def read_tif(inputfile, band):
tifObj = GeoTiffFile(inputfile)
tifObj.readTif()
data = tifObj.getBandData(band)
width = tifObj.getWidth()
height = tifObj.getHeight()
proj = tifObj.getProj()
geotrans = tifObj.getGeoTrans()
return data, width, height, proj, geotrans
def cal_radiance(warp_path, atmo_param, out_tif_path):
radiance_factor = {'svi01': (0.013155036, -0.41), 'svi02': (0.0063949213, -0.24),
'svi03': (0.0013309018, -0.21), 'svi04': (5.52444e-05, -0.01)}
# 先获取行列号
tif_path = warp_path['svi01']
tif_obj = GeoTiffFile(tif_path)
tif_obj.readTif()
width = tif_obj.getWidth()
height = tif_obj.getHeight()
proj = tif_obj.getProj()
geo_trans = tif_obj.getGeoTrans()
del tif_obj
out_tif_obj = GeoTiffFile(out_tif_path)
out_tif_data = np.zeros((4, height, width), dtype=np.float)
i = 0
for key in radiance_factor.keys():
tif_path = warp_path[key]
tif_obj = GeoTiffFile(tif_path)
tif_obj.readTif()
tif_data = tif_obj.getBandData(0)
nan_loc = tif_data >= 65530
# 辐射定标计算
tif_data = tif_data * radiance_factor[key][0] + radiance_factor[key][1]
# 大气校正计算
# y=xa*(measured radiance)-xb; acr=y/(1.+xc*y)
y = atmo_param[key][0] * tif_data - atmo_param[key][1]
ref_data = y / (1 + atmo_param[key][2] * y) * 1000
# ref_data = ref_data.astype(np.uint16)
ref_data[nan_loc] = 65533
out_tif_data[i, :, :] = ref_data
i += 1
out_tif_obj.setDims(width, height, 4)
out_tif_obj.setData(out_tif_data)
out_tif_obj.setProj(proj)
out_tif_obj.setGeoTrans(geo_trans)
out_tif_obj.writeTif()
print("finish")