uniq, indices, inverse, count = np.unique(ar=lonlat,
axis=0,
return_index=True,
return_counts=True,
return_inverse=True)
print(uniq.shape)
loc = np.where(uniq[:, 1] < lat_x)
print(uniq[loc])
print(uniq[loc].shape)
coords = uniq[loc].tolist()
geoms = [
Vector.get_osgeo_geom('POINT ({} {})'.format(str(coord[0]),
str(coord[1])))
for coord in coords
]
outlist = []
for geom in geoms:
if geom.Intersects(geom2):
outlist.append(geom)
print(len(outlist))
def get_path(args):
"""
Method to extract path from a GEDI file
args:
filename: GEDI filename
bounds_wkt: WKT representation of boundary geometry
res: bin resolution (degrees) (default : 0.1 degrees)
buffer: buffer in degrees
:return: (attribute dictionary, geometry WKT, None) if no error is raised while opening file
(None, None, error string) if error is raised
"""
pt_limit = 15
verbose = False
filename, temp_dir, boundary_wkt, spatial_resolution = args
if verbose:
Opt.cprint('Working on - {} '.format(Handler(filename).basename))
Handler(filename).copy_file(temp_dir)
temp_filename = temp_dir + Handler(filename).basename
date_str = Handler(temp_filename).basename.split('_')[2]
year = int(date_str[0:4])
julian_day = int(date_str[4:7])
bounds_geom = ogr.CreateGeometryFromWkt(boundary_wkt)
file_keys = []
try:
fs = h5py.File(temp_filename, 'r')
fs.visit(file_keys.append)
except Exception as e:
return Handler(temp_filename).basename, ' '.join(e.args)
beam_ids = list(set(list(key.split('/')[0].strip() for key in file_keys if 'BEAM' in key)))
feat_list = []
err = 'No Keys found'
for beam in beam_ids:
beam_id = int(beam.replace('BEAM', ''), 2)
if verbose:
Opt.cprint('\nBEAM - {}'.format(beam_id), newline=' ')
try:
lat_arr = np.array(fs['{}/geolocation/latitude_bin0'.format(beam)])
lon_arr = np.array(fs['{}/geolocation/longitude_bin0'.format(beam)])
except Exception as e:
err = ' '.join(e.args)
continue
# make an array of lat lon
pt_arr = np.vstack([lon_arr, lat_arr]).T
# remove NaN values
nan_loc_pre = np.where(np.apply_along_axis(lambda x: (not (np.isnan(x[0])) and (not np.isnan(x[1]))),
1, pt_arr))
pt_arr = pt_arr[nan_loc_pre]
groups = group_nearby(pt_arr)
# find start and end of valid strips
chunks = list(pt_arr[elem[0]:(elem[1] + 1), :] for elem in groups)
main_geom = ogr.Geometry(ogr.wkbMultiLineString)
any_geom = False
# find polygons for each strip and add to main_geom
for chunk in chunks:
if chunk.shape[0] <= pt_limit:
if verbose:
Opt.cprint('chunk too short size={},'.format(chunk.shape[0]), newline=' ')
continue
else:
if verbose:
Opt.cprint('chunk size={},'.format(str(chunk.shape[0])), newline=' ')
try:
resampled_chunk = resample_chunk(chunk, spatial_resolution)
except Exception as e:
if verbose:
Opt.cprint('invalid chunk({})'.format(e.args[0]), newline=' ')
continue
part_geom_json = json.dumps({'type': 'Linestring', 'coordinates': resampled_chunk.tolist()})
part_geom = Vector.get_osgeo_geom(part_geom_json, 'json')
if part_geom.Intersects(bounds_geom):
any_geom = True
part_geom_intersection = part_geom.Intersection(bounds_geom)
# add to main geometry
main_geom.AddGeometryDirectly(part_geom_intersection)
attributes = {'BEAM': beam_id,
'FILE': Handler(temp_filename).basename,
'YEAR': year,
'JDAY': julian_day}
if any_geom:
# Opt.cprint(attributes)
wkt = main_geom.ExportToWkt()
main_geom = None
else:
wkt = None
feat_list.append((wkt, attributes))
fs.close()
Handler(temp_filename).file_delete()
if len(feat_list) == 0:
return Handler(filename).basename, err
else:
return feat_list, None
[-113.466796875, 68.13885164925574],
[-125.947265625, 70.4073476760681],
[-140.09765625, 70.31873847853124],
[-156.708984375, 71.63599288330609],
[-167.431640625, 69.3493386397765],
[-165.146484375, 66.72254132270653],
[-168.662109375, 65.47650756256367],
[-165.673828125, 63.31268278043484],
[-168.837890625, 60.326947742998414],
[-166.552734375, 56.218923189166624]]
# boundary = ee.Geometry.Polygon(bound_coords)
# boundary = ee.FeatureCollection('users/masseyr44/shapefiles/NAboreal_10kmbuffer').first().geometry()
boundary_geom = Vector.get_osgeo_geom(Vector.wkt_from_coords(
bound_coords, 'polygon'),
geom_type='wkt')
# values to copy from fusion table/feature collection
feat_properties = ['site', 'year', 'decid_frac']
KEYS = ee.List(feat_properties)
# properties to retrieve from scene
scene_properties = [
'CLOUD_COVER', 'GEOMETRIC_RMSE_MODEL', 'LANDSAT_ID',
'SOLAR_ZENITH_ANGLE'
]
PROPERTY_LIST = ee.List(scene_properties)
# Bands to retrieve
bands = ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'pixel_qa', 'radsat_qa']
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)))
elem = dict()
for header in list(attr):
elem[header] = row[header]
samp_geom = Vector.get_osgeo_geom(
Vector.wkt_from_coords([row['Lon'], row['Lat']]))
latlon.append([row['Lon'], row['Lat']])
if elem['Lat'] < 52.0 and samp_geom.Intersects(bounds_geom):
wkt_list.append(Vector.wkt_from_coords([row['Lon'], row['Lat']]))
attr_list.append(elem)
count += 1
uniq, indices, inverse, count = np.unique(ar=latlon,
axis=0,
return_index=True,
return_counts=True,
return_inverse=True)
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:
for i, years in enumerate(year_bins):