def classification(data):
# Add channel
pcimod(file=inputfile, pciop='add', pcival=[0, 0, 1, 0, 0, 0])
# Define input parameters
classesNumber = [8] # define number of classes
iterations = [10] # define number iterations
moveThresh = [0.01] # define move threshhold
print "Running unsupervized k-means classification..."
print "Creating " + str(classesNumber) + " classes, applying " + str(
iterations) + " iterations at a move-threshhold of " + str(
moveThresh)
# Run algorithm and create classification report
try:
Report.clear()
enableDefaultReport(report)
kclus(file=inputfile,
dbic=inputChans,
dboc=[chansCount + 1],
numclus=classesNumber,
maxiter=iterations,
movethrs=moveThresh)
finally:
enableDefaultReport('term') # this will close the report file
flag1 = time.time()
print "Classification complete! Time elapsed: " + str(
flag1 - start) + " seconds"
print ""
def orthorectify(self, in_file, out_file, DEM, pixelSpacing_x,pixelSpacing_y, proj):
"""
Method for orthorectification of radarsat2 image
Orthorectify RADARSAT-2 imagery contained in a PCIPIX file.
Outputs the Orthorectified results into a newly created PCIPIX file
Parameters:
in_file -- Input file
out_file -- Output file
DEM -- DEM file
pixelSpacing_x -- x pixel spacing
pixelSpacing_x -- y pixel spacing
proj -- data projection
Return value:
Error statement if error occurs.
Limits and constraints:
"""
try:
logging.info(' Executing: OrthoMosaic.orthorectify')
mfile = in_file # Input image file name
dbic = [1,2] # input HH + incidence angle channels
mmseg = [3] # use the last math segment
dbiw = [] # Use all image
srcbgd = "NONE"
filo = out_file # Uses the default file name
ftype = "PIX" # Use the PCIDSK format
foptions = "BAND"
outbgd = [0]
ulx = ''
uly = ''
lrx = ''
lry = ''
edgeclip = [0]
tipostrn = ""
mapunits = proj
bxpxsz = str(pixelSpacing_x)
bypxsz = str(pixelSpacing_y)
filedem = DEM
dbec = [1]
backelev = []
elevref = ""
elevunit = "METER"
elfactor = [] # Specifies the offset only
proc = ""
sampling = [4] # Ortho correction is computed for every pixel
resample = "BILIN"
Report.clear()
ortho2(mfile, dbic, mmseg, dbiw, srcbgd, filo, ftype,
foptions, outbgd, ulx, uly, lrx, lry, edgeclip, tipostrn, mapunits, bxpxsz, bypxsz, filedem, dbec,
backelev, elevref, elevunit, elfactor, proc, sampling, resample)
enableDefaultReport('term')
logging.info(' Successfully completed OrthoMosaic.orthorectify: ortho2')
except PCIException, e:
EGS_utility.EGSUtility().error('orthorectify(): {:s}'.format(e))
def raster_his(self, in_file, band, mask, rep_file):
"""
Logs histogram.
Parameters:
in_file -- input file
band -- band
rep_file -- report file
Return value:
Logs histogram for input raster image, error statement otherwise.
"""
from pci.api import datasource as ds
from pci.pcimod import pcimod
from pci.exceptions import PCIException
from pci.his import his
from pci.nspio import Report, enableDefaultReport
from osgeo import gdal, ogr, osr
## from gdalconst import *
import numpy
try:
logging.info('')
logging.info(' Executing: EGSUtility.raster_his')
logging.info(' Compare product: ' + in_file)
logging.info(' Band: ' + str(band))
if os.path.exists(rep_file):
os.remove(rep_file)
file = in_file
dbic = [band] # 8-bit unsigned
gmod = 'ON' # show graphic mode
cmod = 'OFF' # no cumulative mode
pcmo = 'OFF' # no percentage mode
nsam = [] # no number of samples
trim = [] # no trimming
hisw = [] # no specific histogram window
mask = [mask] # process entire image
imstat_list = []
imstat = imstat_list
Report.clear()
enableDefaultReport(rep_file)
his(file, dbic, gmod, cmod, pcmo, nsam, trim, hisw, mask, imstat)
enableDefaultReport('term') # this will close the report file
# open results file, output results to log file
#with open(rep_file) as infile:
# for line in infile:
# logging.info(line)
# infile.close()
#logging.info(imstat)
return imstat
except PCIException, e:
self.error('raster_his(): {:s}'.format(e))
def vegcover2bit(self, in_file, out_file, veg_channel=4, size_pixel=10):
"""
IIA Veg Cover Shapefile to ortho file
Parameters:
in_file -- Input file
out_file -- Output file
veg_channel -- Vegetation land cover (vector)
size_pixel -- Pixel size
Return value:
Newly create vegetation land cover bitmap segment # when successful,
Error statement otherwise.
Limits and constraints:
"""
try:
logging.info(' Executing: VegFloodProcess.vegcover2bit')
util = EGS_utility.EGSUtility()
bitmap_ids_before = util.bitmap_list(
out_file
) # Run bitmap_list to get a list of IDs from before poly2bit
fili = in_file
dbvs = [veg_channel] # polygon layer
filo = out_file
dbsd = "" # use default, "Bitmap polygons gridded from vector"
pixres = [size_pixel, size_pixel] # make 10 meter square pixels
ftype = "PIX" # output format type
foptions = "" # output options
Report.clear()
poly2bit(fili, dbvs, filo, dbsd, pixres, ftype, foptions)
logging.info(
' Successfully completed VegFloodProcess.vegcover2bit: poly2bit'
)
enableDefaultReport('term')
bitmap_ids_after = util.bitmap_list(
out_file
) # Run bitmap_list to get a list of IDs from after poly2bit
bit_seg = list(set(bitmap_ids_after) - set(bitmap_ids_before)
) # Get the difference between the two lists
return bit_seg[0]
except PCIException, e:
EGS_utility.EGSUtility().error('vegcover2bit(): {:s}'.format(e))
def make_pca(merged_input, pca_out, identifier):
start_time = time.time()
print "Starting Principal Component Analysis for file %s" % identifier
pca_rep = os.path.join(pcadir, "PCA_" + identifier + "_report.txt")
fexport(fili=merged_input,
filo=pca_out,
dbic=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
ftype="PIX")
try:
Report.clear() # Clear report file
enableDefaultReport(pca_rep) # Change output folder location
pcimod(file=pca_out,
pciop="ADD",
pcival=[0, 0, 3]) # Add 3 16 bit unsigned channels
pca(file=pca_out,
dbic=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], # Use first ten bands
eign=[1, 2, 3], # Output first three eigenchannels
dboc=[11, 12, 13], # Output to 3 new channels
rtype="LONG") # Output extended report format
except PCIException, e:
print e
def threshold_sar(self,
in_file,
band=4,
veg_thr=-3.5,
openwater_thres=-12.5):
"""
Threshold high and low
Apply low threshold for open water areas for Edge preservation filter results
Apply high threshold for flooded tree areas for Edge preservation filter results
The input is a PCIPIX file containing a filtered and scaled imagery.
Bitmaps are added to PCIPIX representing open water and flood vegeatation areas
Note:
PCI's developers are going to try to add a 'last segment created' (lasc) parameter for
this function in the next release, thereby enabling cleaner and more reliable automation.
Parameters:
in_file -- Input file
band -- Input band
veg_thr -- Minimum threshold for vegetation flooded area
openwater_thres -- Maximum threshold for open water flooded areas
Return value:
Newly create vegetation and open water bitmap segment # when successful,
Error statement otherwise.
Limits and constraints:
"""
try:
logging.info(' Executing: VegFloodProcess.threshold_sar')
# Find min and max of band
imstat = EGS_utility.EGSUtility().gdal_stat(in_file, band)
max_pixel = imstat[1]
min_pixel = imstat[0] + 1
# Create and name newly created segment, 'thr' does not rename segments
dataset = ds.open_dataset(in_file, ds.eAM_WRITE)
veg_seg = dataset.create_bitmap(
) # Get the number of the newly created bitmap segment
file = in_file
dbsl = [veg_seg]
dbsn = "vegflood"
dbsd = "Veg Flood seg"
mas(file, dbsl, dbsn, dbsd)
logging.info(
' Successfully completed VegFloodProcess.threshold_sar: mas'
)
# Threshold for flood vegetation
file = in_file
dbic = [band]
#dbob = [] # create new bitmap
dbob = [veg_seg]
tval = [veg_thr, max_pixel] # threshold range (min,max)
comp = 'OFF' # threshold values from 9 to 11
dbsn = 'vegflood' # output segment name
dbsd = 'Veg Flood seg' # output segment description
Report.clear()
thr(file, dbic, dbob, tval, comp, dbsn, dbsd)
enableDefaultReport('term')
logging.info(
' Successfully completed VegFloodProcess.threshold_sar: thr'
)
# Create and name newly created segment, 'thr' does not rename segments
water_seg = dataset.create_bitmap(
) # Get the number of the newly created bitmap segment
file = in_file
dbsl = [water_seg]
dbsn = "openwate"
dbsd = "Open Water seg"
mas(file, dbsl, dbsn, dbsd)
logging.info(
' Successfully completed VegFloodProcess.threshold_sar: mas'
)
# Threshold for open water
file = in_file
dbic = [band]
#dbob = [] # create new bitmap
dbob = [water_seg]
tval = [min_pixel, openwater_thres] # threshold range (min,max)
comp = 'OFF' # threshold values
dbsn = 'openwate' # output segment name
dbsd = 'Open Water seg' # output segment description
Report.clear()
thr(file, dbic, dbob, tval, comp, dbsn, dbsd)
enableDefaultReport('term')
logging.info(
' Successfully completed VegFloodProcess.threshold_sar: thr'
)
return [veg_seg, water_seg]
except PCIException, e:
EGS_utility.EGSUtility().error('threshold_sar(): {:s}'.format(e))
def classification(self, file, alg):
if (alg == 'kmeans'):
print("Your selection is K-means Classification")
else:
print("Your selection is Iso-Cluster Classification")
report = os.getcwd() + "\\Data\\Result\\Report.txt"
if os.path.isfile(report):
print("Deleting old Report")
os.remove(report)
with datasource.open_dataset(file) as dataset:
cc = dataset.chan_count
print("Available Channels: ")
print(cc)
if (alg == 'kmeans'):
file = file
dbic = list(range(1, cc + 1, 1)) # input channels
dboc = [cc + 1] # output channel
print(dboc)
mask = [] # process entire image
numclus = [5] # requested number of clusters
seedfile = '' # automatically generate seeds
maxiter = [20] # no more than 20 iterations
movethrs = [0.01]
print("The file is: " + root.filename)
## enableDefaultReport(prev_report)
pcimod(file=file, pciop='add', pcival=[1, 0, 0, 0, 0, 0])
Report.clear()
enableDefaultReport(report)
print("Applying K-Means Classification")
kcluster = kclus(file, dbic, dboc, mask, numclus, seedfile,
maxiter, movethrs)
print("K-Means Classification is successful")
else:
file = file # input file
dbic = list(range(1, cc + 1, 1)) # input channels
dboc = [cc + 1] # output channel
print(dboc)
mask = [] # process entire image
numclus = [5] # requested number of clusters
maxclus = [7] # at most 20 clusters
minclus = [5] # at least 5 clusters
seedfile = '' # automatically generate seeds
maxiter = [5] # no more than 20 iterations
movethrs = [0.01]
siggen = "NO" # no signature generation
samprm = [5]
stdv = [10.0]
lump = [1.0]
maxpair = [5] # no more than 5 cluster center pairs
# clumped in one iteration
backval = [] # no background value
nsam = [] # default number of samples
print("The file is: " + root.filename)
## enableDefaultReport(prev_report)
pcimod(file=file, pciop='add', pcival=[1, 0, 0, 0, 0, 0])
Report.clear()
enableDefaultReport(report)
print("Applying Iso-cluster Classification")
isoclus( file, dbic, dboc, mask, numclus, maxclus, minclus, seedfile, maxiter,\
movethrs, siggen, samprm, stdv, lump, maxpair, backval, nsam )
print("Iso-Cluster Classification is successful")
pcimod(file=file, pciop='add', pcival=[1])
## root.status.set("Running fmo")
print("Applying MOD filter")
kfmo = fmo(file=file, dbic=[cc + 1], dboc=[cc + 2])
print("MOD filter is successfully applied")
pcimod(file=file, pciop='add', pcival=[1])
## root.status.set("Running sieve")
print("Applying SIEVE filter")
ksieve = sieve(file=file, dbic=[cc + 1], dboc=[cc + 3], sthresh=[32])
print("SIEVE filter is successfully applied")
## Split and insert directory name
split_file = file.split("/")
split_file.insert(-1, "Result")
join_result = "\\".join(split_file)
## Split by .
dot_result = join_result.split(".")
## print(dot_result)
## print("dot result")
## join .shp at last
shp_result = dot_result[0] + ".shp"
current_file_path, ext = os.path.splitext(str(file))
current_file = current_file_path.split("/")[-1]
## print(current_file)
## print("current file")
## Delete previously generated shapefiles
prev_files = glob.glob(os.getcwd() + "\\Data\\Result\\" + "*")
## print(prev_files)
## print("previous files")
for prev_file in prev_files:
prev_file_name, format = os.path.splitext(
str(os.path.basename(prev_file)))
## print(prev_file_name)
## print(" prev file names")
if (current_file in prev_file_name):
print("DELETING: " + str(prev_file))
os.remove(prev_file)
print("Successfully DELETED: " + str(prev_file))
## if(os.path.exists("../Data/Result/"+dot_result[0])):
## print("inside if ......")
## os.remove(shp_result)
## print("shp is deleted...")
print("Exporting to shapefile")
ras2poly(fili=file,
dbic=[cc + 3],
filo=shp_result,
smoothv="Yes",
ftype="SHP",
foptions="")
print("Shapefile is successfully created")
def merge_filter_export(self, in_file, in_file2, out_file, out_file2, out_file3, hole_size):
"""
Imports, merges, filters and exports flooded products.
Import flood products into PCIPIX format, merge products, filters to remove holes / areas.
Outputs resulting products as compressed geotif and shapefile.
Merges image value polygons smaller than a user-specified
threshold with the largest neighboring polygon
Parameters:
in_file -- Input file1
in_file2 -- Input file2
out_file -- Working PCIPIX file
out_file2 -- Resuling output geotif
hole_size -- threshold for filter (hectares)
Return value:
Error statement if error occurs.
"""
#import required PCI Geomatica modules
import pci
from pci.sieve import *
from pci.fimport import *
from pci.fexport import *
from pci.thmrovr import *
from pci.mosaic import *
from pci.thmrmer import *
from pci.model import *
from pci.nspio import Report, enableDefaultReport
from pci.exceptions import PCIException
from pci.ras2poly import *
import arcpy
from osgeo import gdal, ogr, osr
from gdalconst import GA_Update
try:
util = EGS_utility.EGSUtility()
#Import first image (flooded vegetation) into PCIPIX file
logging.info(' Executing: MergeProcess.merge_filter_export')
fili = in_file
filo = out_file
dbiw = []
poption = ""
dblayout = "" #Defaults to "BAND"
Report.clear()
fimport(fili, filo, dbiw, poption, dblayout)
enableDefaultReport('term')
logging.info(' Successfully completed MergeProcess.merge_filter_export: fimport')
#Import second image (open water) into PCIPIX file
new_chans = EGS_utility.EGSUtility().add_8_channel(out_file)
fili = in_file2
dbic = [1] # use channel 1
dbvs = [] # default, no cutline defined
dblut = [] # default, no lookup table
filo = out_file
dboc = [int(new_chans[0])] # overwrite channel 1
blend = [] # default, no blending
backval = [] # default, 0
mosaic( fili, dbic, dbvs, dblut, filo, dboc, blend, backval )
logging.info(' Successfully completed MergeProcess.merge_filter_export: mosaic')
# Convert values using MODEL so 255 = 0
file = out_file
source_model = """if (%2 = 255) then
%2 = 0
endif"""
model( file, source=source_model)
#Merge two image together, possible use thmrovr for one step instead of two
merge_chan = util.add_8_channel(out_file)
fili = out_file # input file
filo = out_file # output file will be created
dbic = [1,int(new_chans[0])] # input thematic raster channels
dbib = [] # no bitmap mask
dboc = [int(merge_chan[0])]
omethod = "UNION" # default, "UNION"
thmrovr( fili, filo, dbic, dbib, dboc, omethod )
logging.info(' Successfully completed MergeProcess.merge_filter_export: thmrovr')
# Combine values using MODEL so zero = not flooded, 255 = flooded
file = out_file
source_model = """if (%3 >= 1) then
%3 = 255
endif"""
model( file, source=source_model)
#Determine filter size as pixel number
filtered_chan = util.add_8_channel(out_file)
pixelwidth = util.gdal_geotransform(out_file)[1]
pixelheight = util.gdal_geotransform(out_file)[5]
logging.info(' pixelwidth: ' + str(pixelwidth))
logging.info(' pixelheight: ' + str(pixelheight))
num_pixel = int((hole_size * 10000)/abs(pixelwidth * pixelheight)) # hole_size is in hectares
logging.info(' Number of pixels for threshold hole size: ' + str(num_pixel))
#Filter in order to remove holes
file = out_file
dbic = [int(merge_chan[0])]
dboc = [int(filtered_chan[0])]
sthresh = [num_pixel] # polygon size threshold in
keepvalu = [] # no keep value
connect = [] # default, 4-connection
sieve( file, dbic, dboc, sthresh, keepvalu, connect )
logging.info(' Successfully completed MergeProcess.merge_filter_export: sieve')
#EGS_utility.EGSUtility().raster_his(out_file,int(filtered_chan[0]))
#Export resulting product as a geotif
fili = out_file
filo = out_file2
dbiw = []
dbic = [int(filtered_chan[0])]
dbib = []
dbvs = []
dblut = []
dbpct = []
ftype = "tif"
foptions = "LZW"
fexport( fili, filo, dbiw, dbic, dbib, dbvs, dblut, dbpct, ftype, foptions )
logging.info(' Successfully completed MergeProcess.merge_filter_export: fexport')
fili = out_file # input raster file
dbic = [int(filtered_chan[0])] # using channel 6 from irvine.pix
filo = out_file # output file to be created
smoothv = "" # default, YES vectors are smoothed
dbsd = "" # defaults to "Created from Raster"
ftype = "" # default, PIX
foptions = "" # output format options
ras2poly(fili, dbic, filo, smoothv, dbsd, ftype, foptions)
logging.info(' Successfully completed MergeProcess.merge_filter_export: ras2poly')
# Export resulting product as a shapefile
# PCI creates shapefile with projection 'UTM 18 S E008 ', compared to 'UTM 18 T D122'
# These projections are the same projection, as E008 is the ellipsoid used by NAD 1983.
# but opted for arcpy export
fili = out_file
filo = out_file3
dbiw = []
dbic = []
dbib = []
dbvs = [3]
dblut = []
dbpct = []
ftype = "shp"
foptions = ""
#fexport( fili, filo, dbiw, dbic, dbib, dbvs, dblut, dbpct, ftype, foptions )
arcpy.RasterToPolygon_conversion(out_file2, out_file3, "NO_SIMPLIFY", "")
logging.info(' Successfully completed MergeProcess.merge_filter_export: arcpy.RasterToPolygon_conversion')
except PCIException, e:
EGS_utility.EGSUtility().error('merge_filter_export(): {:s}'.format(e))
pciop = "ADD"
pcival = [6] # add 6 8-bit channels -->must match raw imagery
pcimod(file, pciop, pcival)
except PCIException as e:
print (e)
except Exception as e:
print (e)
print(" ...raster channels added ")
# report_dir has already been defined at the start
# rep_file = report_dir + "/" + "report.txt"
try:
Report.clear()
enableDefaultReport(rep_file)
pca(file= clip_scene + "/" + "scene_clipped.pix",
dbic=[1,2,3,4,5,6], #import channels
eign=[1,2,3,4,5,6], #eigen channels
dboc=[7,8,9,10,11,12], #where to place them (on newly created channel)
rtype="long")
except PCIException as e:
print (e)
except Exception as e:
print (e)
finally:
enableDefaultReport('Term')
#set location of infile and outfile for fexport
try:
Report.clear() # Clear report file
enableDefaultReport(pca_rep) # Change output folder location
pcimod(file=pca_out,
pciop="ADD",
pcival=[0, 0, 3]) # Add 3 16 bit unsigned channels
pca(file=pca_out,
dbic=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], # Use first ten bands
eign=[1, 2, 3], # Output first three eigenchannels
dboc=[11, 12, 13], # Output to 3 new channels
rtype="LONG") # Output extended report format
except PCIException, e:
print e
finally:
enableDefaultReport('term') # Close the report file
completion_time = time.time() - start_time # Calculate time to complete
print "PCA for %s completed in %i seconds." % (identifier, completion_time)
# ------------------------------------------------------------------------------------------------------------------- #
# Define enhance_pca() function
# 1. Generate a linear stretch LUT for the PCA result.
# 2. Apply LUT enhancement to PCA and output to new file.
# Parameters:
# pcain - The input PIX format file that make_pca() was run on.
# pcaout - The output file for the enhanced PCA composite.
# ------------------------------------------------------------------------------------------------------------------- #
def enhance_pca(pcain, pcaout, identifier):
print "Generating look-up tables for file %s" % identifier
stretch(file=pcain,