You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
549 lines
22 KiB
Python
549 lines
22 KiB
Python
# 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)
|