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| import ee | |
| ''' 0 Good quality fire | |
| 1 Good quality fire-free land | |
| 2 Invalid due to opaque cloud | |
| 3 Invalid due to surface type or sunglint or LZA threshold exceeded or off earth or missing input data | |
| 4 Invalid due to bad input data | |
| 5 Invalid due to algorithm failure''' | |
| # Bit-masking | |
| BitMask_0 = 1 << 0 | |
| BitMask_1 = 1 << 1 | |
| BitMask_2 = 1 << 2 | |
| BitMask_3 = 1 << 3 | |
| BitMask_4 = 1 << 4 | |
| BitMask_5 = 1 << 5 | |
| BitMask_6 = 1 << 6 | |
| BitMask_7 = 1 << 7 | |
| BitMask_8 = 1 << 8 | |
| BitMask_9 = 1 << 9 | |
| def GcalcNBR (goesImg, aoi): | |
| #day = ee.Date(eachImg.get('system:time_start')).get('day','America/Los_Angeles') | |
| fireMode = goesImg.select('fireMode') | |
| fireMin = goesImg.select('fireMin') | |
| CMI_QF3 = goesImg.select('DQF_C03').int() | |
| CMI_QF6 = goesImg.select('DQF_C06').int() | |
| # To include active fire pixels - fireMin.lt(2)\ for next line | |
| QF_Mask = (fireMin.eq(1)\ | |
| .Or(fireMin.gt(3)))\ | |
| .And(CMI_QF3.lt(2))\ | |
| .And(CMI_QF6.lt(2))\ | |
| .rename('QFmask'); | |
| GOESm = goesImg.select(['CMI_C03','CMI_C06']).updateMask(QF_Mask) | |
| NBR = GOESm.normalizedDifference(['CMI_C03', 'CMI_C06']).toFloat().rename('NBR') | |
| return goesImg.addBands([NBR,QF_Mask]) | |
| def GcalcCCsingle (goesImg): | |
| fireDQF = goesImg.select('DQF').int() | |
| CMI_QF3 = goesImg.select('DQF_C03').int() | |
| CMI_QF6 = goesImg.select('DQF_C06').int() | |
| #Right now, cloud mask is excluding clouds and water; active fire, bad data and fire free are unmasked. NBR mask exlcudes fire | |
| F_Mask = fireDQF.eq(0) | |
| C_Mask = (fireDQF.lt(2).Or(fireDQF.gt(2))).rename('C_Mask') | |
| #.And(CMI_QF3.lt(2)).And(CMI_QF6.lt(2)).rename('C_Mask') | |
| QF_Mask = (fireDQF.eq(1).Or(fireDQF.gt(3)))\ | |
| .And(CMI_QF3.lt(2)).And(CMI_QF6.lt(2)).rename('QFmask') | |
| GOESmasked = goesImg.select(['CMI_C03','CMI_C06']).updateMask(QF_Mask) | |
| NBRmasked = GOESmasked.normalizedDifference(['CMI_C03', 'CMI_C06']).toFloat().rename('NBR') | |
| cloudMasked = goesImg.select('CMI_C03').updateMask(C_Mask).toFloat().rename('CC') | |
| fireMasked = goesImg.select('CMI_C03').updateMask(F_Mask).toFloat().rename('FC') | |
| return goesImg.addBands([NBRmasked,cloudMasked, fireMasked,QF_Mask,C_Mask]) | |
| '''Parameter Array Name Value Bit(s) = Value | |
| Sun Glint QF1 Surface Reflectance None 6-7 = 00 | |
| Low Sun Mask QF1 Surface Reflectance High 5 = 0 | |
| Day/Night QF1 Surface Reflectance Day 4 =0 | |
| Cloud Detection QF1 Surface Reflectance Confident Clear 2-3 = 00 or Problably Clear 2-3 = 01 | |
| Cloud Mask Quality QF1 Surface Reflectance High or Medium 0-1 = 10 or 11 | |
| Snow/Ice QF2 Surface Reflectance No Snow or Ice 5 = 0 | |
| Cloud Shadow QF2 Surface Reflectance No Cloud Shadow 3 = 0 | |
| LandWater QF2 Surface Reflectance Land, Snow, Arctic, Antarctic or Greenland, Desert 0-2 = 011, 100, 101, 110, 111 | |
| Thin Cirrus Flag QF7 Surface Reflectance No Thin Cirrus 4 = 0 | |
| Aerosol Quantity QF7 Surface Reflectance Climatology, Low or Medium 2-3 = 00, 01 or 10 | |
| Adjacent to Cloud QF7 Surface Reflectance Not Adjacent to Cloud 1 = 0''' | |
| def VcalcNBR (VIIRSimg): | |
| QF1 = VIIRSimg.select('QF1').int() | |
| QF2 = VIIRSimg.select('QF2').int() | |
| QF7 = VIIRSimg.select('QF7').int() | |
| QF_Mask = (QF1.bitwiseAnd(BitMask_3).eq(0)).And\ | |
| ((QF2.bitwiseAnd(BitMask_2).eq(4)).Or((QF2.bitwiseAnd(BitMask_1).eq(0)))).And\ | |
| (QF2.bitwiseAnd(BitMask_5).eq(0)).rename('QFmask'); | |
| VIIRSm = VIIRSimg.select(['I2','M11']).updateMask(QF_Mask); | |
| NBR = VIIRSm.normalizedDifference(['I2','M11']).toFloat().rename('NBR') | |
| return VIIRSimg.addBands(NBR).addBands(QF_Mask)#.set('avgNBR', avgNBR) | |
| ''' Bit 1: Dilated Cloud | |
| Bit 2: Cirrus (high confidence) | |
| Bit 3: Cloud | |
| Bit 4: Cloud Shadow | |
| Bit 5: Snow | |
| Bit 6: Clear (0: Cloud or Dilated Cloud bits are set, 1: Cloud and Dilated Cloud bits are not set) | |
| Bit 7: Water | |
| Bits 8-9: Cloud Confidence (0: None, 1: Low, 2: Medium, 3: High) | |
| Bits 10-11: Cloud Shadow Confidence (0: None, 1: Low, 2: Medium, 3: High) | |
| Bits 12-13: Snow/Ice Confidence (0: None, 1: Low, 2: Medium, 3: High) | |
| Bits 14-15: Cirrus Confidence (0: None, 1: Low, 2: Medium, 3: High)''' | |
| def LcalcNBR (LSimg): | |
| QApixel = LSimg.select('QA_PIXEL').int() | |
| QF_Mask =(QApixel.bitwiseAnd(BitMask_3).eq(0)).And\ | |
| (QApixel.bitwiseAnd(BitMask_5).eq(0)).And\ | |
| (QApixel.bitwiseAnd(BitMask_7).eq(0)).rename('QFmask'); | |
| LSmasked = LSimg.select(['SR_B5','SR_B7']).updateMask(QF_Mask); | |
| NBR = LSmasked.normalizedDifference(['SR_B5','SR_B7']).toFloat().rename('NBR') | |
| return LSimg.addBands(NBR).addBands(QF_Mask)#.set('avgNBR', avgNBR) | |
| ''' 1 Saturated or defective | |
| 2 Dark Area Pixels | |
| 3 Cloud Shadows | |
| 4 Vegetation | |
| 5 Bare Soils | |
| 6 Water | |
| 7 Clouds Low Probability / Unclassified | |
| 8 Clouds Medium Probability | |
| 9 Clouds High Probability | |
| 10 Cirrus | |
| 11 Snow / Ice''' | |
| def ScalcNBR (sentImg): | |
| SCL = sentImg.select('SCL'); | |
| QF_Mask =(SCL.neq(6)).And\ | |
| (SCL.neq(8)).And\ | |
| (SCL.neq(9)).And\ | |
| (SCL.neq(11))\ | |
| .rename('QFmask'); | |
| sentMasked = sentImg.select(['B8A','B12']).updateMask(QF_Mask); #B8 is another option- broadband NIR | |
| NBR = sentMasked.normalizedDifference(['B8A','B12']).toFloat().rename('NBR') | |
| return sentImg.addBands(NBR).addBands(QF_Mask).addBands(SCL)#.set('avgNBR', avgNBR) |