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"""
make_chips.py
This script reads in HLS S30/L30 data and extracts
band information around a chip_size x chip_size subset
of the original raster grid. Snowy and cloudy chips beyond a
threshold are discarded.
Author: Besart Mujeci, Srija Chakraborty, Christopher Phillips
Usage:
python make_chips.py
"""
import rclone
from pathlib import Path
import shutil
import pandas as pd
from collections import Counter
import cartopy.crs as ccrs
import numpy as np
import rasterio
from rasterio.transform import from_gcps
from rasterio.warp import transform
from rasterio.windows import Window
import os
# --- --- ---
def point_to_index(dataset, long, lat):
"""
Converts long/lat point to row, col position on rasterio grid.
Args:
dataset (Rasterio Object): rasterio object
long (float): longitude float
lat (float): latitude float
Returns:
tuple: tuple representing point mapping on grid
"""
from_crs = rasterio.crs.CRS.from_epsg(4326)
to_crs = dataset.crs
new_x,new_y = transform(from_crs,to_crs, [long], [lat])
new_x = new_x[0]
new_y = new_y[0]
# get row and col
row, col = dataset.index(new_x,new_y)
return(row, col)
# --- --- ---
# --- --- --- Citation for this function: Christopher Phillips
def check_qc_bit(data, bit):
"""
Function to check QC flags
Args:
data (numpy array): rasterio numpy grid
bit (int): 1 or 4 representing cloud or snow
Returns:
numpy array: numpy array with flagged indices marking cloud/snow
"""
qc = np.array(data//(10**bit), dtype='int')
qc = qc-((qc//2)*2)
return np.sum(qc)/qc.size
# --- --- ---
# --- --- --- rclone configuration, file collection
cfg = ""
result = rclone.with_config(cfg).run_cmd("ls", extra_args=[f"{idir}/"])
output_lines = result['out'].decode('utf-8').splitlines()
file_list = [line.split(maxsplit=1)[1] for line in output_lines if line]
# --- --- ---
# --- --- --- Options
hls_type = 'L30' # Switch between 'L30' and 'S30' manually.
idir = "" # Raw Images Dir
odir = "" # Output Chips Dir
chip_size = 50 # Chip dimensions
scale = 0.0001 # Scale value for HLS bandssqm
cthresh = 0.05 # Cloud threshold
sthresh = 0.02 # Snow/ice threshold
# --- --- ---
# --- --- --- Read station site data
df = pd.read_csv("./TILED_filtered_flux_sites_2018_2021.csv")
stations = df['SITE_ID'].tolist()
tiles = [tile.split(";")[0] for tile in df['tiles'].tolist()]
sYear = df['start_year'].tolist()
eYear = df['end_year'].tolist()
longs = df['LOCATION_LONG'].tolist()
lats = df['LOCATION_LAT'].tolist()
all_years = [str(sYear[i]) + "-" + str(eYear[i]) for i in range(len(df))]
coords = [str(lat) + ";" + str(long) for lat, long in zip(lats, longs)]
# --- --- ---
for i, line in enumerate(tiles):
station_data = [stations[i], coords[i].split(";")[0], coords[i].split(";")[1], all_years[i].split("-")[0], all_years[i].split("-")[1], "filler", tiles[i]]
tile = station_data[-1].strip()
print(f"Working on {tile}")
# Determine years for this station
years = range(int(station_data[3]), int(station_data[4])+1)
for year in years:
print(year)
# Build path to this tile and locate all tifs
tifs1 = sorted([filepath for filepath in file_list if tile in filepath and "B01" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs2 = sorted([filepath for filepath in file_list if tile in filepath and "B02" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs3 = sorted([filepath for filepath in file_list if tile in filepath and "B03" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs4 = sorted([filepath for filepath in file_list if tile in filepath and "B04" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs5 = sorted([filepath for filepath in file_list if tile in filepath and "B05" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs6 = sorted([filepath for filepath in file_list if tile in filepath and "B06" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs7 = sorted([filepath for filepath in file_list if tile in filepath and "B07" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs8 = sorted([filepath for filepath in file_list if tile in filepath and "B08" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs8A = sorted([filepath for filepath in file_list if tile in filepath and "B8A" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs9 = sorted([filepath for filepath in file_list if tile in filepath and "B09" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs10 = sorted([filepath for filepath in file_list if tile in filepath and "B10" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs11 = sorted([filepath for filepath in file_list if tile in filepath and "B11" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifs12 = sorted([filepath for filepath in file_list if tile in filepath and "B12" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
tifsF = sorted([filepath for filepath in file_list if tile in filepath and "Fmask" in filepath and hls_type in filepath and str(year) == filepath.split(".")[3][:4]]) # Numbered by band
# Loop over each tif
first = True
chip_flag = False # Flag for detecting chip size errors
for i in range(len(tifs2)):
# Open tifs based on HLS product
skip_file_iteration = False
if (hls_type == 'L30'):
# Ensure the sorted files are aligned correctly.
# If a band is missing then things can go out of order.
# Push 'filler' if layer is missing a band to maintain sorting.
checkListMain = [tifs2, tifs3, tifs4, tifs5, tifs6, tifs7, tifsF]
checkList = [tifs2[i], tifs3[i], tifs4[i], tifs5[i], tifs6[i], tifs7[i], tifsF[i]]
checkList = ['.'.join(ele.split(".")[2:4]) for ele in checkList]
counts = Counter(checkList)
common_value, _ = counts.most_common(1)[0]
for z, value in enumerate(checkList):
if value != common_value:
checkListMain[z].insert(i, "filler") # Push
skip_file_iteration=True
print(f"Misaligned - {checkList}")
break
if skip_file_iteration:
continue
try:
if not os.path.exists(f"./{tile}"):
os.makedirs(f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs2[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs3[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs4[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs5[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs6[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs7[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifsF[i]}", f"./{tile}")
except:
print(f"MISALIGNED FOR - {tifs2[i]} check if all bands exist")
continue
src2 = rasterio.open(tifs2[i])
src3 = rasterio.open(tifs3[i])
src4 = rasterio.open(tifs4[i])
src5 = rasterio.open(tifs5[i])
src6 = rasterio.open(tifs6[i])
src7 = rasterio.open(tifs7[i])
srcF = rasterio.open(tifsF[i])
elif (hls_type == 'S30'):
# Ensure the sorted files are aligned correctly.
# If a band is missing then order is compromised.
# Push 'filler' if layer is missing a band to maintain sorting.
checkListMain = [tifs2, tifs3, tifs4, tifs8A, tifs11, tifs12, tifsF]
checkList = [tifs2[i], tifs3[i], tifs4[i], tifs8A[i], tifs11[i], tifs12[i], tifsF[i]]
checkList = ['.'.join(ele.split(".")[2:4]) for ele in checkList]
counts = Counter(checkList)
common_value, _ = counts.most_common(1)[0]
for z, value in enumerate(checkList):
if value != common_value:
checkListMain[z].insert(i, "filler")
skip_file_iteration=True
break
if skip_file_iteration:
continue
try:
if not os.path.exists(f"./{tile}"):
os.makedirs(f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs2[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs3[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs4[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs8A[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs11[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifs12[i]}", f"./{tile}")
rclone.with_config(cfg).copy(f"{idir}/{tifsF[i]}", f"./{tile}")
except:
print(f"MISALIGNED FOR - {tifs2[i]} check if all bands exist")
continue
src2 = rasterio.open(f"./{tifs2[i]}")
src3 = rasterio.open(f"./{tifs3[i]}")
src4 = rasterio.open(f"./{tifs4[i]}")
src5 = rasterio.open(f"./{tifs8A[i]}")
src6 = rasterio.open(f"./{tifs11[i]}")
src7 = rasterio.open(f"./{tifs12[i]}")
srcF = rasterio.open(f"./{tifsF[i]}")
else:
raise ValueError(f'HLS product type must be \"L30\" or \"S30\" not \"{hls_type}\".')
# Station remains in the same spot/tile so only gather information once.
if first:
row, col = point_to_index(src2, float(station_data[2]), float(station_data[1]))
y_offset = row - (chip_size // 2)
x_offset = col - (chip_size // 2)
window = Window(y_offset, x_offset, chip_size, chip_size)
window_data = src2.read(window=window, boundless=True)
window_transform = src2.window_transform(window)
first = False
# Subset tif
bands = []
for src in (src2,src3,src4,src5,src6,src7): # Set the tuple to match desired bands
# Scale and clip reflectances
band = np.clip(src.read(1)[y_offset:y_offset + chip_size, x_offset:x_offset + chip_size]*scale, 0, 1)
bands.append(band)
bands = np.array(bands)
# Check chip size and break out if wrong shape
if (bands.shape[1] != chip_size) or (bands.shape[2] != chip_size):
print(f'ERROR: Chip for tile {tile} is wronge size!\n Size is {band.shape[1:]} and not ({chip_size},{chip_size}).\nSkipping to next tile.')
chip_flag = True
break
# Subset Fmask to get imperfections
cbands = np.array(srcF.read(1)[y_offset:y_offset + 50, x_offset:x_offset + 50], dtype='int')
cloud_frac = check_qc_bit(cbands, 1)
snow_frac = check_qc_bit(cbands, 4)
# Check cloud fraction
if (cloud_frac > cthresh):
print("CLOUDY")
continue
# Check snow/ice fraction
if (snow_frac > sthresh):
print("SNOWY")
continue
# Save chip with new metadata
out_meta = src2.meta
out_meta.update({'driver':'GTiff', 'height':bands.shape[1],
'width':bands.shape[2], 'count':bands.shape[0], 'dtype':bands.dtype,
'transform':window_transform})
save_name = f'./chips/{tifs2[i].replace("B02", f"{station_data[0]}_merged.{chip_size}x{chip_size}pixels")}'
if not os.path.exists(save_name):
os.makedirs(f"./chips/{tile}")
with rasterio.open(save_name, 'w', **out_meta) as dest:
dest.write(bands)
rclone.with_config(cfg).copy(f"./chips/{tile}", f"{odir}/{tile}/")
shutil.rmtree(Path(f"./chips/"))
# If chip is the wrong size break to next station
if chip_flag:
print("Breaking to tile -- wrong size ")
break
shutil.rmtree(Path(f"./{tile}"))
break
print('Done chipping.') |