def main(ifile,
shp_file,
path_out_10m,
path_out_20m,
path_out_60m,
aero_type=1,
target_type=2,
altitude=0.01,
visibility=15):
if os.path.isfile(ifile):
print('文件解压...')
fz = zipfile.ZipFile(ifile, 'r')
for file in fz.namelist():
fz.extract(file, os.path.split(ifile)[0])
path_name = os.path.split(fz.namelist()[0])[0]
path_in = os.path.join(os.path.split(ifile)[0], path_name)
else:
path_in = ifile
# 卫星经纬度范围
path_xml = os.listdir(os.path.join(path_in, 'GRANULE'))[0]
file_mtd = os.path.join(path_in, 'GRANULE', path_xml, 'MTD_TL.xml')
with open(file_mtd, 'r') as fp:
for line in fp:
res = re.findall(r'psd-\d+', line)
if len(res) != 0:
psd_str = '{https://%s.sentinel2.eo.esa.int/PSD/S2_PDI_Level-1C_Tile_Metadata.xsd}Geometric_Info' % res[
0]
break
tree = ET.parse(file_mtd)
ulx = parse_xml(tree, [[psd_str, None], ['Tile_Geocoding', None],
['Geoposition', None], ['ULX', None]])
ulx = int(ulx)
uly = parse_xml(tree, [[psd_str, None], ['Tile_Geocoding', None],
['Geoposition', None], ['ULY', None]])
uly = int(uly)
# EPSG代码
epsg = parse_xml(tree, [[psd_str, None], ['Tile_Geocoding', None],
['HORIZONTAL_CS_CODE', None]])
epsg = re.findall(r'\d+', epsg)
epsg = int(epsg[0])
# 60m分辨率的行列数
nrows = parse_xml(tree, [[psd_str, None], ['Tile_Geocoding', None],
['Size', {
'resolution': '60'
}], ['NROWS', None]])
nrows = int(nrows)
ncols = parse_xml(tree, [[psd_str, None], ['Tile_Geocoding', None],
['Size', {
'resolution': '60'
}], ['NCOLS', None]])
ncols = int(ncols)
# 计算裁切范围-10m
if shp_file:
tif_tmp = 'tif_tmp.tif'
else:
tif_tmp = shp_file.replace('.shp', '_tmp.tif')
target_ds = gdal.GetDriverByName('GTiff').Create(tif_tmp, ncols * 6,
nrows * 6, 1,
gdal.GDT_Byte)
geo_trans = (ulx, 10, 0, uly, 0, -10)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
data_tmp = np.zeros([nrows, ncols]).astype(np.uint8)
target_ds.GetRasterBand(1).WriteArray(data_tmp)
target_ds = None
if shp_file:
out_file = 'tif_mask.tif'
else:
out_file = shp_file.replace('.shp', '_mask.tif')
cut_range_10m = img_cut.main(tif_tmp, shp_file=shp_file, out_file=out_file)
os.remove(out_file)
os.remove(tif_tmp)
# 计算裁切范围-20m
target_ds = gdal.GetDriverByName('GTiff').Create(tif_tmp, ncols * 3,
nrows * 3, 1,
gdal.GDT_Byte)
geo_trans = (ulx, 20, 0, uly, 0, -20)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
data_tmp = np.zeros([nrows, ncols]).astype(np.uint8)
target_ds.GetRasterBand(1).WriteArray(data_tmp)
target_ds = None
cut_range_20m = img_cut.main(tif_tmp, shp_file=shp_file, out_file=out_file)
os.remove(out_file)
os.remove(tif_tmp)
# 计算裁切范围-60m
target_ds = gdal.GetDriverByName('GTiff').Create(tif_tmp, ncols, nrows, 1,
gdal.GDT_Byte)
geo_trans = (ulx, 60, 0, uly, 0, -60)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
data_tmp = np.zeros([nrows, ncols]).astype(np.uint8)
target_ds.GetRasterBand(1).WriteArray(data_tmp)
target_ds = None
cut_range_60m = img_cut.main(tif_tmp, shp_file=shp_file, out_file=out_file)
os.remove(out_file)
os.remove(tif_tmp)
# 观测天顶角和方位角
salz = parse_xml(
tree, [[psd_str, None], ['Tile_Angles', None],
['Mean_Viewing_Incidence_Angle_List', None],
['Mean_Viewing_Incidence_Angle', None], ['ZENITH_ANGLE', None]])
sala = parse_xml(
tree,
[[psd_str, None], ['Tile_Angles', None],
['Mean_Viewing_Incidence_Angle_List', None],
['Mean_Viewing_Incidence_Angle', None], ['AZIMUTH_ANGLE', None]])
# 太阳天顶角和方位角
path_in_short = os.path.split(path_in)[1]
date_str = path_in_short.split('_')[2]
year = int(date_str[0:4])
month = int(date_str[4:6])
day = int(date_str[6:8])
hour = int(date_str[9:11])
minute = int(date_str[11:13])
second = int(date_str[13:15])
date = '%d/%d/%d %d:%d:%d' % (year, month, day, hour, minute, second)
center_lonlat = coord_trans.trans(epsg, 4326, ulx + (ncols / 2) * 60,
uly - (nrows / 2) * 60)
[solz, sola] = calc_sola_position.main(center_lonlat[0], center_lonlat[1],
date)
path_data = os.path.join(path_in, 'GRANULE', path_xml, 'IMG_DATA')
data_list = os.listdir(path_data)
# 首次循环：识别波段
for item in data_list:
if 'B01' in item:
name_b1 = item
break
name_10m = [
name_b1.replace('B01', 'B02'),
name_b1.replace('B01', 'B03'),
name_b1.replace('B01', 'B04'),
name_b1.replace('B01', 'B08')
]
name_20m = [
name_b1.replace('B01', 'B02'),
name_b1.replace('B01', 'B03'),
name_b1.replace('B01', 'B04'),
name_b1.replace('B01', 'B05'),
name_b1.replace('B01', 'B06'),
name_b1.replace('B01', 'B07'),
name_b1.replace('B01', 'B08'),
name_b1.replace('B01', 'B8A'),
name_b1.replace('B01', 'B11'),
name_b1.replace('B01', 'B12')
]
name_60m = [
name_b1,
name_b1.replace('B01', 'B02'),
name_b1.replace('B01', 'B03'),
name_b1.replace('B01', 'B04'),
name_b1.replace('B01', 'B05'),
name_b1.replace('B01', 'B06'),
name_b1.replace('B01', 'B07'),
name_b1.replace('B01', 'B08'),
name_b1.replace('B01', 'B8A'),
name_b1.replace('B01', 'B09'),
name_b1.replace('B01', 'B10'),
name_b1.replace('B01', 'B11'),
name_b1.replace('B01', 'B12')
]
# 10m波段
print('10m ...')
file_out_short = os.path.split(path_in)[1]
file_out_split = file_out_short.split('_')
date_str = file_out_split[2].replace('T', '')
date_str = str(int(date_str) + 80000) # 转换为北京时间
nrow = file_out_split[3].replace('N', '')
npath = file_out_split[4].replace('R', '')
if file_out_split[0] == 'S2A':
satellite_code = 'A'
elif file_out_split[0] == 'S2B':
satellite_code = 'B'
else:
satellite_code = ''
name_short = 'Sentinel2%s_MSI_10_L2_%s_%s_%s.tif' % (satellite_code,
date_str, nrow, npath)
file_out = os.path.join(path_out_10m, name_short)
nbands = len(name_10m)
xsize = cut_range_10m[1] - cut_range_10m[0]
ysize = cut_range_10m[3] - cut_range_10m[2]
target_ds = gdal.GetDriverByName('GTiff').Create(file_out, xsize, ysize,
nbands, gdal.GDT_Int16)
geo_trans = (ulx + cut_range_10m[0] * 10, 10, 0,
uly - cut_range_10m[2] * 10, 0, -10)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
nband = 0
for item in name_10m:
raster = gdal.Open(os.path.join(path_data, item))
data = raster.GetRasterBand(1).ReadAsArray()
nan_mask = data == 0
raster = None
radi_cali = data.astype(float) / 10000
# 大气校正
mtl_coef = {
'altitude': altitude,
'visibility': visibility,
'aero_type': aero_type,
'target_type': target_type,
'location': center_lonlat,
'month': month,
'day': day,
'solz': solz,
'sola': sola,
'salz': salz,
'sala': sala
}
wave_index = item[-7:-4]
res_atms_corr = arms_corr(radi_cali, mtl_coef, wave_index)
# 裁切
res_atms_corr = res_atms_corr[cut_range_10m[2]:cut_range_10m[3],
cut_range_10m[0]:cut_range_10m[1]]
res_atms_corr = res_atms_corr * 10000
res_atms_corr[nan_mask] = -9999
target_ds.GetRasterBand(nband + 1).WriteArray(
(res_atms_corr).astype(np.int))
target_ds.GetRasterBand(nband + 1).SetNoDataValue(-9999)
nband = nband + 1
print('%s处理完毕...' % wave_index)
target_ds = None
# 20m波段
print('20m ...')
name_short_20m = name_short.replace('_10_', '_20_')
file_out = os.path.join(path_out_20m, name_short_20m)
nbands = len(name_20m)
xsize = cut_range_20m[1] - cut_range_20m[0]
ysize = cut_range_20m[3] - cut_range_20m[2]
target_ds = gdal.GetDriverByName('GTiff').Create(file_out, xsize, ysize,
nbands, gdal.GDT_Int16)
geo_trans = (ulx + cut_range_20m[0] * 20, 20, 0,
uly - cut_range_20m[2] * 20, 0, -20)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
nband = 0
for item in name_20m:
raster = gdal.Open(os.path.join(path_data, item))
data = raster.GetRasterBand(1).ReadAsArray()
# 降采样
if item in name_10m:
data_resample = np.zeros(
[int(data.shape[0] / 2),
int(data.shape[1] / 2)])
for i in range(2):
for j in range(2):
data_resample = data_resample + data[i::2, j::2]
data = data_resample / 4
nan_mask = data == 0
raster = None
radi_cali = data.astype(float) / 10000
# 大气校正
mtl_coef = {
'altitude': altitude,
'visibility': visibility,
'aero_type': aero_type,
'target_type': target_type,
'location': center_lonlat,
'month': month,
'day': day,
'solz': solz,
'sola': sola,
'salz': salz,
'sala': sala
}
wave_index = item[-7:-4]
res_atms_corr = arms_corr(radi_cali, mtl_coef, wave_index)
# 裁切
res_atms_corr = res_atms_corr[cut_range_20m[2]:cut_range_20m[3],
cut_range_20m[0]:cut_range_20m[1]]
res_atms_corr = res_atms_corr * 10000
res_atms_corr[nan_mask] = -9999
target_ds.GetRasterBand(nband + 1).WriteArray(
(res_atms_corr).astype(np.int))
target_ds.GetRasterBand(nband + 1).SetNoDataValue(-9999)
nband = nband + 1
print('%s处理完毕...' % wave_index)
target_ds = None
# 60m波段
print('60m ...')
name_short_60m = name_short.replace('_10_', '_60_')
file_out = os.path.join(path_out_60m, name_short_60m)
nbands = len(name_60m)
xsize = cut_range_60m[1] - cut_range_60m[0]
ysize = cut_range_60m[3] - cut_range_60m[2]
target_ds = gdal.GetDriverByName('GTiff').Create(file_out, xsize, ysize,
nbands, gdal.GDT_Int16)
geo_trans = (ulx + cut_range_60m[0] * 60, 60, 0,
uly - cut_range_60m[2] * 60, 0, -60)
raster_srs = osr.SpatialReference()
raster_srs.ImportFromEPSG(epsg)
proj_ref = raster_srs.ExportToWkt()
target_ds.SetGeoTransform(geo_trans)
target_ds.SetProjection(proj_ref)
nband = 0
for item in name_60m:
raster = gdal.Open(os.path.join(path_data, item))
data = raster.GetRasterBand(1).ReadAsArray()
# 降采样
if item in name_10m:
data_resample = np.zeros(
[int(data.shape[0] / 6),
int(data.shape[1] / 6)])
for i in range(6):
for j in range(6):
data_resample = data_resample + data[i::6, j::6]
data = data_resample / 36
elif item in name_20m:
data_resample = np.zeros(
[int(data.shape[0] / 3),
int(data.shape[1] / 3)])
for i in range(3):
for j in range(3):
data_resample = data_resample + data[i::3, j::3]
data = data_resample / 9
nan_mask = data == 0
raster = None
radi_cali = data.astype(float) / 10000
# 大气校正
mtl_coef = {
'altitude': altitude,
'visibility': visibility,
'aero_type': aero_type,
'target_type': target_type,
'location': center_lonlat,
'month': month,
'day': day,
'solz': solz,
'sola': sola,
'salz': salz,
'sala': sala
}
wave_index = item[-7:-4]
if wave_index == 'B10':
res_atms_corr = radi_cali
else:
res_atms_corr = arms_corr(radi_cali, mtl_coef, wave_index)
# 裁切
res_atms_corr = res_atms_corr[cut_range_60m[2]:cut_range_60m[3],
cut_range_60m[0]:cut_range_60m[1]]
res_atms_corr = res_atms_corr * 10000
res_atms_corr[nan_mask] = -9999
target_ds.GetRasterBand(nband + 1).WriteArray(
(res_atms_corr).astype(np.int))
target_ds.GetRasterBand(nband + 1).SetNoDataValue(-9999)
nband = nband + 1
print('%s处理完毕...' % wave_index)
target_ds = None
# 删除解压文件
if os.path.isfile(ifile):
shutil.rmtree(path_in)
def main(ifile, path_out_30, shp_file=None, altitude=0.01, visibility=40.0, type_aero=1):
'''
@description:
@ifile {str} tar.gz原始数据文件
@path_out_30 {str} 预处理后的文件输出路径
@shp_file {str} 矢量文件路径
@altitude {float} 海拔(km)
@visibility {float} 能见度(km)
@type_aero {int} 气溶胶类型(3默认为城市)
'''
tf = tarfile.open(ifile)
path_short = os.path.split(ifile)[1]
path_short = path_short.replace('.tar.gz', '')
file_path = os.path.join(os.path.split(ifile)[0], path_short)
print('文件解压...')
tf.extractall(path=file_path)
file_list = os.listdir(file_path)
MTLfile = ''
band_list = [0, 1, 2, 3, 4, 5, 6]
for item in file_list:
if 'MTL.txt' in item:
MTLfile = item
break
raster_b1 = os.path.join(file_path, MTLfile.replace('MTL.txt', 'B2.TIF'))
lim = img_cut.main(raster_file = raster_b1, shp_file = shp_file)
xlim = [lim[0], lim[1]]
ylim = [lim[2], lim[3]]
raster_data_res = np.zeros((ylim[1]-ylim[0], xlim[1]-xlim[0], len(band_list)))
MTLfile = os.path.join(file_path, MTLfile)
print('预处理...')
for i in band_list:
print('裁切...')
raster_file = os.path.join(file_path, MTLfile.replace('MTL.txt', 'B'+str(i+1)+'.TIF'))
raster_data = skimage.io.imread(raster_file)
# 裁切
raster_data = raster_data[ylim[0]:ylim[1], xlim[0]:xlim[1]]
# 辐射定标和大气校正(6S)
nan_key = raster_data < 1e-6
band_data_atmscorr = radi_arms_corr(raster_data=raster_data, MTLfile=MTLfile,
altitude=altitude, visibility=visibility, type_aero=type_aero, wave_index=i)
band_data_atmscorr[nan_key] = 0
raster_data_res[:,:,i] = band_data_atmscorr
print('第%d波段已经处理完毕' % (i+1))
# 数据保存为tif
raster_file = os.path.join(file_path, MTLfile.replace('MTL.txt', 'B1.TIF'))
raster = gdal.Open(raster_file)
georef0 = raster.GetGeoTransform()
georef1 = list(georef0)
georef1[0] = georef0[0] + xlim[0] * georef0[1]
georef1[3] = georef0[3] + ylim[0] * georef0[5]
georef1 = tuple(georef1)
# 可见光-短波红外
ifile_name = os.path.split(ifile)[1]
date_str = '%s103000' % (ifile_name.split('_')[3])
nrow = ifile_name.split('_')[2][0:3]
npath = ifile_name.split('_')[2][3:6]
name_short = 'Landsat5_TM_30_L2_%s_%s_%s.tif' % (date_str, nrow, npath)
raster_file_out = os.path.join(path_out_30, name_short)
if os.path.exists(raster_file_out): # 如果文件存在则需要删除
os.remove(raster_file_out)
target_ds = gdal.GetDriverByName('GTiff').Create(
raster_file_out,
raster_data_res.shape[1],
raster_data_res.shape[0],
len(band_list),
gdal.GDT_UInt16
)
target_ds.SetGeoTransform(georef1)
target_ds.SetProjection(raster.GetProjectionRef())
for i in band_list:
print('保存第%d波段...' % (i+1))
if i != 5:
data_tmp = (raster_data_res[:,:,i]*10000).astype(np.int)
else:
data_tmp = (raster_data_res[:,:,i]*100).astype(np.int)
data_tmp[data_tmp<1e-6] = 0
target_ds.GetRasterBand(i+1).WriteArray(data_tmp)
target_ds.GetRasterBand(i+1).SetNoDataValue(0)
target_ds = None
# 删除解压文件
raster = None
shutil.rmtree(file_path)
def satellite_position(ifile, shp_file):
'''
@description: 相对精确的天顶角方位角计算
@ifile {str}: L1B swath文件
@shp_file {str}: 研究区域矢量文件
@return: {salz, sala}
'''
# 设置环境变量
os.environ['MRTDATADIR'] = global_config['MRTDATADIR']
os.environ['PGSHOME'] = global_config['PGSHOME']
os.environ['MRTBINDIR'] = global_config['MRTBINDIR']
run_path = os.path.split(ifile)[0]
heg_bin = os.path.join(global_config['MRTBINDIR'], 'hegtool')
os.system('cd %s && %s -h %s > heg.log' % (run_path, heg_bin, ifile))
info_file = os.path.join(run_path, 'HegHdr.hdr')
if not(os.path.exists(info_file)):
print('获取文件信息出错：%s' % ifile)
return(0)
else:
lat_min = None
lat_max = None
lon_min = None
lon_max = None
pixel_x = None
pixel_y = None
with open(info_file, 'r') as fp:
lines = fp.readlines()
for line in lines:
if 'SWATH_LAT_MIN' in line:
lat_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LAT_MAX' in line:
lat_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MIN' in line:
lon_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MAX' in line:
lon_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_X_PIXEL_RES_DEGREES' in line:
pixel_x = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_Y_PIXEL_RES_DEGREES' in line:
pixel_y = float(re.findall(r'[\d.]+', line)[0])
if lat_min and lat_max and lon_min and lon_max and pixel_x and pixel_y:
prm_file = os.path.join(run_path, 'HegSwath.prm')
# 卫星天顶角、方位角重投影
print('reprojection SALZ ...')
if '.hdf' in ifile:
out_file = ifile.replace('.hdf', '_SALZ.tif')
if os.path.exists(out_file):
os.remove(out_file)
else:
print('无法识别的文件格式：%s' % os.path.split(ifile)[1])
with open(prm_file, 'wb') as fp:
fp.write(b'\nNUM_RUNS = 1\n\n')
fp.write(b'BEGIN\n')
fp.write(bytes('INPUT_FILENAME = %s\n' % ifile, 'utf-8'))
fp.write(b'OBJECT_NAME = MODIS_SWATH_Type_L1B\n')
fp.write(b'FIELD_NAME = SensorZenith|\n')
fp.write(b'BAND_NUMBER = 1\n')
fp.write(bytes('OUTPUT_PIXEL_SIZE_X = %f\n' % pixel_x, 'utf-8'))
fp.write(bytes('OUTPUT_PIXEL_SIZE_Y = %f\n' % pixel_y, 'utf-8'))
fp.write(bytes('SPATIAL_SUBSET_UL_CORNER = ( %f %f )\n' % (lat_max, lon_min), 'utf-8'))
fp.write(bytes('SPATIAL_SUBSET_LR_CORNER = ( %f %f )\n' % (lat_min, lon_max), 'utf-8'))
fp.write(b'OUTPUT_PROJECTION_TYPE = GEO\n')
fp.write(bytes('OUTPUT_FILENAME = %s\n' % out_file, 'utf-8'))
fp.write(b'OUTPUT_TYPE = GEO\n')
fp.write(b'END\n\n')
swtif_bin = os.path.join(global_config['MRTBINDIR'], 'swtif')
os.system('cd %s && %s -P HegSwath.prm > heg.log' % (run_path, swtif_bin))
print('reprojection SALA ...')
if '.hdf' in ifile:
out_file = ifile.replace('.hdf', '_SALA.tif')
if os.path.exists(out_file):
os.remove(out_file)
else:
print('无法识别的文件格式：%s' % os.path.split(ifile)[1])
with open(prm_file, 'wb') as fp:
fp.write(b'\nNUM_RUNS = 1\n\n')
fp.write(b'BEGIN\n')
fp.write(bytes('INPUT_FILENAME = %s\n' % ifile, 'utf-8'))
fp.write(b'OBJECT_NAME = MODIS_SWATH_Type_L1B\n')
fp.write(b'FIELD_NAME = SensorAzimuth|\n')
fp.write(b'BAND_NUMBER = 1\n')
fp.write(bytes('OUTPUT_PIXEL_SIZE_X = %f\n' % pixel_x, 'utf-8'))
fp.write(bytes('OUTPUT_PIXEL_SIZE_Y = %f\n' % pixel_y, 'utf-8'))
fp.write(bytes('SPATIAL_SUBSET_UL_CORNER = ( %f %f )\n' % (lat_max, lon_min), 'utf-8'))
fp.write(bytes('SPATIAL_SUBSET_LR_CORNER = ( %f %f )\n' % (lat_min, lon_max), 'utf-8'))
fp.write(b'OUTPUT_PROJECTION_TYPE = GEO\n')
fp.write(bytes('OUTPUT_FILENAME = %s\n' % out_file, 'utf-8'))
fp.write(b'OUTPUT_TYPE = GEO\n')
fp.write(b'END\n\n')
swtif_bin = os.path.join(global_config['MRTBINDIR'], 'swtif')
os.system('cd %s && %s -P HegSwath.prm > heg.log' % (run_path, swtif_bin))
else:
print('[Error] 未获得全部的所需信息')
return(0)
# 计算研究区域的平均太阳天顶角和方位角
salz_file = ifile.replace('.hdf', '_SALZ.tif')
out_file = salz_file.replace('.tif', '_cut.tif')
cut_range = img_cut.main(salz_file, shp_file=shp_file, out_file=out_file)
raster = gdal.Open(salz_file)
salz_all = raster.GetRasterBand(1).ReadAsArray()
salz_all = salz_all[cut_range[2]:cut_range[3], cut_range[0]:cut_range[1]]
salz = np.mean(salz_all) * 0.01
sala_file = ifile.replace('.hdf', '_SALA.tif')
raster = gdal.Open(sala_file)
sala_all = raster.GetRasterBand(1).ReadAsArray()
sala_all = sala_all[cut_range[2]:cut_range[3], cut_range[0]:cut_range[1]]
sala = np.mean(sala_all) * 0.01
raster = None
# 删除过程文件
file_name = ifile.replace('.hdf', '_SALA.tif')
file_name_met = file_name.replace('.tif', '.tif.met')
if os.path.exists(file_name) and os.path.exists(file_name_met):
os.remove(file_name)
os.remove(file_name_met)
file_name = ifile.replace('.hdf', '_SALZ.tif')
file_name_met = file_name.replace('.tif', '.tif.met')
if os.path.exists(file_name) and os.path.exists(file_name_met):
os.remove(file_name)
os.remove(file_name_met)
file_name = ifile.replace('.hdf', '_SALZ_cut.tif')
if os.path.exists(file_name):
os.remove(file_name)
log_list = ['heg.log', 'swtif.log', 'HegSwath.prm', 'HegHdr.hdr', 'hegtool.log']
for item in log_list:
file_name = os.path.join(run_path, item)
if os.path.exists(file_name):
os.remove(file_name)
return({'salz':salz, 'sala':sala})
def main(ifile,
shp_file,
center_lonlat,
salz,
sala,
satellite,
aerotype=1,
altitude=0.01,
visibility=15,
band_need=['all'],
path_out_radi=None,
path_out_6s=None):
'''
@description: 主程序
@ifile {str}: L1B swath文件
@shp_file {str}: 研究区域矢量文件
@center_lonlat {[lon, lat]}: 中心经纬度
@aerotype {int}: 气溶胶类型(默认大陆型)
@altitude {float}: 海拔(km)
@visibility {float}: 能见度(km)
@band_need {list}: 所选波段, all表示全部处理
@path_6s {str}: 大气校正结果输出路径
@return:
'''
# 设置环境变量
os.environ['MRTDATADIR'] = global_config['MRTDATADIR']
os.environ['PGSHOME'] = global_config['PGSHOME']
os.environ['MRTBINDIR'] = global_config['MRTBINDIR']
run_path = os.path.split(ifile)[0]
# step 1: 获取hdf信息
SD_file = SD(ifile)
sds_obj = SD_file.select('EV_250_Aggr500_RefSB')
sds_info = sds_obj.attributes()
scales = sds_info['radiance_scales']
offsets = sds_info['radiance_offsets']
sds_obj = SD_file.select('EV_500_RefSB')
sds_info = sds_obj.attributes()
scales_t = sds_info['radiance_scales']
offsets_t = sds_info['radiance_offsets']
for i in range(len(scales_t)):
scales.append(scales_t[i])
offsets.append(offsets_t[i])
SD_file.end()
nbands = len(scales)
date_str = os.path.split(ifile)[1].split('.')[1]
time_str = os.path.split(ifile)[1].split('.')[2]
date_str = date_teanslator.jd_to_cale(date_str[1:])
year = int(date_str.split('.')[0])
month = int(date_str.split('.')[1])
day = int(date_str.split('.')[2])
hour = int(time_str[0:2])
minute = int(time_str[2:])
date = '%d/%d/%d %d:%d:00' % (year, month, day, hour, minute)
sola_position = calc_sola_position.main(center_lonlat[0], center_lonlat[1],
date)
solz = sola_position[0]
sola = sola_position[1]
heg_bin = os.path.join(global_config['MRTBINDIR'], 'hegtool')
os.system('cd %s && %s -h %s > heg.log' % (run_path, heg_bin, ifile))
info_file = os.path.join(run_path, 'HegHdr.hdr')
if not (os.path.exists(info_file)):
print('获取文件信息出错：%s' % ifile)
return ('')
else:
lat_min = None
lat_max = None
lon_min = None
lon_max = None
pixel_x = None
pixel_y = None
with open(info_file, 'r') as fp:
lines = fp.readlines()
for line in lines:
if 'SWATH_LAT_MIN' in line:
lat_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LAT_MAX' in line:
lat_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MIN' in line:
lon_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MAX' in line:
lon_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_X_PIXEL_RES_DEGREES' in line:
pixel_x = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_Y_PIXEL_RES_DEGREES' in line:
pixel_y = float(re.findall(r'[\d.]+', line)[0])
if lat_min and lat_max and lon_min and lon_max and pixel_x and pixel_y:
prm_file = os.path.join(run_path, 'HegSwath.prm')
# 重投影
for i_band in range(nbands):
modis_band = 'B%d' % (i_band + 1)
if (modis_band in band_need) or ('all' in band_need):
print('reprojection %s ...' % modis_band)
out_file = ifile.replace('.hdf',
'_reproj_' + modis_band + '.tif')
if '.hdf' in ifile:
if os.path.exists(out_file):
os.remove(out_file)
else:
print('无法识别的文件格式：%s' % os.path.split(ifile)[1])
with open(prm_file, 'wb') as fp:
fp.write(b'\nNUM_RUNS = 1\n\n')
fp.write(b'BEGIN\n')
fp.write(
bytes('INPUT_FILENAME = %s\n' % ifile, 'utf-8'))
fp.write(b'OBJECT_NAME = MODIS_SWATH_Type_L1B\n')
if i_band >= 0 and i_band <= 1:
fp.write(b'FIELD_NAME = EV_250_Aggr500_RefSB|\n')
fp.write(
bytes('BAND_NUMBER = %d\n' % (i_band + 1),
'utf-8'))
else:
fp.write(b'FIELD_NAME = EV_500_RefSB|\n')
fp.write(
bytes('BAND_NUMBER = %d\n' % (i_band - 1),
'utf-8'))
fp.write(
bytes('OUTPUT_PIXEL_SIZE_X = %f\n' % pixel_x,
'utf-8'))
fp.write(
bytes('OUTPUT_PIXEL_SIZE_Y = %f\n' % pixel_y,
'utf-8'))
fp.write(
bytes(
'SPATIAL_SUBSET_UL_CORNER = ( %f %f )\n' %
(lat_max, lon_min), 'utf-8'))
fp.write(
bytes(
'SPATIAL_SUBSET_LR_CORNER = ( %f %f )\n' %
(lat_min, lon_max), 'utf-8'))
fp.write(b'OUTPUT_PROJECTION_TYPE = GEO\n')
fp.write(
bytes('OUTPUT_FILENAME = %s\n' % out_file,
'utf-8'))
fp.write(b'OUTPUT_TYPE = GEO\n')
fp.write(b'END\n\n')
swtif_bin = os.path.join(global_config['MRTBINDIR'],
'swtif')
os.system('cd %s && %s -P HegSwath.prm > heg.log' %
(run_path, swtif_bin))
else:
print('[Error] 未获得全部的所需信息')
return (0)
# 裁切与合并
if 'all' in band_need:
raster_file = ifile.replace('.hdf', '_reproj_B1.tif')
else:
raster_file = ifile.replace('.hdf',
'_reproj_' + band_need[0] + '.tif')
if not (os.path.exists(raster_file)):
return ('')
out_file = raster_file.replace('.tif', '_cut.tif')
cut_range = img_cut.main(raster_file,
shp_file=shp_file,
out_file=out_file)
xsize = cut_range[1] - cut_range[0]
ysize = cut_range[3] - cut_range[2]
# 影像裁切
print('裁切...')
for i_band in range(nbands):
modis_band = 'B%d' % (i_band + 1)
if (modis_band in band_need) or ('all' in band_need):
raster_file = ifile.replace('.hdf',
'_reproj_' + modis_band + '.tif')
out_file = raster_file.replace('.tif', '_cut.tif')
img_cut.main(raster_file, sub_lim=cut_range, out_file=out_file)
# 辐射定标
print('辐射定标...')
raster = gdal.Open(raster_file)
date_str = '%d%02d%02d%02d%02d%02d' % (year, month, day, hour + 8,
minute, 0)
nrow = os.path.split(ifile)[1].split('.')[3]
if satellite == 'AQUA':
out_name = 'AQUA_MODIS_500_L2_%s_%s_00.tif' % (date_str, nrow)
elif satellite == 'TERRA':
out_name = 'TERRA_MODIS_500_L2_%s_%s_00.tif' % (date_str, nrow)
else:
print('[Error] 无法识别卫星类型')
return (0)
if os.path.exists(path_out_radi):
raster_fn_out_radi = os.path.join(path_out_radi, out_name)
driver = gdal.GetDriverByName('GTiff')
target_ds = driver.Create(raster_fn_out_radi, xsize, ysize, nbands,
gdal.GDT_Int16)
target_ds.SetGeoTransform(raster.GetGeoTransform())
target_ds.SetProjection(raster.GetProjectionRef())
nan_mask = None
for i_band in range(nbands):
modis_band = 'B%d' % (i_band + 1)
if (modis_band in band_need) or ('all' in band_need):
raster_file = ifile.replace(
'.hdf', '_reproj_' + modis_band + '.tif')
out_file = raster_file.replace('.tif', '_cut.tif')
raster_cut = gdal.Open(out_file)
raster_data = (
raster_cut.GetRasterBand(1).ReadAsArray()).astype(
np.int)
if nan_mask is None:
nan_mask = raster_data > 65530
raster_data[nan_mask] = -9999
target_ds.GetRasterBand(i_band + 1).WriteArray(raster_data)
target_ds.GetRasterBand(i_band + 1).SetNoDataValue(-9999)
raster_cut = None
target_ds = None
else:
print('[Warning] without radiation-correction output!')
# 大气校正
print('大气校正 ...')
nan_mask = None
driver = gdal.GetDriverByName('GTiff')
raster_fn_out_6s = os.path.join(path_out_6s, out_name)
target_ds = driver.Create(raster_fn_out_6s, xsize, ysize, nbands,
gdal.GDT_Int16)
target_ds.SetGeoTransform(raster.GetGeoTransform())
target_ds.SetProjection(raster.GetProjectionRef())
for i_band in range(nbands):
modis_band = 'B%d' % (i_band + 1)
if (modis_band in band_need) or ('all' in band_need):
raster_file = ifile.replace('.hdf',
'_reproj_' + modis_band + '.tif')
out_file = raster_file.replace('.tif', '_cut.tif')
raster_cut = gdal.Open(out_file)
raster_data = raster_cut.GetRasterBand(1).ReadAsArray()
if nan_mask is None:
nan_mask = raster_data > 65530
raster_data = raster_data.astype(float)
raster_data = scales[i_band] * (raster_data - offsets[i_band])
mtl_coef = {
'altitude': altitude,
'visibility': visibility,
'aero_type': aerotype,
'location': center_lonlat,
'month': month,
'day': day,
'solz': solz,
'sola': sola,
'salz': salz,
'sala': sala
}
wave_index = i_band + 42
data_tmp = (arms_corr(raster_data, mtl_coef, wave_index) *
10000).astype(np.int)
data_tmp[nan_mask] = -9999
target_ds.GetRasterBand(i_band + 1).WriteArray(data_tmp)
target_ds.GetRasterBand(i_band + 1).SetNoDataValue(-9999)
raster_cut = None
target_ds = None
raster = None
# 删除过程文件
for item in modis_band_list:
file_name = ifile.replace('.hdf', '_reproj_' + item + '.tif')
file_name_met = file_name.replace('.tif', '.tif.met')
file_name_cut = ifile.replace('.hdf',
'_reproj_' + item + '_cut.tif')
if os.path.exists(file_name) and os.path.exists(file_name_met):
os.remove(file_name)
os.remove(file_name_met)
if os.path.exists(file_name_cut):
os.remove(file_name_cut)
log_list = [
'heg.log', 'swtif.log', 'HegSwath.prm', 'HegHdr.hdr', 'hegtool.log'
]
for item in log_list:
file_name = os.path.join(run_path, item)
if os.path.exists(file_name):
os.remove(file_name)
return (raster_fn_out_6s)
def main(ifile,
shp_file,
center_lonlat,
salz,
sala,
cut_range=None,
aerotype=1,
altitude=0.01,
visibility=15,
band_need=['all'],
path_out=None):
'''
@description:
@ifile {str}: L1B swath文件
@shp_file {str}: 研究区域矢量文件
@center_lonlat {[lon, lat]}: 中心经纬度
@aerotype {int}: 气溶胶类型(默认大陆型)
@altitude {float}: 海拔(km)
@visibility {float}: 能见度(km)
@return:
'''
# 设置环境变量
os.environ['MRTDATADIR'] = global_config['MRTDATADIR']
os.environ['PGSHOME'] = global_config['PGSHOME']
os.environ['MRTBINDIR'] = global_config['MRTBINDIR']
run_path = os.path.split(ifile)[0]
# step 1: 获取hdf信息
nbands = 16
SD_file = SD(ifile)
scales = []
offsets = []
for i_band in range(nbands):
if i_band + 1 == 9:
sds_obj = SD_file.select('Reflectance_M%d' % (i_band + 1))
elif i_band + 1 >= 12:
sds_obj = SD_file.select('BrightnessTemperature_M%d' %
(i_band + 1))
else:
sds_obj = SD_file.select('Radiance_M%d' % (i_band + 1))
sds_info = sds_obj.attributes()
if 'Scale' in sds_info:
scales.append(sds_info['Scale'])
else:
scales.append(1)
if 'Offset' in sds_info:
offsets.append(sds_info['Offset'])
else:
offsets.append(0)
SD_file.end()
date_str = os.path.split(ifile)[1].split('.')[1]
time_str = os.path.split(ifile)[1].split('.')[2]
date_str = date_teanslator.jd_to_cale(date_str[1:])
year = int(date_str.split('.')[0])
month = int(date_str.split('.')[1])
day = int(date_str.split('.')[2])
hour = int(time_str[0:2])
minute = int(time_str[2:])
date = '%d/%d/%d %d:%d:00' % (year, month, day, hour, minute)
sola_position = calc_sola_position.main(center_lonlat[0], center_lonlat[1],
date)
solz = sola_position[0]
sola = sola_position[1]
heg_bin = os.path.join(global_config['MRTBINDIR'], 'hegtool')
os.system('cd %s && %s -h %s > heg.log' % (run_path, heg_bin, ifile))
info_file = os.path.join(run_path, 'HegHdr.hdr')
if not (os.path.exists(info_file)):
print('获取文件信息出错：%s' % ifile)
return (0)
else:
lat_min = None
lat_max = None
lon_min = None
lon_max = None
pixel_x = None
pixel_y = None
with open(info_file, 'r') as fp:
lines = fp.readlines()
for line in lines:
if 'SWATH_LAT_MIN' in line:
lat_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LAT_MAX' in line:
lat_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MIN' in line:
lon_min = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_LON_MAX' in line:
lon_max = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_X_PIXEL_RES_DEGREES' in line:
pixel_x = float(re.findall(r'[\d.]+', line)[0])
elif 'SWATH_Y_PIXEL_RES_DEGREES' in line:
pixel_y = float(re.findall(r'[\d.]+', line)[0])
if not (cut_range is None):
lat_min = cut_range[2]
lat_max = cut_range[3]
lon_min = cut_range[0]
lon_max = cut_range[1]
if lat_min and lat_max and lon_min and lon_max and pixel_x and pixel_y:
prm_file = os.path.join(run_path, 'HegSwath.prm')
# 反射波段值重投影
for i_band in range(nbands):
viirs_band = 'M%d' % (i_band + 1)
if (viirs_band in band_need) or ('all' in band_need):
print('reprojection %s ...' % viirs_band)
out_file = ifile.replace('.hdf',
'_reproj_' + viirs_band + '.tif')
if '.hdf' in ifile:
if os.path.exists(out_file):
os.remove(out_file)
else:
print('无法识别的文件格式：%s' % os.path.split(ifile)[1])
with open(prm_file, 'wb') as fp:
fp.write(b'\nNUM_RUNS = 1\n\n')
fp.write(b'BEGIN\n')
fp.write(
bytes('INPUT_FILENAME = %s\n' % ifile, 'utf-8'))
fp.write(b'OBJECT_NAME = VIIRS_EV_750M_SDR\n')
if viirs_band == 'M9':
fp.write(
bytes(
'FIELD_NAME = Reflectance_M%d|\n' %
(i_band + 1), 'utf-8'))
elif viirs_band == 'M15' or viirs_band == 'M16':
fp.write(
bytes(
'FIELD_NAME = BrightnessTemperature_M%d|\n'
% (i_band + 1), 'utf-8'))
else:
fp.write(
bytes(
'FIELD_NAME = Radiance_M%d|\n' %
(i_band + 1), 'utf-8'))
fp.write(b'BAND_NUMBER = 1\n')
fp.write(
bytes('OUTPUT_PIXEL_SIZE_X = %f\n' % pixel_x,
'utf-8'))
fp.write(
bytes('OUTPUT_PIXEL_SIZE_Y = %f\n' % pixel_y,
'utf-8'))
fp.write(
bytes(
'SPATIAL_SUBSET_UL_CORNER = ( %f %f )\n' %
(lat_max, lon_min), 'utf-8'))
fp.write(
bytes(
'SPATIAL_SUBSET_LR_CORNER = ( %f %f )\n' %
(lat_min, lon_max), 'utf-8'))
fp.write(b'OUTPUT_PROJECTION_TYPE = GEO\n')
fp.write(
bytes('OUTPUT_FILENAME = %s\n' % out_file,
'utf-8'))
fp.write(b'OUTPUT_TYPE = GEO\n')
fp.write(b'END\n\n')
swtif_bin = os.path.join(global_config['MRTBINDIR'],
'swtif')
os.system('cd %s && %s -P HegSwath.prm > heg.log' %
(run_path, swtif_bin))
else:
print('[Error] 未获得全部的所需信息')
return (0)
# 裁切与合并
if 'all' in band_need:
raster_file = ifile.replace('.hdf', '_reproj_M1.tif')
else:
raster_file = ifile.replace('.hdf',
'_reproj_' + band_need[0] + '.tif')
out_file = raster_file.replace('.tif', '_cut.tif')
cut_range = img_cut.main(raster_file,
shp_file=shp_file,
out_file=out_file)
xsize = cut_range[1] - cut_range[0]
ysize = cut_range[3] - cut_range[2]
data_join = np.zeros([ysize, xsize, nbands])
print('大气校正 ...')
for i_band in range(nbands):
viirs_band = 'M%d' % (i_band + 1)
if (viirs_band in band_need) or ('all' in band_need):
raster_file = ifile.replace('.hdf',
'_reproj_' + viirs_band + '.tif')
out_file = raster_file.replace('.tif', '_cut.tif')
img_cut.main(raster_file, sub_lim=cut_range, out_file=out_file)
# 辐射定标和大气校正
raster = gdal.Open(out_file)
raster_data = raster.GetRasterBand(1).ReadAsArray()
raster_data = raster_data.astype(float)
mask = raster_data >= 65530
raster_data = scales[i_band] * raster_data + offsets[i_band]
mtl_coef = {
'altitude': altitude,
'visibility': visibility,
'aero_type': aerotype,
'location': center_lonlat,
'month': month,
'day': day,
'solz': solz,
'sola': sola,
'salz': salz,
'sala': sala
}
if i_band <= 11:
wave_index = i_band + 149
else:
wave_index = None
if not (wave_index is None):
if viirs_band == 'M9':
tmp = raster_data
else:
tmp = arms_corr(raster_data, mtl_coef, wave_index)
# tmp = raster_data
tmp[mask] = 65535
data_join[:, :, i_band] = tmp
else:
tmp = raster_data
tmp[mask] = 65535
data_join[:, :, i_band] = tmp
driver = gdal.GetDriverByName('GTiff')
if 'all' in band_need:
raster_file = ifile.replace('.hdf', '_reproj_M1_cut.tif')
else:
raster_file = ifile.replace('.hdf',
'_reproj_' + band_need[0] + '_cut.tif')
raster = gdal.Open(raster_file)
# 输出文件名
date_str = '%d%02d%02d%02d%02d%02d' % (year, month, day, hour + 8,
minute, 0)
nrow = os.path.split(ifile)[1].split('.')[3]
out_name = 'NPP_VIIRS_750_L2_%s_%s_00.tif' % (date_str, nrow)
if path_out is None:
raster_fn_out = os.path.join(os.path.split(ifile)[0], out_name)
else:
raster_fn_out = os.path.join(path_out, out_name)
target_ds = driver.Create(raster_fn_out, xsize, ysize, nbands,
gdal.GDT_UInt16)
target_ds.SetGeoTransform(raster.GetGeoTransform())
target_ds.SetProjection(raster.GetProjectionRef())
for i in range(nbands):
if i < 11:
target_ds.GetRasterBand(i + 1).WriteArray(
(data_join[:, :, i] * 10000).astype(np.int))
else:
target_ds.GetRasterBand(i + 1).WriteArray(
(data_join[:, :, i] * 100).astype(np.int))
band = target_ds.GetRasterBand(i + 1)
band.SetNoDataValue(65535)
target_ds = None
raster = None
# 删除过程文件
for item in viirs_band_list:
file_name = ifile.replace('.hdf', '_reproj_' + item + '.tif')
file_name_met = file_name.replace('.tif', '.tif.met')
file_name_cut = ifile.replace('.hdf',
'_reproj_' + item + '_cut.tif')
if os.path.exists(file_name) and os.path.exists(file_name_met):
os.remove(file_name)
os.remove(file_name_met)
if os.path.exists(file_name_cut):
os.remove(file_name_cut)
log_list = [
'heg.log', 'swtif.log', 'HegSwath.prm', 'HegHdr.hdr', 'hegtool.log'
]
for item in log_list:
file_name = os.path.join(run_path, item)
if os.path.exists(file_name):
os.remove(file_name)
return (raster_fn_out)