def get_ref(self):
"""
return Ref
"""
data = dict()
if self.resolution == 750: # 分辨率为 1000
satellite_type1 = ['NPP', 'JPSS-1']
# NPP
if self.satellite in satellite_type1:
data_file = self.in_file
with h5py.File(data_file, 'r') as h5r:
# 前12个通道是ref
# 由于不确定性 比较了14和15年的数据值一致，定值。偶尔出现-999.33导致计算错
ref_a = 2.4417415E-5
vmin = 0
vmax = 60000
sunz = self.get_solar_zenith()
dsl = sun_earth_dis_correction(self.ymd)
# 逐个通道处理
for i in xrange(1, 12, 1):
band = 'CH_{:02d}'.format(i)
sds_name = '/All_Data/VIIRS-M%d-SDR_All/Reflectance' % i
ary_ref = h5r.get(sds_name)[:]
data_pre = ary_ref
data_pre = data_pre.astype(np.float32)
invalid_index = np.logical_or(data_pre <= vmin,
data_pre > vmax)
data_pre[invalid_index] = np.nan
# 修正，徐娜提供
data[band] = data_pre * ref_a * \
np.cos(np.deg2rad(sunz)) * dsl
else:
raise ValueError('Cant read this satellite`s data.: {}'.format(
self.satellite))
else:
raise ValueError(
'Cant read this data, please check its resolution: {}'.format(
self.in_file))
return data
def get_ref(self):
"""
return ref
"""
data = dict()
dsl = sun_earth_dis_correction(self.ymd)
if self.resolution == 1000: # 分辨率为 1000
satellite_type = ['AQUA', 'TERRA']
data_file = self.in_file
if self.satellite in satellite_type:
dn = self.get_dn()
h4r = SD(data_file, SDC.READ)
# 12通道ab
ary_ch1_2_a = h4r.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_scales']
ary_ch1_2_b = h4r.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_offsets']
ary_ch3_7_a = h4r.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_scales']
ary_ch3_7_b = h4r.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_offsets']
ary_ch8_19and26_a = h4r.select(
'EV_1KM_RefSB').attributes()['reflectance_scales']
ary_ch8_19and26_b = h4r.select(
'EV_1KM_RefSB').attributes()['reflectance_offsets']
# ary_ch20_36_a = h4r.select(
# 'EV_1KM_Emissive').attributes()['radiance_scales']
# ary_ch20_36_b = h4r.select(
# 'EV_1KM_Emissive').attributes()['radiance_offsets']
h4r.end()
# 删除13i 14i通道的下标
ary_ch8_19and26_a.pop(6)
ary_ch8_19and26_a.pop(8)
# 逐个通道处理
for i in xrange(self.channels):
band = 'CH_{:02d}'.format(i + 1)
# 1,2通道
if i < 2:
k = i
data_pre = (dn[band] - ary_ch1_2_b[k]) * ary_ch1_2_a[k]
# 3,4,5,6,7通道
elif i >= 2 and i < 7:
k = i - 2
data_pre = (dn[band] - ary_ch3_7_b[k]) * ary_ch3_7_a[k]
# 8,9,10,11,12,13lo,14lo,15,16,17,18,19,26通道
elif i >= 7 and i <= 19:
k = i - 7
if i == 19:
band = 'CH_{:02d}'.format(i + 7)
data_pre = (dn[band] - ary_ch8_19and26_b[k]
) * ary_ch8_19and26_a[k]
else:
continue
data[band] = data_pre * dsl
return data
def Load(self, L1File):
print u'读取 L1所有数据信息...... %s' % L1File
try:
h5File_R = h5py.File(L1File, 'r')
ary_lon = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/Longitude')[:]
ary_lat = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/Latitude')[:]
ary_satz = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SatelliteZenithAngle')[:]
ary_sata = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SatelliteAzimuthAngle')[:]
ary_sunz = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SolarZenithAngle')[:]
ary_suna = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SolarAzimuthAngle')[:]
ary_time = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/StartTime')[:]
Ref = {}
# 由于不确定性 比较了14和15年的数据值一致，定值。偶尔出现-999.33导致计算错
Ref_a = 2.4417415E-5
Rad = {}
Rad_a = {}
Rad_b = {}
Tbb = {}
Tbb_a = {}
Tbb_b = {}
for i in xrange(1, 17, 1):
if i < 12:
Ref[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/Reflectance' % i)[:]
elif i == 13:
Rad[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/Radiance' % i)[:]
Tbb[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperature' % i)[:]
Rad_a[i] = 1.
Rad_b[i] = 0.
Tbb_a[i] = 1.
Tbb_b[i] = 0.
else:
Rad[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/Radiance' % i)[:]
Rad_a[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/RadianceFactors' % i)[:][0]
Rad_b[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/RadianceFactors' % i)[:][1]
Tbb[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperature' % i)[:]
Tbb_a[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperatureFactors' % i)[:][0]
Tbb_b[i] = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperatureFactors' % i)[:][1]
except Exception as e:
print str(e)
finally:
h5File_R.close()
# 11111111通道的中心波数和光谱响应
# for i in xrange(self.Band):
i = 14
BandName = 'CH_%02d' % (i + 1)
srfFile = os.path.join(
MainPath, 'SRF', '%s_%s_SRF_CH%02d_Pub.txt' % (self.sat, self.sensor, (i + 1)))
dictWave = np.loadtxt(
srfFile, dtype={'names': ('num', 'rad'), 'formats': ('f4', 'f4')})
waveNum = 10 ** 7 / dictWave['num'][::-1]
waveRad = dictWave['rad'][::-1]
self.waveNum[BandName] = waveNum
self.waveRad[BandName] = waveRad
# 2222222 数据大小 使用经度维度 ###############
dshape = ary_lon.shape
# 对时间进行赋值合并
v_ymd2seconds = np.vectorize(npp_ymd2seconds)
T1 = v_ymd2seconds(ary_time)
Time = np.full(dshape, -999)
for i in xrange(len(Time)):
Time[i, :] = T1[i / 16]
if self.Time == []:
self.Time = Time
else:
self.Time = np.concatenate((self.Time, Time))
ymd = time.gmtime(self.Time[0, 0])
ymd1 = time.strftime('%Y%m%d', ymd)
dsol = sun_earth_dis_correction(ymd1)
# 3333333 1-12通道的可见光数据进行定标 ########
for i in range(1, 12, 1):
BandName = 'CH_%02d' % i
condition = np.logical_and(Ref[i] > 0, Ref[i] < 65500)
idx = np.where(condition)
Ref_data = np.full(dshape, np.nan)
Ref_data[idx] = Ref[i][idx]
Ref_data = Ref_data * Ref_a * np.cos(np.deg2rad(ary_sunz)) * dsol
if BandName not in self.Ref.keys():
self.Ref[BandName] = Ref_data
else:
self.Ref[BandName] = np.concatenate(
(self.Ref[BandName], Ref_data))
# 红外
for i in xrange(12, 17, 1):
BandName = 'CH_%02d' % i
condition = np.logical_and(Rad[i] > 0, Rad[i] < 65500)
idx = np.where(condition)
Rad_data = np.full(dshape, np.nan)
Tbb_data = np.full(dshape, np.nan)
Rad_data[idx] = Rad[i][idx] * \
((10000 / self.WN[BandName]) ** 2) / 10.
Rad_data[idx] = Rad_data[idx] * Rad_a[i] + Rad_b[i]
Tbb_data[idx] = Tbb[i][idx] * Tbb_a[i] + Tbb_b[i]
if BandName not in self.Rad.keys():
self.Rad[BandName] = Rad_data
else:
self.Rad[BandName] = np.concatenate(
(self.Rad[BandName], Rad_data))
if BandName not in self.Tbb.keys():
self.Tbb[BandName] = Tbb_data
else:
self.Tbb[BandName] = np.concatenate(
(self.Tbb[BandName], Tbb_data))
# 经纬度
ary_lon_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_lon > -180., ary_lon < 180.)
ary_lon_idx[condition] = ary_lon[condition]
if self.Lons == []:
self.Lons = ary_lon_idx
else:
self.Lons = np.concatenate((self.Lons, ary_lon_idx))
ary_lat_idx = np.full(dshape, np.nan)
condition = np.logical_and(ary_lat > -90., ary_lat < 90.)
ary_lat_idx[condition] = ary_lat[condition]
if self.Lats == []:
self.Lats = ary_lat_idx
else:
self.Lats = np.concatenate((self.Lats, ary_lat_idx))
# 角度信息
if self.satAzimuth == []:
self.satAzimuth = ary_sata
else:
self.satAzimuth = np.concatenate((self.satAzimuth, ary_sata))
if self.satZenith == []:
self.satZenith = ary_satz
else:
self.satZenith = np.concatenate((self.satZenith, ary_satz))
if self.sunAzimuth == []:
self.sunAzimuth = ary_suna
else:
self.sunAzimuth = np.concatenate((self.sunAzimuth, ary_suna))
if self.sunZenith == []:
self.sunZenith = ary_sunz
else:
self.sunZenith = np.concatenate((self.sunZenith, ary_sunz))
def Load(self, L1File):
print(u'读取 L1 %s' % L1File)
iname = os.path.basename(L1File)
try:
h4File = SD(L1File, SDC.READ)
# 读取1-2通道数据
in_data_r250 = h4File.select('EV_250_Aggr1km_RefSB').get()
in_data_r250_s = h4File.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_scales']
in_data_r250_o = h4File.select(
'EV_250_Aggr1km_RefSB').attributes()['reflectance_offsets']
# 读取 3-7通道数据
in_data_r500 = h4File.select('EV_500_Aggr1km_RefSB').get()
in_data_r500_s = h4File.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_scales']
in_data_r500_o = h4File.select(
'EV_500_Aggr1km_RefSB').attributes()['reflectance_offsets']
# 读取8-20通道， 包含26通道
in_data_r1km = h4File.select('EV_1KM_RefSB').get()
in_data_r1km_s = h4File.select(
'EV_1KM_RefSB').attributes()['reflectance_scales']
in_data_r1km_o = h4File.select(
'EV_1KM_RefSB').attributes()['reflectance_offsets']
# 读取20-36通道 不包含26通道
in_data_t1km = h4File.select('EV_1KM_Emissive').get()
in_data_t1km_s = h4File.select(
'EV_1KM_Emissive').attributes()['radiance_scales']
in_data_t1km_o = h4File.select(
'EV_1KM_Emissive').attributes()['radiance_offsets']
except Exception as e:
print str(e)
finally:
h4File.end()
# 处理定位文件，默认和L1同一目录
geoFile = find_modis_geo_file(L1File)
print(u'读取geo %s' % geoFile)
try:
h4File = SD(geoFile, SDC.READ)
in_data_lon = h4File.select('Longitude').get()
in_data_lat = h4File.select('Latitude').get()
# in_data_LandSeaMask = h4File.select('Land/SeaMask').get() #
# 多个/不知道是bug还是就这样
in_data_satz = h4File.select('SensorZenith').get()
in_data_satz_s = h4File.select(
'SensorZenith').attributes()['scale_factor']
in_data_sata = h4File.select('SensorAzimuth').get()
in_data_sata_s = h4File.select(
'SensorAzimuth').attributes()['scale_factor']
in_data_sunz = h4File.select('SolarZenith').get()
in_data_sunz_s = h4File.select(
'SolarZenith').attributes()['scale_factor']
in_data_suna = h4File.select('SolarAzimuth').get()
in_data_suna_s = h4File.select(
'SolarAzimuth').attributes()['scale_factor']
except Exception as e:
print(str(e))
finally:
h4File.end()
# 角度信息赋值
self.satZenith = in_data_satz * in_data_satz_s
self.satAzimuth = in_data_sata * in_data_sata_s
self.sunZenith = in_data_sunz * in_data_sunz_s
self.sunAzimuth = in_data_suna * in_data_suna_s
self.Lons = in_data_lon
self.Lats = in_data_lat
# 1-2通道
modis_shape2 = in_data_r250.shape[1:]
modis_shape3 = (38, ) + modis_shape2
data_ch38 = np.full(modis_shape3, np.nan)
for i in range(0, 2, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r250[i] < 32767,
in_data_r250[i] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r250[i][idx] -
in_data_r250_o[i]) * in_data_r250_s[i]
# 3-7通道
for i in range(2, 7, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r500[i - 2] < 32767,
in_data_r500[i - 2] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r500[i - 2][idx] -
in_data_r500_o[i - 2]) * in_data_r500_s[i - 2]
# 8-19 外加一个 26通道
for i in range(7, 22, 1):
# 过滤 无效值
condition = np.logical_and(in_data_r1km[i - 7] < 32767,
in_data_r1km[i - 7] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_r1km[i - 7][idx] -
in_data_r1km_o[i - 7]) * in_data_r1km_s[i - 7]
# 20-36通道 不包括26通道
for i in range(22, 38, 1):
# 过滤 无效值
condition = np.logical_and(in_data_t1km[i - 22] < 32767,
in_data_t1km[i - 22] > 0)
idx = np.where(condition)
data_ch38[i][idx] = (in_data_t1km[i - 22][idx] -
in_data_t1km_o[i - 22]) * in_data_t1km_s[i -
22]
# 删除通道13hi 和 14 hi
data_ch36 = np.delete(data_ch38, (13, 15), 0)
newRad = np.full((16, ) + modis_shape2, np.nan)
# 对时间进行赋值
self.Time = np.full(modis_shape2, -999.)
nameClass = pb_name.nameClassManager()
info = nameClass.getInstance(iname)
ymd = info.dt_s.strftime('%Y%m%d')
print ymd
dsol = sun_earth_dis_correction(ymd)
# print info.dt_s
secs = int((info.dt_s - datetime(1970, 1, 1, 0, 0, 0)).total_seconds())
self.Time[:] = secs
# 把modis的rad转换和FY的单位一致
# 20,21, 22,23,24,25,27,28,29,30,31,32,33,34,35,36
cwn = [
2.647409E+03, 2.511760E+03, 2.517908E+03, 2.462442E+03,
2.248296E+03, 2.209547E+03, 1.474262E+03, 1.361626E+03,
1.169626E+03, 1.028740E+03, 9.076813E+02, 8.308411E+02,
7.482978E+02, 7.307766E+02, 7.182094E+02, 7.035007E+02
]
for i in xrange(16):
newRad[i] = data_ch36[i + 20] * \
((10000 / cwn[i]) ** 2) / 10. * dsol
if i <= 5:
self.Rad['CH_%02d' % (i + 20)] = newRad[i]
else:
self.Rad['CH_%02d' % (i + 21)] = newRad[i]
# 把rad转亮温
radiance2tbb(data_ch36)
# 整理通道顺序，把26通道放在对应的26通道
# del26_data_ch35 = np.delete(data_ch36, 19, 0)
# order_data_ch36 = np.insert(del26_data_ch35, 25, data_ch36[19], 0)
for i in range(0, 36, 1):
# self.CA['CH_%02d' % (i + 1)] = order_data_ch36[i]
if i < 19:
self.Ref['CH_%02d' % (i + 1)] = data_ch36[i]
elif i == 19: # 26
self.Ref['CH_%02d' % (i + 7)] = data_ch36[i]
elif i > 19 and i <= 25:
self.Tbb['CH_%02d' % (i)] = data_ch36[i]
elif i > 25:
self.Tbb['CH_%02d' % (i + 1)] = data_ch36[i]
def Load(self, L1File):
print u'读取 L1所有数据信息...... %s' % L1File
if not os.path.isfile(L1File):
print 'Error: %s not found' % L1File
return
try:
h5File_R = h5py.File(L1File, 'r')
except Exception as e:
print str(e)
return
try:
ary_lon = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/Longitude')[:]
ary_lat = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/Latitude')[:]
self.satAzimuth = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SatelliteAzimuthAngle')[:]
self.satZenith = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SatelliteZenithAngle')[:]
self.sunAzimuth = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SolarAzimuthAngle')[:]
self.sunZenith = h5File_R.get(
'/All_Data/VIIRS-MOD-GEO_All/SolarZenithAngle')[:]
# Times = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/MidTime')[:]
Times = h5File_R.get('/All_Data/VIIRS-MOD-GEO_All/StartTime')[:]
tmpTime = np.full_like(ary_lon, -999, dtype='i4')
v_ymd2seconds = np.vectorize(npp_ymd2seconds)
T1 = v_ymd2seconds(Times)
for i in xrange(len(tmpTime)):
tmpTime[i, :] = T1[i / 16]
self.Time = tmpTime
ymd = time.gmtime(self.Time[0, 0])
ymd = time.strftime('%Y%m%d', ymd)
# print ymd
dsol = sun_earth_dis_correction(ymd)
for i in xrange(1, 17, 1):
# sv,bb 赋值 None, 有值则赋真实值
bandName = 'CH_%02d' % i
if i < 12:
ref = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/Reflectance' % i)[:]
# ref_fac = h5File_R.get('/All_Data/VIIRS-M%d-SDR_All/ReflectanceFactors' % i)[:][0]
# 由于不确定性 比较了14和15年的数据值一致，定值。偶尔出现-999.33导致计算错
ref_fac = 2.4417415E-5
idx = np.where(ref < 65500)
newRef = np.full_like(ref, np.nan, 'f4')
newRef[idx] = ref[idx]
self.Ref[bandName] = newRef * ref_fac * \
np.cos(np.deg2rad(self.sunZenith)) * dsol
elif i == 13:
rad = h5File_R.get('/All_Data/VIIRS-M%d-SDR_All/Radiance' %
i)[:]
tbb = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperature' %
i)[:]
idx = np.where(rad > 0)
newRad = np.full_like(rad, np.nan, 'f4')
newRad[idx] = rad[idx] * \
((10000 / self.WN['CH_%02d' % i]) ** 2) / 10.
idx = np.where(tbb > 0)
newTbb = np.full_like(tbb, np.nan, 'f4')
newTbb[idx] = tbb[idx]
self.Rad[bandName] = newRad
self.Tbb[bandName] = newTbb
else:
rad = h5File_R.get('/All_Data/VIIRS-M%d-SDR_All/Radiance' %
i)[:]
rad_fac = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/RadianceFactors' %
i)[:][0]
rad_int = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/RadianceFactors' %
i)[:][1]
tbb = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperature' %
i)[:]
tbb_fac = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperatureFactors'
% i)[:][0]
tbb_int = h5File_R.get(
'/All_Data/VIIRS-M%d-SDR_All/BrightnessTemperatureFactors'
% i)[:][1]
idx = np.where(rad < 65500)
newRad = np.full_like(rad, np.nan, 'f4')
newRad[idx] = rad[idx] * \
((10000 / self.WN['CH_%02d' % i]) ** 2) / 10.
idx = np.where(tbb < 65500)
newTbb = np.full_like(tbb, np.nan, 'f4')
newTbb[idx] = tbb[idx]
self.Rad[bandName] = newRad * rad_fac + rad_int
self.Tbb[bandName] = newTbb * tbb_fac + tbb_int
except Exception as e:
print str(e)
return
finally:
h5File_R.close()
# 通道的中心波数和光谱响应
# for i in xrange(self.Band):
i = 14
BandName = 'CH_%02d' % (i + 1)
srfFile = os.path.join(
MainPath, 'SRF',
'%s_%s_SRF_CH%02d_Pub.txt' % (self.sat, self.sensor, (i + 1)))
dictWave = np.loadtxt(srfFile,
dtype={
'names': ('num', 'rad'),
'formats': ('f4', 'f4')
})
waveNum = 10**7 / dictWave['num'][::-1]
waveRad = dictWave['rad'][::-1]
self.waveNum[BandName] = waveNum
self.waveRad[BandName] = waveRad
# 经纬度
ary_lon_idx = np.full(ary_lon.shape, np.nan)
condition = np.logical_and(ary_lon > -180., ary_lon < 180.)
ary_lon_idx[condition] = ary_lon[condition]
if self.Lons == []:
self.Lons = ary_lon_idx
else:
self.Lons = np.concatenate((self.Lons, ary_lon_idx))
ary_lat_idx = np.full(ary_lon.shape, np.nan)
condition = np.logical_and(ary_lat > -90., ary_lat < 90.)
ary_lat_idx[condition] = ary_lat[condition]
if self.Lats == []:
self.Lats = ary_lat_idx
else:
self.Lats = np.concatenate((self.Lats, ary_lat_idx))