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Delete historical_fires.py
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historical_fires.py
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import ee
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import geemap
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import solara
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import ipywidgets as widgets
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#from NBR_calculations import GcalcNBR, VcalcNBR, LcalcNBR, ScalcNBR, GcalcCCsingle
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import requests
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# Bit-masking
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BitMask_0 = 1 << 0
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BitMask_1 = 1 << 1
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BitMask_2 = 1 << 2
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BitMask_3 = 1 << 3
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BitMask_4 = 1 << 4
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BitMask_5 = 1 << 5
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BitMask_6 = 1 << 6
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BitMask_7 = 1 << 7
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BitMask_8 = 1 << 8
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BitMask_9 = 1 << 9
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def GcalcCCsingle (goesImg):
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fireDQF = goesImg.select('DQF').int()
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CMI_QF3 = goesImg.select('DQF_C03').int()
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CMI_QF6 = goesImg.select('DQF_C06').int()
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#Right now, cloud mask is excluding clouds and water; active fire, bad data and fire free are unmasked. NBR mask exlcudes fire
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F_Mask = fireDQF.eq(0)
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C_Mask = (fireDQF.lt(2).Or(fireDQF.gt(2))).rename('C_Mask')
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#.And(CMI_QF3.lt(2)).And(CMI_QF6.lt(2)).rename('C_Mask')
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QF_Mask = (fireDQF.eq(1).Or(fireDQF.gt(3)))\
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.And(CMI_QF3.lt(2)).And(CMI_QF6.lt(2)).rename('QFmask')
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GOESmasked = goesImg.select(['CMI_C03','CMI_C06']).updateMask(QF_Mask)
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NBRmasked = GOESmasked.normalizedDifference(['CMI_C03', 'CMI_C06']).toFloat().rename('NBR')
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cloudMasked = goesImg.select('CMI_C03').updateMask(C_Mask).toFloat().rename('CC')
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fireMasked = goesImg.select('CMI_C03').updateMask(F_Mask).toFloat().rename('FC')
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return goesImg.addBands([NBRmasked,cloudMasked, fireMasked,QF_Mask,C_Mask])
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'''Parameter Array Name Value Bit(s) = Value
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Sun Glint QF1 Surface Reflectance None 6-7 = 00
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Low Sun Mask QF1 Surface Reflectance High 5 = 0
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Day/Night QF1 Surface Reflectance Day 4 =0
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Cloud Detection QF1 Surface Reflectance Confident Clear 2-3 = 00 or Problably Clear 2-3 = 01
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Cloud Mask Quality QF1 Surface Reflectance High or Medium 0-1 = 10 or 11
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Snow/Ice QF2 Surface Reflectance No Snow or Ice 5 = 0
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Cloud Shadow QF2 Surface Reflectance No Cloud Shadow 3 = 0
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LandWater QF2 Surface Reflectance Land, Snow, Arctic, Antarctic or Greenland, Desert 0-2 = 011, 100, 101, 110, 111
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Thin Cirrus Flag QF7 Surface Reflectance No Thin Cirrus 4 = 0
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Aerosol Quantity QF7 Surface Reflectance Climatology, Low or Medium 2-3 = 00, 01 or 10
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Adjacent to Cloud QF7 Surface Reflectance Not Adjacent to Cloud 1 = 0'''
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def VcalcNBR (VIIRSimg):
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QF1 = VIIRSimg.select('QF1').int()
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QF2 = VIIRSimg.select('QF2').int()
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QF7 = VIIRSimg.select('QF7').int()
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QF_Mask = (QF1.bitwiseAnd(BitMask_3).eq(0)).And\
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((QF2.bitwiseAnd(BitMask_2).eq(4)).Or((QF2.bitwiseAnd(BitMask_1).eq(0)))).And\
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(QF2.bitwiseAnd(BitMask_5).eq(0)).rename('QFmask');
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VIIRSm = VIIRSimg.select(['I2','M11']).updateMask(QF_Mask);
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NBR = VIIRSm.normalizedDifference(['I2','M11']).toFloat().rename('NBR')
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return VIIRSimg.addBands(NBR).addBands(QF_Mask)#.set('avgNBR', avgNBR)
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''' Bit 1: Dilated Cloud
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Bit 2: Cirrus (high confidence)
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Bit 3: Cloud
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Bit 4: Cloud Shadow
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Bit 5: Snow
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Bit 6: Clear (0: Cloud or Dilated Cloud bits are set, 1: Cloud and Dilated Cloud bits are not set)
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Bit 7: Water
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Bits 8-9: Cloud Confidence (0: None, 1: Low, 2: Medium, 3: High)
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Bits 10-11: Cloud Shadow Confidence (0: None, 1: Low, 2: Medium, 3: High)
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Bits 12-13: Snow/Ice Confidence (0: None, 1: Low, 2: Medium, 3: High)
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Bits 14-15: Cirrus Confidence (0: None, 1: Low, 2: Medium, 3: High)'''
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def LcalcNBR (LSimg):
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QApixel = LSimg.select('QA_PIXEL').int()
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QF_Mask =(QApixel.bitwiseAnd(BitMask_3).eq(0)).And\
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(QApixel.bitwiseAnd(BitMask_5).eq(0)).And\
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(QApixel.bitwiseAnd(BitMask_7).eq(0)).rename('QFmask');
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LSmasked = LSimg.select(['SR_B5','SR_B7']).updateMask(QF_Mask);
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NBR = LSmasked.normalizedDifference(['SR_B5','SR_B7']).toFloat().rename('NBR')
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return LSimg.addBands(NBR).addBands(QF_Mask)#.set('avgNBR', avgNBR)
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''' 1 Saturated or defective
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2 Dark Area Pixels
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3 Cloud Shadows
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4 Vegetation
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5 Bare Soils
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6 Water
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7 Clouds Low Probability / Unclassified
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8 Clouds Medium Probability
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9 Clouds High Probability
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10 Cirrus
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11 Snow / Ice'''
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def ScalcNBR (sentImg):
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SCL = sentImg.select('SCL');
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QF_Mask =(SCL.neq(6)).And\
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(SCL.neq(8)).And\
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(SCL.neq(9)).And\
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(SCL.neq(11))\
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.rename('QFmask');
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sentMasked = sentImg.select(['B8A','B12']).updateMask(QF_Mask); #B8 is another option- broadband NIR
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NBR = sentMasked.normalizedDifference(['B8A','B12']).toFloat().rename('NBR')
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return sentImg.addBands(NBR).addBands(QF_Mask).addBands(SCL)#.set('avgNBR', avgNBR)
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fireList = ["North Complex", "Dixie", "Cameron Peak", "August Complex", "South Fork"]
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selected_fire = solara.reactive(fireList[4])
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selected_days = solara.reactive(25) #30
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dNBRvisParams = {'min': 0.0,'max': 0.8, 'palette': ['green', 'yellow','orange','red']}
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class Map(geemap.Map):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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self.add_basemap('OpenStreetMap')
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self.customize_ee_data(selected_fire.value, selected_days.value)
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self.add_selector()
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self.add_intSlider()
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self.add_dwnldButton()
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self.add("layer_manager")
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self.remove("draw_control")
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def customize_ee_data(self, fire, elapDays):
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elapDayNum = ee.Number(elapDays)
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elapDay_plusOne = elapDayNum.add(ee.Number(1))
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north_startDate = ee.Date('2020-08-16')
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dixie_startDate = ee.Date('2021-07-13')
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cam_startDate = ee.Date('2020-08-13')
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aug_startDate = ee.Date('2020-08-15')
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sfork_startDate = ee.Date('2024-05-25')
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north_complex_bb = ee.Geometry.BBox(-121.616097, 39.426723, -120.668526, 40.030845)
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dixie_bb = ee.Geometry.BBox(-121.680467, 39.759303, -120.065477, 40.873387)
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cam_peak_bb = ee.Geometry.BBox(-106.014784, 40.377907, -105.116651, 40.822094)
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aug_complex_bb = ee.Geometry.BBox(-123.668726, 39.337654, -122.355860, 40.498304)
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sfork_bb = ee.Geometry.BBox(-106.192, 33.1, -105.065, 33.782)
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def calc_nbr(pre_start, pre_stop, post_start, post_stop, bbox, goes):
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def MergeBands (eachImage):
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oneImage = ee.Image.cat(eachImage.get('CMI'), eachImage.get('FDC'))
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return oneImage
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displacementImg18 = ee.Image.load('projects/ee-losos/assets/G18-F-meter-offset_GEE')
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y_dif = displacementImg18.select([1])
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x_dif = displacementImg18.select([0]).multiply(-1)
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displacement18 = ee.Image([x_dif, y_dif])
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displacementImg16 = ee.Image.load('projects/ee-losos/assets/G16-F-meter-offset_GEE')
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y_dif = displacementImg16.select([1])
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x_dif = displacementImg16.select([0]).multiply(-1)
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displacement16 = ee.Image([x_dif, y_dif]);
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preCMIcol = ee.ImageCollection(f"NOAA/GOES/{goes}/MCMIPF").filter(ee.Filter.date(pre_start, pre_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST
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preFDCcol = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(pre_start, pre_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST
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postCMIcol = ee.ImageCollection(f"NOAA/GOES/{goes}/MCMIPF").filter(ee.Filter.date(post_start, post_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST
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postFDCcol = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(post_start, post_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST
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prejoinedGOES = ee.Join.inner('CMI','FDC').apply(
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primary = preCMIcol,
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secondary = preFDCcol,
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condition = ee.Filter.maxDifference(
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difference = 10, #milliseconds
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leftField = 'system:time_start',
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rightField = 'system:time_start',))
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preMiddayGOEScol = ee.ImageCollection(prejoinedGOES.map(lambda object: MergeBands(object)))
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preMiddayGOEScol = preMiddayGOEScol.map(GcalcCCsingle)
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pre_meanNBR = preMiddayGOEScol.select(['NBR']).mean()
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pre_meanNBR = pre_meanNBR.multiply(1.18).subtract(0.12)
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postjoinedGOES = ee.Join.inner('CMI','FDC').apply(
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primary = postCMIcol,
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secondary = postFDCcol,
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condition = ee.Filter.maxDifference(
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difference = 10, #milliseconds
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leftField = 'system:time_start',
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rightField = 'system:time_start',))
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postMiddayGOEScol = ee.ImageCollection(postjoinedGOES.map(lambda object: MergeBands(object)))
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postMiddayGOEScol = postMiddayGOEScol.map(GcalcCCsingle)
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post_meanNBR = postMiddayGOEScol.select(['NBR']).mean()
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post_meanNBR = post_meanNBR.multiply(1.18).subtract(0.12)
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dNBR_goes17 = pre_meanNBR.subtract(post_meanNBR).select('NBR')
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#GOES-16
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preCMIcol = ee.ImageCollection("NOAA/GOES/16/MCMIPF").filter(ee.Filter.date(pre_start, pre_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST
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preFDCcol = ee.ImageCollection("NOAA/GOES/16/FDCF").filter(ee.Filter.date(pre_start, pre_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST
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prejoinedGOES = ee.Join.inner('CMI','FDC').apply(
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primary = preCMIcol,
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secondary = preFDCcol,
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condition = ee.Filter.maxDifference(
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difference = 10, #milliseconds
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leftField = 'system:time_start',
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rightField = 'system:time_start',))
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preMiddayGOEScol = ee.ImageCollection(prejoinedGOES.map(lambda object: MergeBands(object)))
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preMiddayGOEScol = preMiddayGOEScol.map(GcalcCCsingle)
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pre_meanNBR = preMiddayGOEScol.select(['NBR']).mean()
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pre_meanNBR = pre_meanNBR.multiply(1.18).subtract(0.12)
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postCMIcol = ee.ImageCollection("NOAA/GOES/16/MCMIPF").filter(ee.Filter.date(post_start, post_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST
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postFDCcol = ee.ImageCollection("NOAA/GOES/16/FDCF").filter(ee.Filter.date(post_start, post_stop))\
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.filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST
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postjoinedGOES = ee.Join.inner('CMI','FDC').apply(
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primary = postCMIcol,
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secondary = postFDCcol,
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condition = ee.Filter.maxDifference(
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difference = 10, #milliseconds
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leftField = 'system:time_start',
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rightField = 'system:time_start',))
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postMiddayGOEScol = ee.ImageCollection(postjoinedGOES.map(lambda object: MergeBands(object)))
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postMiddayGOEScol = postMiddayGOEScol.map(GcalcCCsingle)
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post_meanNBR = postMiddayGOEScol.select(['NBR']).mean()
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post_meanNBR = post_meanNBR.multiply(1.18).subtract(0.12)
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dNBR_goes16 = pre_meanNBR.subtract(post_meanNBR).select('NBR')
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dNBRclip_goes17= dNBR_goes17.clip(bbox)
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dNBRclip_goes16= dNBR_goes16.clip(bbox)
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dNBRdisp_goes17 = dNBRclip_goes17.displace(displacement18, 'bicubic')
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dNBRdisp_goes16 = dNBRclip_goes16.displace(displacement16, 'bicubic')
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dNBRgoes_compos = ee.ImageCollection([dNBRdisp_goes17,dNBRdisp_goes16]).mean()
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#ACTIVE fire
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activeFire18 = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(pre_stop, post_stop))
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activeFire16 = ee.ImageCollection(f"NOAA/GOES/16/FDCF").filter(ee.Filter.date(pre_stop, post_stop))
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sumFRP18 = activeFire18.select('Power').sum().rename('sumFRP')
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sumFRP16 = activeFire16.select('Power').sum().rename('sumFRP')
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maskNoFire18 = sumFRP18.gt(200).displace(displacement18, 'bicubic')
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maskNoFire16 = sumFRP16.gt(200).displace(displacement16, 'bicubic')
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maskNoFire = ee.ImageCollection([maskNoFire18,maskNoFire16]).sum().gt(0)
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'''
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activeSNPP = ee.ImageCollection("NASA/LANCE/SNPP_VIIRS/C2").filter(ee.Filter.date(pre_stop, post_stop))
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activeNOAA20 = ee.ImageCollection("NASA/LANCE/NOAA20_VIIRS/C2").filter(ee.Filter.date(pre_stop, post_stop))
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sumFRP_SNPP = activeSNPP.select('confidence').max().rename('sumFRP')
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sumFRP_NOAA20 = activeNOAA20.select('confidence').max().rename('sumFRP')
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#maskNoFire = ee.ImageCollection([sumFRP_SNPP,sumFRP_NOAA20]).sum().gt(0)
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maskNoFire = sumFRP_SNPP.gt(0)
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'''
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#VIIRS
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preVIIRSimg = ee.ImageCollection("NASA/VIIRS/002/VNP09GA").filter(ee.Filter.date(pre_start, pre_stop)).mean()
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#postVIIRSimgCol = ee.ImageCollection("NASA/VIIRS/002/VNP09GA").filter(ee.Filter.date(post_start, post_stop))
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postVIIRSimgCol = ee.ImageCollection("NASA/VIIRS/002/VNP09GA").filter(ee.Filter.date(post_start, post_stop)) #TO FIX ON JUNE 18 sfork_startDate.advance(24, 'day'), sfork_startDate.advance(25,'day')
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#Landsat
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prelandsat8col = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox)
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postlandsat8col = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").filterDate(post_start, post_stop).filterBounds(bbox)
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prelandsat9col = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox)
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postlandsat9col = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2").filterDate(post_start, post_stop).filterBounds(bbox)
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prelandsatcol = prelandsat8col.merge(prelandsat9col)
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postlandsatcol = postlandsat8col.merge(postlandsat9col)
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#Sentinel
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presentCol = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox)
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postsentCol = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filterDate(post_start, post_stop).filterBounds(bbox) #TO FIX on JULY 5: sfork_startDate.advance(32, 'day'), sfork_startDate.advance(33,'day')
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olderPostSentCol = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filterDate(sfork_startDate.advance(37, 'day'), sfork_startDate.advance(38,'day')).filterBounds(bbox)
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#SAR
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#SARimg = ee.Image('projects/ovcrge-ssec-burn-scar-map-c116/assets/burned_20200907_20200919_test')
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#SARmask = SARimg.eq(1)
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if postVIIRSimgCol.size().getInfo() > 0:
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280 |
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postVIIRSimg = postVIIRSimgCol.mean()
|
281 |
-
preVIIRSimg = VcalcNBR(preVIIRSimg)
|
282 |
-
postVIIRSimg = VcalcNBR(postVIIRSimg)
|
283 |
-
dNBR_viirs = preVIIRSimg.subtract(postVIIRSimg).select('NBR')
|
284 |
-
dNBRclip_viirs = dNBR_viirs.clip(bbox)
|
285 |
-
else:
|
286 |
-
dNBR_composite = dNBRgoes_compos
|
287 |
-
if postsentCol.size().getInfo() > 0:
|
288 |
-
presentMean = presentCol.mean()
|
289 |
-
postsentMean = postsentCol.mean()
|
290 |
-
postsent2Mean = olderPostSentCol.mean()
|
291 |
-
presentImg = ScalcNBR(presentMean)
|
292 |
-
postsentImg = ScalcNBR(postsentMean)
|
293 |
-
postsentImg2 = ScalcNBR(postsent2Mean)
|
294 |
-
postSentCombo = ee.ImageCollection([postsentImg,postsentImg2]).mosaic()
|
295 |
-
dnbr_sent = presentImg.subtract(postSentCombo).multiply(1.3).add(0.05).select('NBR')
|
296 |
-
dNBRclip_sent = dnbr_sent.clip(bbox)
|
297 |
-
dNBR_composite = ee.ImageCollection([dNBRgoes_compos,dNBRclip_viirs,dNBRclip_sent]).mosaic()
|
298 |
-
elif postlandsatcol.size().getInfo() > 0:
|
299 |
-
print(postlandsatcol.size().getInfo())
|
300 |
-
prelandsat = prelandsatcol.mean()
|
301 |
-
prelandsatImg = LcalcNBR(prelandsat)
|
302 |
-
postlandsat = postlandsatcol.mean()
|
303 |
-
postlandsatImg = LcalcNBR(postlandsat)
|
304 |
-
dNBR_landsat = prelandsatImg.subtract(postlandsatImg).multiply(3.23).add(0.01).select('NBR')
|
305 |
-
dNBRclip_ls = dNBR_landsat.clip(bbox)
|
306 |
-
dNBR_composite = ee.ImageCollection([dNBRgoes_compos,dNBRclip_viirs,dNBRclip_ls]).mosaic()
|
307 |
-
else:
|
308 |
-
dNBR_composite = ee.ImageCollection([dNBRgoes_compos,dNBRclip_viirs]).mosaic()
|
309 |
-
|
310 |
-
masked_compos = dNBR_composite.updateMask(maskNoFire) #(SARmask)
|
311 |
-
#doubleMasked_compos = masked_compos.updateMask(maskNoFire)
|
312 |
-
doubleMasked_compos = masked_compos.mask(masked_compos.mask()).float()
|
313 |
-
downloadArgs = {'name': 'VIIRS_burnMap',
|
314 |
-
'crs': 'EPSG:4326',
|
315 |
-
'scale': 60,
|
316 |
-
'region': bbox}
|
317 |
-
url = doubleMasked_compos.getDownloadURL(downloadArgs)
|
318 |
-
|
319 |
-
print(url)
|
320 |
-
noDataVal = -9999
|
321 |
-
unmaskedImage = doubleMasked_compos.unmask(noDataVal, False)
|
322 |
-
|
323 |
-
task = ee.batch.Export.image.toDrive(**{
|
324 |
-
'image': unmaskedImage,
|
325 |
-
'description': "Composite_burnMap6",
|
326 |
-
'folder': "Earth Engine Outputs",
|
327 |
-
'fileNamePrefix': "Composite_burnMap_noData_VIIRS_June18_espg3857_60m",
|
328 |
-
'region': bbox,
|
329 |
-
'crs': 'EPSG:3857',
|
330 |
-
'scale': 60,})
|
331 |
-
#task.start()
|
332 |
-
return masked_compos
|
333 |
-
|
334 |
-
|
335 |
-
self.clear_specific_layers()
|
336 |
-
|
337 |
-
if fire == "North Complex":
|
338 |
-
north_complex = calc_nbr(north_startDate.advance(-7, 'day'), north_startDate, north_startDate.advance(elapDayNum, 'day'), north_startDate.advance(elapDay_plusOne,'day'), north_complex_bb, 17)
|
339 |
-
self.addLayer(north_complex, dNBRvisParams, 'North Complex GOES NBR', True)
|
340 |
-
self.centerObject(north_complex_bb, 9)
|
341 |
-
file = north_complex
|
342 |
-
elif fire == "Dixie":
|
343 |
-
dixie = calc_nbr(dixie_startDate.advance(-7, 'day'), dixie_startDate, dixie_startDate.advance(elapDayNum, 'day'), dixie_startDate.advance(elapDay_plusOne,'day'), dixie_bb, 17)
|
344 |
-
self.addLayer(dixie, dNBRvisParams, 'Dixie Complex GOES NBR', True)
|
345 |
-
self.centerObject(dixie_bb, 9)
|
346 |
-
file = dixie
|
347 |
-
elif fire == "Cameron Peak":
|
348 |
-
cam_peak = calc_nbr(cam_startDate.advance(-7, 'day'), cam_startDate, cam_startDate.advance(elapDayNum, 'day'), cam_startDate.advance(elapDay_plusOne,'day'), cam_peak_bb, 17)
|
349 |
-
self.addLayer(cam_peak, dNBRvisParams, 'Cameron Peak GOES NBR', True)
|
350 |
-
self.centerObject(cam_peak_bb, 9)
|
351 |
-
file = cam_peak
|
352 |
-
elif fire == "August Complex":
|
353 |
-
aug_complex = calc_nbr(aug_startDate.advance(-7, 'day'), aug_startDate, aug_startDate.advance(elapDayNum, 'day'), aug_startDate.advance(elapDay_plusOne,'day'), aug_complex_bb, 17)
|
354 |
-
self.addLayer(aug_complex, dNBRvisParams, 'August Complex GOES NBR', True)
|
355 |
-
self.centerObject(aug_complex_bb, 9)
|
356 |
-
file = aug_complex
|
357 |
-
elif fire == "South Fork":
|
358 |
-
sfork = calc_nbr(sfork_startDate.advance(-7, 'day'), sfork_startDate, sfork_startDate.advance(elapDayNum, 'day'), sfork_startDate.advance(elapDay_plusOne,'day'), sfork_bb, 18)
|
359 |
-
self.addLayer(sfork, dNBRvisParams, 'South Fork GOES NBR', True)
|
360 |
-
self.centerObject(sfork_bb, 9)
|
361 |
-
file = sfork
|
362 |
-
|
363 |
-
def clear_specific_layers(self):
|
364 |
-
layers_to_keep = ['OpenStreetMap']
|
365 |
-
layers = list(self.layers)
|
366 |
-
for layer in layers:
|
367 |
-
if layer.name not in layers_to_keep:
|
368 |
-
self.remove_layer(layer)
|
369 |
-
|
370 |
-
|
371 |
-
def add_selector(self):
|
372 |
-
selector = widgets.Dropdown(options=fireList, value="South Fork", description='Wildfire Case Study:', style={'description_width': '125px'}, layout=widgets.Layout(width='400px'))
|
373 |
-
|
374 |
-
def on_selector_change(change):
|
375 |
-
if change['name'] == 'value':
|
376 |
-
selected_fire.value = change['new']
|
377 |
-
self.customize_ee_data(selected_fire.value, selected_days.value)
|
378 |
-
|
379 |
-
selector.observe(on_selector_change, names='value')
|
380 |
-
self.add_widget(selector, position="topleft")
|
381 |
-
|
382 |
-
def add_intSlider(self):
|
383 |
-
slider = widgets.IntSlider(value=selected_days.value,min=1,max=40,step=1,description='Elapsed days:',style={'description_width': '125px'}, layout=widgets.Layout(width='400px'))
|
384 |
-
|
385 |
-
def on_slider_change(change):
|
386 |
-
if change['name'] == 'value':
|
387 |
-
selected_days.value = change['new']
|
388 |
-
self.customize_ee_data(selected_fire.value, selected_days.value)
|
389 |
-
|
390 |
-
slider.observe(on_slider_change, names='value')
|
391 |
-
self.add_widget(slider, position="topleft")
|
392 |
-
|
393 |
-
def add_dwnldButton(self):
|
394 |
-
button = widgets.Button(description='Download',icon='cloud-arrow-down')
|
395 |
-
|
396 |
-
#def on_button_click(change, file):
|
397 |
-
# if change['name'] == 'value':
|
398 |
-
# selected_days.value = change['new']
|
399 |
-
# self.download_ee_image(file, "trial_file.tif", scale=30)
|
400 |
-
def on_button_click(b):
|
401 |
-
# Get the currently selected fire and elapsed days
|
402 |
-
fire = selected_fire.value
|
403 |
-
elapDays = selected_days.value
|
404 |
-
|
405 |
-
# Customize the EE data and download the image
|
406 |
-
file = self.customize_ee_data(fire, elapDays)
|
407 |
-
#self.download_ee_image(file, f"{fire}_NBR_{elapDays}days.tif", scale=30)
|
408 |
-
|
409 |
-
button.observe(on_button_click)
|
410 |
-
self.add_widget(button, position="topleft")
|
411 |
-
|
412 |
-
|
413 |
-
|
414 |
-
@solara.component
|
415 |
-
def Page():
|
416 |
-
|
417 |
-
with solara.Column(align="center"):
|
418 |
-
markdown = """
|
419 |
-
## Historical Western US wildfires from 2020-2021 """
|
420 |
-
solara.Markdown(markdown)
|
421 |
-
|
422 |
-
# Isolation is required to prevent the map from overlapping navigation (when screen width < 960px)
|
423 |
-
with solara.Column(style={"isolation": "isolate"}):
|
424 |
-
map_widget = Map.element(
|
425 |
-
center=[39, -120.5],
|
426 |
-
zoom=8,
|
427 |
-
height="600px",
|
428 |
-
toolbar_ctrl=False
|
429 |
-
)
|
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