def get_atl03_classification(atl03filepath, atl08filepath, df, gt):
# Read ATL03 metrics for class mapping
atl03_ph_index_beg, atl03_segment_id = \
readAtl03DataMapping(atl03filepath,gt)
# Read ATL08 for class mapping
atl08_classed_pc_indx, atl08_classed_pc_flag, atl08_segment_id = \
readAtl08DataMapping(atl08filepath, gt)
# Map ATL08 classifications to ATL03 Photons
allph_classed = getAtl08Mapping(atl03_ph_index_beg, atl03_segment_id,
atl08_classed_pc_indx,
atl08_classed_pc_flag, atl08_segment_id)
# Add classifications to ATL03 DF
df = pd.concat(
[df, pd.DataFrame(allph_classed, columns=['classification'])], axis=1)
# Replace nan with -1 (unclassified)
df.replace({'classification': np.nan}, -1)
return df
def getAtlMeasuredSwath(atl03FilePath=False,
atl08FilePath=False,
outFilePath=False,
gtNum='gt1r',
trimInfo='auto',
createAtl03LasFile=False,
createAtl03KmlFile=False,
createAtl08KmlFile=False,
createAtl03CsvFile=False,
createAtl08CsvFile=False,
logFileID=False):
# pklHeaderFile = None, LAS_DIR = None):
# Initialize outputs
atl03Data = []
headerData = False
rotationData = False
# Initialize ATL08 data
atl08Data = []
atl08_lat = []
atl08_lon = []
atl08_maxCanopy = []
atl08_teBestFit = []
atl08_teMedian = []
atl08_time = []
atl08_easting = []
atl08_northing = []
atl08_crossTrack = []
atl08_alongTrack = []
atl08_classification = []
atl08_intensity = []
# pklHeader = False
# if type(pklHeaderFile) != type(None):
# pklHeader = True
# if type(LAS_DIR) == type(None):
# raise ValueError('LAS_DIR == None, please input LAS_DIR argument')
# Only execute code if input ATL03 .h5 file and output path declared
if (atl03FilePath and outFilePath):
# Start timer
timeStart = runTime.time()
# Get beam # and S/W
beamNum = GtToBeamNum(atl03FilePath, gtNum)
beamStrength = GtToBeamSW(atl03FilePath, gtNum)
# Print message
writeLog(
' Ground Track Number: %s (Beam #%s, Beam Strength: %s)\n' %
(gtNum, beamNum, beamStrength), logFileID)
# Get ATL03 file path/name
atl03FilePath = os.path.normpath(os.path.abspath(atl03FilePath))
atl03FileName = os.path.splitext(os.path.basename(atl03FilePath))[0]
# Read ATL03 data from h5 file
writeLog(' Reading ATL03 .h5 file: %s' % atl03FilePath, logFileID)
lat_all = readAtl03H5(atl03FilePath, '/heights/lat_ph', gtNum)
lon_all = readAtl03H5(atl03FilePath, '/heights/lon_ph', gtNum)
z_all = readAtl03H5(atl03FilePath, '/heights/h_ph', gtNum)
deltaTime_all = readAtl03H5(atl03FilePath, '/heights/delta_time',
gtNum)
signalConf_all = readAtl03H5(atl03FilePath, '/heights/signal_conf_ph',
gtNum)
zGeoidal = readAtl03H5(atl03FilePath, '/geophys_corr/geoid', gtNum)
zGeoidal_deltaTime = readAtl03H5(atl03FilePath,
'/geophys_corr/delta_time', gtNum)
zGeoidal_all = interp_vals(zGeoidal_deltaTime,
zGeoidal,
deltaTime_all,
removeThresh=True)
zMsl_all = z_all - zGeoidal_all
atl03_ph_index_beg, atl03_segment_id = readAtl03DataMapping(
atl03FilePath, gtNum)
badVars = []
if (len(lat_all) == 0):
badVar = 'Latitude (lat_ph)'
badVars.append(badVar)
# endIf
if (len(lon_all) == 0):
badVar = 'Longitude (lon_ph)'
badVars.append(badVar)
# endIf
if (len(z_all) == 0):
badVar = 'Height (h_ph)'
badVars.append(badVar)
# endIf
if (len(deltaTime_all) == 0):
badVar = 'Delta Time (delta_time)'
badVars.append(badVar)
# endIf
if (len(signalConf_all) == 0):
badVar = 'Signal Confidence (signal_conf_ph)'
badVars.append(badVar)
# endIf
if (len(badVars) == 0):
# Get time from delta time
min_delta_time = np.min(deltaTime_all)
time_all = deltaTime_all - min_delta_time
# Get track direction
if (np.abs(lat_all[-1]) >= np.abs(lat_all[0])):
trackDirection = 'Ascending'
else:
trackDirection = 'Descending'
# endIf
writeLog(' Track Direction: %s' % trackDirection, logFileID)
# Extract metadata from ATL03 file name
atl03h5Info = getNameParts(atl03FileName)
# Map ATL08 to ATL03 ground photons
if (atl08FilePath):
# Get ATL08 file path/name
atl08FilePath = os.path.normpath(
os.path.abspath(atl08FilePath))
atl08FileName = os.path.splitext(
os.path.basename(atl08FilePath))[0]
atl08h5Info = getNameParts(atl08FileName)
# Read ATL08 data from .h5 file
writeLog(' Reading ATL08 .h5 file: %s' % atl08FilePath,
logFileID)
atl08_lat = readAtl08H5(atl08FilePath,
'/land_segments/latitude', gtNum)
atl08_lon = readAtl08H5(atl08FilePath,
'/land_segments/longitude', gtNum)
atl08_maxCanopy = readAtl08H5(
atl08FilePath, '/land_segments/canopy/h_max_canopy_abs',
gtNum)
atl08_teBestFit = readAtl08H5(
atl08FilePath, '/land_segments/terrain/h_te_best_fit',
gtNum)
atl08_teMedian = readAtl08H5(
atl08FilePath, '/land_segments/terrain/h_te_median', gtNum)
atl08_deltaTime = readAtl08H5(atl08FilePath,
'/land_segments/delta_time',
gtNum)
atl08_zGeoidal = interp_vals(zGeoidal_deltaTime,
zGeoidal,
atl08_deltaTime,
removeThresh=True)
atl08_maxCanopyMsl = atl08_maxCanopy - atl08_zGeoidal
atl08_teBestFitMsl = atl08_teBestFit - atl08_zGeoidal
atl08_teMedianMsl = atl08_teMedian - atl08_zGeoidal
atl08_classed_pc_indx, atl08_classed_pc_flag, atl08_segment_id = readAtl08DataMapping(
atl08FilePath, gtNum)
atl08_signalConf = np.zeros(np.size(atl08_lat))
atl08_classification = np.zeros(np.size(atl08_lat))
atl08_intensity = np.zeros(np.size(atl08_lat))
if ((len(atl08_lat) > 0) and (len(atl08_lon) > 0)):
# Get time from delta time
atl08_time = atl08_deltaTime - min_delta_time
# Do ATL08 to ATL03 mapping
writeLog(' Mapping ATL08 to ATL03 Ground Photons...',
logFileID)
try:
classification_all = getAtl08Mapping(
atl03_ph_index_beg, atl03_segment_id,
atl08_classed_pc_indx, atl08_classed_pc_flag,
atl08_segment_id)
except:
writeLog(
' WARNING: Could not map ATL08 to ATL03 Ground Photons.',
logFileID)
classification_all = atl08_classification
# endTry
# Get length to trim data by
class_length = len(classification_all)
lat_length = len(lat_all)
data_length = np.min([class_length, lat_length])
# Trim ATL03 data down to size of classification array
atl03_lat = lat_all[0:data_length]
atl03_lon = lon_all[0:data_length]
atl03_z = z_all[0:data_length]
atl03_zMsl = zMsl_all[0:data_length]
atl03_time = time_all[0:data_length]
atl03_deltaTime = deltaTime_all[0:data_length]
atl03_signalConf = signalConf_all[0:data_length]
atl03_classification = classification_all[0:data_length]
atl03_intensity = np.zeros(np.size(atl03_lat))
dataIsMapped = True
else:
writeLog(
' WARNING: ATL08 file does not contain usable data.',
logFileID)
atl08FilePath = False
# Store data
atl03_lat = lat_all
atl03_lon = lon_all
atl03_z = z_all
atl03_zMsl = zMsl_all
atl03_time = time_all
atl03_deltaTime = deltaTime_all
atl03_signalConf = signalConf_all
atl03_classification = np.zeros(np.size(atl03_lat))
atl03_intensity = np.zeros(np.size(atl03_lat))
dataIsMapped = False
# endIf
else:
# Message to screen
writeLog(' Not Mapping ATL08 to ATL03 Ground Photons',
logFileID)
# Store data
atl03_lat = lat_all
atl03_lon = lon_all
atl03_z = z_all
atl03_zMsl = zMsl_all
atl03_time = time_all
atl03_deltaTime = deltaTime_all
atl03_signalConf = signalConf_all
atl03_classification = np.zeros(np.size(atl03_lat))
atl03_intensity = np.zeros(np.size(atl03_lat))
dataIsMapped = False
# endIf
# Get trim options
trimParts = trimInfo.split(',')
trimMode = trimParts[0]
trimType = 'None'
if (('manual' in trimMode.lower()) and (len(trimParts) > 1)):
trimType = trimParts[1]
trimMin = float(trimParts[2])
trimMax = float(trimParts[3])
# endIf
# If selected to manually trim data, do this first
if ('manual' in trimMode.lower()):
# Trim by lat or time
if ('lonlat' in trimType.lower()):
lonMin, lonMax = float(trimParts[2]), float(trimParts[3])
latMin, latMax = float(trimParts[4]), float(trimParts[5])
writeLog(
' Manual Trim Mode (Min Lon: %s, Max Lon: %s)' %
(lonMin, lonMax), logFileID)
writeLog(
' Manual Trim Mode (Min Lat: %s, Max Lat: %s)' %
(latMin, latMax), logFileID)
atl03IndsToKeepLon = (atl03_lon >= lonMin) & (atl03_lon <=
lonMax)
atl03IndsToKeepLat = (atl03_lat >= latMin) & (atl03_lat <=
latMax)
atl03IndsToKeep = atl03IndsToKeepLon & atl03IndsToKeepLat
if (atl08FilePath):
atl08IndsToKeepLon = (atl08_lon >=
lonMin) & (atl08_lon <= lonMax)
atl08IndsToKeepLat = (atl08_lat >=
latMin) & (atl08_lat <= latMax)
atl08IndsToKeep = atl08IndsToKeepLon & atl08IndsToKeepLat
elif ('lat' in trimType.lower()):
writeLog(
' Manual Trim Mode (Min Lat: %s, Max Lat: %s)' %
(trimMin, trimMax), logFileID)
atl03IndsToKeep = (atl03_lat >= trimMin) & (atl03_lat <=
trimMax)
if (atl08FilePath):
atl08IndsToKeep = (atl08_lat >= trimMin) & (atl08_lat
<= trimMax)
# endIf
elif ('lon' in trimType.lower()):
writeLog(
' Manual Trim Mode (Min Lon: %s, Max Lon: %s)' %
(trimMin, trimMax), logFileID)
atl03IndsToKeep = (atl03_lon >= trimMin) & (atl03_lon <=
trimMax)
if (atl08FilePath):
atl08IndsToKeep = (atl03_lon >= trimMin) & (atl03_lon
<= trimMax)
# endIf
elif ('time' in trimType.lower()):
writeLog(
' Manual Trim Mode (Min Time: %s, Max Time: %s)' %
(trimMin, trimMax), logFileID)
atl03IndsToKeep = (atl03_time >= trimMin) & (atl03_time <=
trimMax)
if (atl08FilePath):
atl08IndsToKeep = (atl08_time >=
trimMin) & (atl08_time <= trimMax)
# endIf
else:
writeLog(
' Manual Trim Mode is Missing Args, Not Trimming Data',
logFileID)
atl03IndsToKeep = np.ones(np.shape(atl03_lat), dtype=bool)
if (atl08FilePath):
atl08IndsToKeep = np.ones(np.shape(atl08_lat),
dtype=bool)
# endIf
# endif
# Trim ATL03 data
if atl03IndsToKeep.sum() == 0:
# no data left given manual constraints
return atl03Data, atl08Data, headerData, rotationData
# endIf
atl03_lat = atl03_lat[atl03IndsToKeep]
atl03_lon = atl03_lon[atl03IndsToKeep]
atl03_z = atl03_z[atl03IndsToKeep]
atl03_zMsl = atl03_zMsl[atl03IndsToKeep]
atl03_time = atl03_time[atl03IndsToKeep]
atl03_deltaTime = atl03_deltaTime[atl03IndsToKeep]
atl03_signalConf = atl03_signalConf[atl03IndsToKeep]
atl03_classification = atl03_classification[atl03IndsToKeep]
atl03_intensity = atl03_intensity[atl03IndsToKeep]
# Trim ATL08 data
if (atl08FilePath):
atl08_lat = atl08_lat[atl08IndsToKeep]
atl08_lon = atl08_lon[atl08IndsToKeep]
atl08_maxCanopy = atl08_maxCanopy[atl08IndsToKeep]
atl08_teBestFit = atl08_teBestFit[atl08IndsToKeep]
atl08_teMedian = atl08_teMedian[atl08IndsToKeep]
atl08_maxCanopyMsl = atl08_maxCanopyMsl[atl08IndsToKeep]
atl08_teBestFitMsl = atl08_teBestFitMsl[atl08IndsToKeep]
atl08_teMedianMsl = atl08_teMedianMsl[atl08IndsToKeep]
atl08_time = atl08_time[atl08IndsToKeep]
atl08_deltaTime = atl08_deltaTime[atl08IndsToKeep]
atl08_signalConf = atl08_signalConf[atl08IndsToKeep]
atl08_classification = atl08_classification[
atl08IndsToKeep]
atl08_intensity = atl08_intensity[atl08IndsToKeep]
# endIf
elif ('none' in trimMode.lower()):
writeLog(' Trim Mode: None', logFileID)
# endIf
# Remove ATL08 points above 1e30
if (atl08FilePath):
indsBelowThresh = (atl08_maxCanopy <= 1e30) | (
atl08_teBestFit <= 1e30) | (atl08_teMedian <= 1e30)
atl08_lat = atl08_lat[indsBelowThresh]
atl08_lon = atl08_lon[indsBelowThresh]
atl08_maxCanopy = atl08_maxCanopy[indsBelowThresh]
atl08_teBestFit = atl08_teBestFit[indsBelowThresh]
atl08_teMedian = atl08_teMedian[indsBelowThresh]
atl08_maxCanopyMsl = atl08_maxCanopyMsl[indsBelowThresh]
atl08_teBestFitMsl = atl08_teBestFitMsl[indsBelowThresh]
atl08_teMedianMsl = atl08_teMedianMsl[indsBelowThresh]
atl08_time = atl08_time[indsBelowThresh]
atl08_deltaTime = atl08_deltaTime[indsBelowThresh]
atl08_signalConf = atl08_signalConf[indsBelowThresh]
atl08_classification = atl08_classification[indsBelowThresh]
atl08_intensity = atl08_intensity[indsBelowThresh]
# endIf
# If selected to auto trim data, then trim if truth region exists
if ('auto' in trimMode.lower()):
# Message to user
writeLog(' Trim Mode: Auto', logFileID)
# Read kmlBounds.txt file to get min/max extents to auto trim
kmlBoundsTextFile = 'kmlBounds.txt'
kmlRegionName = False
if (os.path.exists(kmlBoundsTextFile)): # and not pklHeader:
# Message to user
writeLog(' Finding Reference Region...', logFileID)
try:
# Read kmlBounds.txt file and get contents
kmlInfo = readTruthRegionsTxtFile(kmlBoundsTextFile)
# Loop through kmlBounds.txt and find matching TRUTH area
maxCounter = len(kmlInfo.regionName)
counter = 0
while (not kmlRegionName):
latInFile = (
atl03_lat >= kmlInfo.latMin[counter]) & (
atl03_lat <= kmlInfo.latMax[counter])
lonInFile = (
atl03_lon >= kmlInfo.lonMin[counter]) & (
atl03_lon <= kmlInfo.lonMax[counter])
trackInRegion = any(latInFile & lonInFile)
if (trackInRegion):
# Get truth region info
kmlRegionName = kmlInfo.regionName[counter]
kmlLatMin = kmlInfo.latMin[counter]
kmlLatMax = kmlInfo.latMax[counter]
kmlLonMin = kmlInfo.lonMin[counter]
kmlLonMax = kmlInfo.lonMax[counter]
# Print truth region
writeLog(
' Reference File Region: %s' %
kmlRegionName, logFileID)
# endIf
if (counter >= maxCounter):
# Send message to user
writeLog(
' No Reference File Region Found in kmlBounds.txt',
logFileID)
break
# endIf
# Increment counter
counter += 1
# endWhile
except:
pass
# endTry
# endIf
if (kmlRegionName):
# Trim ATL03 data based on TRUTH region
writeLog(
' Auto-Trimming Data Based on Reference Region...',
logFileID)
atl03IndsInRegion = (atl03_lat >= kmlLatMin) & (
atl03_lat <= kmlLatMax) & (atl03_lon >= kmlLonMin) & (
atl03_lon <= kmlLonMax)
atl03_lat = atl03_lat[atl03IndsInRegion]
atl03_lon = atl03_lon[atl03IndsInRegion]
atl03_z = atl03_z[atl03IndsInRegion]
atl03_zMsl = atl03_zMsl[atl03IndsInRegion]
atl03_time = atl03_time[atl03IndsInRegion]
atl03_deltaTime = atl03_deltaTime[atl03IndsInRegion]
atl03_signalConf = atl03_signalConf[atl03IndsInRegion]
atl03_classification = atl03_classification[
atl03IndsInRegion]
atl03_intensity = atl03_intensity[atl03IndsInRegion]
# Trim ATL08 data based on TRUTH region
if (atl08FilePath):
atl08IndsInRegion = (atl08_lat >= kmlLatMin) & (
atl08_lat <= kmlLatMax
) & (atl08_lon >= kmlLonMin) & (atl08_lon <= kmlLonMax)
atl08_lat = atl08_lat[atl08IndsInRegion]
atl08_lon = atl08_lon[atl08IndsInRegion]
atl08_maxCanopy = atl08_maxCanopy[atl08IndsInRegion]
atl08_teBestFit = atl08_teBestFit[atl08IndsInRegion]
atl08_teMedian = atl08_teMedian[atl08IndsInRegion]
atl08_maxCanopyMsl = atl08_maxCanopyMsl[
atl08IndsInRegion]
atl08_teBestFitMsl = atl08_teBestFitMsl[
atl08IndsInRegion]
atl08_teMedianMsl = atl08_teMedianMsl[
atl08IndsInRegion]
atl08_time = atl08_time[atl08IndsInRegion]
atl08_deltaTime = atl08_deltaTime[atl08IndsInRegion]
atl08_signalConf = atl08_signalConf[atl08IndsInRegion]
atl08_classification = atl08_classification[
atl08IndsInRegion]
atl08_intensity = atl08_intensity[atl08IndsInRegion]
#endIf
# endIf
# endIf
# Convert lat/lon coordinates to UTM
writeLog(' Converting Lat/Lon to UTM...', logFileID)
# Allow function to determine UTM zone for ATL03
atl03_easting, atl03_northing, zone, hemi = getLatLon2UTM(
atl03_lon, atl03_lat)
# Allow function to determine UTM zone for ATL03
if (atl08FilePath):
atl08_easting, atl08_northing, atl08_zone, atl08_hemi = getLatLon2UTM(
atl08_lon, atl08_lat)
# endIf
# Print UTM zone
writeLog(' UTM Zone: %s %s' % (zone, hemi), logFileID)
# Transform MEASURED data to CT/AT plane
writeLog(' Computing CT/AT Frame Rotation...', logFileID)
desiredAngle = 90
atl03_crossTrack, atl03_alongTrack, R_mat, xRotPt, yRotPt, phi = getCoordRotFwd(
atl03_easting, atl03_northing, [], [], [], desiredAngle)
if (atl08FilePath):
atl08_crossTrack, atl08_alongTrack, _, _, _, _ = getCoordRotFwd(
atl08_easting, atl08_northing, R_mat, xRotPt, yRotPt, [])
# endIf
# Store rotation object
rotationData = atlRotationStruct(R_mat, xRotPt, yRotPt,
desiredAngle, phi)
# Reassign class -1 to 0 (NOTE: this may need to change later)
inds_eq_neg1 = atl03_classification == -1
atl03_classification[inds_eq_neg1] = 0
# Store data in class structure
atl03Data = atl03Struct(atl03_lat, atl03_lon, \
atl03_easting, atl03_northing, \
atl03_crossTrack, atl03_alongTrack, \
atl03_z, \
atl03_zMsl,
atl03_time, \
atl03_deltaTime, \
atl03_signalConf, atl03_classification, atl03_intensity, \
gtNum, beamNum, beamStrength, zone, hemi, \
atl03FilePath, atl03FileName, \
trackDirection, \
atl03h5Info, \
dataIsMapped)
# Store data in class structure
if (atl08FilePath):
atl08Data = atl08Struct(atl08_lat, atl08_lon, \
atl08_easting, atl08_northing, \
atl08_crossTrack, atl08_alongTrack, \
atl08_maxCanopy, atl08_teBestFit, atl08_teMedian, \
atl08_maxCanopyMsl, atl08_teBestFitMsl, atl08_teMedianMsl, \
atl08_time, \
atl08_deltaTime, \
atl08_signalConf, atl08_classification, atl08_intensity, \
gtNum, atl08_zone, atl08_hemi, \
atl08FilePath, atl08FileName, \
trackDirection, \
atl08h5Info, \
dataIsMapped)
# endIf
# Create output ATL03 .las file
if (createAtl03LasFile):
writeLog(' Writing ATL03 .las file...', logFileID)
outName = atl03Data.atl03FileName + '_' + atl03Data.gtNum + '.las'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Get projection
if (atl03Data.zone == '3413' or atl03Data.zone == '3976'):
# NSIDC Polar Stereographic North/South cases (3413 = Arctic, 3976 = Antarctic)
lasProjection = atl03Data.hemi
# Write .las file
writeLas(np.ravel(atl03Data.easting),
np.ravel(atl03Data.northing),
np.ravel(atl03Data.z), lasProjection, outPath,
np.ravel(atl03Data.classification),
np.ravel(atl03Data.intensity),
np.ravel(atl03Data.signalConf))
else:
# Write .las file for UTM projection case
writeLas(np.ravel(atl03Data.easting),
np.ravel(atl03Data.northing),
np.ravel(atl03Data.z), 'utm', outPath,
np.ravel(atl03Data.classification),
np.ravel(atl03Data.intensity),
np.ravel(atl03Data.signalConf), atl03Data.hemi,
atl03Data.zone)
# endIf
# endIf
# Create output ATL03 .kml file
if (createAtl03KmlFile):
writeLog(' Writing ATL03 .kml file...', logFileID)
outName = atl03Data.atl03FileName + '_' + atl03Data.gtNum + '.kml'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Get array of input time values
timeStep = 1 # seconds
timeVals = np.arange(np.min(atl03Data.time),
np.max(atl03Data.time) + 1, timeStep)
# Get closest time values from IceSat MEASURED data
timeIn, indsToUse = getClosest(atl03Data.time, timeVals)
# Reduce lat/lon values to user-specified time scale
lonsIn = atl03Data.lon[indsToUse]
latsIn = atl03Data.lat[indsToUse]
# Write .kml file
writeKml(latsIn, lonsIn, timeIn, outPath)
# endIf
# Create output ATL08 .kml file
if (createAtl08KmlFile):
if (atl08FilePath):
writeLog(' Writing ATL08 .kml file...', logFileID)
outName = atl08Data.atl08FileName + '_' + atl08Data.gtNum + '.kml'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Get array of input time values
timeStep = 1 # seconds
timeVals = np.arange(np.min(atl08Data.time),
np.max(atl08Data.time) + 1, timeStep)
# Get closest time values from IceSat MEASURED data
timeIn, indsToUse = getClosest(atl08Data.time, timeVals)
# Reduce lat/lon values to user-specified time scale
lonsIn = atl08Data.lon[indsToUse]
latsIn = atl08Data.lat[indsToUse]
# Write .kml file
writeKml(latsIn, lonsIn, timeIn, outPath)
# endIf
# endIf
# Create output ATL03 .csv file
if (createAtl03CsvFile):
writeLog(' Writing ATL03 .csv file...', logFileID)
outName = atl03Data.atl03FileName + '_' + atl03Data.gtNum + '.csv'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Write .csv file
if (atl03Data.zone == '3413' or atl03Data.zone == '3976'):
namelist = ['Time (sec)', 'Delta Time (sec)', \
'Latitude (deg)', 'Longitude (deg)', \
'Polar Stereo X (m)', 'Polar Stereo Y (m)', \
'Cross-Track (m)', 'Along-Track (m)', \
'Height (m HAE)', 'Height (m MSL)', \
'Classification', 'Signal Confidence']
else:
namelist = ['Time (sec)', 'Delta Time (sec)', \
'Latitude (deg)', 'Longitude (deg)', \
'Easting (m)', 'Northing (m)', \
'Cross-Track (m)', 'Along-Track (m)', \
'Height (m HAE)', 'Height (m MSL)', \
'Classification', 'Signal Confidence']
# endIf
datalist = [atl03Data.time, atl03Data.deltaTime, \
atl03Data.lat, atl03Data.lon, \
atl03Data.easting, atl03Data.northing, \
atl03Data.crossTrack, atl03Data.alongTrack,\
atl03Data.z, atl03Data.zMsl, \
atl03Data.classification, atl03Data.signalConf]
writeArrayToCSV(outPath, namelist, datalist)
# endIf
# Create output ATL08 .csv file
if (createAtl08CsvFile):
if (atl08FilePath):
writeLog(' Writing ATL08 .csv file...', logFileID)
outName = atl08Data.atl08FileName + '_' + atl08Data.gtNum + '.csv'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Write .csv file
if (atl03Data.zone == '3413' or atl03Data.zone == '3976'):
namelist = ['Time (sec)', 'Delta Time (sec)', \
'Latitude (deg)', 'Longitude (deg)', \
'Polar Stereo X (m)', 'Polar Stereo Y (m)', \
'Cross-Track (m)', 'Along-Track (m)', \
'Max Canopy (m)', \
'Terrain Best Fit (m)', 'Terrain Median (m)']
else:
namelist = ['Time (sec)', 'Delta Time (sec)', \
'Latitude (deg)', 'Longitude (deg)', \
'Easting (m)', 'Northing (m)', \
'Cross-Track (m)', 'Along-Track (m)', \
'Max Canopy (m)', \
'Terrain Best Fit (m)', 'Terrain Median (m)']
# endIf
datalist = [atl08Data.time, atl08Data.deltaTime, \
atl08Data.lat, atl08Data.lon, \
atl08Data.easting, atl08Data.northing, \
atl08Data.crossTrack, atl08Data.alongTrack,\
atl08Data.maxCanopy, \
atl08Data.teBestFit, atl08Data.teMedian]
writeArrayToCSV(outPath, namelist, datalist)
# endIf
# endIf
# End timer
timeEnd = runTime.time()
timeElapsedTotal = timeEnd - timeStart
timeElapsedMin = np.floor(timeElapsedTotal / 60)
timeElapsedSec = timeElapsedTotal % 60
# Print completion message
writeLog('', logFileID)
writeLog(
' Module Completed in %d min %d sec.' %
(timeElapsedMin, timeElapsedSec), logFileID)
writeLog('\n', logFileID)
else:
writeLog('\n', logFileID)
writeLog(' *** Could not process data.', logFileID)
writeLog(' *** ATL03 .h5 file missing these fields:', logFileID)
for i in range(0, len(badVars)):
writeLog(' %s) %s' % (i + 1, badVars[i]), logFileID)
writeLog('\n', logFileID)
# endIf
else:
# Message to user
writeLog('Input correct ATL03 input .h5 file and/or output path.',
logFileID)
# endIf
# Return object
return atl03Data, atl08Data, rotationData
def getAtlMeasuredSwath(atl03FilePath=False,
atl08FilePath=False,
outFilePath=False,
gtNum='gt1r',
trimInfo='auto',
createLasFile=False,
createKmlFile=False,
createCsvFile=False):
# Initialize outputs
atlMeasuredData = False
headerData = False
coordType = False
rotationData = False
# Only execute code if input ATL03 .h5 file and output path declared
if (atl03FilePath and outFilePath):
# Start timer
timeStart = runTime.time()
# Print message
print(' Ground Track Number: %s' % gtNum)
# Get ATL03 file path/name
atl03FilePath = os.path.normpath(os.path.abspath(atl03FilePath))
atl03FileName = os.path.splitext(os.path.basename(atl03FilePath))[0]
# Read ATL03 data from h5 file
print(' Reading ATL03 .h5 file: %s' % atl03FilePath)
lat_all = readAtl03H5(atl03FilePath, 'lat_ph', gtNum)
lon_all = readAtl03H5(atl03FilePath, 'lon_ph', gtNum)
z_all = readAtl03H5(atl03FilePath, 'h_ph', gtNum)
deltaTime_all = readAtl03H5(atl03FilePath, 'delta_time', gtNum)
signalConf_all = readAtl03H5(atl03FilePath, 'signal_conf_ph', gtNum)
atl03_ph_index_beg, atl03_segment_id = readAtl03DataMapping(
atl03FilePath, gtNum)
# Get time from delta time
time_all = deltaTime_all - np.min(deltaTime_all)
# Get track direction
if (lat_all[-1] > lat_all[0]):
trackDirection = 'Ascending'
else:
trackDirection = 'Descending'
# endIf
# Extract metadata from ATL03 file name
atl03h5Info = getNameParts(atl03FileName)
# Map ATL08 to ATL03 ground photons
if (atl08FilePath):
# Get ATL08 file path/name
atl08FilePath = os.path.normpath(os.path.abspath(atl08FilePath))
# Message to screen
print(' Reading ATL08 .h5 file: %s' % atl08FilePath)
atl08_classed_pc_indx, atl08_classed_pc_flag, atl08_segment_id = readAtl08DataMapping(
atl08FilePath, gtNum)
print(' Mapping ATL08 to ATL03 Ground Photons...')
classification = getAtl08Mapping(atl03_ph_index_beg,
atl03_segment_id,
atl08_classed_pc_indx,
atl08_classed_pc_flag,
atl08_segment_id)
# Get length to trim data by
class_length = len(classification)
lat_length = len(lat_all)
data_length = np.min([class_length, lat_length])
# Trim ATL03 data down to size of classification array
lat = lat_all[0:data_length]
lon = lon_all[0:data_length]
z = z_all[0:data_length]
time = time_all[0:data_length]
signalConf = signalConf_all[0:data_length]
classification = classification[0:data_length]
dataIsMapped = True
else:
# Message to screen
print(' Not Mapping ATL08 to ATL03 Ground Photons')
# Store data
lat = lat_all
lon = lon_all
z = z_all
time = time_all
signalConf = signalConf_all
classification = np.zeros(np.size(lat_all))
dataIsMapped = False
# endIf
# Get trim options
trimParts = trimInfo.split(',')
trimMode = trimParts[0]
trimType = 'None'
if (('manual' in trimMode.lower()) and (len(trimParts) > 1)):
trimType = trimParts[1]
trimMin = float(trimParts[2])
trimMax = float(trimParts[3])
# endIf
# If selected to manually trim data, do this first
if ('manual' in trimMode.lower()):
# Trim by lat or time
if ('lat' in trimType.lower()):
print(' Manual Trim Mode (Min Lat: %s, Max Lat: %s)' %
(trimMin, trimMax))
indsToKeep = (lat >= trimMin) & (lat <= trimMax)
elif ('time' in trimType.lower()):
print(' Manual Trim Mode (Min Time: %s, Max Time: %s)' %
(trimMin, trimMax))
indsToKeep = (time >= trimMin) & (time <= trimMax)
else:
print(' Manual Trim Mode is Missing Args, Not Trimming Data')
indsToKeep = np.ones(np.shape(lat), dtype=bool)
# endif
# Trim data
lat = lat[indsToKeep]
lon = lon[indsToKeep]
z = z[indsToKeep]
time = time[indsToKeep]
signalConf = signalConf[indsToKeep]
classification = classification[indsToKeep]
# EndIf
# Determine if ATL03 track goes over a lidar truth region
kmlBoundsTextFile = 'kmlBounds.txt'
kmlRegionName = False
headerFilePath = False
truthFilePath = False
if (os.path.exists(kmlBoundsTextFile)):
# Message to user
print(' Finding Truth Region...')
try:
# Read kmlBounds.txt file and get contents
kmlInfo = readTruthRegionsTxtFile(kmlBoundsTextFile)
# Loop through kmlBounds.txt and find matching TRUTH area
maxCounter = len(kmlInfo.regionName)
counter = 0
while (not kmlRegionName):
latInFile = (lat >= kmlInfo.latMin[counter]) & (
lat <= kmlInfo.latMax[counter])
lonInFile = (lon >= kmlInfo.lonMin[counter]) & (
lon <= kmlInfo.lonMax[counter])
trackInRegion = any(latInFile & lonInFile)
if (trackInRegion):
# Get truth region info
kmlRegionName = kmlInfo.regionName[counter]
headerFilePath = os.path.normpath(
kmlInfo.headerFilePath[counter])
truthFilePath = os.path.normpath(
kmlInfo.truthFilePath[counter])
kmlLatMin = kmlInfo.latMin[counter]
kmlLatMax = kmlInfo.latMax[counter]
kmlLonMin = kmlInfo.lonMin[counter]
kmlLonMax = kmlInfo.lonMax[counter]
# Print truth region
print(' Truth File Region: %s' % kmlRegionName)
# Read truth header .mat file
headerData = readHeaderMatFile(headerFilePath)
coordType = headerData.coordType
# endIf
# Increment counter
counter += 1
if (counter >= maxCounter):
# Send message to user
print(' No Truth File Region Found in kmlBounds.txt')
break
# endIf
# endWhile
except:
# Could not read kmlBounds.txt file
print(
' Could not read truth header .mat file. Auto-assigning UTM zone.'
)
# endIf
# If selected to auto trim data, then trim if truth region exists
if ('auto' in trimMode.lower()):
if (kmlRegionName):
# Trim data based on TRUTH region
print(
' Auto Trim Mode (Trimming Data Based on Truth Region)...'
)
indsInRegion = (lat >= kmlLatMin) & (lat <= kmlLatMax) & (
lon >= kmlLonMin) & (lon <= kmlLonMax)
lat = lat[indsInRegion]
lon = lon[indsInRegion]
z = z[indsInRegion]
time = time[indsInRegion]
signalConf = signalConf[indsInRegion]
classification = classification[indsInRegion]
# endIf
# endIf
# Convert lat/lon coordinates to UTM
print(' Converting Lat/Lon to UTM...')
if (kmlRegionName and coordType == 'UTM'):
# Force UTM zone to match region header file
zoneToUse = headerData.zone
hemiToUse = headerData.hemi
easting, northing, zone, hemi = getLatLon2UTM(
lon, lat, zoneToUse, hemiToUse)
else:
# Allow function to determine UTM zone
easting, northing, zone, hemi = getLatLon2UTM(lon, lat)
# endIf
# Print UTM zone
print(' UTM Zone: %s' % zone)
# Transform MEASURED data to CT/AT plane
print(' Computing CT/AT Frame Rotation...')
desiredAngle = 90
crossTrack, alongTrack, R_mat, xRotPt, yRotPt, phi = getCoordRotFwd(
easting, northing, [], [], [], desiredAngle)
# Store rotation object
rotationData = atlRotationStruct(R_mat, xRotPt, yRotPt, desiredAngle,
phi)
# Store data in class structure
atlMeasuredData = atlMeasuredStruct(lat, lon, \
easting, northing, \
crossTrack, alongTrack, \
z, time, \
signalConf, classification, \
gtNum, zone, hemi, \
kmlRegionName, headerFilePath, truthFilePath, \
atl03FilePath, atl03FileName, \
atl08FilePath, atl03FileName, \
trackDirection, \
atl03h5Info, \
dataIsMapped)
# Create output .las file
if (createLasFile):
print(' Writing measured .las file...')
outName = atlMeasuredData.atl03FileName + '_' + atlMeasuredData.gtNum + '_MEASURED.las'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Write .las file
writeLas(np.ravel(atlMeasuredData.easting),
np.ravel(atlMeasuredData.northing),
np.ravel(atlMeasuredData.z), 'utm', outPath,
np.ravel(atlMeasuredData.classification),
np.ravel(atlMeasuredData.intensity), atlMeasuredData.hemi,
atlMeasuredData.zone)
# endIf
# Create output .kml file
if (createKmlFile):
print(' Writing measured .kml file...')
outName = atlMeasuredData.atl03FileName + '_' + atlMeasuredData.gtNum + '_MEASURED.kml'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Get array of input time values
timeStep = 1 # seconds
timeVals = np.arange(np.min(atlMeasuredData.time),
np.max(atlMeasuredData.time) + 1, timeStep)
# Get closest time values from IceSat MEASURED data
timeIn, indsToUse = getClosest(atlMeasuredData.time, timeVals)
# Reduce lat/lon values to user-specified time scale
lonsIn = atlMeasuredData.lon[indsToUse]
latsIn = atlMeasuredData.lat[indsToUse]
# Write .kml file
writeKml(latsIn, lonsIn, timeIn, outPath)
# endIf
# Create output .csv file
if (createCsvFile):
print(' Writing measured .csv file...')
outName = atlMeasuredData.atl03FileName + '_' + atlMeasuredData.gtNum + '_MEASURED.csv'
outPath = os.path.normpath(outFilePath + '/' + outName)
# If output directory does not exist, create it
if (not os.path.exists(os.path.normpath(outFilePath))):
os.mkdir(os.path.normpath(outFilePath))
# EndIf
# Write .csv file
namelist = ['Time (sec)', 'Latitude (deg)', 'Longitude (deg)', \
'Easting (m)', 'Northing (m)', \
'Cross-Track (m)', 'Along-Track (m)', \
'Height (m)', \
'Classification', 'Signal Confidence']
datalist = [atlMeasuredData.time, atlMeasuredData.lat, atlMeasuredData.lon, \
atlMeasuredData.easting, atlMeasuredData.northing, \
atlMeasuredData.crossTrack, atlMeasuredData.alongTrack,\
atlMeasuredData.z, \
atlMeasuredData.classification, atlMeasuredData.signalConf]
writeArrayToCSV(outPath, namelist, datalist)
# endIf
# End timer
timeEnd = runTime.time()
timeElapsedTotal = timeEnd - timeStart
timeElapsedMin = np.floor(timeElapsedTotal / 60)
timeElapsedSec = timeElapsedTotal % 60
# Print completion message
print(' Module Completed in %d min %d sec.' %
(timeElapsedMin, timeElapsedSec))
print('\n')
else:
# Message to user
print('Input correct ATL03 input .h5 file and/or output path.')
# endIf
# Return object
return atlMeasuredData, headerData, rotationData