidth = frame.instrument.pulseLength * frame.instrument.chirpSlope
meta['rangeResolution'] = abs(SPEED_OF_LIGHT / (2.0 * rgBandwidth))
meta['rangePixelSize'] = frame.instrument.rangePixelSize
elp = Planet(pname='Earth').ellipsoid
llh = elp.xyz_to_llh(peg.getPosition())
elp.setSCH(llh[0], llh[1], orbit.getENUHeading(frame.sensingMid))
meta['HEADING'] = orbit.getENUHeading(frame.sensingMid)
meta['earthRadius'] = elp.pegRadCur
meta['altitude'] = llh[2]
# for StripMap
meta['beam_mode'] = 'SM'
return meta, frame
def extract_alosStack_metadata(meta_file, geom_dir):
"""Read metadata for ISCE/alosStack from the following files:
pairs/*-*/
{date1}.track.xml
f1_{frame1}/{date1}.frame.xml
f2_{frame2}/{date1}.frame.xml
...
Parameters: meta_file : str, path of the track xml file, i.e. pairs/*-*/150408/track.xml
geom_dir : str, path of the geometry directory, i.e. dates_resampled/150408/insar
Returns: meta : dict, metadata
track : isceobj.Sensor.MultiMode.Track.Track object
"""
import isce
import isceobj
from isceobj.Planet.Planet import Planet
# default geom_dir
if not geom_dir:
geom_dir_cand = os.path.join(os.path.dirname(meta_file), 'insar')
if os.path.isdir(geom_dir_cand):
geom_dir = geom_dir_cand
track = load_track(os.path.dirname(meta_file), dateStr=os.path.basename(meta_file).strip('.track.xml'))
rlooks, alooks, width, length = extract_image_size_alosStack(geom_dir)
spotlightModes, stripmapModes, scansarNominalModes, scansarWideModes, scansarModes = alos2_acquisition_modes()
meta = {}
meta['prf'] = track.prf
meta['startUTC'] = track.sensingStart + datetime.timedelta(seconds=(alooks-1.0)/2.0*track.azimuthLineInterval)
meta['stopUTC'] = meta['startUTC'] + datetime.timedelta(seconds=(length-1)*alooks*track.azimuthLineInterval)
meta['radarWavelength'] = track.radarWavelength
meta['startingRange'] = track.startingRange + (rlooks-1.0)/2.0*track.rangePixelSize
meta['passDirection'] = track.passDirection.upper()
meta['polarization'] = track.frames[0].swaths[0].polarization
#meta['trackNumber'] = track.trackNumber
#meta['orbitNumber'] = track.orbitNumber
meta['PLATFORM'] = sensor.standardize_sensor_name('alos2')
sensingSec = (meta['stopUTC'] - meta['startUTC']).total_seconds()
sensingMid = meta['startUTC'] + datetime.timedelta(seconds=sensingSec/2.0)
time_seconds = (sensingMid.hour * 3600.0 +
sensingMid.minute * 60.0 +
sensingMid.second)
meta['CENTER_LINE_UTC'] = time_seconds
peg = track.orbit.interpolateOrbit(sensingMid, method='hermite')
Vs = np.linalg.norm(peg.getVelocity())
meta['satelliteSpeed'] = Vs
meta['azimuthPixelSize'] = Vs * track.azimuthLineInterval
meta['rangePixelSize'] = track.rangePixelSize
azBandwidth = track.prf * 0.8
if track.operationMode in scansarNominalModes:
azBandwidth /= 5.0
if track.operationMode in scansarWideModes:
azBandwidth /= 7.0
#use a mean burst synchronizatino here
if track.operationMode in scansarModes:
azBandwidth *= 0.85
meta['azimuthResolution'] = Vs * (1.0/azBandwidth)
meta['rangeResolution'] = 0.5 * SPEED_OF_LIGHT * (1.0/track.frames[0].swaths[0].rangeBandwidth)
elp = Planet(pname='Earth').ellipsoid
llh = elp.xyz_to_llh(peg.getPosition())
elp.setSCH(llh[0], llh[1], track.orbit.getENUHeading(sensingMid))
meta['HEADING'] = track.orbit.getENUHeading(sensingMid)
meta['earthRadius'] = elp.pegRadCur
meta['altitude'] = llh[2]
meta['beam_mode'] = track.operationMode
meta['swathNumber'] = ''.join(str(swath.swathNumber) for swath in track.frames[0].swaths)
meta['firstFrameNumber'] = track.frames[0].frameNumber
meta['lastFrameNumber'] = track.frames[-1].frameNumber
meta['ALOOKS'] = alooks
meta['RLOOKS'] = rlooks
# NCORRLOOKS for coherence calibration
rgfact = float(meta['rangeResolution']) / float(meta['rangePixelSize'])
azfact = float(meta['azimuthResolution']) / float(meta['azimuthPixelSize'])
meta['NCORRLOOKS'] = meta['RLOOKS'] * meta['ALOOKS'] / (rgfact * azfact)
# update pixel_size for multilooked data
meta['rangePixelSize'] *= meta['RLOOKS']
meta['azimuthPixelSize'] *= meta['ALOOKS']
# LAT/LON_REF1/2/3/4
edge = 3
lat_file = glob.glob(os.path.join(geom_dir, f'*_{rlooks}rlks_{alooks}alks.lat'))[0]
img = isceobj.createImage()
img.load(lat_file+'.xml')
width = img.width
length = img.length
data = np.memmap(lat_file, dtype='float64', mode='r', shape=(length, width))
meta['LAT_REF1'] = str(data[ 0+edge, 0+edge])
meta['LAT_REF2'] = str(data[ 0+edge, -1-edge])
meta['LAT_REF3'] = str(data[-1-edge, 0+edge])
meta['LAT_REF4'] = str(data[-1-edge, -1-edge])
lon_file = glob.glob(os.path.join(geom_dir, f'*_{rlooks}rlks_{alooks}alks.lon'))[0]
data = np.memmap(lon_file, dtype='float64', mode='r', shape=(length, width))
meta['LON_REF1'] = str(data[ 0+edge, 0+edge])
meta['LON_REF2'] = str(data[ 0+edge, -1-edge])
meta['LON_REF3'] = str(data[-1-edge, 0+edge])
meta['LON_REF4'] = str(data[-1-edge, -1-edge])
# CENTER_INCIDENCE_ANGLE is optional
los_files = glob.glob(os.path.join(geom_dir, f'*_{rlooks}rlks_{alooks}alks.los'))
if len(los_files) > 0:
data = np.memmap(los_files[0], dtype='float32', mode='r', shape=(length*2, width))[0:length*2:2, :]
inc_angle = data[int(length/2), int(width/2)]
meta['CENTER_INCIDENCE_ANGLE'] = str(inc_angle)
pointingDirection = {'right': -1, 'left' :1}
meta['ANTENNA_SIDE'] = str(pointingDirection[track.pointingDirection])
return meta, track
def alos2_acquisition_modes():
'''
return ALOS-2 acquisition mode
'''
spotlightModes = ['SBS']
# StripMap: Ultrafine [3 m], High sensitive [6 m], Fine [10 m]
stripmapModes = ['UBS', 'UBD', 'HBS', 'HBD', 'HBQ', 'FBS', 'FBD', 'FBQ']
scansarNominalModes = ['WBS', 'WBD', 'WWS', 'WWD']
scansarWideModes = ['VBS', 'VBD']
scansarModes = scansarNominalModes + scansarWideModes
return (spotlightModes, stripmapModes, scansarNominalModes, scansarWideModes, scansarModes)
def extract_image_size_alosStack(geom_dir):
import isce
import isceobj
# grab the number of looks in azimuth / range direction
lats = glob.glob(os.path.join(geom_dir, '*_*rlks_*alks.lat'))
rlooks = max(int(os.path.splitext(os.path.basename(x))[0].split('_')[1].strip('rlks')) for x in lats)
alooks = max(int(os.path.splitext(os.path.basename(x))[0].split('_')[2].strip('alks')) for x in lats)
# grab the number of rows / coluns
lat = glob.glob(os.path.join(geom_dir, f'*_{rlooks}rlks_{alooks}alks.lat'))[0]
img = isceobj.createImage()
img.load(lat+'.xml')
width = img.width
length = img.length
return (rlooks, alooks, width, length)
def load_track(trackDir, dateStr):
'''Load the track using Product Manager.
Parameters: trackDir - str, directory of the *.track.xml file
dateStr - str, date in YYMMDD format
Returns: track - isceobj.Sensor.MultiMode.Track.Track object
'''
# read *.track.xml file
track = load_product(os.path.join(trackDir, f'{dateStr}.track.xml'))
# read *.frame.xml files
track.frames = []
fnames = sorted(glob.glob(os.path.join(trackDir, f'f*_*/{dateStr}.frame.xml')))
for fname in fnames:
track.frames.append(load_product(fname))
return track
##################################### geometry #######################################
def extract_multilook_number(geom_dir, meta=dict(), fext_list=['.rdr','.geo','.rdr.full','.geo.full']):
for fbase in ['hgt','lat','lon','los']:
fbase = os.path.join(geom_dir, fbase)
for fext in fext_list:
fnames = glob.glob(fbase+fext)
if len(fnames) > 0:
break
if len(fnames) > 0:
fullXmlFile = f'{fnames[0]}.full.xml'
if os.path.isfile(fullXmlFile):
fullXmlDict = readfile.read_isce_xml(fullXmlFile)
xmlDict = readfile.read_attribute(fnames[0])
meta['ALOOKS'] = int(int(fullXmlDict['LENGTH']) / int(xmlDict['LENGTH']))
meta['RLOOKS'] = int(int(fullXmlDict['WIDTH']) / int(xmlDict['WIDTH']))
break
# default value
for key in ['ALOOKS', 'RLOOKS']:
if key not in meta:
meta[key] = 1
# NCORRLOOKS for coherence calibration
rgfact = float(meta['rangeResolution']) / float(meta['rangePixelSize'])
azfact = float(meta['azimuthResolution']) / float(meta['azimuthPixelSize'])
meta['NCORRLOOKS'] = meta['RLOOKS'] * meta['ALOOKS'] / (rgfact * azfact)
return meta
def extract_geometry_metadata(geom_dir, meta=dict(), box=None, fbase_list=['hgt','lat','lon','los'],
fext_list=['.rdr','.geo','.rdr.full','.geo.full']):
"""Extract / update metadata from geometry files
extract LAT_REF1/2/3/4 from lat*
extract LON_REF1/2/3/4 from lon*
extract HEADING from los (azimuth angle)
extract A/RLOOKS by comparing hgt.xml and hgt.full.xml file
update azimuthPixelSize / rangePixelSize based on A/RLOOKS
extract LENGTH/WIDTH from the first geom file
update corresponding metadata if box is not None
"""
def get_nonzero_row_number(data, buffer=2):
"""Find the first and last row number of rows without zero value
for multiple swaths data
"""
if np.all(data):
r0, r1 = 0 + buffer, -1 - buffer
else:
row_flag = np.sum(data != 0., axis=1) == data.shape[1]
row_idx = np.where(row_flag)[0]
r0, r1 = row_idx[0] + buffer, row_idx[-1] - buffer
return r0, r1
# grab existing files
geom_dir = os.path.abspath(geom_dir)
for fext in fext_list:
geom_files = [os.path.join(geom_dir, fbase+fext) for fbase in fbase_list]
geom_files = [i for i in geom_files if os.path.isfile(i)]
if len(geom_files) > 0:
break
# printout message
if len(geom_files) == 0:
msg = 'WARNING: No geometry files found with the following pattern!'
msg += f'\n file basenme: {fbase_list}'
msg += f'\n file extension: {fext_list}'
print(msg)
return meta
print(f'extract metadata from geometry files: {[os.path.basename(i) for i in geom_files]}')
# get A/RLOOKS
meta = extract_multilook_number(geom_dir, meta, fext_list=fext_list)
# update pixel_size for multilooked data
meta['rangePixelSize'] *= meta['RLOOKS']
meta['azimuthPixelSize'] *= meta['ALOOKS']
# get LENGTH/WIDTH
atr = readfile.read_attribute(geom_files[0])
meta['LENGTH'] = atr['LENGTH']
meta['WIDTH'] = atr['WIDTH']
# update due to subset
if box:
meta = attr.update_attribute4subset(meta, box)
# get LAT/LON_REF1/2/3/4 into metadata
for geom_file in geom_files:
if 'lat' in os.path.basename(geom_file):
data = readfile.read(geom_file, box=box)[0]
r0, r1 = get_nonzero_row_number(data)
meta['LAT_REF1'] = str(data[r0, 0])
meta['LAT_REF2'] = str(data[r0, -1])
meta['LAT_REF3'] = str(data[r1, 0])
meta['LAT_REF4'] = str(data[r1, -1])
if 'lon' in os.path.basename(geom_file):
data = readfile.read(geom_file, box=box)[0]
r0, r1 = get_nonzero_row_number(data)
meta['LON_REF1'] = str(data[r0, 0])
meta['LON_REF2'] = str(data[r0, -1])
meta['LON_REF3'] = str(data[r1, 0])
meta['LON_REF4'] = str(data[r1, -1])
if 'los' in os.path.basename(geom_file):
# CENTER_INCIDENCE_ANGLE
data = readfile.read(geom_file, datasetName='inc', box=box)[0]
data[data == 0.] = np.nan
inc_angle = data[int(data.shape[0]/2), int(data.shape[1]/2)]
meta['CENTER_INCIDENCE_ANGLE'] = str(inc_angle)
return meta
##################################### baseline #######################################
def read_tops_baseline(baseline_file):
"""Read baseline file generated by ISCE/topsStack processor.
Example:
baselines/20141213_20160418/20141213_20160418.txt:
swath: IW1
Bperp (average): 62.62863491739495
Bpar (average): -29.435602419751426
swath: IW2
Bperp (average): 60.562020649374034
Bpar (average): -34.56105358031081
"""
bperps = []
with open(baseline_file) as f:
for line in f:
c = line.split(":")
if c[0] == "Bperp (average)":
bperps.append(float(c[1]))
bperp_top = np.mean(bperps)
bperp_bottom = np.mean(bperps)
return [bperp_top, bperp_bottom]
def read_stripmap_baseline(baseline_file):
"""Read baseline file generated by ISCE/stripmapStack processor.
Example:
baselines/20200111_20200125.txt
PERP_BASELINE_BOTTOM 173.97914535263297
PERP_BASELINE_TOP 174.05612879066618
"""
fDict = readfile.read_template(baseline_file, delimiter=' ')
bperp_top = float(fDict['PERP_BASELINE_TOP'])
bperp_bottom = float(fDict['PERP_BASELINE_BOTTOM'])
return [bperp_top, bperp_bottom]
def read_alosStack_baseline(baseline_file):
'''read baseline file generated by alosStack
'''
bDict = {}
with open(baseline_file) as f:
lines = [line for line in f if line.strip() != '']
for x in lines[2:]:
blist = x.split()
#to fit into the format of other processors, all alos satellites are after 2000
blist[0] = '20' + blist[0]
blist[1] = '20' + blist[1]
bDict[blist[1]] = [float(blist[3]), float(blist[3])]
bDict[blist[0]] = [0, 0]
return bDict, blist[0]
def read_baseline_timeseries(baseline_dir, processor='tops', ref_date=None):
"""Read bperp time-series from files in baselines directory
Parameters: baseline_dir : str, path to the baselines directory
processor : str, tops for Sentinel-1/TOPS
stripmap for StripMap data
ref_date : str, reference date in (YY)YYMMDD
Returns: bDict : dict, in the following format:
{'20141213': [0.0, 0.0],
'20141225': [104.6, 110.1],
...
}
"""
# grab all existed baseline files
print(f'read perp baseline time-series from {baseline_dir}')
if processor == 'tops':
bFiles = sorted(glob.glob(os.path.join(baseline_dir, '*/*.txt')))
elif processor == 'stripmap':
bFiles = sorted(glob.glob(os.path.join(baseline_dir, '*.txt')))
elif processor == 'alosStack':
# all baselines are in baseline_center.txt
bFiles = glob.glob(os.path.join(baseline_dir, 'baseline_center.txt'))
else:
raise ValueError(f'Un-recognized ISCE stack processor: {processor}')
if len(bFiles) == 0:
print(f'WARNING: no baseline text file found in dir {os.path.abspath(baseline_dir)}')
return None
if processor in ['tops', 'stripmap']:
# ignore files with different date1
# when re-run with different reference date
date1s = [os.path.basename(i).split('_')[0] for i in bFiles]
date1c = ut.most_common(date1s)
bFiles = [i for i in bFiles if os.path.basename(i).split('_')[0] == date1c]
# ignore empty files
bFiles = [i for i in bFiles if os.path.getsize(i) > 0]
# read files into dict
bDict = {}
for bFile in bFiles:
dates = os.path.basename(bFile).split('.txt')[0].split('_')
if processor == 'tops':
bDict[dates[1]] = read_tops_baseline(bFile)
else:
bDict[dates[1]] = read_stripmap_baseline(bFile)
bDict[dates[0]] = [0, 0]
ref_date0 = dates[0]
elif processor == 'alosStack':
bDict, ref_date0 = read_alosStack_baseline(bFiles[0])
else:
raise ValueError(f'Un-recognized ISCE stack processor: {processor}')
# change reference date
if ref_date is not None and ref_date != ref_date0:
ref_date = ptime.yyyymmdd(ref_date)
print(f'change reference date to {ref_date}')
ref_bperp = bDict[ref_date]
for key in bDict.keys():
bDict[key][0] -= ref_bperp[0]
bDict[key][1] -= ref_bperp[1]
return bDict
##################################### multilook #######################################
def multilook_number2resolution(meta_file, az_looks, rg_looks):
# get full resolution info
az_pixel_size, az_spacing, rg_pixel_size, rg_spacing = get_full_resolution(meta_file)
# print out message
print(f'Azimuth pixel size : {az_pixel_size:.1f}')
print(f'Azimuth ground spacing : {az_spacing:.1f}')
print(f'Azimuth ground spacing : {az_spacing*az_looks:.1f} after multilooking by {az_looks}')
print(f'Range pixel size : {rg_pixel_size:.1f}')
print(f'Range ground spacing : {rg_spacing:.1f}')
print(f'Range ground spacing : {rg_spacing*rg_looks:.1f} after multilooking by {rg_looks}')
return
def resolution2multilook_number(meta_file, resolution):
"""
Calculate multilook number for InSAR processing given a disired output resolution on the ground
Parameters: meta_file : str, path of ISCE metadata file, i.e. IW1.xml, data.dat
resolution : float, target output resolution on the ground in meters
Returns: az/rg_looks : int, number of looks in azimuth / range direction
"""
# get full resolution info
az_pixel_size, az_spacing, rg_pixel_size, rg_spacing = get_full_resolution(meta_file)
# calculate number of looks
# 1. adjust the final resolution in one direction closest to the input resolution
az_looks = resolution / az_spacing
rg_looks = resolution / rg_spacing
az_round_frac = abs(az_looks - np.rint(az_looks))
rg_round_frac = abs(rg_looks - np.rint(rg_looks))
if az_round_frac < rg_round_frac:
resolution = np.rint(az_looks) * az_spacing
else:
resolution = np.rint(rg_looks) * rg_spacing
# 2. calculate the multilook number based on the adjusted resolution
az_looks = np.rint(resolution / az_spacing).astype(int)
rg_looks = np.rint(resolution / rg_spacing).astype(int)
# print out message
print(f'Azimuth pixel size : {az_pixel_size:.1f}')
print(f'Azimuth ground spacing : {az_spacing:.1f}')
print(f'Azimuth ground spacing : {az_spacing*az_looks:.1f} after multilooking by {az_looks}')
print(f'Range pixel size : {rg_pixel_size:.1f}')
print(f'Range ground spacing : {rg_spacing:.1f}')
print(f'Range ground spacing : {rg_spacing*rg_looks:.1f} after multilooking by {rg_looks}')
return az_looks, rg_looks
def get_full_resolution(meta_file):
"""
Grab the full resolution in terms of pixel_size and ground spacing
"""
# check metadata file extension: only ISCE format is supported.
fext = os.path.splitext(meta_file)[1]
if fext not in ['.xml', '.dat']:
raise ValueError(f'input ISCE metadata file extension "{fext}" not in [.xml, .dat]')
# get middle sub-swath xml file for Sentinel-1 data
if meta_file.endswith('.xml'):
meta_files = glob.glob(meta_file)
mid_idx = int(len(meta_files) / 2)
meta_file = meta_files[mid_idx]
# extract metadata
meta, frame = extract_isce_metadata(meta_file, update_mode=False)
meta['WIDTH'] = frame.numberOfSamples
# calculate the full azimuth/range ground resolution
az_pixel_size = float(meta['AZIMUTH_PIXEL_SIZE']) #azimuth pixel size on the orbit
rg_pixel_size = float(meta['RANGE_PIXEL_SIZE']) #range pixel size in LOS direction
az_pixel_size /= int(meta.get('ALOOKS', 1))
rg_pixel_size /= int(meta.get('RLOOKS', 1))
height = float(meta['HEIGHT'])
inc_angle = ut.incidence_angle(meta, dimension=0)
az_spacing = az_pixel_size * EARTH_RADIUS / (EARTH_RADIUS + height) #azimuth pixel size on the ground
rg_spacing = rg_pixel_size / np.sin(inc_angle / 180. * np.pi) #range pixel size on the ground
return az_pixel_size, az_spacing, rg_pixel_size, rg_spacing
##################################### miscellaneous #######################################
def get_IPF(proj_dir, ts_file):
"""Grab the IPF version number of each sub-swatch for Sentinel-1 time-series
Parameters: proj_dir - str, path of the project directory
E.g.: ~/data/AtacamaSenDT149
ts_file - str, path of HDF5 file for time-series
Returns: date_list - list of str, dates in YYYYMMDD format
IFP_IW1/2/3 - list of str, IFP version number
"""
from mintpy.objects import timeseries
s_dir = os.path.join(proj_dir, 'secondarys')
m_dir = os.path.join(proj_dir, 'reference')
# date list
date_list = timeseries(ts_file).get_date_list()
num_date = len(date_list)
# reference date
m_date = [i for i in date_list if not os.path.isdir(os.path.join(s_dir, i))][0]
# grab IPF numver
IPF_IW1, IPF_IW2, IPF_IW3 = [], [], []
prog_bar = ptime.progressBar(maxValue=num_date)
for i in range(num_date):
date_str = date_list[i]
# get xml_dir
if date_str == m_date:
xml_dir = m_dir
else:
xml_dir = os.path.join(s_dir, date_str)
# grab IPF version number
for j, IPF_IW in enumerate([IPF_IW1, IPF_IW2, IPF_IW3]):
xml_file = os.path.join(xml_dir, f'IW{j+1}.xml')
IPFv = load_product(xml_file).processingSoftwareVersion
IPF_IW.append(f'{float(IPFv):.02f}')
prog_bar.update(i+1, suffix=f'{date_str} IW1/2/3')
prog_bar.close()
return date_list, IPF_IW1, IPF_IW2, IPF_IW3
def get_sensing_datetime_list(proj_dir, date_list=None):
"""Get the sensing datetime objects from ISCE stack results.
It assumes the default directory structure from topsStack, as below:
/proj_dir
/reference/IW*.xml
/secondarys
/20150521/IW*.xml
/20150614/IW*.xml
...
/20210113/IW*.xml
Parameters: proj_dir - str, path to the root directory of stack processing
Returns: sensingMid - list of datetime.datetime.obj
sensingStart - list of datetime.datetime.obj
sensingStop - list of datetime.datetime.obj
"""
# determine xml file basename
ref_fname = glob.glob(os.path.join(proj_dir, 'reference', 'IW*.xml'))[0]
fbase = os.path.basename(ref_fname)
# get xml files for all acquisitions
sec_fnames = sorted(glob.glob(os.path.join(proj_dir, 'secondarys', '*', fbase)))
fnames = [ref_fname] + sec_fnames
num_file = len(fnames)
# loop to read file one by one
sensingStart = []
sensingStop = []
for i, fname in enumerate(fnames):
print(f'[{i+1}/{num_file}] read {fname}')
obj = load_product(fname)
sensingStart.append(obj.bursts[0].sensingStart)
sensingStop.append(obj.bursts[-1].sensingStop)
sensingStart = sorted(sensingStart)
sensingStop = sorted(sensingStop)
# sensingStart/Stop --> sensingMid
sensingMid = [i + (j - i)/2 for i, j in zip(sensingStart, sensingStop)]
# round to the nearest second
print('round sensingStart/Stop/Mid to the nearest second.')
sensingStart = [ptime.round_seconds(i) for i in sensingStart]
sensingStop = [ptime.round_seconds(i) for i in sensingStop]
sensingMid = [ptime.round_seconds(i) for i in sensingMid]
if date_list is not None:
date_str_format = ptime.get_date_str_format(date_list[0])
date_list_out = [i.strftime(date_str_format) for i in sensingMid]
# check possible missing dates
dates_missing = [i for i in date_list if i not in date_list_out]
if dates_missing:
raise ValueError(f'The following dates are missing:\n{dates_missing}')
# prune dates not-needed
flag = np.array([i in date_list for i in date_list_out], dtype=np.bool_)
if np.sum(flag) > 0:
sensingMid = np.array(sensingMid)[flag].tolist()
sensingStart = np.array(sensingStart)[flag].tolist()
sensingStop = np.array(sensingStop)[flag].tolist()
dates_removed = np.array(date_list_out)[~flag].tolist()
print(f'The following dates are not needed and removed:\n{dates_removed}')
return sensingMid, sensingStart, sensingStop
############################## Standard Processing ###########################################
def gaussian_kernel(sx, sy, sig_x, sig_y):
'''Generate a guassian kernal (with all elements sum to 1).
Parameters: sx/y - int, dimensions of kernal
sig_x/y - float, standard deviation of the guassian distribution
'''
# ensure sx/y are odd number
sx += 1 if np.mod(sx, 2) == 0 else 0
sy += 1 if np.mod(sy, 2) == 0 else 0
x, y = np.meshgrid(np.arange(sx), np.arange(sy))
x += 1
y += 1
xc = (sx + 1) / 2
yc = (sy + 1) / 2
fx = ((x-xc)**2.) / (2.*sig_x**2.)
fy = ((y-yc)**2.) / (2.*sig_y**2.)
k = np.exp(-1.0 * (fx+fy))
a = 1./np.sum(k)
k = a * k
return k
def convolve(data, kernel):
'''Convolve / filter the complex data based on the given kernel.
Parameters: data - 2D np.ndarray in complex
kernel - 2D np.ndarray in float, convolution kernel
'''
real = ndimage.convolve(data.real, kernel, mode='constant', cval=0.0)
imag = ndimage.convolve(data.imag, kernel, mode='constant', cval=0.0)
return real + 1J * imag
def estimate_coherence(intfile, corfile):
'''Estimate the spatial coherence (phase sigma) of the wrapped interferogram.
Parameters: intfile - str, path to the *.int file
corfile - str, path to the output correlation file
'''
import isce
import isceobj
from mroipac.icu.Icu import Icu
# create filt interferogram file object
filtImage = isceobj.createIntImage()
filtImage.load(intfile + '.xml')
filtImage.setAccessMode('read')
filtImage.createImage()
# create phase sigma correlation file object
phsigImage = isceobj.createImage()
phsigImage.dataType='FLOAT'
phsigImage.bands = 1
phsigImage.setWidth(filtImage.getWidth())
phsigImage.setFilename(corfile)
phsigImage.setAccessMode('write')
phsigImage.createImage()
# setup Icu() object
icuObj = Icu(name='sentinel_filter_icu')
icuObj.configure()
icuObj.unwrappingFlag = False
icuObj.useAmplitudeFlag = False
#icuObj.correlationType = 'NOSLOPE'
# run
icuObj.icu(intImage=filtImage, phsigImage=phsigImage)
phsigImage.renderHdr()
# close
filtImage.finalizeImage()
phsigImage.finalizeImage()
return
def unwrap_snaphu(int_file, cor_file, unw_file, defo_max=2.0, max_comp=32,
init_only=True, init_method='MCF', cost_mode='SMOOTH'):
'''Unwrap interferograms using SNAPHU via isce2.
Modified from ISCE-2/topsStack/unwrap.py
Notes from Piyush:
SNAPHU is an iterative solver, starting from the initial solution. It can get
stuck in an infinite loop.
The initial solution is created using MCF or MST method. The MST initial solution
typically require lots of iterations and may not be a good starting point.
DEFO cost mode requires geometry info for the program to interpret the coherence
correctly and setup costs based on that. DEFO always sounds more theoretical
to me, but I haven not fully explored it. TOPO cost mode requires spatial baseline.
SMOOTH cost mode is purely data driven.
Amplitude of zero is a mask in all cost modes. For TOPO mode, amplitude is used to find
layover; for SMOOTH mode, only non-zero amplitude matters.