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| import ee | |
| import geemap | |
| import solara | |
| import ipywidgets as widgets | |
| import datetime | |
| #from NBR_calculations import GcalcNBR, VcalcNBR, LcalcNBR, ScalcNBR, GcalcCCsingle | |
| import requests | |
| # 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 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) | |
| #createDates = NIFC_perims_716.aggregate_array('attr_Cre_1') | |
| #incidentIDs = NIFC_perims_716.aggregate_array('poly_Incid') | |
| #fireList = incidentIDs.getInfo() | |
| fireList = wildfire_names = [ "FRESNO JUNE LIGHTNING COMPLEX", "Larch Creek","Deadman","Cow Valley","0404 RV LONE ROCK", | |
| "PIONEER","South Fork", "Deer Springs","Basin","Lake","Horse Gulch","Falls","Silver King","Indios"] | |
| selected_fire = solara.reactive(fireList[6]) | |
| dNBRvisParams = {'min': 0.0,'max': 0.8, 'palette': ['green', 'yellow','orange','red']} | |
| today = datetime.datetime.today().strftime('%Y-%m-%d') | |
| class Map(geemap.Map): | |
| def __init__(self, **kwargs): | |
| super().__init__(**kwargs) | |
| self.add_basemap('OpenStreetMap') | |
| self.customize_ee_data(selected_fire.value, today) | |
| self.add_selector() | |
| self.add_dwnldButton() | |
| self.add("layer_manager") | |
| self.remove("draw_control") | |
| def customize_ee_data(self, fireID, elapDays): | |
| NIFC_perims_716 = ee.FeatureCollection('projects/ovcrge-ssec-burn-scar-map-c116/assets/NIFC_perimeters_7-16') | |
| fire = NIFC_perims_716.filter(ee.Filter.eq('poly_Incid',fireID)).first() | |
| timestamp = fire.get('attr_Cre_1') | |
| geom = fire.geometry() | |
| startDate = ee.Date(timestamp)#.format('YYYY-MM-dd') | |
| endDate = ee.Date.parse('YYYY-MM-dd', str(today)) | |
| boundingBox = ee.Geometry(geom.buffer(5000).bounds()) | |
| elapDayNum = ee.Number(10) | |
| elapDay_plusOne = elapDayNum.add(ee.Number(1)) | |
| def calc_nbr(pre_start, pre_stop, post_start, post_stop, bbox, goes): | |
| def MergeBands (eachImage): | |
| oneImage = ee.Image.cat(eachImage.get('CMI'), eachImage.get('FDC')) | |
| return oneImage | |
| displacementImg18 = ee.Image.load('projects/ee-losos/assets/G18-F-meter-offset_GEE') | |
| y_dif = displacementImg18.select([1]) | |
| x_dif = displacementImg18.select([0]).multiply(-1) | |
| displacement18 = ee.Image([x_dif, y_dif]) | |
| displacementImg16 = ee.Image.load('projects/ee-losos/assets/G16-F-meter-offset_GEE') | |
| y_dif = displacementImg16.select([1]) | |
| x_dif = displacementImg16.select([0]).multiply(-1) | |
| displacement16 = ee.Image([x_dif, y_dif]); | |
| preCMIcol = ee.ImageCollection(f"NOAA/GOES/{goes}/MCMIPF").filter(ee.Filter.date(pre_start, pre_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST | |
| preFDCcol = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(pre_start, pre_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST | |
| postCMIcol = ee.ImageCollection(f"NOAA/GOES/{goes}/MCMIPF").filter(ee.Filter.date(post_start, post_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST | |
| postFDCcol = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(post_start, post_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST | |
| prejoinedGOES = ee.Join.inner('CMI','FDC').apply( | |
| primary = preCMIcol, | |
| secondary = preFDCcol, | |
| condition = ee.Filter.maxDifference( | |
| difference = 10, #milliseconds | |
| leftField = 'system:time_start', | |
| rightField = 'system:time_start',)) | |
| preMiddayGOEScol = ee.ImageCollection(prejoinedGOES.map(lambda object: MergeBands(object))) | |
| preMiddayGOEScol = preMiddayGOEScol.map(GcalcCCsingle) | |
| pre_meanNBR = preMiddayGOEScol.select(['NBR']).mean() | |
| pre_meanNBR = pre_meanNBR.multiply(1.18).subtract(0.12) | |
| postjoinedGOES = ee.Join.inner('CMI','FDC').apply( | |
| primary = postCMIcol, | |
| secondary = postFDCcol, | |
| condition = ee.Filter.maxDifference( | |
| difference = 10, #milliseconds | |
| leftField = 'system:time_start', | |
| rightField = 'system:time_start',)) | |
| postMiddayGOEScol = ee.ImageCollection(postjoinedGOES.map(lambda object: MergeBands(object))) | |
| postMiddayGOEScol = postMiddayGOEScol.map(GcalcCCsingle) | |
| post_meanNBR = postMiddayGOEScol.select(['NBR']).mean() | |
| post_meanNBR = post_meanNBR.multiply(1.18).subtract(0.12) | |
| dNBR_goes17 = pre_meanNBR.subtract(post_meanNBR).select('NBR') | |
| #GOES-16 | |
| preCMIcol = ee.ImageCollection("NOAA/GOES/16/MCMIPF").filter(ee.Filter.date(pre_start, pre_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST | |
| preFDCcol = ee.ImageCollection("NOAA/GOES/16/FDCF").filter(ee.Filter.date(pre_start, pre_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST | |
| prejoinedGOES = ee.Join.inner('CMI','FDC').apply( | |
| primary = preCMIcol, | |
| secondary = preFDCcol, | |
| condition = ee.Filter.maxDifference( | |
| difference = 10, #milliseconds | |
| leftField = 'system:time_start', | |
| rightField = 'system:time_start',)) | |
| preMiddayGOEScol = ee.ImageCollection(prejoinedGOES.map(lambda object: MergeBands(object))) | |
| preMiddayGOEScol = preMiddayGOEScol.map(GcalcCCsingle) | |
| pre_meanNBR = preMiddayGOEScol.select(['NBR']).mean() | |
| pre_meanNBR = pre_meanNBR.multiply(1.18).subtract(0.12) | |
| postCMIcol = ee.ImageCollection("NOAA/GOES/16/MCMIPF").filter(ee.Filter.date(post_start, post_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour'))#10-2pm PCT, 11am-3pm MST | |
| postFDCcol = ee.ImageCollection("NOAA/GOES/16/FDCF").filter(ee.Filter.date(post_start, post_stop))\ | |
| .filter(ee.Filter.calendarRange(17, 21, 'hour')) #10-2pm PCT, 11am-3pm MST | |
| postjoinedGOES = ee.Join.inner('CMI','FDC').apply( | |
| primary = postCMIcol, | |
| secondary = postFDCcol, | |
| condition = ee.Filter.maxDifference( | |
| difference = 10, #milliseconds | |
| leftField = 'system:time_start', | |
| rightField = 'system:time_start',)) | |
| postMiddayGOEScol = ee.ImageCollection(postjoinedGOES.map(lambda object: MergeBands(object))) | |
| postMiddayGOEScol = postMiddayGOEScol.map(GcalcCCsingle) | |
| post_meanNBR = postMiddayGOEScol.select(['NBR']).mean() | |
| post_meanNBR = post_meanNBR.multiply(1.18).subtract(0.12) | |
| dNBR_goes16 = pre_meanNBR.subtract(post_meanNBR).select('NBR') | |
| dNBRclip_goes17= dNBR_goes17.clip(bbox) | |
| dNBRclip_goes16= dNBR_goes16.clip(bbox) | |
| dNBRdisp_goes17 = dNBRclip_goes17.displace(displacement18, 'bicubic') | |
| dNBRdisp_goes16 = dNBRclip_goes16.displace(displacement16, 'bicubic') | |
| dNBRgoes_compos = ee.ImageCollection([dNBRdisp_goes17,dNBRdisp_goes16]).mean() | |
| #ACTIVE fire | |
| activeFire18 = ee.ImageCollection(f"NOAA/GOES/{goes}/FDCF").filter(ee.Filter.date(pre_stop, post_stop)) | |
| activeFire16 = ee.ImageCollection(f"NOAA/GOES/16/FDCF").filter(ee.Filter.date(pre_stop, post_stop)) | |
| sumFRP18 = activeFire18.select('Power').sum().rename('sumFRP') | |
| sumFRP16 = activeFire16.select('Power').sum().rename('sumFRP') | |
| maskNoFire18 = sumFRP18.gt(200).displace(displacement18, 'bicubic') | |
| maskNoFire16 = sumFRP16.gt(200).displace(displacement16, 'bicubic') | |
| maskNoFire = ee.ImageCollection([maskNoFire18,maskNoFire16]).sum().gt(0) | |
| ''' | |
| activeSNPP = ee.ImageCollection("NASA/LANCE/SNPP_VIIRS/C2").filter(ee.Filter.date(pre_stop, post_stop)) | |
| activeNOAA20 = ee.ImageCollection("NASA/LANCE/NOAA20_VIIRS/C2").filter(ee.Filter.date(pre_stop, post_stop)) | |
| sumFRP_SNPP = activeSNPP.select('confidence').max().rename('sumFRP') | |
| sumFRP_NOAA20 = activeNOAA20.select('confidence').max().rename('sumFRP') | |
| #maskNoFire = ee.ImageCollection([sumFRP_SNPP,sumFRP_NOAA20]).sum().gt(0) | |
| maskNoFire = sumFRP_SNPP.gt(0) | |
| ''' | |
| #VIIRS | |
| preVIIRSimg = ee.ImageCollection("NASA/VIIRS/002/VNP09GA").filter(ee.Filter.date(pre_start, pre_stop)).mean() | |
| 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') | |
| #Landsat | |
| prelandsat8col = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox) | |
| postlandsat8col = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").filterDate(post_start, post_stop).filterBounds(bbox) | |
| prelandsat9col = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox) | |
| postlandsat9col = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2").filterDate(post_start, post_stop).filterBounds(bbox) | |
| prelandsatcol = prelandsat8col.merge(prelandsat9col) | |
| postlandsatcol = postlandsat8col.merge(postlandsat9col) | |
| #Sentinel | |
| presentCol = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filterDate(pre_start.advance(-10, 'day'), pre_stop).filterBounds(bbox) | |
| 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') | |
| #olderPostSentCol = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED").filterDate(sfork_startDate.advance(37, 'day'), sfork_startDate.advance(38,'day')).filterBounds(bbox) | |
| #SAR | |
| #SARimg = ee.Image('projects/ovcrge-ssec-burn-scar-map-c116/assets/burned_20200907_20200919_test') | |
| #SARmask = SARimg.eq(1) | |
| if postVIIRSimgCol.size().getInfo() > 0: | |
| postVIIRSimg = postVIIRSimgCol.mean() | |
| preVIIRSimg = VcalcNBR(preVIIRSimg) | |
| postVIIRSimg = VcalcNBR(postVIIRSimg) | |
| dNBR_viirs = preVIIRSimg.subtract(postVIIRSimg).select('NBR') | |
| dNBRclip_viirs = dNBR_viirs.clip(bbox) | |
| else: | |
| dNBR_composite = dNBRgoes_compos | |
| if postsentCol.size().getInfo() > 0: | |
| presentMean = presentCol.mean() | |
| postsentMean = postsentCol.mean() | |
| presentImg = ScalcNBR(presentMean) | |
| postsentImg = ScalcNBR(postsentMean) | |
| dnbr_sent = presentImg.subtract(postsentImg).multiply(1.3).add(0.05).select('NBR') | |
| dNBRclip_sent = dnbr_sent.clip(bbox) | |
| dNBR_composite = ee.ImageCollection([dNBRgoes_compos,dNBRclip_sent]).mosaic() #dNBRclip_viirs SHOULD GO IN IF UP TO DATE | |
| elif postlandsatcol.size().getInfo() > 0: | |
| prelandsat = prelandsatcol.mean() | |
| prelandsatImg = LcalcNBR(prelandsat) | |
| postlandsat = postlandsatcol.mean() | |
| postlandsatImg = LcalcNBR(postlandsat) | |
| dNBR_landsat = prelandsatImg.subtract(postlandsatImg).multiply(3.23).add(0.01).select('NBR') | |
| dNBRclip_ls = dNBR_landsat.clip(bbox) | |
| dNBR_composite = ee.ImageCollection([dNBRgoes_compos,dNBRclip_ls]).mosaic() #dNBRclip_viirs SHOULD GO IN IF UP TO DATE | |
| else: | |
| dNBR_composite = ee.ImageCollection([dNBRgoes_compos]).mosaic() #dNBRclip_viirs SHOULD GO IN IF UP TO DATE | |
| masked_compos = dNBR_composite.updateMask(maskNoFire) #(SARmask) | |
| #doubleMasked_compos = masked_compos.updateMask(maskNoFire) | |
| doubleMasked_compos = masked_compos.mask(masked_compos.mask()).float() | |
| downloadArgs = {'name': 'VIIRS_burnMap', | |
| 'crs': 'EPSG:4326', | |
| 'scale': 60, | |
| 'region': bbox} | |
| url = doubleMasked_compos.getDownloadURL(downloadArgs) | |
| print(url) | |
| noDataVal = -9999 | |
| unmaskedImage = doubleMasked_compos.unmask(noDataVal, False) | |
| task = ee.batch.Export.image.toDrive(**{ | |
| 'image': unmaskedImage, | |
| 'description': "Composite_burnMap6", | |
| 'folder': "Earth Engine Outputs", | |
| 'fileNamePrefix': "Composite_burnMap_noData_VIIRS_June18_espg3857_60m", | |
| 'region': bbox, | |
| 'crs': 'EPSG:3857', | |
| 'scale': 60,}) | |
| task.start() | |
| return masked_compos | |
| self.clear_specific_layers() | |
| fireImg = calc_nbr(startDate.advance(-7, 'day'), startDate, endDate.advance(-3, 'day'), endDate, boundingBox, 18) | |
| self.addLayer(fireImg, dNBRvisParams, fireID, True) | |
| self.centerObject(boundingBox, 10) | |
| file = fireImg | |
| def clear_specific_layers(self): | |
| layers_to_keep = ['OpenStreetMap'] | |
| layers = list(self.layers) | |
| for layer in layers: | |
| if layer.name not in layers_to_keep: | |
| self.remove_layer(layer) | |
| def add_selector(self): | |
| selector = widgets.Dropdown(options=fireList, value=fireList[6], description='Current wildfire :', style={'description_width': '125px'}, layout=widgets.Layout(width='400px')) | |
| def on_selector_change(change): | |
| if change['name'] == 'value': | |
| selected_fire.value = change['new'] | |
| self.customize_ee_data(selected_fire.value, today) | |
| selector.observe(on_selector_change, names='value') | |
| self.add_widget(selector, position="topleft") | |
| def add_dwnldButton(self): | |
| button = widgets.Button(description='Export to Drive',icon='cloud-arrow-down') | |
| #def on_button_click(change, file): | |
| # if change['name'] == 'value': | |
| # selected_days.value = change['new'] | |
| # self.download_ee_image(file, "trial_file.tif", scale=30) | |
| def on_button_click(b): | |
| # Get the currently selected fire and elapsed days | |
| fire = selected_fire.value | |
| elapDays = today | |
| # Customize the EE data and download the image | |
| file = self.customize_ee_data(fire, elapDays) | |
| #self.download_ee_image(file, f"{fire}_NBR_{elapDays}days.tif", scale=30) | |
| button.observe(on_button_click) | |
| self.add_widget(button, position="topleft") | |
| def Page(): | |
| with solara.Column(align="center"): | |
| markdown = """ | |
| ## Current 2024 wildfires over 10,000 acres""" | |
| solara.Markdown(markdown) | |
| # Isolation is required to prevent the map from overlapping navigation (when screen width < 960px) | |
| with solara.Column(style={"isolation": "isolate"}): | |
| map_widget = Map.element( | |
| center=[39, -120.5], | |
| zoom=8, | |
| height="600px", | |
| toolbar_ctrl=False | |
| ) |