def AtmosphericCorrection(BandId):
global metedata, config, SatelliteID, SensorID
#读取头文件
dom = xml.dom.minidom.parse(metedata)
# 6S模型
s = SixS()
# 传感器类型 自定义
s.geometry = Geometry.User()
s.geometry.solar_z = 90 - float(
dom.getElementsByTagName('SolarZenith')[0].firstChild.data)
s.geometry.solar_a = float(
dom.getElementsByTagName('SolarAzimuth')[0].firstChild.data)
# s.geometry.view_z = float(dom.getElementsByTagName('SatelliteZenith')[0].firstChild.data)
# s.geometry.view_a = float(dom.getElementsByTagName('SatelliteAzimuth')[0].firstChild.data)
s.geometry.view_z = 0
s.geometry.view_a = 0
# 日期
DateTimeparm = dom.getElementsByTagName('CenterTime')[0].firstChild.data
DateTime = DateTimeparm.split(' ')
Date = DateTime[0].split('-')
s.geometry.month = int(Date[1])
s.geometry.day = int(Date[2])
# print(s.geometry)
# 中心经纬度
TopLeftLat = float(
dom.getElementsByTagName('TopLeftLatitude')[0].firstChild.data)
TopLeftLon = float(
dom.getElementsByTagName('TopLeftLongitude')[0].firstChild.data)
TopRightLat = float(
dom.getElementsByTagName('TopRightLatitude')[0].firstChild.data)
TopRightLon = float(
dom.getElementsByTagName('TopRightLongitude')[0].firstChild.data)
BottomRightLat = float(
dom.getElementsByTagName('BottomRightLatitude')[0].firstChild.data)
BottomRightLon = float(
dom.getElementsByTagName('BottomRightLongitude')[0].firstChild.data)
BottomLeftLat = float(
dom.getElementsByTagName('BottomLeftLatitude')[0].firstChild.data)
BottomLeftLon = float(
dom.getElementsByTagName('BottomLeftLongitude')[0].firstChild.data)
ImageCenterLat = (TopLeftLat + TopRightLat + BottomRightLat +
BottomLeftLat) / 4
# 大气模式类型
if ImageCenterLat > -15 and ImageCenterLat < 15:
s.atmos_profile = AtmosProfile.PredefinedType(AtmosProfile.Tropical)
if ImageCenterLat > 15 and ImageCenterLat < 45:
if s.geometry.month > 4 and s.geometry.month < 9:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.MidlatitudeSummer)
else:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.MidlatitudeWinter)
if ImageCenterLat > 45 and ImageCenterLat < 60:
if s.geometry.month > 4 and s.geometry.month < 9:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.SubarcticSummer)
else:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.SubarcticWinter)
# 气溶胶类型大陆
s.aero_profile = AtmosProfile.PredefinedType(AeroProfile.Continental)
# 下垫面类型
s.ground_reflectance = GroundReflectance.HomogeneousLambertian(0.36)
# 550nm气溶胶光学厚度,对应能见度为40km
s.aot550 = 0.14497
# 通过研究去区的范围去求DEM高度。
pointUL = dict()
pointDR = dict()
pointUL["lat"] = max(TopLeftLat, TopRightLat, BottomRightLat,
BottomLeftLat)
pointUL["lon"] = min(TopLeftLon, TopRightLon, BottomRightLon,
BottomLeftLon)
pointDR["lat"] = min(TopLeftLat, TopRightLat, BottomRightLat,
BottomLeftLat)
pointDR["lon"] = max(TopLeftLon, TopRightLon, BottomRightLon,
BottomLeftLon)
meanDEM = (MeanDEM(pointUL, pointDR)) * 0.001
# 研究区海拔、卫星传感器轨道高度
s.altitudes = Altitudes()
s.altitudes.set_target_custom_altitude(meanDEM)
s.altitudes.set_sensor_satellite_level()
# 校正波段（根据波段名称）
if BandId == 1:
SRFband = config["Parameter"][SatelliteID][SensorID]["SRF"]["1"]
s.wavelength = Wavelength(0.450, 0.520, SRFband)
elif BandId == 2:
SRFband = config["Parameter"][SatelliteID][SensorID]["SRF"]["2"]
s.wavelength = Wavelength(0.520, 0.590, SRFband)
elif BandId == 3:
SRFband = config["Parameter"][SatelliteID][SensorID]["SRF"]["3"]
s.wavelength = Wavelength(0.630, 0.690, SRFband)
elif BandId == 4:
SRFband = config["Parameter"][SatelliteID][SensorID]["SRF"]["4"]
s.wavelength = Wavelength(0.770, 0.890, SRFband)
s.atmos_corr = AtmosCorr.AtmosCorrLambertianFromReflectance(-0.1)
# 运行6s大气模型
s.run()
xa = s.outputs.coef_xa
xb = s.outputs.coef_xb
xc = s.outputs.coef_xc
# x = s.outputs.values
return (xa, xb, xc)
def AtmosphericCorrection(BandId):
global data
# 6S模型
s = SixS()
s.geometry = Geometry.User()
s.geometry.solar_z = 90 - float(''.join(
re.findall('SUN_ELEVATION.+', data2)).split("=")[1])
s.geometry.solar_a = float(''.join(re.findall('SUN_AZIMUTH.+',
data2)).split("=")[1])
s.geometry.view_z = 0
s.geometry.view_a = 0
# 日期
Dateparm = ''.join(re.findall('DATE_ACQUIRED.+', data2)).split("=")
Date = Dateparm[1].split('-')
s.geometry.month = int(Date[1])
s.geometry.day = int(Date[2])
# 中心经纬度
point1lat = float(''.join(re.findall('CORNER_UL_LAT_PRODUCT.+',
data2)).split("=")[1])
point1lon = float(''.join(re.findall('CORNER_UL_LON_PRODUCT.+',
data2)).split("=")[1])
point2lat = float(''.join(re.findall('CORNER_UR_LAT_PRODUCT.+',
data2)).split("=")[1])
point2lon = float(''.join(re.findall('CORNER_UR_LON_PRODUCT.+',
data2)).split("=")[1])
point3lat = float(''.join(re.findall('CORNER_LL_LAT_PRODUCT.+',
data2)).split("=")[1])
point3lon = float(''.join(re.findall('CORNER_LL_LON_PRODUCT.+',
data2)).split("=")[1])
point4lat = float(''.join(re.findall('CORNER_LR_LAT_PRODUCT.+',
data2)).split("=")[1])
point4lon = float(''.join(re.findall('CORNER_LR_LON_PRODUCT.+',
data2)).split("=")[1])
sLongitude = (point1lon + point2lon + point3lon + point4lon) / 4
sLatitude = (point1lat + point2lat + point3lat + point4lat) / 4
# 大气模式类型
if sLatitude > -15 and sLatitude <= 15:
s.atmos_profile = AtmosProfile.PredefinedType(AtmosProfile.Tropical)
if sLatitude > 15 and sLatitude <= 45:
if s.geometry.month > 4 and s.geometry.month <= 9:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.MidlatitudeSummer)
else:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.MidlatitudeWinter)
if sLatitude > 45 and sLatitude <= 60:
if s.geometry.month > 4 and s.geometry.month <= 9:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.SubarcticSummer)
else:
s.atmos_profile = AtmosProfile.PredefinedType(
AtmosProfile.SubarcticWinter)
# 气溶胶类型大陆
s.aero_profile = AtmosProfile.PredefinedType(AeroProfile.Continental)
# 目标地物？？？？？？
s.ground_reflectance = GroundReflectance.HomogeneousLambertian(0.36)
# 550nm气溶胶光学厚度,根据日期从MODIS处获取。
#s.visibility=40.0
s.aot550 = 0.14497
# 通过研究去区的范围去求DEM高度。
pointUL = dict()
pointDR = dict()
pointUL["lat"] = point1lat
pointUL["lon"] = point1lon
pointDR["lat"] = point4lat
pointDR["lon"] = point2lon
meanDEM = (MeanDEM(pointUL, pointDR)) * 0.001
# 研究区海拔、卫星传感器轨道高度
s.altitudes = Altitudes()
s.altitudes.set_target_custom_altitude(meanDEM)
s.altitudes.set_sensor_satellite_level()
# 校正波段（根据波段名称）
if BandId == '1':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B1)
elif BandId == '2':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B2)
elif BandId == '3':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B3)
elif BandId == '4':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B4)
elif BandId == '5':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B5)
elif BandId == '6':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B6)
elif BandId == '7':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B7)
elif BandId == '8':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B8)
elif BandId == '9':
s.wavelength = Wavelength(PredefinedWavelengths.LANDSAT_OLI_B9)
# 下垫面非均一、朗伯体
s.atmos_corr = AtmosCorr.AtmosCorrLambertianFromReflectance(-0.1)
# 运行6s大气模型
s.run()
xa = s.outputs.coef_xa
xb = s.outputs.coef_xb
xc = s.outputs.coef_xc
x = s.outputs.values
return (xa, xb, xc)
def BasicParameters():
'''
获取6s大气校正所需的参数
'''
global dom
SixsParameters = dict()
#太阳天顶角、方位角
SunAngle = dom.getElementsByTagName('Mean_Sun_Angle')
SixsParameters["SolarZenithAngle"] = float(
SunAngle[0].getElementsByTagName('ZENITH_ANGLE')[0].firstChild.data)
SixsParameters["SolarAzimuthAngle"] = float(
SunAngle[0].getElementsByTagName('AZIMUTH_ANGLE')[0].firstChild.data)
#卫星天顶角、方位角
ViewAngles = dom.getElementsByTagName('Mean_Viewing_Incidence_Angle')
ViewZeniths = dict()
ViewAzimuths = dict()
for angle in ViewAngles:
ViewAngle = int(angle.getAttribute('bandId'))
#print(ViewAngle)
ViewZeniths[ViewAngle + 1] = float(
angle.getElementsByTagName('ZENITH_ANGLE')[0].firstChild.data)
ViewAzimuths[ViewAngle + 1] = float(
angle.getElementsByTagName('AZIMUTH_ANGLE')[0].firstChild.data)
SixsParameters["ViewZenithAngle"] = ViewZeniths
SixsParameters["ViewAzimuthAngle"] = ViewAzimuths
# 日期:月、日
Date = dom.getElementsByTagName('SENSING_TIME')[0].firstChild.data.split(
'T')[0]
SixsParameters["ImgMonth"] = int(Date.split('-')[1])
SixsParameters["ImgDay"] = int(Date.split('-')[2])
#求影像中心经纬度
PointULX = int(dom.getElementsByTagName('ULX')[0].firstChild.data)
PointULY = int(dom.getElementsByTagName('ULY')[0].firstChild.data)
Imgsizes = dom.getElementsByTagName('Size')
for Imgsize in Imgsizes:
Resolution = Imgsize.getAttribute('resolution')
if Resolution == '10':
SixsParameters["Nrows"] = int(
Imgsize.getElementsByTagName('NROWS')[0].firstChild.data)
SixsParameters["Ncols"] = int(
Imgsize.getElementsByTagName('NCOLS')[0].firstChild.data)
PointBRX = PointULX + 10 * SixsParameters["Ncols"]
PointBRY = PointULY - 10 * SixsParameters["Nrows"]
# 将投影坐标转为经纬度坐标（具体的投影坐标系由给定数据确定）
Proj = dom.getElementsByTagName('HORIZONTAL_CS_CODE')[0].firstChild.data
ProjCode = int(Proj.split(':')[1])
source = osr.SpatialReference()
source.ImportFromEPSG(ProjCode)
target = osr.SpatialReference()
target.ImportFromEPSG(4326)
ct = osr.CoordinateTransformation(source, target)
CoordsUL, CoordsBR = ct.TransformPoints([(PointULX, PointULY),
(PointBRX, PointBRY)])
ULLat = CoordsUL[0]
ULLon = CoordsUL[1]
BRLat = CoordsBR[0]
BRLon = CoordsBR[1]
sLongitude = (ULLon + BRLon) / 2
sLatitude = (ULLat + ULLat) / 2
#大气模式类型
if sLatitude > -15 and sLatitude <= 15:
SixsParameters["AtmosphericProfile"] = 1 #Tropical
elif sLatitude > 15 and sLatitude <= 45:
if SixsParameters["ImgMonth"] > 4 and SixsParameters["ImgMonth"] <= 9:
SixsParameters["AtmosphericProfile"] = 2 #MidlatitudeSummer
else:
SixsParameters["AtmosphericProfile"] = 3 #MidlatitudeWinter
elif sLatitude > 45 and sLatitude <= 60:
if SixsParameters["ImgMonth"] > 4 and SixsParameters["ImgMonth"] <= 9:
SixsParameters["AtmosphericProfile"] = 4 #SubarctivWinter
else:
SixsParameters["AtmosphericProfile"] = 5 #SubarcticWinter
pointUL = dict()
pointDR = dict()
pointUL["lat"] = ULLat
pointUL["lon"] = ULLon
pointDR["lat"] = BRLat
pointDR["lon"] = BRLon
SixsParameters["meanDEM"] = (MeanDEM(pointUL, pointDR)) * 0.001
return SixsParameters