def main(gedi_dir, temp_dir, bounds_file, outfile, nproc, res):
"""
Main function to execute python script
"""
nproc = int(nproc) - 1
attrib = {'BEAM': 'int', 'FILE': 'str', 'YEAR': 'int', 'JDAY': 'int'}
res = float(res)
bounds_vec = Vector(bounds_file)
bounds_wkt = bounds_vec.wktlist[0]
args_list = list((filename, temp_dir, bounds_wkt, res)
for filename in Handler(dirname=gedi_dir).find_all('*.h5'))
n_files = len(args_list)
Opt.cprint('Number of files: {}'.format(str(n_files)))
out_res = {}
Handler(outfile).file_delete()
pool = mp.Pool(processes=nproc)
for file_output, err_str in pool.imap_unordered(get_path, args_list):
if err_str is None and len(file_output) > 0:
add_on = ''
count = 0
for geom_wkt, attrs in file_output:
if geom_wkt is not None:
write_to_txt(geom_wkt, attrs, outfile)
out_res[geom_wkt] = attrs
count += 1
if count > 0:
add_on = ' - FOUND {} BEAMS'.format(str(count))
out_str = str(list(set([attr['FILE'] for _, attr in file_output]))[0]) + ' : READ' + add_on
Opt.cprint(out_str)
else:
if err_str is None:
err_str = 'Unknown File I/O Error'
Opt.cprint('{}: {}'.format(file_output,
err_str))
pool.close()
Opt.cprint(outfile)
from geosoup import Vector
import numpy as np
if __name__ == '__main__':
# file1 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/samples/all_samp_pre_v1.shp"
file1 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/samples/CAN_PSP/PSP_data/CAN_PSP_v1.shp"
file2 = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/STUDY_AREA/ABoVE_Study_Domain_geo.shp"
lat_x = 52.0
vec = Vector(file1)
vec2 = Vector(file2)
geom2 = vec2.features[0].GetGeometryRef()
lonlat = []
for i in range(vec.nfeat):
geom = vec.features[i].GetGeometryRef()
pt = geom.GetPoint()
lonlat.append(pt[0:2])
print(len(lonlat))
uniq, indices, inverse, count = np.unique(ar=lonlat,
axis=0,
start_year = 2000
end_year = 2017
pixel_size = 0.0021 # 250m MODIS resolution
fire_year_col = 'FireYear'
fire_id_col = 'FIREID'
filelist = [
'D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/FIRE/ak_fire/FireAreaHistory.shp'
]
outfolder = 'D:/temp/fire/'
for infile in filelist:
vec = Vector(infile)
sys.stdout.write(
'========================\nInput Vector file: {}\n'.format(infile))
attr = vec.attributes[0]
attr_dict = dict()
for k, v in attr.items():
attr_dict[k] = Vector.string_to_ogr_type(v, 'name')
order = np.argsort(
np.array([
int(attr_dict[fire_year_col]) for attr_dict in vec.attributes
])).tolist()
x_min, x_max, y_min, y_max = vec.layer.GetExtent()
sys.stdout.write('Extent: {}\n'.format(' '.join(
import pandas as pd
import json
from osgeo import ogr
import numpy as np
if __name__ == '__main__':
infilename = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/samples/CAN_PSP/" \
"CAN_PSPs_Hember-20180207T213138Z-001/CAN_PSPs_Hember/NAFP_L4_SL_ByJur_R16d_ForBrendanRogers1.csv"
outfilename = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/samples/CAN_PSP/" \
"CAN_PSPs_Hember-20180207T213138Z-001/CAN_PSPs_Hember/NAFP_L4_SL_ByJur_R16d_ForBrendanRogers1_lat52_ABoVE.shp"
bounds = "D:/Shared/Dropbox/projects/NAU/landsat_deciduous/data/STUDY_AREA/ABoVE_Study_Domain_geo.shp"
bounds_vec = Vector(bounds)
bounds_geom = bounds_vec.features[0].GetGeometryRef()
attr = {'ID_Plot': 'str', 'Lat': 'float', 'Lon': 'float'}
samp_data = Handler(infilename).read_from_csv(return_dicts=True)
wkt_list = list()
attr_list = list()
spref_str = '+proj=longlat +datum=WGS84'
latlon = list()
count = 0
for row in samp_data:
print('Reading elem: {}'.format(str(count + 1)))
ls8_1 = ee.ImageCollection("LANDSAT/LC08/C01/T1_SR")
ls8_2 = ee.ImageCollection("LANDSAT/LC08/C01/T2_SR")
elevation = ee.Image('USGS/GMTED2010')
slope = ee.Terrain.slope(elevation)
aspect = ee.Terrain.aspect(elevation)
topo_image = elevation.addBands(slope).addBands(aspect).select(
[0, 1, 2], ['elevation', 'slope', 'aspect'])
topo_bandlist = ['elevation', 'slope', 'aspect']
bands = bands + topo_bandlist
feat_list = list()
samp_vec = Vector(infile)
log.lprint('{}: {}'.format(os.path.basename(infile), samp_vec))
intersect_count = 0
for i, wkt in enumerate(samp_vec.wktlist):
if boundary_geom.Intersects(Vector.get_osgeo_geom(wkt)):
intersect_count += 1
feat_dict = dict()
in_dict = samp_vec.attributes[i]
for k, v in in_dict.items():
if k in feat_properties:
feat_dict[k] = v
ini_outfile = outdir + "all_samp_pre_v1.shp"
outfile = outdir + "all_samp_postbin_v{}.csv".format(version)
outshpfile = outdir + "all_samp_postbin_v{}.shp".format(version)
trn_outfile = outdir + "all_samp_post_v{}_trn_samp.shp".format(version)
val_outfile = outdir + "all_samp_post_v{}_val_samp.shp".format(version)
boreal_bounds = "D:/shared/Dropbox/projects/NAU/landsat_deciduous/data/STUDY_AREA/boreal/" \
"NABoreal_simple_10km_buffer_geo.shp"
year_bins = [(1984, 1997), (1998, 2002), (2003, 2007), (2008, 2012),
(2013, 2018)]
# script-----------------------------------------------------------------------------------------------
boreal_vec = Vector(boreal_bounds)
boreal_geom = Vector.get_osgeo_geom(boreal_vec.wktlist[0])
year_samp = list(list() for _ in range(len(year_bins)))
year_samp_reduced = list(list() for _ in range(len(year_bins)))
# get data and names
file_data = Handler(infile).read_from_csv(return_dicts=True)
header = list(file_data[0])
print('\nTotal samples: {}'.format(str(len(file_data))))
boreal_samp_count = 0
# bin all samples based on sample years using year_bins
for elem in file_data: