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Add las_manipulation.py

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etta-drone
Dan Howe 6 years ago
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las_manipulation.py
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# 2017088 Central Coast job
# this is aimed at recieving a large lidar file and
#first cropping the lidar to a chosen shp (ie to a single beach)
#second try to reclassify vegetation and buildings where possible
#cropping the las file to remove the wave runup zone (and making a shapefile to crop it) --> This is a deliverable
#make a raster at a given step value and crop by the above shapefile --> this is what will be used to extract all the values and do heat maps
#cropping the las file to remove the wave runup zone (and making a shapefile to crop it) --> This is a deliverable
# extract values along a given line --> This is a deliverable
########################### IMPORTS ###########################################
import subprocess
import pandas as pd
import numpy as np
import shapefile
from scipy import interpolate
from shapely.geometry import Point
import os
from tqdm import tqdm
###############################################################################
########################## FIXED INPUTS #######################################
#path to LasTools NOTE THERE CAN BE NO SPACES
path_2_lastools='C:/ProgramData/chocolatey/'
#input_file=r"J:\Project\wrl2017088 Central Coast Council Aerial Survey and Coastal Analysis\04_Working\Python\Parameter Files\Survey 2\las manipulation survey2.xlsx"
# input_file=r"J:\Project\wrl2017088 Central Coast Council Aerial Survey and Coastal Analysis\04_Working\Python\Parameter Files\Survey 2\las manipulation patonga2.xlsx"
input_file='Parameter Files/las manipulation survey2.xlsx'
##################### UNCOMMENT THIS SECTION IF YOU WANT TO DO INDIVIDUAL BEACHES#########
##STEP ONE
#input_las1="C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Wamberal2013\\wamberal2013.las" #CANNOT HAVE SPACES
#initial_crop_poly="C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\CC_Crop\\copacabana.shp"
#temp_las1 = "C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Temp\\tmp1.las"
#
##STEP TWO
#input_las2 = temp_las1
#temp_las2= "C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Temp\\tmp2.las"
#step_veg=5 #step size to remove vege. Probably don't change
#temp_las3="C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Temp\\tmp3.las"
#step_build=35 #step size to remove buildings. May need to change. bigger buildings mean bigger step etc
#
##STEP THREE
#input_las3=temp_las3
#temp_xyz= "C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Temp\\tmp_thinned.xyz"
#zone_MGA=56 #assumes it is in MGA
#check_value=1 #m AHD value above which you believe, shouldn't delete
#direct = 'west_east' #at the moment can only be north_south or west_east, wont work if it is south_north
#check_distance=1000 #maximum distance you can crop away from the desnified polygon (should probably be somewhere between 10 - 50m)
#polygon_name="copacabana_crop"
#path_2_poly="C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Results\\"
#tmp_dir="C:\\Users\\z3331378\\Desktop\\LAStools\\XXFiles\\Temp"
###############################################################################
############################### SUB ROUTINES ##################################
def check_output(command,console):
if console == True:
process = subprocess.Popen(command)
else:
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, universal_newlines=True)
output,error = process.communicate()
returncode = process.poll()
return returncode,output
def crop_las(las, shp, output, lastools_loc):
# output is the full path and filename (inc extension) to put in
path_2_lasclip=lastools_loc+"\\bin\\lasclip"
command="%s -i %s -poly %s -o %s" % (path_2_lasclip, las, shp, output)
returncode,output = check_output(command, False)
if returncode!= 0:
print("Error. lasclip failed on %s" % shp.split('//')[-1].split('.')[0])
else:
return None
def colour_las(las, tif, out_las, lastools_loc):
# output is the full path and filename (inc extension) to put in
path_2_lascolor=lastools_loc+"\\bin\\lascolor"
command="%s -i %s -image %s -o %s" % (path_2_lascolor, las, tif, out_las)
returncode,output = check_output(command, False)
if returncode!= 0:
print("Error. lascolor failed on")
else:
return None
def remove_veg(las, output, lastools_loc, step=5):
# output is the full path and filename (inc extension) to put in
#step is how the features are removes - the step size should be able to distinguish between the features you are removing
#I THINK that the way lasground works is to create a tin at the step size specified and find points that don't make sense
# by comparing to the tin
#to remove veg, a step size of 3 - 5 is typically used
path_2_lasground=lastools_loc+"\\bin\\lasground_new"
command="%s -i %s -o %s -step 5" % (path_2_lasground, las, output)
returncode,output = check_output(command, False)
if returncode!= 0:
print("Error. lasground failed on %s" % las.split('\\')[-1].split('.')[0])
else:
return None
def remove_buildings(las, output, lastools_loc, step=50):
# output is the full path and filename (inc extension) to put in
#step is how the features are removes - the step size should be able to distinguish between the features you are removing
#I THINK that the way lasground works is to create a tin at the step size specified and find points that don't make sense
# by comparing to the tin
#to remove buildings, a step size of 10 -50 is typically used
#too high a step size will miss small buildings (eg garages, SLSC huts etc), too small will miss large buildings (ie stadiums and warehouses)
# use a step size of ~25m for houses etc.
path_2_lasground=lastools_loc+"\\bin\\lasground_new"
command="%s -i %s -o %s -step %s" % (path_2_lasground, las, output, step)
returncode,output = check_output(command, False)
if returncode!= 0:
print("Error. lasground failed on %s" % las.split('\\')[-1].split('.')[0])
else:
return None
def make_raster(las, output, lastools_loc, keep_only_ground=False):
#not that keep ground only option only rasters points classified as "2" in the lidar (ie ground)
#this effectively creates a "bare earth dem"
#note that this should only be used after remove_veg and/or remove_buildings has been run
path_2_blastdem=lastools_loc+"\\bin\\blast2dem"
if keep_only_ground==False:
command="%s -i %s -o %s -step 0.2" % (path_2_blastdem, las, output)
else:
command="%s -i %s -o %s -step 0.2 -keep_class 2" % (path_2_blastdem, las, output)
returncode,output2 = check_output(command, False)
if returncode!= 0:
print("Error. blast2dem failed on %s" % las.split('\\')[-1].split('.')[0])
else:
return None
def make_xyz(las, output, lastools_loc, step=1):
#to thin the las and create regular grid to allow the computation of the wave runup polygon
#output must have location and .xyz file extension
path_2_blastdem=lastools_loc+"\\bin\\blast2dem"
command="%s -i %s -o %s -step %s" % (path_2_blastdem, las, output, step)
returncode,output2 = check_output(command, False)
if returncode!= 0:
print("Error. blast2dem failed on %s" % las.split('\\')[-1].split('.')[0])
else:
return None
def remove_problems(x_list, y_list, z_list, x_now, y_now, check_value):
z_ave=nine_pt_moving_average(z_list)
deriv_ave, chainage=forward_derivative(x_list, y_list, z_ave)
deriv_real, chainage=two_point_derivative(x_list, y_list, z_list)
#first find the reference contour on the beach
#index_contour, x_now, y_now, distance=find_beach_reference_contour_choose_closest(chainage, z_ave, x_list, y_list, x_now, y_now,deriv_ave, check_value)
index_contour, x_now, y_now, distance=find_beach_reference_contour(chainage, z_ave, x_list, y_list, x_now, y_now,deriv_ave,deriv_real,check_value)
if index_contour<len(chainage): #other wise keep everthing
#find the beach slope, get the interpolated line (beach line) and the index of the reference contour +1
beach_slope, beach_line, index_high=find_beach_slope(chainage, z_ave,index_contour, check_value)
#find the natural deviation of the lower beach
nat_dev=get_natural_deviation(chainage, z_list, index_contour, index_high, beach_line)
for i in range(index_contour, len(z_list)):
if abs(z_list[i]-float(beach_line(chainage[i])))>nat_dev:
break
else:
i=index_contour
z_return=z_list[0:i]
chainage_return=chainage[0:i]
return z_return, chainage_return, x_now, y_now, distance
def two_point_derivative(x_list, y_list, z_list):
chain=[((x_list[0]-x_list[i])**2+(y_list[0]-y_list[i])**2)**0.5 for i in range(0,len(x_list))]
deriv=[(z_list[i+1]-z_list[i-1])/(chain[i+1]-chain[i-1]) for i in range(1, len(z_list)-1)]
deriv.insert(0,0)
deriv.append(0)
return deriv, chain
def forward_derivative(x_list, y_list, z_list):
chain=[((x_list[0]-x_list[i])**2+(y_list[0]-y_list[i])**2)**0.5 for i in range(0,len(x_list))]
deriv=[(z_list[i]-z_list[i-1])/(chain[i]-chain[i-1]) for i in range(0, len(z_list)-1)]
deriv.insert(0,0)
return deriv, chain
def find_first_over_reference(z_list, value):
i=len(z_list)-1
while i>0 and z_list[i]<value:
i=i-1
return i
def nine_pt_moving_average(z_list):
i=0
move_ave=[]
while i<len(z_list):
if i<5:
ave=np.mean([z_list[j] for j in range(0,i+5)])
elif i>len(z_list)-5:
ave=np.mean([z_list[j] for j in range(i-4,len(z_list))])
else:
ave=np.mean([z_list[j] for j in range(i-4,i+5)])
move_ave.append(ave)
i=i+1
return move_ave
def find_neg_derivative(z_list, deriv_list):
i=len(z_list)-5
while z_list[i]>=0 and z_list[i+1]>=0 and z_list[i+2]>=0 and z_list[i+3]>=0 and z_list[i+4]>=0:
i=i-1
return i
def find_beach_reference_contour_choose_closest(chain_list, z_ave_list, x_list, y_list, x_last, y_last, deriv_ave_list, check_value):
#note that z_list should be the 9 point moving average
#assumes that beaches are shallow (|derivative|<0.3), sloping and between 0 - 4 m AHD
i=0
choice_list=[]
distance_list=[]
if z_ave_list[i]>check_value:
state_now='over'
else:
state_now='under'
while i<len(z_ave_list):
if state_now=='under' and z_ave_list[i]>check_value: #only keep if it is downward sloping
state_now='over'
elif state_now=='over' and z_ave_list[i]<check_value:
choice_list.append(i)
state_now='under'
if x_last!=None:
distance_list.append(((x_last - x_list[i])**2+(y_last - y_list[i])**2)**0.5)
i=i+1
if len(choice_list)>0 and x_last==None: #choose the first time for the first point
i=choice_list[0]
distance=0
elif len(choice_list)>0 and x_last!=None:
assert(len(choice_list)==len(distance_list))
i=choice_list[distance_list.index(min(distance_list))]
distance=min(distance_list)
if i>=len(x_list):
i=len(x_list)-1
if x_last!=None:
distance=((x_last - x_list[i])**2+(y_last - y_list[i])**2)**0.5
else:
distance=0
x=x_list[i]
y=y_list[i]
return i, x, y, distance
def find_beach_reference_contour(chain_list, z_ave_list, x_list, y_list, x_last, y_last, deriv_ave_list,deriv_real_list, check_value):
#note that z_list should be the 9 point moving average
#assumes that beaches are shallow (|derivative|<0.3), sloping and between 0 - 4 m AHD
i=len(z_ave_list)-1
while i>=0 and (z_ave_list[i]>check_value+2 or z_ave_list[i]<check_value-2 or deriv_ave_list[i]>0 or max([abs(i) for i in deriv_real_list[max(0,i-7):i]]+[0])>0.3):#beaches are shallow sloping, low
i=i-1
#find the first time it gets to check_value after this
while i>=0 and z_ave_list[i]<check_value:
i=i-1
if i==0:
i=len(z_ave_list)-1 # the whole this is above the beach
if x_last!=None:
distance=((x_last - x_list[i])**2+(y_last - y_list[i])**2)**0.5
else:
distance=0
x=x_list[i]
y=y_list[i]
return i, x, y, distance
def find_beach_slope(chain_list, z_ave_list, ref_index, check_value):
#ref index is the index of the check value
#find the beach slope between this point and 1 m above this point
i=ref_index
while i>0 and z_ave_list[i]<check_value+1:
i=i-1
slope=(z_ave_list[i]-z_ave_list[ref_index])/(chain_list[i]-chain_list[ref_index])
beach_ave=interpolate.interp1d([min(chain_list),max(chain_list)], [(min(chain_list)-chain_list[ref_index])*slope+z_ave_list[ref_index], (z_ave_list[ref_index]-(chain_list[ref_index]-max(chain_list))*slope)])
return slope, beach_ave, i
def get_natural_deviation(chain_list, z_list, ref_index, ref_high, beach_ave):
#for the points considered to be on the beach (reference contour to reference contour +1), find the average natural deviation
deviation=[]
for i in range(ref_high, ref_index+1):
dev_tmp=abs(z_list[i] - float(beach_ave(chain_list[i])))
deviation.append(dev_tmp)
natural_deviation=min(np.max(deviation),0.4) #THIS MAY BE TOO CONSERVATIVE
return natural_deviation
def distance_point_to_poly(x_list, y_list, x_now, y_now):
#make a line from the mid of x_list, y_list
end=Point(x_list[-1], y_list[-1])
point=Point(x_now, y_now)
dist=point.distance(end)
return dist
def polygon_wave_runup(xyz_1m, direction, path_2_crop_polygon, crop_poly_name, set_check_value, distance_check, zone):
#print('starting processing of wave runup')
all_data=pd.read_csv(xyz_1m, header=None, names=['X','Y','Z'])
if direction=='north_south':
all_data_sorted=all_data.sort_values(by=['X', 'Y'], ascending=[1,0])
elif direction=='west_east':
all_data_sorted=all_data.sort_values(by=['Y', 'X'], ascending=[0,1])
fixed_now=0
a=0
X_tmp=[]
processed_data = pd.DataFrame(columns=['X','Y','Z'])
list_to_print=[10,20,30,40,50,60,70,80,90]
crop_line=[]
top_line=[]
tmp_x_last=None
tmp_y_last=None
exceed_list=[]
# Create progress bar
pbar = tqdm(all_data_sorted.iterrows(), total=all_data_sorted.shape[0])
for index, line in pbar:
a=a+1
percent_done=round(a/len(all_data_sorted)*100,1)
if percent_done in list_to_print:
#print("Finished %s%% of the processing" % percent_done)
list_to_print=list_to_print[1:len(list_to_print)]
if direction=='north_south':
check_this=line['X']
elif direction=='west_east':
check_this=line['Y']
if check_this==fixed_now:
X_tmp.append(line['X'])
Y_tmp.append(line['Y'])
Z_tmp.append(line['Z'])
else:
if len(X_tmp)!=0:
#try: ########may need to change!~!
if len(X_tmp)>10:
Z_set, chainage_tmp, temp_x, temp_y, distance=remove_problems(X_tmp, Y_tmp, Z_tmp,tmp_x_last, tmp_y_last, set_check_value)
#except:
else:
Z_set=Z_tmp
temp_x=X_tmp[len(Z_set)-1]
temp_y=Y_tmp[len(Z_set)-1]
distance=0
distance_2_old=distance_point_to_poly(X_tmp, Y_tmp, temp_x, temp_y)
if distance_2_old<distance_check: # find a way to change so it is checking the distance from the first crop polyogn, concave_now.buffer(buffer)
tmp_x_last=temp_x
tmp_y_last=temp_y
crop_line.append([X_tmp[len(Z_set)-1], Y_tmp[len(Z_set)-1]])
top_line.append([X_tmp[0], Y_tmp[0]])
#otherwise crop by the distance_check
else:
exceed_list.append(1)
try:
tmp_x_last=X_tmp[len(X_tmp)-distance_check] #beacuse this is a 1m DSM, this works
tmp_y_last=Y_tmp[len(Y_tmp)-distance_check]
crop_line.append([tmp_x_last, tmp_y_last])
top_line.append([X_tmp[0], Y_tmp[0]])
except:
print('problem with the last crop point, keeping whole line')
crop_line.append([X_tmp[-1], Y_tmp[-1]])
top_line.append([X_tmp[0], Y_tmp[0]])
if direction=='north_south':
fixed_now=line['X']
elif direction=='west_east':
fixed_now=line['Y']
X_tmp=[line['X']]
Y_tmp=[line['Y']]
Z_tmp=[line['Z']]
else:
if direction=='north_south':
fixed_now=line['X']
elif direction=='west_east':
fixed_now=line['Y']
X_tmp=[line['X']]
Y_tmp=[line['Y']]
Z_tmp=[line['Z']]
#for the last line
derivative, chainage=forward_derivative(X_tmp, Y_tmp, Z_tmp)
if len(X_tmp)>10:
Z_set, chainage_tmp, temp_x, temp_y, distance=remove_problems(X_tmp, Y_tmp, Z_tmp,tmp_x_last, tmp_y_last, set_check_value)
#except:
else:
Z_set=Z_tmp
temp_x=X_tmp[len(Z_set)-1]
temp_y=Y_tmp[len(Z_set)-1]
distance=0
X_set=X_tmp[0:len(Z_set)]
Y_set=Y_tmp[0:len(Z_set)]
#write to new data frame
#if len(Z_set)>0:
# for i in range(0, len(Z_set)):
# processed_data =processed_data.append({'X':X_set[i],'Y':Y_set[i],'Z':Z_set[i],'r':r_set[i],'g':g_set[i],'b':b_set[i]}, ignore_index=True)
#add to crop line
distance_2_old=distance_point_to_poly(X_tmp, Y_tmp, temp_x, temp_y)
if distance_2_old<distance_check: # find a way to change so it is checking the distance from the first crop polyogn, concave_now.buffer(buffer)
tmp_x_last=temp_x
tmp_y_last=temp_y
crop_line.append([X_tmp[len(Z_set)-1], Y_tmp[len(Z_set)-1]])
top_line.append([X_tmp[0], Y_tmp[0]])
#otherwise crop by the distance_check
else:
exceed_list.append(1)
tmp_x_last=X_tmp[len(X_tmp)-distance_check]
tmp_y_last=Y_tmp[len(Y_tmp)-distance_check]
crop_line.append(tmp_x_last, tmp_y_last)
top_line.append([X_tmp[0], Y_tmp[0]])
#otherwise dont add. straight line is better
if direction=='north_south':
y_filtered=nine_pt_moving_average([i[1] for i in crop_line])
crop_new=[[crop_line[i][0],y_filtered[i]] for i in range(0, len(crop_line))]
elif direction=='west_east':
x_filtered=nine_pt_moving_average([i[0] for i in crop_line])
crop_new=[[x_filtered[i],crop_line[i][1]] for i in range(0, len(crop_line))]
for_shape=crop_new+top_line[::-1]
for_shape.append(crop_new[0])
#print('exceeded the manual distance_check %s%% of the time. manually cropping undertaken' % (round(len(exceed_list)/a,2)*100))
#making the cropping shapefile
#print('making the crop polygon')
w = shapefile.Writer(shapefile.POLYGON)
w.poly(parts=[for_shape])
fname = crop_poly_name
zone=56
w.field('FIRST_FLD','C','40')
w.field('SECOND_FLD','C','40')
w.record('Poly','PolyTest')
w.save('%s%s' % (path_2_crop_polygon,fname))
prjfname='%s%s.prj'%(path_2_crop_polygon,fname)
prj=open(prjfname, 'w')
if zone==56:
prj.write('PROJCS["GDA_1994_MGA_Zone_56",GEOGCS["GCS_GDA_1994",DATUM["D_GDA_1994",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",153.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]')
elif zone==55:
prj.write('PROJCS["GDA_1994_MGA_Zone_55",GEOGCS["GCS_GDA_1994",DATUM["D_GDA_1994",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",147.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]')
elif zone==57:
prj.write('PROJCS["GDA_1994_MGA_Zone_57",GEOGCS["GCS_GDA_1994",DATUM["D_GDA_1994",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",159.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]')
prj.close()
return None
def remove_temp_files(directory):
for f in os.listdir(directory):
os.unlink(os.path.join(directory, f))
return None
###############################################################################
############################### CODE #########################################
# read the parameters file and scroll through it
params_file=pd.read_excel(input_file, sheet_name="PARAMS")
for i in range(0, len(params_file)): #0, len(params_file)
print("Starting to process %s" % params_file['Beach'][i])
input_las1=params_file['INPUT LAS1'][i]
initial_crop_poly=params_file['INITIAL CROP POLY'][i]
temp_las1=params_file['TEMP LAS1'][i]
temp_las2 = params_file['TEMP LAS2'][i]
step_veg = params_file['STEP VEG'][i]
temp_las3 = params_file['TEMP LAS3'][i]
step_build= params_file['STEP BUILD'][i]
temp_xyz=params_file['TEMP XYZ'][i]
zone_MGA=params_file['ZONE MGA'][i]
check_value=params_file['CHECK VALUE'][i]
direct=params_file['DIRECTION'][i]
check_distance=params_file['CHECK DISTANCE'][i]
polygon_name=params_file['POLYGON NAME'][i]
path_2_poly = params_file['PATH TO POLYGON'][i]
temp_las4= params_file['TEMP LAS4'][i]
picture= params_file['PICTURE'][i]
tmp_dir=params_file['TMP FOLDER'][i]
#STEP ONE CROP TO BEACH
crop_las(input_las1,initial_crop_poly, temp_las1, path_2_lastools)
#STEP TWO REMOVE VEG
remove_veg(temp_las1, temp_las2, path_2_lastools, step=step_veg)
remove_buildings(temp_las2, temp_las3, path_2_lastools, step=step_build)
#STEP THREE MAKE WAVE RUNUP REMOVAL POLYGON
make_xyz(temp_las3, temp_xyz, path_2_lastools)
polygon_wave_runup(temp_xyz, direct, path_2_poly, polygon_name, check_value, check_distance, zone_MGA)
#NOTE THAT YOU NEED TO CHECK THE OUTPUT SHP FILE AND ADJUST AS REQUIRED
#STEP FOUR COLOURISE THE LAS
#colour_las(temp_las3, picture, temp_las4, path_2_lastools)
#delete the temp files
remove_temp_files(tmp_dir)
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