def __getmetadata__(self, f=None):
'''Populate the metadata'''
if not f: f = self.fileinfo['filepath']
self._gdaldataset = geometry.OpenDataset(f)
led = glob.glob(os.path.dirname(f) +
'/[Ll][Ee][Aa][Dd]*')[0] #volume file
meta = open(led, 'rb').read()
'''
metadata has 4 records, each is 4320 (LS) or 6120 (SPOT) bytes long:
File descriptor record;
Scene header record;
Map projection (scene-related) ancillary record;
Radiometric transformation ancillary record.
'''
#Record 2 - Scene header record
record = 2
recordlength = 4320 #LS 5
satellite = utilities.readbinary(meta, (record - 1) * recordlength,
309, 324)
#Scene ID, path/row & image date/time
start, stop = 37, 52
sceneid = utilities.readbinary(meta, (record - 1) * recordlength,
start, stop)
start, stop = 165, 180
pathrow = utilities.readbinary(meta, (record - 1) * recordlength,
start, stop)[1:]
start, stop = 117, 148
imgdate = utilities.readbinary(meta, (record - 1) * recordlength,
start, stop)
self.metadata['imgdate'] = time.strftime(
utilities.datetimeformat,
time.strptime(imgdate[0:14], '%Y%m%d%H%M%S')) #ISO 8601
#Ascending/descending flag
start, stop = 357, 372
if utilities.readbinary(meta, (record - 1) * recordlength, start,
stop) == 'D':
self.metadata['orbit'] = 'Descending'
else:
self.metadata['orbit'] = 'Ascending'
#Processing level
start, stop = 1573, 1588
self.metadata['level'] = utilities.readbinary(
meta, (record - 1) * recordlength, start, stop)
#Bands
start, stop = 1653, 1659
bands = []
actbands = utilities.readbinary(meta, (record - 1) * recordlength,
start, stop)
for i in range(0, 7): #Loop thru the 7 LS 5 bands
if actbands[i] == '1': bands.append(str(i + 1))
self._gdaldataset.GetRasterBand(i + 1).SetNoDataValue(0)
#Record 3 - Map projection (scene-related) ancillary record
record = 3
#Bands, rows & columns and rotation
nbands = int(self._gdaldataset.RasterCount)
start, stop = 333, 348
ncols = float(
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop))
start, stop = 349, 364
nrows = float(
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop))
start, stop = 445, 460
self.metadata['rotation'] = float(
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop))
if abs(self.metadata['rotation']) < 1:
self.metadata['orientation'] = 'Map oriented'
self.metadata['rotation'] = 0.0
else:
self.metadata['orientation'] = 'Path oriented'
#Sun elevation and azimuth
start, stop = 605, 620
self.metadata['sunelevation'] = float(
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop))
start, stop = 621, 636
self.metadata['sunazimuth'] = float(
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop))
#geometry.CellSizes
start, stop = 365, 396
(cellx, celly) = map(
float,
utilities.readbinary(meta, (record - 1) * recordlength, start,
stop).split())
start, stop = 397, 412
projection = utilities.readbinary(meta, (record - 1) * recordlength,
start, stop).split()
datum = projection[0]
zone = projection[1]
# lat/lons
start, stop = 765, 892
coords = utilities.readbinary(meta, (record - 1) * recordlength, start,
stop).split()
uly, ulx, ury, urx, lry, lrx, lly, llx = map(float, coords)
ext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly], [ulx, uly]]
if int(zone) != 0:
# UTM
type = 'UTM'
units = 'm'
#start,stop = 637,764
#coords = utilities.readbinary(meta,(record-1)*recordlength,start,stop).split()
#uly,ulx,ury,urx,lry,lrx,lly,llx = map(float, coords)
#ext=[[ulx,uly],[urx,ury],[lrx,lry],[llx,lly],[ulx,uly]]
if datum == 'GDA94': epsg = int('283' + zone)
elif datum == 'AGD66': epsg = int('202' + zone)
elif datum == 'WGS84': epsg = int('327' + zone)
else: #Assume
type = 'GEO'
units = 'deg'
if datum == 'GDA94': epsg = 4283
else: epsg = 4326 #Assume WGS84
gcps = []
i = 0
lr = [[0, 0], [ncols, 0], [ncols, nrows], [0, nrows]]
while i < len(ext) - 1: #don't need the last xy pair
gcp = gdal.GCP()
gcp.GCPPixel, gcp.GCPLine = lr[i]
gcp.GCPX, gcp.GCPY = ext[i]
gcp.Id = str(i)
gcps.append(gcp)
i += 1
geotransform = gdal.GCPsToGeoTransform(gcps)
cellx, celly = geometry.CellSize(geotransform)
rotation = geometry.Rotation(geotransform)
srs = osr.SpatialReference()
srs.ImportFromEPSG(epsg)
srs = srs.ExportToWkt()
self.metadata['satellite'] = satellite
if satellite == 'LANDSAT-5':
self.metadata['sensor'] = 'TM'
self.metadata['filetype'] = 'CEOS/Landsat CCRS Format'
else:
self.metadata['sensor'] = 'HRV'
self.metadata['filetype'] = 'CEOS/SPOT CCRS Format'
self.metadata['filesize'] = sum(
[os.path.getsize(file) for file in self.filelist])
self.metadata['srs'] = srs
self.metadata['epsg'] = epsg
self.metadata['units'] = units
self.metadata['cols'] = ncols
self.metadata['rows'] = nrows
self.metadata['nbands'] = nbands
self.metadata['bands'] = ','.join(bands)
self.metadata['nbits'] = 8
self.metadata['datatype'] = 'Byte'
self.metadata['nodata'] = 0
self.metadata['cellx'], self.metadata['celly'] = map(
float, [cellx, celly])
self.metadata['UL'] = '%s,%s' % tuple(ext[0])
self.metadata['UR'] = '%s,%s' % tuple(ext[1])
self.metadata['LR'] = '%s,%s' % tuple(ext[2])
self.metadata['LL'] = '%s,%s' % tuple(ext[3])
metadata = self._gdaldataset.GetMetadata()
self.metadata['metadata'] = '\n'.join(
['%s: %s' % (m, hdf_self.metadata[m]) for m in metadata])
self.metadata['compressionratio'] = 0
self.metadata['compressiontype'] = 'None'
self.extent = ext
def __getmetadata__(self):
'''Read Metadata for recognised EO1 ALI (L1G & L1R) & Hyperion (L1R) images as GDAL doesn't'''
f = self.fileinfo['filepath']
self.metadata['satellite'] = 'E01'
self.metadata['nbits'] = 16
self.metadata['datatype'] = 'Int16'
self.metadata['nodata'] = 0
if re.search(r'eo1a.*\.m[1-4]r$', f, re.I):
self.ali_l1r(f)
elif re.search(r'eo1.*_mtl\.tif$', f):
self.ali_l1g_tiff(f)
elif re.search(r'eo1.*_hdf\.l1g$', f):
self.ali_l1g_hdf(f)
elif re.search(r'eo1h.*\.l[1-4]r$', f):
self.hyp_l1r(f)
elif re.search(r'eo1.*_mtl_.*\.l1t$', f, re.I):
self.hyp_l1t(f)
self.metadata['cols'] = self.ncols
self.metadata['rows'] = self.nrows
self.metadata['nbands'] = self.nbands
#Geotransform
ncols = map(int, str(self.ncols).split(','))
nrows = map(int, str(self.nrows).split(','))
cellx, celly = [], []
j = 0
while j < len(ncols):
gcps = []
i = 0
lr = [[0, 0], [ncols[j], 0], [ncols[j], nrows[j]], [0, nrows[j]]]
while i < len(self.prjext) - 1: #don't need the last xy pair
gcp = gdal.GCP()
gcp.GCPPixel, gcp.GCPLine = lr[i]
gcp.GCPX, gcp.GCPY = self.prjext[i]
gcp.Id = str(i)
gcps.append(gcp)
i += 1
j += 1
geotransform = gdal.GCPsToGeoTransform(gcps)
x, y = geometry.CellSize(geotransform)
cellx.append(str(x))
celly.append(str(abs(y)))
self.metadata['cellx'] = ','.join(cellx)
self.metadata['celly'] = ','.join(celly)
self.metadata['UL'] = '%s,%s' % tuple(self.geoext[0])
self.metadata['UR'] = '%s,%s' % tuple(self.geoext[1])
self.metadata['LR'] = '%s,%s' % tuple(self.geoext[2])
self.metadata['LL'] = '%s,%s' % tuple(self.geoext[3])
self.metadata['rotation'] = geometry.Rotation(geotransform)
if abs(self.metadata['rotation']) < 1.0:
self.metadata['orientation'] = 'Map oriented'
self.metadata['rotation'] = 0.0
else:
self.metadata['orientation'] = 'Path oriented'
self.metadata['filesize'] = sum(
[os.path.getsize(tmp) for tmp in self.filelist])
self.metadata['compressionratio'] = 0
self.metadata['compressiontype'] = 'None'
self.extent = self.geoext
def __getmetadata__(self):
'''Read Metadata for recognised EO1 ALI (L1G & L1R) & Hyperion (L1R) images as GDAL doesn't'''
f = self.fileinfo['filepath']
self.metadata['satellite'] = 'E01'
self.metadata['nbits'] = 16
self.metadata['datatype'] = 'Int16'
self.metadata['nodata'] = 0
if re.search(r'\.m[1-4]r$', f, re.I):
self.metadata['level'] = 'L1R'
self.metadata['sensor'] = 'ALI'
gdalDataset = geometry.OpenDataset(f)
#if not gdalDataset: #Error now raised in geometry.OpenDataset
# errmsg=gdal.GetLastErrorMsg()
# raise IOError, 'Unable to open %s\n%s' % (f,errmsg.strip())
self.metadata['filetype'] = '%s/%s (%s %s)' % (
gdalDataset.GetDriver().ShortName,
gdalDataset.GetDriver().LongName, self.metadata['sensor'],
self.metadata['level'])
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
self.metadata['srs'] = srs.ExportToWkt()
self.metadata['epsg'] = 4326
self.metadata['units'] = 'deg'
hdf_sd = gdalDataset.GetSubDatasets()
hdf_md = gdalDataset.GetMetadata()
sd, sz = hdf_sd[0]
sd = geometry.OpenDataset(sd)
sd_md = sd.GetMetadata()
nbands = sd.RasterCount
ncols = str(
sd.RasterXSize * 4 - 30
) #Account for the four SCA strips and the overlap between SCA strips
nrows = sd_md[
'Number of along track pixels'] #sd.RasterYSize is incorrect
if len(hdf_sd) == 6: #Includes pan band (3 sds each)
sd, sz = hdf_sd[3]
sd = geometry.OpenDataset(sd)
sd_md = sd.GetMetadata()
cols = str(
int(sd_md['Number of cross track pixels']) * 4 - 30
) #Account for the four SCA strips and the overlap between SCA strips
rows = sd_md['Number of along track pixels']
#set up to create multispectral only self._gdaldatset for overview generation
if nbands == 1:
multi = 3
multibands = sd_md['Number of bands']
multicols = cols
multirows = rows
else:
multi = 0
multibands = nbands
multicols = ncols
multirows = nrows
multibands = range(1, int(multibands) + 1)
#Make a csv list of cols, bands
ncols = [ncols for i in range(0, nbands)]
nrows = [nrows for i in range(0, nbands)]
ncols.extend([cols for i in range(0, sd.RasterCount)])
nrows.extend([rows for i in range(0, sd.RasterCount)])
#nbands='%s,%s' % (nbands, sd_md['Number of bands'])
nbands = nbands + int(sd_md['Number of bands'])
ncols = ','.join(ncols)
nrows = ','.join(nrows)
else:
#set up to create multispectral only _gdaldatset for overview generation
multi = 0
multibands = range(1, nbands + 1)
multicols = ncols
multirows = nrows
#create multispectral only _gdaldatset for overview generation
#Get all the data files and mosaic the strips
#strips=[s for s in utilities.rglob(os.path.dirname(f),r'\.m[1-4]r$',True,re.I,False)]
strips = glob.glob(os.path.join(os.path.dirname(f), '*.m[1-4]r'))
strips.sort()
strips.reverse() #west->east = *.m4r-m1
scols = (int(multicols) +
30) / 4 # +30 handles the 10 pixel overlap
xoff = 10
yoff = 400
srows = int(multirows) - yoff
srcrects = [[0, yoff, scols, srows]] * 4
dstrects = []
srcrect = [0, yoff, scols, srows]
#dstrect=[None,0,scols,srows]
files = []
sd, sz = hdf_sd[multi]
vrt_opts = []
indatasetlist = []
for i in range(0, 4):
files.append(sd.replace(f, strips[i]))
dstrects.append([i * (scols - xoff), 0, scols, srows])
self._gdaldataset = geometry.OpenDataset(
geometry.CreateMosaicedVRT(files, multibands, srcrects,
dstrects, multicols, srows,
'Int16'))
self._gdaldataset.GetRasterBand(2).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(3).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(4).SetNoDataValue(0)
self._stretch = ('STDDEV', (4, 3, 2), [2])
#Extract other metadata
met = os.path.splitext(f)[0] + '.met'
for line in open(met, 'r').readlines():
if line[0:16] == 'Scene Request ID':
line = line.strip().split()
self.metadata['sceneid'] = line[3]
if line[0:14] == 'ALI Start Time':
line = line.strip().split()
hdf_md['ImageStartTime'] = line[3] + line[4]
if line[0:8] == 'PRODUCT_':
line = line.strip()
line = map(string.strip, line.split('='))
if line[0] == 'PRODUCT_UL_CORNER_LAT': uly = float(line[1])
if line[0] == 'PRODUCT_UL_CORNER_LON': ulx = float(line[1])
if line[0] == 'PRODUCT_UR_CORNER_LAT': ury = float(line[1])
if line[0] == 'PRODUCT_UR_CORNER_LON': urx = float(line[1])
if line[0] == 'PRODUCT_LR_CORNER_LAT': lry = float(line[1])
if line[0] == 'PRODUCT_LR_CORNER_LON': lrx = float(line[1])
if line[0] == 'PRODUCT_LL_CORNER_LAT': lly = float(line[1])
if line[0] == 'PRODUCT_LL_CORNER_LON': llx = float(line[1])
geoext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly],
[ulx, uly]]
prjext = geoext
elif re.search(r'eo1.*_mtl\.tif$', f):
self.metadata['level'] = 'L1G'
self.metadata['sensor'] = 'ALI'
self.metadata['sceneid'] = self.metadata['filename'].split('_')[0]
self.metadata['filetype'] = 'GTiff/GeoTIFF'
ncols = []
nrows = []
nbands = 0
bands = glob.glob(os.path.join(os.path.dirname(f), 'eo1*_b*.tif'))
for band in bands:
band = geometry.OpenDataset(band)
ncols.append(str(band.RasterXSize))
nrows.append(str(band.RasterYSize))
nbands += 1
#rb=sd.GetRasterBand(1)
#get all multi bands for use in overview generation
pancols = max(ncols)
panindex = ncols.index(pancols)
multibands = bands
multincols = ncols
multinrows = nrows
if pancols > min(ncols): #there is a pan band
multibands.pop(panindex)
multincols.pop(panindex)
multinrows.pop(panindex)
multibands.sort()
self._gdaldataset = geometry.OpenDataset(
geometry.CreateSimpleVRT(multibands, multincols[0],
multinrows[0], 'Int16'))
self._gdaldataset.GetRasterBand(2).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(3).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(4).SetNoDataValue(0)
self._stretch = ('STDDEV', (4, 3, 2), [2])
ncols = ','.join(ncols)
nrows = ','.join(nrows)
met = f
md = {}
for line in open(met, 'r'):
line = line.replace('"', '')
line = [l.strip() for l in line.split('=')]
if line[0] == 'END': #end of the metadata file
break
elif line[0] == 'GROUP': #start of a metadata group
if line[1] != 'L1_METADATA_FILE':
group = line[1]
md[group] = {}
elif line[0] == 'END_GROUP': #end of a metadata group
pass
else: #metadata value
md[group][line[0]] = line[1]
uly = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_LAT'])
ulx = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_LON'])
ury = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_LAT'])
urx = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_LON'])
lry = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_LAT'])
lrx = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_LON'])
lly = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_LAT'])
llx = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_LON'])
geoext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly],
[ulx, uly]]
uly = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_MAPY'])
ulx = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_MAPX'])
ury = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_MAPY'])
urx = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_MAPX'])
lry = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_MAPY'])
lrx = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_MAPX'])
lly = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_MAPY'])
llx = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_MAPX'])
prjext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly],
[ulx, uly]]
self.metadata['imgdate'] = md['PRODUCT_METADATA'][
'ACQUISITION_DATE']
self.metadata['resampling'] = md['PROJECTION_PARAMETERS'][
'RESAMPLING_OPTION']
try:
self.metadata['viewangle'] = float(
md['PRODUCT_PARAMETERS']['SENSOR_LOOK_ANGLE'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
try:
self.metadata['sunazimuth'] = float(
md['PRODUCT_PARAMETERS']['SUN_AZIMUTH'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
try:
self.metadata['sunelevation'] = float(
md['PRODUCT_PARAMETERS']['SUN_ELEVATION'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
#EPSG:32601: WGS 84 / UTM zone 1N
#EPSG:32701: WGS 84 / UTM zone 1S
srs = osr.SpatialReference()
zone = int(md['UTM_PARAMETERS']['ZONE_NUMBER'])
if zone > 0: epsg = 32600 + zone #North
else: epsg = 32700 - zone #South
srs.ImportFromEPSG(epsg)
self.metadata['units'] = 'm'
self.metadata['srs'] = srs.ExportToWkt()
self.metadata['epsg'] = str(epsg)
elif re.search(r'eo1.*_hdf\.l1g$', f):
self.metadata['level'] = 'L1G'
self.metadata['sensor'] = 'ALI'
self.metadata['sceneid'] = self.metadata['filename'].split('_')[0]
gdalDataset = geometry.OpenDataset(f)
#if not gdalDataset: #Error now raised in geometry.OpenDataset
# errmsg=gdal.GetLastErrorMsg()
# raise IOError, 'Unable to open %s\n%s' % (f,errmsg.strip())
self.metadata['filetype'] = '%s/%s (%s %s)' % (
gdalDataset.GetDriver().ShortName,
gdalDataset.GetDriver().LongName, self.metadata['sensor'],
self.metadata['level'])
hdf_sd = gdalDataset.GetSubDatasets()
hdf_md = gdalDataset.GetMetadata()
sd, sz = hdf_sd[0]
sd = geometry.OpenDataset(sd)
sd_md = sd.GetMetadata()
ncols = []
nrows = []
nbands = 0
bands = []
for sd, sz in hdf_sd:
bands.append(sd)
ds = geometry.OpenDataset(sd)
ncols.append(str(ds.RasterXSize))
nrows.append(str(ds.RasterYSize))
nbands += 1
#get all multi bands for use in overview generation
pancols = max(ncols)
panindex = ncols.index(pancols)
multibands = bands
multincols = ncols
multinrows = nrows
if pancols > min(ncols): #there is a pan band
multibands.pop(panindex)
multincols.pop(panindex)
multinrows.pop(panindex)
multibands.sort()
self._gdaldataset = geometry.OpenDataset(
geometry.CreateSimpleVRT(multibands, multincols[0],
multinrows[0], 'Int16'))
self._gdaldataset.GetRasterBand(2).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(3).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(4).SetNoDataValue(0)
self._stretch = ('STDDEV', (4, 3, 2), [2])
ncols = ','.join(ncols)
nrows = ','.join(nrows)
met = f.lower().replace('_hdf.l1g', '_mtl.l1g')
md = {}
for line in open(met, 'r'):
line = line.replace('"', '')
line = [l.strip() for l in line.split('=')]
if line[0] == 'END': #end of the metadata file
break
elif line[0] == 'GROUP': #start of a metadata group
if line[1] != 'L1_METADATA_FILE':
group = line[1]
md[group] = {}
elif line[0] == 'END_GROUP': #end of a metadata group
pass
else: #metadata value
md[group][line[0]] = line[1]
uly = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_LAT'])
ulx = float(md['PRODUCT_METADATA']['PRODUCT_UL_CORNER_LON'])
ury = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_LAT'])
urx = float(md['PRODUCT_METADATA']['PRODUCT_UR_CORNER_LON'])
lry = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_LAT'])
lrx = float(md['PRODUCT_METADATA']['PRODUCT_LR_CORNER_LON'])
lly = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_LAT'])
llx = float(md['PRODUCT_METADATA']['PRODUCT_LL_CORNER_LON'])
geoext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly],
[ulx, uly]]
prjext = geoext
self.metadata['imgdate'] = md['PRODUCT_METADATA'][
'ACQUISITION_DATE']
self.metadata['resampling'] = md['PROJECTION_PARAMETERS'][
'RESAMPLING_OPTION']
try:
self.metadata['viewangle'] = float(
md['PRODUCT_PARAMETERS']['SENSOR_LOOK_ANGLE'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
try:
self.metadata['sunazimuth'] = float(
md['PRODUCT_PARAMETERS']['SUN_AZIMUTH'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
try:
self.metadata['sunelevation'] = float(
md['PRODUCT_PARAMETERS']['SUN_ELEVATION'])
except:
pass #Exception raised if value == 'UNAVAILABLE'
#EPSG:32601: WGS 84 / UTM zone 1N
#EPSG:32701: WGS 84 / UTM zone 1S
srs = osr.SpatialReference()
zone = int(md['UTM_PARAMETERS']['ZONE_NUMBER'])
if zone > 0: epsg = 32600 + zone #North
else: epsg = 32700 - zone #South
srs.ImportFromEPSG(epsg)
self.metadata['units'] = 'm'
self.metadata['srs'] = srs.ExportToWkt()
self.metadata['epsg'] = str(epsg)
else:
self.metadata['level'] = 'L1R'
self.metadata['sensor'] = 'HYPERION'
gdalDataset = geometry.OpenDataset(f)
#if not gdalDataset: #Error now raised in geometry.OpenDataset
# errmsg=gdal.GetLastErrorMsg()
# raise IOError, 'Unable to open %s\n%s' % (f,errmsg.strip())
self.metadata['filetype'] = '%s/%s (%s %s)' % (
gdalDataset.GetDriver().ShortName,
gdalDataset.GetDriver().LongName, self.metadata['sensor'],
self.metadata['level'])
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
self.metadata['srs'] = srs.ExportToWkt()
self.metadata['epsg'] = 4326
self.metadata['units'] = 'deg'
hdf_sd = gdalDataset.GetSubDatasets()
hdf_md = gdalDataset.GetMetadata()
sd, sz = hdf_sd[0]
sd = geometry.OpenDataset(sd)
sd_md = sd.GetMetadata()
nbands = sd.RasterCount
ncols = sd.RasterXSize
nrows = sd.RasterYSize
met = os.path.splitext(f)[0] + '.met'
for line in open(met, 'r').readlines():
if line[0:16] == 'Scene Request ID':
line = line.strip().split()
self.metadata['sceneid'] = line[3]
if line[0:14] == 'HYP Start Time':
line = line.strip().split()
imgdate = time.strptime(line[3] + line[4], '%Y%j')
self.metadata['imgdate'] = time.strftime(
'%Y-%m-%d', imgdate) #ISO 8601
if line[0:8] == 'PRODUCT_':
line = line.strip()
line = map(string.strip, line.split('='))
if line[0] == 'PRODUCT_UL_CORNER_LAT': uly = float(line[1])
if line[0] == 'PRODUCT_UL_CORNER_LON': ulx = float(line[1])
if line[0] == 'PRODUCT_UR_CORNER_LAT': ury = float(line[1])
if line[0] == 'PRODUCT_UR_CORNER_LON': urx = float(line[1])
if line[0] == 'PRODUCT_LR_CORNER_LAT': lry = float(line[1])
if line[0] == 'PRODUCT_LR_CORNER_LON': lrx = float(line[1])
if line[0] == 'PRODUCT_LL_CORNER_LAT': lly = float(line[1])
if line[0] == 'PRODUCT_LL_CORNER_LON': llx = float(line[1])
geoext = [[ulx, uly], [urx, ury], [lrx, lry], [llx, lly],
[ulx, uly]]
prjext = geoext
#########################################################################################################
##set self._gdaldataset for use in overview generation
##we'll use bands 21, 30 & 43 for RGB (http://edcsns17.cr.usgs.gov/eo1/Hyperion_Spectral_Coverage.htm)
##as they're near the center of the equivalent ALI bands
##This generates verrrryyy looong overviews cos hyperion data is one long thin strip eg. 256*3000 etc...
#self._gdaldataset = geometry.CreateVRTCopy(sd)
##Instead we can clip out some of the centre rows
#vrtcols=ncols
#vrtrows=int(ncols*1.5)
#srcrect=[0, int(nrows/2-vrtrows/2),ncols,vrtrows]
#dstrect=[0, 0,ncols,vrtrows]
##Or we can fill out the ncols with nodata
vrtcols = int(nrows / 1.5)
vrtrows = nrows
srcrect = [0, 0, ncols, nrows]
dstrect = [int(nrows / 2.5 - ncols), 0, ncols, nrows]
vrt = geometry.CreateMosaicedVRT([sd.GetDescription()],
[43, 30, 21], [srcrect],
[dstrect], vrtcols, vrtrows,
self.metadata['datatype'])
self._gdaldataset = geometry.OpenDataset(vrt)
self._gdaldataset.GetRasterBand(3).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(2).SetNoDataValue(0)
self._gdaldataset.GetRasterBand(1).SetNoDataValue(0)
self._stretch = ('STDDEV', (1, 2, 3), [2])
#########################################################################################################
self.metadata['cols'] = ncols
self.metadata['rows'] = nrows
self.metadata['nbands'] = nbands
#Geotransform
ncols = map(int, str(ncols).split(','))
nrows = map(int, str(nrows).split(','))
cellx, celly = [], []
j = 0
while j < len(ncols):
gcps = []
i = 0
lr = [[0, 0], [ncols[j], 0], [ncols[j], nrows[j]], [0, nrows[j]]]
while i < len(prjext) - 1: #don't need the last xy pair
gcp = gdal.GCP()
gcp.GCPPixel, gcp.GCPLine = lr[i]
gcp.GCPX, gcp.GCPY = prjext[i]
gcp.Id = str(i)
gcps.append(gcp)
i += 1
j += 1
geotransform = gdal.GCPsToGeoTransform(gcps)
x, y = geometry.CellSize(geotransform)
cellx.append(str(x))
celly.append(str(abs(y)))
self.metadata['cellx'] = ','.join(cellx)
self.metadata['celly'] = ','.join(celly)
self.metadata['UL'] = '%s,%s' % tuple(geoext[0])
self.metadata['UR'] = '%s,%s' % tuple(geoext[1])
self.metadata['LR'] = '%s,%s' % tuple(geoext[2])
self.metadata['LL'] = '%s,%s' % tuple(geoext[3])
self.metadata['rotation'] = geometry.Rotation(geotransform)
if abs(self.metadata['rotation']) < 1.0:
self.metadata['orientation'] = 'Map oriented'
self.metadata['rotation'] = 0.0
else:
self.metadata['orientation'] = 'Path oriented'
self.metadata['filesize'] = sum(
[os.path.getsize(tmp) for tmp in self.filelist])
self.metadata['compressionratio'] = 0
self.metadata['compressiontype'] = 'None'
self.extent = geoext
def __getmetadata__(self,f=None):
'''Populate metadata'''
if not f:f=self.fileinfo['filepath']
self._gdaldataset = geometry.OpenDataset(f)
led=glob.glob(os.path.dirname(f) + '/[Ll][Ee][Aa][Dd]*')[0] #volume file
meta = open(led,'rb').read()
######################
# Scene header record
######################
record=2
recordlength=3960 #SPOT recordlength=3960
##################
#SCENE PARAMETERS
##################
sceneid=utilities.readbinary(meta,(record-1)*recordlength,37,52)
cy=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,85,100),'HDDDMMSS') #Latitude of the Scene Centre
cx=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,101,116),'HDDDMMSS') #Longitude of the Scene Centre
uly=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,149,164),'HDDDMMSS')
ulx=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,165,180),'HDDDMMSS')
ury=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,213,228),'HDDDMMSS')
urx=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,229,244),'HDDDMMSS')
lly=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,277,292),'HDDDMMSS')
llx=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,293,308),'HDDDMMSS')
lry=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,341,356),'HDDDMMSS')
lrx=geometry.DMS2DD(utilities.readbinary(meta,(record-1)*recordlength,357,372),'HDDDMMSS')
ext=[[ulx,uly],[urx,ury],[lrx,lry],[llx,lly],[ulx,uly]]
######################
#IMAGING PARAMETERS
######################
self.metadata['rotation']=float(utilities.readbinary(meta,(record-1)*recordlength,437,452))
if abs(self.metadata['rotation']) < 1:
self.metadata['orientation']='Map oriented'
self.metadata['rotation']=0.0
else:self.metadata['orientation']='Path oriented'
self.metadata['sunazimuth']=float(utilities.readbinary(meta,(record-1)*recordlength,469,484))
self.metadata['sunelevation']=float(utilities.readbinary(meta,(record-1)*recordlength,485,500))
imgdate=utilities.readbinary(meta,(record-1)*recordlength,581,612)
#self.metadata['imgdate']=time.strftime(utilities.dateformat,time.strptime(imgdate[0:8],'%Y%m%d')) #ISO 8601
self.metadata['imgdate']=time.strftime(utilities.datetimeformat,time.strptime(imgdate[0:14],'%Y%m%d%H%M%S')) #ISO 8601
satellite=utilities.readbinary(meta,(record-1)*recordlength,613,628)
sensor=utilities.readbinary(meta,(record-1)*recordlength,629,644)
mode=utilities.readbinary(meta,(record-1)*recordlength,645,660)
######################
#IMAGE PARAMETERS
######################
ncols=int(utilities.readbinary(meta,(record-1)*recordlength,997,1012))
nrows=int(utilities.readbinary(meta,(record-1)*recordlength,1013,1028))
nbands=int(utilities.readbinary(meta,(record-1)*recordlength,1045,1060))
bands=utilities.readbinary(meta,(record-1)*recordlength,1061,1316).replace(' ',',')
self.metadata['level']=utilities.readbinary(meta,(record-1)*recordlength,1317,1332)
self.metadata['resampling']=utilities.readbinary(meta,(record-1)*recordlength,1365,1380)
if self.metadata['level']=='1A': #Not geometrically corrected. Cell size isn't really appropriate
gcps=geometry.ExtentToGCPs(ext,ncols,nrows)
gt=gdal.GCPsToGeoTransform(gcps)
cellx,celly=geometry.CellSize(gt)
else:
cellx=float(utilities.readbinary(meta,(record-1)*recordlength,1381,1396))
celly=float(utilities.readbinary(meta,(record-1)*recordlength,1397,1412))
#################################################
#Ancillary "Ephemeris / Attitude" record,
#################################################
record=3
viewangle=float(utilities.readbinary(meta,(record-1)*recordlength,3065,3076))
#################################################
#Map projection (scene-related) ancillary record
#################################################
record=26
projection = utilities.readbinary(meta,(record-1)*recordlength,21,52).replace('\x00','')
ellipsoid = utilities.readbinary(meta,(record-1)*recordlength,57,88).replace('\x00','')
datum = utilities.readbinary(meta,(record-1)*recordlength,101,132).replace('\x00','')
if 'UTM' in projection:
# UTM
type='UTM'
units='m'
zone=projection[3:-1]
if not zone:
zone=str(spatialreferences.lon2utmzone(cx))
if 'GDA' in datum: epsg=int('283'+zone)
elif 'AGD' in datum: epsg=int('202'+zone)
elif 'WGS' in datum: epsg=int('327'+zone) if projection[-1] =='S' else int('326'+zone)
else: #Assume
type='GEO'
units='deg'
if datum=='GDA94':epsg=4283
else:epsg=4326 #Assume WGS84
if 'GDA' in datum: epsg=4283
elif 'AGD' in datum: epsg=202
else: epsg=4326 #Assume WGS84'
#cell sizes are reported in metres even for geo projections
gcps=[];i=0
lr=[[0,0],[ncols,0],[ncols,nrows],[0,nrows]]
while i < len(ext)-1: #don't need the last xy pair
gcp=gdal.GCP()
gcp.GCPPixel,gcp.GCPLine=lr[i]
gcp.GCPX,gcp.GCPY=ext[i]
gcp.Id=str(i)
gcps.append(gcp)
i+=1
geotransform = gdal.GCPsToGeoTransform(gcps)
cellx,celly=geometry.CellSize(geotransform)
rotation=geometry.Rotation(geotransform)
srs = osr.SpatialReference()
srs.ImportFromEPSG(epsg)
srs=srs.ExportToWkt()
self.metadata['satellite']=satellite
self.metadata['sensor']=sensor
self.metadata['filetype'] ='CEOS/SPOT CCT Format'
self.metadata['filesize']=sum([os.path.getsize(file) for file in self.filelist])
self.metadata['sceneid'] = sceneid
self.metadata['srs'] = srs
self.metadata['epsg'] = epsg
self.metadata['units'] = units
self.metadata['cols'] = ncols
self.metadata['rows'] = nrows
self.metadata['nbands'] = nbands
self.metadata['bands'] = bands
self.metadata['nbits'] = 8
self.metadata['datatype'] = 'Byte'
self.metadata['nodata'] = 0
self.metadata['mode'] = mode
self.metadata['cellx'],self.metadata['celly']=map(float,[cellx,celly])
self.metadata['UL']='%s,%s' % tuple(ext[0])
self.metadata['UR']='%s,%s' % tuple(ext[1])
self.metadata['LR']='%s,%s' % tuple(ext[2])
self.metadata['LL']='%s,%s' % tuple(ext[3])
metadata=self._gdaldataset.GetMetadata()
self.metadata['metadata']='\n'.join(['%s: %s' %(m,hdf_self.metadata[m]) for m in metadata])
self.metadata['compressionratio']=0
self.metadata['compressiontype']='None'
self.extent=ext
def __getmetadata__(self, f=None):
'''
Generate metadata for generic imagery
@type f: string
@param f: a filepath to the dataset or a VRT XML string
@return: None
@todo: We force a NoData value. This is not ideal, but it makes for better overview images.
'''
if not f: f = self.fileinfo['filepath']
try:
cwd = os.path.abspath(os.curdir)
if os.path.exists(f) and os.path.dirname(f):
p = os.path.split(f)[0]
os.chdir(p)
if not self._gdaldataset:
self._gdaldataset = geometry.OpenDataset(
f
) #in case we're subclassed and there's already a dataset open
if self._gdaldataset:
driver = self._gdaldataset.GetDriver().ShortName
if driver[0:3] == 'HDF':
raise NotImplementedError, 'HDF files are not yet implemented except by custom formats'
self.metadata[
'filetype'] = driver + '/' + self._gdaldataset.GetDriver(
).LongName
self.metadata['cols'] = self._gdaldataset.RasterXSize
self.metadata['rows'] = self._gdaldataset.RasterYSize
self.metadata['nbands'] = self._gdaldataset.RasterCount
self.metadata['srs'] = self._gdaldataset.GetProjection()
if not self.metadata['srs'] and self._gdaldataset.GetGCPCount(
) > 0:
self.metadata['srs'] = self._gdaldataset.GetGCPProjection()
self.metadata['epsg'] = spatialreferences.IdentifyAusEPSG(
self.metadata['srs'])
self.metadata['units'] = spatialreferences.GetLinearUnitsName(
self.metadata['srs'])
geotransform = self._gdaldataset.GetGeoTransform()
if geotransform == (0, 1, 0, 0, 0, 1):
if self._gdaldataset.GetGCPCount() > 0:
gcps = self._gdaldataset.GetGCPs()
geotransform = gdal.GCPsToGeoTransform(gcps)
gcps = geometry.GeoTransformToGCPs(
geotransform, self.metadata['cols'], self.
metadata['rows']) #Just get the 4 corner GCP's
else:
raise NotImplementedError, 'Dataset is not georeferenced'
else:
gcps = geometry.GeoTransformToGCPs(geotransform,
self.metadata['cols'],
self.metadata['rows'])
ext = [[gcp.GCPX, gcp.GCPY] for gcp in gcps]
ext.append([gcps[0].GCPX, gcps[0].GCPY
]) #Add the 1st point to close the polygon)
#Reproject corners to lon,lat
geom = geometry.GeomFromExtent(ext)
src_srs = osr.SpatialReference()
src_srs.ImportFromWkt(self.metadata['srs'])
tgt_srs = osr.SpatialReference()
tgt_srs.ImportFromEPSG(4326)
geom = geometry.ReprojectGeom(geom, src_srs, tgt_srs)
points = geom.GetGeometryRef(0) #geom.GetBoundary()
ext = [[points.GetX(i), points.GetY(i)]
for i in range(0, points.GetPointCount())]
self.metadata['cellx'], self.metadata[
'celly'] = geometry.CellSize(geotransform)
self.metadata['rotation'] = geometry.Rotation(geotransform)
if abs(self.metadata['rotation']) < 1.0:
self.metadata['orientation'] = 'Map oriented'
self.metadata['rotation'] = 0.0
else:
self.metadata['orientation'] = 'Path oriented'
self.metadata['UL'] = '%s,%s' % tuple(ext[0])
self.metadata['LL'] = '%s,%s' % tuple(ext[1])
self.metadata['LR'] = '%s,%s' % tuple(ext[2])
self.metadata['UR'] = '%s,%s' % tuple(ext[3])
rb = self._gdaldataset.GetRasterBand(1)
if rb:
self.metadata['datatype'] = gdal.GetDataTypeName(
rb.DataType)
self.metadata['nbits'] = gdal.GetDataTypeSize(rb.DataType)
nodata = rb.GetNoDataValue()
if nodata is not None:
self.metadata['nodata'] = str(nodata)
else:
ct = rb.GetColorTable() #Fix for Issue 31
if ct is None:
if self.metadata['datatype'][0:4] in [
'Byte', 'UInt'
]:
nodata = 0 #Unsigned, assume 0
else:
nodata = -2**(
self.metadata['nbits'] - 1
) #Signed, assume min value in data range
self.metadata['nodata'] = str(nodata)
#Fix for Issue 17
for i in range(1,
self._gdaldataset.RasterCount + 1):
self._gdaldataset.GetRasterBand(
i).SetNoDataValue(nodata)
else:
raise IOError, 'No valid rasterbands found.'
metadata = self._gdaldataset.GetMetadata()
self.metadata['metadata'] = '\n'.join(
['%s: %s' % (m, metadata[m]) for m in metadata])
self.metadata['filesize'] = sum(
[os.path.getsize(tmp) for tmp in self.filelist])
if self.metadata['filesize'] > 0:
self.metadata['compressionratio'] = int(
(self.metadata['nbands'] * self.metadata['cols'] *
self.metadata['rows'] *
(self.metadata['nbits'] / 8.0)) /
self.metadata['filesize'])
if self.metadata['compressionratio'] > 0:
try:
if driver[0:3] == 'JP2':
self.metadata['compressiontype'] = "JPEG2000"
elif driver[0:3] == 'ECW':
self.metadata['compressiontype'] = "ECW"
else:
mdis = self._gdaldataset.GetMetadata(
'IMAGE_STRUCTURE')
#self.metadata['compressiontype']=mdis['IMAGE_STRUCTURE']
self.metadata['compressiontype'] = mdis[
'COMPRESSION']
except:
self.metadata['compressiontype'] = 'Unknown'
else:
self.metadata['compressiontype'] = 'None'
self.extent = ext
else:
errmsg = gdal.GetLastErrorMsg()
raise IOError, 'Unable to open %s\n%s' % (f, errmsg.strip())
finally: #Cleanup
gdal.ErrorReset()
os.chdir(cwd)