Delete utils

utils/NBR_calculations.py

@@ -1,130 +0,0 @@
-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)