def main():
# define a shapefile for the study area
shp = '/.../testsite.shp'
# define the output name of the DEM (no file extension like .tif etc.!)
outname = '/path/to/demfile'
# define a buffer around the study area boundaries (in degrees)
buffer = 0.01
# load the defined shapefile
site = vector.Vector(shp)
# reproject the shapefile to latlon (in-memory, no file written or modified)
site.reproject('+proj=longlat +datum=WGS84 +no_defs ')
# define a GDAL VRT file containing all SRTM tiles
# this file has all hgt tiles in the same directory registered and is used for subsetting/mosaicing
srtm_vrt = '/path/to/SRTM_1_HGT.vrt'
# extract the extent (bounding box) of the shapefile
ext = site.extent
# add the buffer to the bounding box
ext['xmin'] -= buffer
ext['ymin'] -= buffer
ext['xmax'] += buffer
ext['ymax'] += buffer
# create a temporary directory for writing intermediate files (will be deleted at the end)
tmpdir = outname + '__tmp'
if not os.path.isdir(tmpdir):
os.makedirs(tmpdir)
# define a name for a temporary DEM file
dem_tmp = os.path.join(tmpdir, 'srtm_tmp.tif')
# create a DEM mosaic for the study site
run([
'gdalwarp', '-q', '-of', 'GTiff', '-te', ext['xmin'], ext['ymin'],
ext['xmax'], ext['ymax'], srtm_vrt, dem_tmp
])
# transform the DEM to GAMMA format (including EGM96 geoid to WGS84 ellipsoid height reference correction)
gamma.process(['srtm2dem', dem_tmp, outname, outname + '.par', 2, '-'],
outdir=tmpdir)
# create an ENVI header file
hdr(outname + '.par')
# remove the temporary directory with all intermediate files
shutil.rmtree(tmpdir)
# optional: transform DEM to UTM projection
# the UTM zone is automatically computed for the center of the DEM file
srtm.transform(outname, outname + '_utm', posting=20)
def worker(sitename):
#######################################################################################
# setup general processing parameters
resolution = 20
#######################################################################################
# define the directories for writing temporary and final results
sitedir = os.path.join(maindir, sitename)
outdir = os.path.join(sitedir, 'proc_out')
#######################################################################################
# load the test site geometry into a vector object
sites = vector.Vector('/.../testsites.shp')
# query the test site by name; a column name 'Site_Name' must be saved in your shapefile
site = sites['Site_Name={}'.format(sitename)]
#######################################################################################
# query the database for scenes to be processed
with Archive(dbfile) as archive:
selection_proc = archive.select(vectorobject=site,
processdir=outdir,
sensor=('S1A', 'S1B'),
product='GRD',
acquisition_mode='IW',
vv=1)
print('{0}: {1} scenes found for site {2}'.format(socket.gethostname(),
len(selection_proc),
sitename))
#######################################################################################
# call to processing utility
if len(selection_proc) > 1:
print('start processing')
for scene in selection_proc:
geocode(infile=scene, outdir=outdir, tr=resolution, scaling='db')
return len(selection_proc)
def worker(sitename):
#######################################################################################
# setup general processing parameters
resolution = 20
# number of processes for Python pathos framework (multiple scenes in parallel)
parallel1 = 6
# number of parallel OpenMP threads; this is used by GAMMA internally
parallel2 = 6
os.environ['OMP_NUM_THREADS'] = str(parallel2)
#######################################################################################
# get the maximum date of the precise orbit files
# as type also 'RES' can be selected. These files are not as precise as POE and thus geocoding might not be
# quite as accurate
with OSV(osvdir) as osv:
maxdate = osv.maxdate(osvtype='POE', datetype='stop')
#######################################################################################
# define the directories for writing temporary and final results
sitedir = os.path.join(maindir, sitename)
tempdir = os.path.join(sitedir, 'proc_in')
outdir = os.path.join(sitedir, 'proc_out')
#######################################################################################
# load the test site geometry into a vector object
sites = vector.Vector('/.../testsites.shp')
# query the test site by name; a column name 'Site_Name' must be saved in your shapefile
site = sites["Site_Name='{}'".format(sitename)]
#######################################################################################
# query the database for scenes to be processed
with Archive(dbfile) as archive:
selection_proc = archive.select(vectorobject=site,
processdir=outdir,
maxdate=maxdate,
sensor=('S1A', 'S1B'),
product='GRD',
acquisition_mode='IW',
vv=1)
print('{0}: {1} scenes found for site {2}'.format(socket.gethostname(),
len(selection_proc),
sitename))
#######################################################################################
# define the DEM file
demfile = '{0}/{1}/DEM/{1}_srtm_utm'.format(maindir, sitename)
if not os.path.isfile(demfile):
print('DEM missing for site {}'.format(sitename))
return
#######################################################################################
# call to processing utility
if len(selection_proc) > 1:
print('start processing')
if len(selection_proc) > 1:
if len(selection_proc) < parallel1:
parallel1 = len(selection_proc)
# run the function on multiple cores in parallel
multicore(geocode,
cores=parallel1,
multiargs={'scene': selection_proc},
dem=demfile,
tempdir=tempdir,
outdir=outdir,
targetres=resolution,
scaling='db',
func_geoback=2,
func_interp=0,
sarsimulation=False,
osvdir=osvdir,
cleanup=True,
allow_RES_OSV=False)
elif len(selection_proc) == 1:
scene = selection_proc[0]
# run the function on a single core
geocode(scene,
dem=demfile,
tempdir=tempdir,
outdir=outdir,
targetres=resolution,
scaling='db',
func_geoback=2,
func_interp=0,
sarSimCC=False,
osvdir=osvdir,
cleanup=True,
allow_RES_OSV=False)
return len(selection_proc)