sys.exit()
filename = sys.argv[1]
basename = os.path.splitext(filename)[0]
extension = os.path.splitext(filename)[1]
In = filename
fn = basename+'_dsm.tif'
# read point cloud
x,y,z,c = getpoints(In)
# intiate grid system (coordinates of center point grid cells)
res = 1
xi, yi = np.arange(x.min(), x.max()+res/2, res), np.arange(y.min(), y.max()+res/2, res)
extent = [xi.min(), xi.max(), yi.min(), yi.max()] # only used to set extent to plots
grid = np.zeros((len(yi),len(xi)))*np.NaN
# retreive gridcell border coordinates
bx, by = gridcellborders(xi,yi,res)
# georeferencing info
geotransform = (x.min(), res, 0, y.max(), 0, -res) # used for georeference metadata in geotiff
proj = '' # mandatory setting used to store projection information in metadata geotiff (not assigned as metadata is not stored in lidar txt)
# create DSM
dsm = createDSM(x,y,z,xi,yi,bx,by,res,geotransform, proj)
# write tiff
saveimg(np.flipud(dsm), fn, len(xi), len(yi), geotransform, proj)
# georeferencing info
geotransform = (x.min(), res, 0, y.max(), 0, -res) # used for georeference metadata in geotiff
proj = '' # mandatory setting used to store projection information in metadata geotiff (not assigned as metadata is not stored in lidar txt)
# dtm
if os.path.isfile(fn_dtm) == True:
# load dtm
from generic_tools import openimg
dtm, _,_,_,_,_ = openimg(fn_dtm)
dtm = np.flipud(dtm)
else: # create dtm
from dtm import createDTM
g = c == 2
dtm = createDTM(x[g],y[g],z[g],xi,yi,res,geotransform, proj, method='idw')
saveimg(np.flipud(dtm), fn_dtm , len(xi), len(yi), geotransform, proj)
# dsm
if os.path.isfile(fn_dsm) == True:
# load dsm
from generic_tools import openimg
dsm, _,_,_,_,_ = openimg(fn_dsm)
dsm = np.flipud(dsm)
else:
# create dsm
from dsm import createDSM
dsm = createDSM(x,y,z,xi,yi,bx,by,res,geotransform, proj)
saveimg(np.flipud(dsm), fn_dsm, len(xi), len(yi), geotransform, proj)
# create chm
chm = createCHM(dtm,dsm)
res = 1
xi, yi = np.arange(x.min(), x.max()+res/2, res), np.arange(y.min(), y.max()+res/2, res)
extent = [xi.min(), xi.max(), yi.min(), yi.max()] # only used to set extent to plots
grid = np.zeros((len(yi),len(xi)))*np.NaN
# retreive gridcell border coordinates
bx, by = gridcellborders(xi,yi,res)
# georeferencing info
geotransform = (x.min(), res, 0, y.max(), 0, -res) # used for georeference metadata in geotiff
proj = '' # mandatory setting used to store projection information in metadata geotiff (not assigned as metadata is not stored in lidar txt)
# create dsm
from dsm import createDSM
dsm = createDSM(x,y,z,xi,yi,bx,by,res,geotransform, proj)
saveimg(np.flipud(dsm), basename+"_dsm.tif", len(xi), len(yi), geotransform, proj)
# calculate slope and aspect in radians
slope_rad = np.core.umath.deg2rad(calcSlope(dsm))
asp_rad = np.core.umath.deg2rad(calcAspect(dsm))
slope_rad = np.flipud(slope_rad)
asp_rad = np.flipud(asp_rad)
# calculate solar radiation
SR = calcSR(dsm, slope_rad, asp_rad, xi, yi, 0.2)
# write tiff
saveimg(SR, fn, len(xi), len(yi), geotransform, proj)
plt.figure(figsize=(15,5))
# georeferencing info
geotransform = (x.min(), res, 0, y.max(), 0, -res) # used for georeference metadata in geotiff
proj = '+proj=utm +zone=21 +south +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs ' # mandatory setting used to store projection information in metadata geotiff (not assigned as metadata is not stored in lidar txt)
# create dtm
from dtm import createDTM
g = c == 2
dtm = createDTM(x[g],y[g],z[g],xi,yi,res,geotransform, proj, method='idw')
# Calculate cover
#from cover import Cover
#cover = Cover(x,y,c,grid,bx,by)
# Calculate RH50
from relativeheight import createRH
rh50 = createRH(x,y,z,grid,dtm,bx,by,50)
# Calculate biomass
#agb = calcAGB(cover,rh50)
agb = calcAGB(rh50)
# write tiff
saveimg(np.flipud(agb), fn, len(xi), len(yi), geotransform, proj)
# write intermediate results
fn = basename+'_dtm.tif'
saveimg(np.flipud(dtm), fn, len(xi), len(yi), geotransform, proj)
fn = basename+'_rh50.tif'
saveimg(np.flipud(rh50), fn, len(xi), len(yi), geotransform, proj)
In = filename
fn = basename+'_aspect.tif'
# read point cloud
x,y,z,c = getpoints(In)
g = c==2 # ground points
# intiate grid system (coordinates of center point grid cells)
res = 1
xi, yi = np.arange(x.min(), x.max()+res/2, res), np.arange(y.min(), y.max()+res/2, res)
extent = [xi.min(), xi.max(), yi.min(), yi.max()] # only used to set extent to plots
grid = np.zeros((len(yi),len(xi)))*np.NaN
# retreive gridcell border coordinates
bx, by = gridcellborders(xi,yi,res)
# georeferencing info
geotransform = (x.min(), res, 0, y.max(), 0, -res) # used for georeference metadata in geotiff
proj = '' # mandatory setting used to store projection information in metadata geotiff (not assigned as metadata is not stored in lidar txt)
# create DTM
from dtm import createDTM
dtm = createDTM(x[g],y[g],z[g],xi,yi,res,geotransform, proj, method='idw')
# calculate slope angle
aspect = calcAspect(dtm)
# write tiff
saveimg(np.flipud(aspect), fn, len(xi), len(yi), geotransform, proj)
tree_x = Xi[coo[0], coo[1]]
tree_y = Yi[coo[0], coo[1]]
tree_z = chm[coo[0], coo[1]]
else: # more peaks in one crown, determine highest peak=tree top
tree_z = chm[coo[:, 0], coo[:, 1]]
highest_peak = np.argwhere(tree_z == tree_z.max())
tree_x = Xi[coo[highest_peak, 0], coo[highest_peak, 1]]
tree_y = Yi[coo[highest_peak, 0], coo[highest_peak, 1]]
tree_z = chm[coo[highest_peak, 0], coo[highest_peak, 1]]
tree_record = "%.2f, %.2f, %.2f\n" % (tree_x, tree_y, tree_z)
f.write(tree_record)
f.close()
print "Tree coordinates and heights stored in", fn_heights
# write tiff
saveimg(np.flipud(crowns), fn_tree, len(xi), len(yi), geotransform, proj)
saveimg(np.flipud(crowns == -999), fn_gaps, len(xi), len(yi), geotransform, proj)
# polygonize tree crowns
polygonize(fn_tree, fn_shape)
# plot
import pylab as plt
fig = plt.figure(figsize=(15, 5))
ax = fig.add_subplot(131)
plt.imshow(chm, extent=[Xi.min(), Xi.max(), Yi.min(), Yi.max()])
plt.scatter(peak_x, peak_y, c="k", marker="+", s=100)
plt.xlim([Xi.min(), Xi.max()])
plt.ylim([Yi.min(), Yi.max()])
title = "local peaks (n=%d)" % (peak)
plt.title(title)
