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update_viirs.py
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# https://git.earthdata.nasa.gov/projects/LPDUR
# wavelength: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/viirs/
# viirs ftp: https://e4ftl01.cr.usgs.gov/VIIRS/VNP09GA.001/2021.07.05/
# https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/VNP09GA/
# hHHvVV GRID: https://modis-land.gsfc.nasa.gov/MODLAND_grid.html
# DoY (Day of Year): https://asd.gsfc.nasa.gov/Craig.Markwardt/doy2021.html
from itertools import product
import os
import datetime as dt
from genericpath import isfile
from glob import glob
import numbers
from pathlib import Path
import shutil
import ee
# ee.Initialize()
# from ee import data
# from numpy.char import startswith
import h5py
import numpy as np
from osgeo import gdal, gdal_array
from LaadsDataHandler.laads_client import LaadsClient
def get_geoInfo_and_projection(f):
fileMetadata = f['HDFEOS INFORMATION']['StructMetadata.0'][()].split() # Read file metadata
fileMetadata = [m.decode('utf-8') for m in fileMetadata] # Clean up file metadata
# fileMetadata[0:33] # Print a subset of the entire file metadata record
ulc = [i for i in fileMetadata if 'UpperLeftPointMtrs' in i][0] # Search file metadata for the upper left corner of the file
ulcLon = float(ulc.split('=(')[-1].replace(')', '').split(',')[0]) # Parse metadata string for upper left corner lon value
ulcLat = float(ulc.split('=(')[-1].replace(')', '').split(',')[1]) # Parse metadata string for upper left corner lat value
yRes, xRes = -926.6254330555555, 926.6254330555555 # Define the x and y resolution
# yRes, xRes = -500, 500 # Define the x and y resolution
'''Currently, VIIRS HDF-EOS5 files do not contain information regarding the spatial resolution of the dataset within.'''
# if nRow == 1200: # VIIRS A1 - 1km or 1000m
# yRes = -926.6254330555555
# xRes = 926.6254330555555
# elif nRow == 2400: # VIIRS H1 - 500m
# yRes = -463.31271652777775
# xRes = 463.31271652777775
# elif nRow == 3600 and nCol == 7200: # VIIRS CMG
# yRes = -0.05
# xRes = 0.05
# # Re-set upper left dims for CMG product
# ulcLon = -180.00
# ulcLat = 90.00
geoInfo = (ulcLon, xRes, 0, ulcLat, 0, yRes) # Define geotransform parameters
prj = 'PROJCS["Sphere_Sinusoidal",\
GEOGCS["GCS_Sphere",\
DATUM["Not_specified_based_on_Authalic_Sphere",\
SPHEROID["Sphere",6371000,0]],\
PRIMEM["Greenwich",0],\
UNIT["Degree",0.017453292519943295]],\
PROJECTION["Sinusoidal"],\
PARAMETER["False_Easting",0],\
PARAMETER["False_Northing",0],\
PARAMETER["Central_Meridian",0],\
UNIT["Meter",1],\
AUTHORITY["EPSG","53008"]]'
projInfo = {'SINU':'PROJCS["unnamed",GEOGCS["Unknown datum based upon the custom spheroid", DATUM["Not specified (based on custom spheroid)", SPHEROID["Custom spheroid",6371007.181,0]],PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433]], PROJECTION["Sinusoidal"],PARAMETER["longitude_of_center",0],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["Meter",1]]',
'GEO':'GEOGCS["Unknown datum based upon the Clarke 1866 ellipsoid", DATUM["Not specified (based on Clarke 1866 spheroid)", SPHEROID["Clarke 1866",6378206.4,294.9786982139006]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433]]'}
return geoInfo, prj
def convert_h5_to_cog(inDir, outDir, BANDS=["M3", "M4", "M5", "M7", "M10", "M11", "QF2"], band_scale_flag=False):
# os.chdir(inDir)
# VNP = Path(os.path.split(inDir)[0]) # Change to working directory
# outDir = Path(os.path.split(VNP)[0]) / 'COG' # Set output directory
print("BADNS: ", BANDS)
if not os.path.exists(outDir): os.makedirs(outDir) # Create output directory
fileList = [file for file in os.listdir(inDir) if file.endswith('.h5') and file.startswith('VNP09GA')] # Search for .h5 files in current directory
print("------------------------------------")
for f in fileList: print(f)
print("------------------------------------") # Print files in list
date = [] # Create empty list to store dates of each file
i = 0 # Set up iterator for automation in cell block below
for t in fileList:
print(f"\n----> {t} <----")
yeardoy = t.split('.')[1][1:] # Split name,retrieve ob date
outName = t.rsplit('.', 1)[0] # Keep filename for outname
date1 = dt.datetime.strptime(yeardoy,'%Y%j').strftime('%m/%d/%Y') # Convert date
date.append(date1) # Append to list of dates
f = h5py.File(os.path.normpath(Path(inDir) / t), "r") # Read in VIIRS HDF-EOS5 file
# geoInfo and Projection
geoInfo, prj = get_geoInfo_and_projection(f)
h5_objs = [] # Create empty list
f.visit(h5_objs.append) # Retrieve obj append to list
# Search for SDS with 1km or 500m grid
grids = list(f['HDFEOS']['GRIDS']) # List contents of GRIDS directory # Clean up file metadata
allSDS = [o for grid in grids for o in h5_objs if isinstance(f[o],h5py.Dataset) and grid in o] # Create list of SDS in file
r = f[[a for a in allSDS if 'M5' in a][0]]
scaleFactor = r.attrs['Scale'][0] # Set scale factor to a variable
fillValue = r.attrs['_FillValue'][0] # Set fill value to a variable
print(f"scaleFactor: {scaleFactor}")
band_dict = {}
for band_name in BANDS:
# print(band_name)
band = f[[a for a in allSDS if band_name in a][0]][()]
# Open SDS M5 = Red
if band_scale_flag and ('QF' not in band_name):
band = band * scaleFactor
band_dict[band_name] = band
data = np.dstack(tuple(band_dict.values()))
print(data.shape)
data[data == fillValue * scaleFactor] = 0 # Set fill value equal to nan
# qf = f[[a for a in allSDS if 'QF5' in a][0]][()] # Import QF5 SDS
# qf2 = f[[a for a in allSDS if 'QF2' in a][0]][()] # Import QF2 SDS # Append to list
params = {
'all':{'data':data, 'band': 'all'}
}
for p in params:
try:
data = params[p]['data'] # Define array to be exported
data[data.mask == True] = fillValue # Masked values = fill value
except: AttributeError
# outputName = os.path.normpath('{}{}.tif'.format(outDir, outName)) # Generate output filename
outputName = str(outDir / f"{outName}.tif") # Generate output filename
nRow, nCol = data.shape[0], data.shape[1] # Define row/col from array
dataType = gdal_array.NumericTypeCodeToGDALTypeCode(data.dtype) # Define output data type
driver = gdal.GetDriverByName('GTiff') # Select GDAL GeoTIFF driver
# Diff for exporting RGBs
data = params[p]['data'] # Define the array to export
dataType = gdal_array.NumericTypeCodeToGDALTypeCode(data.dtype) # Define output data type
options = [
# 'PHOTOMETRIC=RGB',
# 'PROFILE=GeoTIFF'
"TILED=YES",
"COMPRESS=LZW",
"INTERLEAVE=BAND"] # Set options to RGB TIFF
outFile = driver.Create(outputName, nCol, nRow, len(BANDS), dataType, options=options) # Specify parameters of GTIFF
for idx, band in enumerate(BANDS):
print(idx, band) # loop through each band (3)
rb = outFile.GetRasterBand(idx+1)
rb.WriteArray(data[..., idx]) # Write to output bands 1-3
# rb.SetNoDataValue(1.1) # Set fill val for each band
# rb.SetDescription(band)
rb = None
outFile.SetGeoTransform(geoInfo) # Set Geotransform
outFile.SetProjection(prj) # Set projection
outFile = None # Close file
print('Processed file: {} of {}'.format(i+1, len(fileList))) # Print the progress
i += 1
def crs_cloud_optimization(url):
input_raster = gdal.Open(url)
raster_name = os.path.split(url)[-1][:-4].replace(".", "_")
input_dir = Path(os.path.split(url)[0])
output_dir = input_dir / "reprojected"
if not os.path.exists(output_dir): os.makedirs(output_dir)
output_url = output_dir / f"{raster_name}.tif"
print(output_url)
gdal.WarpOptions(dstSRS='EPSG:4326')
warp = gdal.Warp(output_url, input_raster, dstNodata=0)
warp.GetRasterBand(1).SetNoDataValue(0)
warp = None
# cloud optimized tif
dst_url = input_dir / "COG" / raster_name
os.system(f"gdal_translate {output_url} {dst_url} -co TILED=YES -co COPY_SRC_OVERVIEWS=YES -co COMPRESS=LZW")
def download_viirs_on(julian_day, year, hh_list=['10', '11'], vv_list =['03']):
for hh in hh_list:
for vv in vv_list:
print(f"\njulian_day: {julian_day}， h{hh}v{vv}")
print("-----------------------------------------------------------")
url_part = f"5000/{PRODUCT}/2021/{julian_day}/{PRODUCT}.A2021{julian_day}.h{hh}v{vv}.001.h5"
command = "c:/wget/wget.exe -e robots=off -m -np -R .html,.tmp -nH --cut-dirs=5 " + \
f"\"https://nrt3.modaps.eosdis.nasa.gov/api/v2/content/archives/allData/\"{url_part} \
--header \"Authorization: Bearer emhhb3l1dGltOmVtaGhiM2wxZEdsdFFHZHRZV2xzTG1OdmJRPT06MTYyNjQ0MTQyMTphMzhkYTcwMzc5NTg1M2NhY2QzYjY2NTU0ZWFkNzFjMGEwMTljMmJj\" \
-P {dataPath}"
print(command)
save_url = f"{dataPath}/{url_part}"
print(save_url)
if not os.path.exists(save_url):
os.system(command)
def viirs_preprocessing_and_upload(dataPath):
# CRS optimization and cloud optimization
if os.path.exists(dataPath / "COG"):
shutil.rmtree(dataPath / 'COG')
if not os.path.exists(dataPath / "COG"):
os.makedirs(dataPath / 'COG')
inDir = dataPath / "5000" / "VNP09_NRT" / "2022"
print(inDir)
julianDay_list = [folder for folder in os.listdir(str(inDir)) if folder != ".DS_Store"]
for date in julianDay_list:
outDir = dataPath / 'COG'
print(f"outDir: {outDir}")
convert_h5_to_cog(inDir=inDir / date, outDir=outDir, BANDS=["M3", "M4", "M5", "M7", "M10", "M11", "QF2"])
# upload to Gcloud
fileList = [file for file in os.listdir(dataPath / "COG") if file[-4:] == ".tif"]
# pprint(fileList)
dstList = []
for file in fileList:
# crs_cloud_optimization(url)
url = dataPath / "COG" / file
print(url)
filename = file[:-4].replace(".", "_")
# if is not available in gee, then upload
if(ee.ImageCollection("users/omegazhangpzh/VIIRS_NRT")
.filter(ee.Filter.eq("system:index", filename)).size().getInfo() == 0):
rprjDir = Path(f"{os.path.split(url)[0]}_rprj")
if not os.path.exists(rprjDir): os.makedirs(rprjDir)
dst_url = rprjDir / f"{filename}.tif"
tmp_url = rprjDir / f"{filename}_tmp.tif"
os.system(f"gdalwarp {url} {tmp_url} -t_srs EPSG:4326 -r bilinear -ts 1200 1200 -dstnodata 0")
os.system(f"gdal_translate {tmp_url} {dst_url} -co TILED=YES -co COPY_SRC_OVERVIEWS=YES -co COMPRESS=LZW")
if isfile(tmp_url): os.remove(tmp_url)
os.system(f"gsutil -m cp -r {dst_url} {gs_dir}/")
os.system(f"earthengine upload image --force --asset_id={VIIRS_NRT_ImgCol}/{filename} {gs_dir}/{filename}.tif")
dstList.append(filename)
else:
print(f"{filename}: [already in GEE!]")
return dstList
from prettyprinter import pprint
if __name__ == "__main__":
# # 1km vs. 500m --> "M5", "M7", "M10" vs. "I1", "I2", "I3"
# # 500m: "M3", "M4", "I1", "I2", "I3", "M11", "QF2"
# # 1km: "M3", "M4", "M5", "M7", "M10", "M11", "QF2"
# # "Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2", "BitMask"
# BANDS = ["M3", "M4", "M5", "M7", "M10", "M11", "QF2"]
hh_list_na = ['08', '09', '10', '11', '12', '13']
vv_list_na = ['02', '03', '04', '05']
hh_list_eu = ['08', '09', '10', '11', '12', '13']
vv_list_eu = ['02', '03', '04', '05']
# workspace = Path(os.getcwd())
eeImgColName = "VIIRS_NRT"
products_id = "VNP09_NRT"
date = '2022-08-31'
year=2022
workspace = Path("data")
dataPath = workspace / 'data' / eeImgColName
download = True
if download:
if os.path.exists(dataPath): shutil.rmtree(f"{str(dataPath)}/")
tmpPath = dataPath / f"5000/{products_id}" / str(year) # VNP09GA_NRT
if not os.path.exists(tmpPath): os.makedirs(tmpPath)
gs_dir = f"gs://ai4wildfire/{eeImgColName}"
VIIRS_NRT_ImgCol = f"users/eo4wildfire/{eeImgColName}"
# Download from Lance
# lance_date = datetime.date.today() - datetime.date(year, 1, 3)
# julian_today = lance_date.days
# if download:
# for julian_day in range(julian_today, julian_today+1):
# # North America
# if not os.path.exists(tmpPath / str(julian_day)):
# os.mkdir(tmpPath / str(julian_day))
# download_viirs_on(julian_day, year, hh_list=hh_list_na, vv_list =vv_list_na)
# # Europe
# download_viirs_on(julian_day, year, hh_list=hh_list_eu, vv_list =vv_list_eu)
date_ndays = (dt.datetime.strptime(date, '%Y-%m-%d') - dt.datetime.strptime(date[:4] + '-01-01', '%Y-%m-%d')).days + 1
julian_today=date_ndays
print(f"julian_today: {julian_today}")
laads_client = LaadsClient()
laads_client.query_filelist_with_date_range_and_area_of_interest(date, products_id=[products_id], collection_id='5000', data_path=f'../data/data/VIIRS_NRT/5000/{products_id}/2022', julian_day=str(date_ndays))
laads_client.download_files_to_local_based_on_filelist(date, products_id=[products_id], collection_id='5000', data_path=f'../data/data/VIIRS_NRT/5000/{products_id}/2022', julian_day=str(date_ndays))
fileList = viirs_preprocessing_and_upload(dataPath)
pprint(fileList)
# fileList = [
# "VNP09GA_NRT_A2021200_h10v03_001",
# "VNP09GA_NRT_A2021200_h11v03_001",
# ]
""" set property """
import time, subprocess
from datetime import datetime, timedelta
fileListCopy = fileList.copy()
imgCol_name = os.path.split(gs_dir)[-1]
while(len(fileListCopy) > 0):
print()
pprint(fileListCopy)
print("-------------------------------------------------------------------")
response = subprocess.getstatusoutput(f"earthengine ls {VIIRS_NRT_ImgCol}")
asset_list = response[1].replace("projects/earthengine-legacy/assets/", "").split("\n")
for filename in fileList:
asset_id = f"{VIIRS_NRT_ImgCol}/{filename}" # VNP09GA_NRT_A2021198_h10v03_001
julian_day = eval(filename.split("_")[2][5:])
standard_date = datetime(year, 1, 1) + timedelta(days=julian_day)
standard_date = standard_date.strftime("%Y-%m-%d")
if asset_id in asset_list:
# set_image_property(asset_id, query_info)
os.system(f'earthengine asset set --time_start {standard_date} {asset_id}')
# os.system(f'earthengine asset set --index {standard_date.replace("-","_")} {asset_id}')
try:
fileListCopy.remove(filename)
print(f"{asset_id} [set time_start!]")
except:
print(f"{asset_id} [failed to remove!]")
else:
print(f"{asset_id} [Not Ready in GEE!]")
if(len(fileListCopy) > 0):
time.sleep(60) # wait?