def create_10x10_plantation(tile_id, plant_1x1_vrt):
print "Getting bounding coordinates for tile", tile_id
xmin, ymin, xmax, ymax = uu.coords(tile_id)
print " xmin:", xmin, "; xmax:", xmax, "; ymin", ymin, "; ymax:", ymax
tile_10x10 = '{0}_{1}.tif'.format(
tile_id, cn.pattern_annual_gain_AGC_BGC_planted_forest_unmasked)
print "Rasterizing", tile_10x10
cmd = [
'gdalwarp', '-tr', '{}'.format(str(cn.Hansen_res)),
'{}'.format(str(cn.Hansen_res)), '-co', 'COMPRESS=LZW', '-tap', '-te',
str(xmin),
str(ymin),
str(xmax),
str(ymax), '-dstnodata', '0', '-t_srs', 'EPSG:4326', '-overwrite',
'-ot', 'Float32', plant_1x1_vrt, tile_10x10
]
subprocess.check_call(cmd)
print "Checking if {} contains any data...".format(tile_id)
stats = uu.check_for_data(tile_10x10)
if stats[0] > 0:
print " Data found in {}. Copying tile to s3...".format(tile_id)
uu.upload_final(cn.annual_gain_AGC_BGC_planted_forest_unmasked_dir,
tile_id,
cn.pattern_annual_gain_AGC_BGC_planted_forest_unmasked)
print " Tile converted and copied to s3"
else:
print " No data found. Not copying {}.".format(tile_id)
def create_mangrove_tiles(tile_id):
print "Getting bounding coordinates for tile", tile_id
xmin, xmax, ymin, ymax = utilities.coords(tile_id)
print " ymax:", ymax, "; ymin:", ymin, "; xmax", xmax, "; xmin:", xmin
print "Creating tile", tile_id
out_tile = '{0}_{1}.tif'.format(tile_id, cn.pattern_mangrove_biomass_2000)
cmd = ['gdalwarp', '-t_srs', 'EPSG:4326', '-co', 'COMPRESS=LZW', '-tr', '0.00025', '0.00025', '-tap', '-te',
str(xmin), str(ymin), str(xmax), str(ymax), '-dstnodata', '0', '-overwrite', utilities.mangrove_vrt, out_tile]
subprocess.check_call(cmd)
print " Tile created"
print "Checking if {} contains any data...".format(tile_id)
stats = uu.check_for_data(out_tile)
if stats[0] > 0:
print " Data found in {}. Copying tile to s3...".format(tile_id)
uu.upload_final(cn.mangrove_biomass_2000_dir, tile_id, cn.pattern_mangrove_biomass_2000)
print " Tile copied to s3"
else:
print " No data found. Not copying {}.".format(tile_id)
def create_10x10_plantation_type(tile_id, plant_type_1x1_vrt):
uu.print_log("Getting bounding coordinates for tile", tile_id)
xmin, ymin, xmax, ymax = uu.coords(tile_id)
uu.print_log(" xmin:", xmin, "; xmax:", xmax, "; ymin", ymin, "; ymax:", ymax)
tile_10x10 = '{0}_{1}.tif'.format(tile_id, cn.pattern_planted_forest_type_unmasked)
uu.print_log("Rasterizing", tile_10x10)
cmd = ['gdalwarp', '-tr', '{}'.format(str(cn.Hansen_res)), '{}'.format(str(cn.Hansen_res)),
'-co', 'COMPRESS=LZW', '-tap', '-te', str(xmin), str(ymin), str(xmax), str(ymax),
'-dstnodata', '0', '-t_srs', 'EPSG:4326', '-overwrite', '-ot', 'Byte', plant_type_1x1_vrt, tile_10x10]
# Solution for adding subprocess output to log is from https://stackoverflow.com/questions/21953835/run-subprocess-and-print-output-to-logging
process = Popen(cmd, stdout=PIPE, stderr=STDOUT)
with process.stdout:
uu.log_subprocess_output(process.stdout)
uu.print_log("Checking if {} contains any data...".format(tile_id))
stats = uu.check_for_data(tile_10x10)
if stats[0] > 0:
uu.print_log(" Data found in {}. Copying tile to s3...".format(tile_id))
uu.upload_final(cn.planted_forest_type_unmasked_dir, tile_id, cn.pattern_planted_forest_type_unmasked)
uu.print_log(" Tile converted and copied to s3")
else:
print(" No data found. Not copying {}.".format(tile_id))
def prep_FIA_regions(tile_id):
uu.print_log("Creating Hansen tile for FIA regions")
# Start time
start = datetime.datetime.now()
uu.print_log("Getting extent of", tile_id)
xmin, ymin, xmax, ymax = uu.coords(tile_id)
uu.print_log("Rasterizing FIA region shapefile", tile_id)
blocksizex = 1024
blocksizey = 1024
uu.rasterize(
'{}.shp'.format(cn.name_FIA_regions_raw[:-4]),
"{0}_{1}.tif".format(tile_id, cn.pattern_FIA_regions_processed), xmin,
ymin, xmax, ymax, blocksizex, blocksizey, '.00025', 'Byte',
'regionCode', '0')
uu.print_log("Checking if {} contains any data...".format(tile_id))
no_data = uu.check_for_data("{0}_{1}.tif".format(
tile_id, cn.pattern_FIA_regions_processed))
if no_data:
uu.print_log(" No data found. Deleting {}.".format(tile_id))
os.remove("{0}_{1}.tif".format(tile_id,
cn.pattern_FIA_regions_processed))
else:
uu.print_log(
" Data found in {}. Copying tile to s3...".format(tile_id))
uu.upload_final(cn.FIA_regions_processed_dir, tile_id,
cn.pattern_FIA_regions_processed)
uu.print_log(" Tile copied to s3")
# Prints information about the tile that was just processed
uu.end_of_fx_summary(start, tile_id, cn.pattern_FIA_regions_processed)
def create_emitted_biomass(tile_id):
start = datetime.datetime.now()
# Names of the input tiles
natrl_forest_biomass_2000 = '{0}_{1}.tif'.format(
tile_id, cn.pattern_natrl_forest_biomass_2000)
mangrove_biomass_2000 = '{0}_{1}.tif'.format(
tile_id, cn.pattern_mangrove_biomass_2000)
natrl_forest_gain = '{0}_{1}.tif'.format(
tile_id, cn.pattern_cumul_gain_AGC_natrl_forest)
mangrove_gain = '{0}_{1}.tif'.format(tile_id,
cn.pattern_cumul_gain_AGC_mangrove)
natrl_forest_emitted = '{0}_{1}.tif'.format(
tile_id, cn.pattern_natrl_forest_biomass_2000)
mangrove_emitted = '{0}_{1}.tif'.format(tile_id,
cn.pattern_cont_eco_processed)
print " Reading input files and evaluating conditions"
# Opens biomass tile
with rasterio.open(loss) as loss_src:
# Grabs metadata about the tif, like its location/projection/cellsize
kwargs = loss_src.meta
# Grabs the windows of the tile (stripes) so we can iterate over the entire tif without running out of memory
windows = loss_src.block_windows(1)
# Opens gain tile
with rasterio.open(gain) as gain_src:
# Opens ifl tile
with rasterio.open(ifl) as ifl_src:
# Opens continent-ecozone combinations tile
with rasterio.open(cont_eco) as cont_eco_src:
# Opens biomass 2000 tile
with rasterio.open(biomass) as biomass_src:
# Opens tree cover density tile
with rasterio.open(tcd) as extent_src:
# Updates kwargs for the output dataset
kwargs.update(driver='GTiff',
count=1,
compress='lzw',
nodata=0)
# Opens the output tile, giving it the arguments of the input tiles
with rasterio.open(
'{0}{1}.tif'.format(
tile_id,
cn.pattern_age_cat_natrl_forest), 'w',
**kwargs) as dst:
# Iterates across the windows (1 pixel strips) of the input tile
for idx, window in windows:
# Creates windows for each input raster
loss = loss_src.read(1, window=window)
gain = gain_src.read(1, window=window)
tcd = extent_src.read(1, window=window)
ifl = ifl_src.read(1, window=window)
cont_eco = cont_eco_src.read(1,
window=window)
biomass = biomass_src.read(1,
window=window)
# Creates a numpy array that has the <=20 year secondary forest growth rate x 20
# based on the continent-ecozone code of each pixel (the dictionary).
# This is used to assign pixels to the correct age category.
gain_20_years = np.vectorize(
gain_table_dict.get)(cont_eco) * 20
# Create a 0s array for the output
dst_data = np.zeros(
(window.height, window.width),
dtype='uint8')
# Logic tree for assigning age categories begins here
# No change pixels- no loss or gain
if tropics == 0:
dst_data[np.where((tcd > 0)
& (gain == 0)
& (loss == 0))] = 1
if tropics == 1:
dst_data[np.where((tcd > 0)
& (gain == 0)
& (loss == 0)
& (ifl != 1))] = 2
dst_data[np.where((tcd > 0)
& (gain == 0)
& (loss == 0)
& (ifl == 1))] = 3
# Loss-only pixels
dst_data[np.where(
(gain == 0) & (loss > 0) & (ifl != 1)
& (biomass <= gain_20_years))] = 4
dst_data[np.where(
(gain == 0) & (loss > 0) & (ifl != 1)
& (biomass > gain_20_years))] = 5
dst_data[np.where((gain == 0) & (loss > 0)
& (ifl == 1))] = 6
# Gain-only pixels
dst_data[np.where((gain == 1)
& (loss == 0))] = 7
# Pixels with loss and gain
dst_data[np.where((gain == 1)
& (loss >= 13))] = 8
dst_data[np.where((gain == 1) & (loss > 0)
& (loss <= 6))] = 9
dst_data[np.where((gain == 1) & (loss > 6)
& (loss < 13))] = 10
# Writes the output window to the output
dst.write_band(1, dst_data, window=window)
print 'Uploading tiles to s3'
for type in cn.pool_types:
uu.upload_final('{0}/{1}/'.format(cn.agc_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_agc, type))
uu.upload_final('{0}/{1}/'.format(cn.bgc_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_bgc, type))
uu.upload_final('{0}/{1}/'.format(cn.deadwood_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_deadwood, type))
uu.upload_final('{0}/{1}/'.format(cn.litter_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_litter, type))
uu.upload_final('{0}/{1}/'.format(cn.soil_C_pool_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_soil_pool, type))
uu.upload_final('{0}/{1}/'.format(cn.total_C_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_total_C, type))
print "Elapsed time: {}".format(datetime.datetime.now() - start)
def create_carbon_pools(tile_id):
start = datetime.datetime.now()
print 'Writing aboveground carbon, belowground carbon, deadwood, litter, soil, and total carbon tiles'
calc_all_cmd = ['./calc_carbon_pools.exe', tile_id]
subprocess.check_call(calc_all_cmd)
print 'Uploading tiles to s3'
for type in cn.pool_types:
uu.upload_final('{0}/{1}/'.format(cn.agc_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_agc, type))
uu.upload_final('{0}/{1}/'.format(cn.bgc_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_bgc, type))
uu.upload_final('{0}/{1}/'.format(cn.deadwood_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_deadwood, type))
uu.upload_final('{0}/{1}/'.format(cn.litter_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_litter, type))
uu.upload_final('{0}/{1}/'.format(cn.soil_C_pool_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_soil_pool, type))
uu.upload_final('{0}/{1}/'.format(cn.total_C_dir, type), tile_id,
'{0}_{1}'.format(cn.pattern_total_C, type))
print "Deleting intermediate tiles"
tiles_to_remove = glob.glob('*{}*'.format(tile_id))
for tile in tiles_to_remove:
try:
os.remove(tile)
except:
pass
print "elapsed time: {}".format(datetime.datetime.now() - start)