# data_mon_1
scenes_mon_1 = [
Scene(reader="seviri_l1b_nc", filenames=[f]) for f in data_mon_1
]
mscn_mon_1 = MultiScene(scenes_mon_1)
# data_mon_21
scenes_mon_2 = [
Scene(reader="seviri_l1b_nc", filenames=[f]) for f in data_mon_2
]
mscn_mon_2 = MultiScene(scenes_mon_2)
## load the IR_134 Band
scenes_mon_1[1].all_dataset_names()
mscn_mon_1.load(["IR_134"])
mscn_mon_2.load(["IR_134"])
# area definition
area_def_kongo = AreaDefinition(
"Kongo", "A lambert azimutal equal area projection of Kongo",
"Projection of Kongo", {
"proj": "laea",
"lat_0": 2.5,
"lon_0": 6.0
}, 1000, 1000, (4E5, -17E5, 30E5, 8E5))
# resampling mscn's to area of kongo
## mscn_mon_1
new_mscn_mon_1 = mscn_mon_1.resample(area_def_kongo)
#load multiscene object
scenes_mon1 = [Scene(reader="seviri_l1b_nc", filenames=[f]) for f in data_mon1]
mscn_mon1 = MultiScene(scenes_mon1)
scenes_mon2 = [Scene(reader="seviri_l1b_nc", filenames=[f]) for f in data_mon2]
mscn_mon2 = MultiScene(scenes_mon2)
#show all available spectral bands
scenes_mon1[1].all_dataset_names()
#https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-1c/cloud-masks
#https://gisgeography.com/spectral-signature/
#load SWIR
mscn_mon1.load(["IR_134"])
mscn_mon2.load(["IR_134"])
#Area definition dem. rep kongo
area_def_kongo = AreaDefinition("Kongo",
"A Lambert Azimutal Equal Area projection of Kongo",
"Projection of Kongo", {"proj":"laea", "lat_0":2.5, "lon_0":6},
1000, 1000, (4E5, -17E5, 30E5, 8E5))
mscn1_kongo = mscn_mon1.resample(area_def_kongo)
mscn2_kongo = mscn_mon2.resample(area_def_kongo)
blended_scene1 = mscn1_kongo.blend()
blended_scene2 = mscn2_kongo.blend()
import os
os.chdir(r"C:\Users\timhe\Documents\VIIRStest")
filenames = glob.glob(
"GIMGO-SVI05_npp_d20190910_t1038162_e1043566_b40776_c20190912092651273026_noac_ops*"
)
global_scene = Scene(reader="viirs_sdr", filenames=filenames)
nebraska_scene = global_scene.resample('nebraska', resampler='nearest')
nebraska_scene.save_datasets()
from satpy import MultiScene
mscn = MultiScene(global_scene)
mscn.load(['I05'])
my_area = global_scene['I05'].load().attrs['area'].compute_optimal_bb_area({
'proj':
'lcc',
'lon_0':
-95.,
'lat_0':
25.,
'lat_1':
25.,
'lat_2':
25.
})
new_scn = global_scene.resample(my_area)
new_scn.save_dataset(10.5)
