def get_lc(year, tile, fips):
'''
Return LC mask for year,tile,fips
'''
kwargs = {
'tile': tile,
'product': 'MCD12Q1',
}
doy = 1
# get the LC data
modis = Modis(**kwargs)
warp_args = {
'dstNodata': 255,
'format': 'MEM',
'cropToCutline': True,
'cutlineWhere': f"FIPS='{fips}'",
'cutlineDSName': 'data/TM_WORLD_BORDERS-0.3.shp'
}
# specify day of year (DOY) and year
lcfiles = modis.get_modis(year, doy, warp_args=warp_args)
# get the item we want
g = gdal.Open(lcfiles['LC_Type3'])
# error checking
if not g:
print(f"cannot open LC file {lcfiles['LC_Type3']}")
return None
lc = g.ReadAsArray()
del g
# in your function, print out the unique values in the
# landcover dataset to give some feedback to the user
print(f"class codes: {np.unique(lc)}")
return lc
def pull(year, tile=['h09v05'], doy="*", month=None, day=None, step=1):
product = 'MYD10A1'
kwargs = {'tile': list(tile), 'product': product, 'verbose': True}
# get the data
print(kwargs)
modis = Modis(**kwargs)
mfiles = modis.get_modis(year, doy, step=step)
return mfiles
def modis_annual_dataset(year, tile, product, step=1, verbose=False):
# load into kwargs
kwargs = {
'verbose': verbose,
'tile': list(tile),
'product': product,
}
# list of doys we want
doys = "*"
modis = Modis(**kwargs)
ifiles = modis.get_modis(year, doys, step=step)
return ifiles
def uk_lai(year=2019):
kwargs = {
'tile' : ['h17v03', 'h17v04', 'h18v03', 'h18v04'],
'product' : 'MCD15A3H',
'sds' : 'Lai_500m',
'log' : f'work/uk_lai_{year}_log.txt',
'db_file' : ['data/database.db',f'work/uk_lai_{year}.db'],
'local_dir' : 'work',
'verbose' : True
}
modis = Modis(**kwargs)
result = modis.get_year(year,step=4)
return result
def main():
'''example of use'''
try:
from geog0111.modis import Modis
except:
from modis import Modis
# first get a MODIS hdf file
modis = Modis(product='MCD15A3H', local_dir='work')
hdf_files, sds = modis.stitch_date(2019, 1, get_files=True)
filename = hdf_files[0]
# generate output filename
ofile = filename.split('.hdf')[0] + '_blank.hdf'
create_blank_file(sds[0][0], ofile)
def pull(product, year, tile, doy=None, month=None, day=None, step=1):
kwargs = {
'tile': list(tile),
'product': product,
'log': f'{gwork}/{product}_{year}_{tidy(tile)}_log.txt',
'db_file': [f'{gwork}/database.db', f'{gwork}/{product}_database.db'],
'local_dir': f'{gwork}',
'verbose': True
}
# get the data
print(kwargs)
modis = Modis(**kwargs)
#modis.get_data(year,doy=doy,day=day,step=step,month=month)
modis.stitch(year, doy=doy, day=day, step=step, month=month)
return modis
at the command prompt.
'''
import gdal
try:
from geog0111.modis import Modis
except:
from modis import Modis
import matplotlib.pyplot as plt
kwargs = {
'verbose': True,
'tile': ['h17v03', 'h18v03', 'h17v04', 'h18v04'],
'product': 'MCD15A3H',
}
year = 2018
# list of doys we want
doys = "*"
modis = Modis(**kwargs)
warp_args = {
'dstNodata': 255,
'format': 'MEM',
'cropToCutline': True,
'cutlineWhere': "FIPS='UK'",
'cutlineDSName': 'data/TM_WORLD_BORDERS-0.3.shp'
}
mfiles = modis.get_modis(year, doys, warp_args=warp_args, step=4)
print(mfiles.keys())
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
Example script to get all days of data for MCD64A1
for the tiles and year spewcified.
To run this, simply type:
geog0111/get_lai.py
at the command prompt.
'''
from osgeo import gdal
try:
from geog0111.modis import Modis
except:
from modis import Modis
import matplotlib.pyplot as plt
kwargs = {
'verbose': True,
'tile': ['h17v03', 'h18v03', 'h17v04', 'h18v04'],
'product': 'MCD64A1',
}
for year in [2017, 1018, 2019]:
modis = Modis(**kwargs)
modis.stitch(year, day=1, month="*")