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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,53 +1,110 @@ | ||
| import ee | ||
| import mercury as mr | ||
|
|
||
| class SentinelInitialization: | ||
| class LandsatInitialization: | ||
| def __init__(self, m, date_one, date_two, max_cloud_covering): | ||
| self.m = m | ||
| self.date_one = date_one | ||
| self.date_two = date_two | ||
| self.max_cloud_covering = max_cloud_covering | ||
|
|
||
| def sen2msisr_init(self): | ||
| self.sen2msibands = mr.MultiSelect(label="Select Sentinel 2 MSI (TOA/SR) bands", | ||
| value=['B2', 'B3', 'B4'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B8A', 'B9', 'B11', 'B12']) | ||
| def ls7sr_init(self): | ||
| self.ls7bands = mr.MultiSelect(label="Select LandSat 7 SR bands", | ||
| value=['SR_B3', 'SR_B2', 'SR_B1'], | ||
| choices=['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7']) | ||
| ls7 = ee.ImageCollection("LANDSAT/LE07/C02/T1_L2").filterDate(str(self.date_one.value), str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| vis_ls7 = {'bands': self.ls7bands.value} | ||
| self.m.addLayer(ls7, vis_ls7, "LandSat 7 SR", True, 0.7) | ||
|
|
||
| sen2msi_sr = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED').filterDate(str(self.date_one.value),str(self.date_two.value)).filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', self.max_cloud_covering.value)) | ||
| composite_sr = sen2msi_sr.median() | ||
| def ls8toa_init(self): | ||
| self.ls8bands = mr.MultiSelect(label="Select LandSat 8 TOA/RAW bands", | ||
| value=['B4', 'B3', 'B2'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11']) | ||
| ls8 = ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA").filterDate(str(self.date_one.value), str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| vis_ls8 = { | ||
| 'bands': self.ls8bands.value, | ||
| 'min': 0.0, | ||
| 'max': 0.4, | ||
| } | ||
| self.m.addLayer(ls8, vis_ls8, 'LandSat 8 TOA') | ||
|
|
||
| vis_sen2sr = { | ||
| 'bands': self.sen2msibands.value, | ||
| 'min': 0, | ||
| 'max': 3000, | ||
| 'gamma': 1.4, | ||
| def ls8rawtc_init(self): | ||
| self.ls8bands = mr.MultiSelect(label="Select LandSat 8 TOA/RAW bands", | ||
| value=['B4', 'B3', 'B2'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11']) | ||
| ls8raw = ee.ImageCollection('LANDSAT/LC09/C02/T1').filterDate(str(self.date_one.value), str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| ls8raw_tc = ls8raw.select(self.ls8bands.value) | ||
| vis_ls8raw_tc = { | ||
| min: 0.0, | ||
| max: 30000.0, | ||
| } | ||
| self.m.addLayer(ls8raw_tc, vis_ls8raw_tc, "LandSat 8 RAW") | ||
|
|
||
| def ls8sr_init(self): | ||
| self.ls8srbands = mr.MultiSelect(label="Select LandSat 8 SR bands", | ||
| value=['SR_B4', 'SR_B3', 'SR_B2'], | ||
| choices=['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7']) | ||
|
|
||
| self.m.addLayer(composite_sr, vis_sen2sr, 'Sentinel 2 MSI SR') | ||
| ls8sr = ee.ImageCollection('LANDSAT/LC08/C02/T1_L2').filterDate(str(self.date_one.value), | ||
| str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| vis_ls8sr = { | ||
| 'bands': self.ls8srbands.value, | ||
| min: 0.0, | ||
| max: 0.3, | ||
| } | ||
| self.m.addLayer(ls8sr, vis_ls8sr, 'LandSat 8 SR') | ||
|
|
||
| def sen2msitoa_init(self): | ||
| self.sen2msibands = mr.MultiSelect(label="Select Sentinel 2 MSI (TOA/SR) bands", | ||
| value=['B2', 'B3', 'B4'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B8A', 'B9', 'B11', 'B12']) | ||
| def ls9_init(self): | ||
| self.ls9bands = mr.MultiSelect(label="Select LandSat 9 SR bands", | ||
| value=['SR_B4', 'SR_B3', 'SR_B2'], | ||
| choices=['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7']) | ||
| def apply_scale_factors(image): | ||
| opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2) | ||
| thermalBands = image.select('ST_B.*').multiply(0.00341802).add(149.0) | ||
| return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True) | ||
|
|
||
| sen2msi_toa = ee.ImageCollection('COPERNICUS/S2_HARMONIZED').filterDate(str(self.date_one.value), str(self.date_two.value)).filter(ee.Filter.lte('CLOUDY_PIXEL_PERCENTAGE', self.max_cloud_covering.value)) | ||
| composite_toa = sen2msi_toa.median() | ||
| collection = ee.ImageCollection('LANDSAT/LC09/C02/T1_L2').filterDate(str(self.date_one.value), | ||
| str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
|
|
||
| vis_sen2toa = { | ||
| 'bands': self.sen2msibands.value, | ||
| 'min': 0, | ||
| 'max': 3000, | ||
| 'gamma': 1.4, | ||
| median = collection.median() | ||
| ls9 = apply_scale_factors(median) | ||
|
|
||
| vis_ls9 = { | ||
| 'bands': self.ls9bands.value, | ||
| 'min': 0.0, | ||
| 'max': 0.3, | ||
| } | ||
| self.m.addLayer(ls9, vis_ls9, 'LandSat 9 SR') | ||
|
|
||
| self.m.addLayer(composite_toa, vis_sen2toa, 'Sentinel 2 MSI TOA') | ||
|
|
||
| def sen5pc_init(self): | ||
| sen5pc = ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_CLOUD").select('cloud_fraction').filterDate(str(self.date_one.value),str(self.date_two.value)) | ||
| vis_sen5pc = { | ||
| min: 0, | ||
| max: 0.95, | ||
| 'palette': ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red'] | ||
| def ls9rawtc_init(self): | ||
| self.ls9rawbands = mr.MultiSelect(label="Select LandSat 9 RAW/TOA bands", | ||
| value=['B4', 'B3', 'B2'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11']) | ||
| ls9raw = ee.ImageCollection("LANDSAT/LC09/C02/T2").filterDate(str(self.date_one.value), str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| ls9raw_tc = ls9raw.select(self.ls9rawbands.value) | ||
| vis_ls9raw_tc = { | ||
| 'min': 0.0, | ||
| 'max': 30000.0, | ||
| } | ||
| self.m.addLayer(ls9raw_tc, vis_ls9raw_tc, 'LandSat 9 RAW') | ||
|
|
||
| self.m.addLayer(sen5pc, vis_sen5pc, 'Sentinel 5P Cloud') | ||
| def ls9toatc_init(self): | ||
| self.ls9rawbands = mr.MultiSelect(label="Select LandSat 9 RAW/TOA bands", | ||
| value=['B4', 'B3', 'B2'], | ||
| choices=['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11']) | ||
| ls9toa = ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA').filterDate(str(self.date_one.value), | ||
| str(self.date_two.value)).filter( | ||
| ee.Filter.lte('CLOUD_COVER', self.max_cloud_covering.value)) | ||
| ls9toa_tc = ls9toa.select(self.ls9rawbands.value) | ||
| vis_ls9toa_tc = { | ||
| min: 0.0, | ||
| max: 0.4, | ||
| } | ||
| self.m.addLayer(ls9toa_tc, vis_ls9toa_tc, 'LandSat 9 TOA') |