# 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)