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update_viirs_nrt.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
import datetime
# 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 PRODUCT_ID, 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):
fmt = '.hdf' # .h5
# 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(fmt) and file.startswith(PRODUCTS_ID)] # 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)
''' for hdf5 only ?! ''' # 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_nrt_data_on(julian_day, YEAR):
print(f"\njulian_day: {julian_day}")
print("-----------------------------------------------------------")
url_part = f"{COLLECTION}/{PRODUCTS_ID}/{YEAR}/{julian_day}"
command = "c:/wget/wget.exe -e robots=off -m -np -R .html,.tmp -nH --cut-dirs=4 " + \
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 / COLLECTION / PRODUCTS_ID / "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"]
PRODUCTS_STORE = {
# NRT
'MOD02HKM': {
"collection": "61",
"eeImgColName": 'MODIS_NRT',
"instance": "MOD02HKM.A2022243.0000.061.2022243005534.NRT.hdf"
},
'VNP09_NRT': {
"collection": '5000',
"eeImgColName": "VIIRS_NRT",
}
}
# workspace = Path(os.getcwd())
PRODUCTS_ID = "VNP09_NRT"
date = '2022-09-01'
YEAR=2022
download = False
COLLECTION = PRODUCTS_STORE[PRODUCTS_ID]["collection"]
eeImgColName = PRODUCTS_STORE[PRODUCTS_ID]["eeImgColName"]
workspace = Path("C:/eo4wildfire")
dataPath = workspace / 'data' / eeImgColName
if download:
if os.path.exists(dataPath): shutil.rmtree(f"{str(dataPath)}/")
tmpPath = dataPath / f"{COLLECTION}/{PRODUCTS_ID}/{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 NRT
lance_date = datetime.date.today() - datetime.date(YEAR, 1, 1)
julian_today = lance_date.days + 1
print("julian_today: ", julian_today)
if False:
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_nrt_data_on(julian_day, YEAR)
# 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",
# ]
# wget -e robots=off -m -np -R .html,.tmp -nH --cut-dirs=4 "https://nrt3.modaps.eosdis.nasa.gov/api/v2/content/archives/allData/5000/VNP09_NRT/2022/243" --header "Authorization: Bearer cHV6aGFvX2FnYjpjSFY2YUdGdlFHdDBhQzV6WlE9PToxNjYxOTU1NTU5OjFmM2EyY2IwZWY4NWFkNTE5N2RiOGZiYjY2MzA4N2QxMjEwMTgyMjg" -P TARGET_DIRECTORY_ON_YOUR_FILE_SYSTEM