添加四极化后向散射系数到特征图中
tian jiax
parent
3dde5efe21
commit
08eb3a0846
|
|
@ -35,3 +35,7 @@
|
|||
|
||||
/soilSalinity/tool/
|
||||
/landcover_c_sar/tool/
|
||||
/atmosphericDelay-C-SAR/tool/
|
||||
/deformation-C-SAR/tool/
|
||||
/dem-C-SAR/tool/
|
||||
/soilMoistureTop/tool/
|
||||
|
|
|
|||
|
|
@ -12,6 +12,8 @@ import os
|
|||
import numpy as np
|
||||
import glob
|
||||
import struct
|
||||
|
||||
from tool.algorithm.algtools.MetaDataHandler import MetaDataHandler
|
||||
from tool.algorithm.image.ImageHandle import ImageHandler
|
||||
|
||||
|
||||
|
|
@ -461,6 +463,65 @@ class AHVToPolsarpro:
|
|||
self._hh_hv_vh_vv_path_list = []
|
||||
return out_dir
|
||||
|
||||
@staticmethod
|
||||
def sar_backscattering_sigma(in_sar_tif, meta_file_path, out_sar_tif, replece_VV=False, is_DB=True):
|
||||
|
||||
# 读取原始SAR影像
|
||||
proj, geotrans, in_data = ImageHandler.read_img(in_sar_tif)
|
||||
|
||||
# 计算强度信息
|
||||
I = np.array(in_data[0], dtype="float32")
|
||||
Q = np.array(in_data[1], dtype="float32")
|
||||
|
||||
where_9999_0 = np.where(I == -9999)
|
||||
where_9999_1 = np.where(Q == -9999)
|
||||
I[where_9999_0] = 1.0
|
||||
Q[where_9999_1] = 1.0
|
||||
|
||||
I2 = np.square(I)
|
||||
Q2 = np.square(Q)
|
||||
intensity_arr = I2 + Q2
|
||||
|
||||
# 获取极化类型
|
||||
if 'HH' in os.path.basename(in_sar_tif):
|
||||
polarization = 'HH'
|
||||
elif 'HV' in os.path.basename(in_sar_tif):
|
||||
polarization = 'HV'
|
||||
elif 'VH' in os.path.basename(in_sar_tif):
|
||||
polarization = 'VH'
|
||||
elif 'VV' in os.path.basename(in_sar_tif):
|
||||
polarization = 'VV'
|
||||
if replece_VV:
|
||||
polarization = 'HV' # 土壤水分算法中可能会用HV替换VV
|
||||
elif 'DH' in os.path.basename(in_sar_tif):
|
||||
polarization = 'HH'
|
||||
else:
|
||||
raise Exception('there are not HH、HV、VH、VV in path:', in_sar_tif)
|
||||
|
||||
# 获取参数
|
||||
QualifyValue = MetaDataHandler.get_QualifyValue(meta_file_path, polarization)
|
||||
Kdb = MetaDataHandler.get_Kdb(meta_file_path, polarization)
|
||||
|
||||
# 计算后向散射系数
|
||||
# 对数形式
|
||||
coef_arr = 10 * (np.log10(intensity_arr * ((QualifyValue / 32767) ** 2))) - Kdb
|
||||
coef_arr[np.isnan(coef_arr)] = -9999
|
||||
coef_arr[np.isinf(coef_arr)] = -9999
|
||||
coef_arr[where_9999_0] = -9999
|
||||
coef_arr[where_9999_1] = -9999
|
||||
## 输出的SAR后向散射系数产品
|
||||
# ImageHandler.write_img(out_sar_tif, proj, geotrans, coef_arr, 0)
|
||||
|
||||
tif_array = np.power(10.0, coef_arr / 10.0) # dB --> 线性值 后向散射系数
|
||||
|
||||
tif_array[np.isnan(tif_array)] = 0
|
||||
tif_array[np.isinf(tif_array)] = 0
|
||||
tif_array[where_9999_0] = 0
|
||||
tif_array[where_9999_1] = 0
|
||||
|
||||
ImageHandler.write_img(out_sar_tif, proj, geotrans, tif_array, 0)
|
||||
return True
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
|
|
|||
|
|
@ -37,7 +37,7 @@
|
|||
<ParaType>File</ParaType>
|
||||
<DataType>tar.gz</DataType>
|
||||
<ParaSource>Man</ParaSource>
|
||||
<ParaValue>E:\VP-lk\GF3C_MYC_QPSI_006270_E100.4_N27.0_20230615_L1A_AHV_L10000158764-ortho.tar.gz</ParaValue>
|
||||
<ParaValue>G:\VegetationPhenology-likun\rusuoces\GF3C_MYC_QPSI_006270_E100.4_N27.0_20230615_L1A_AHV_L10000158764-ortho.tar.gz</ParaValue>
|
||||
<MaxValue>DEFAULT</MaxValue>
|
||||
<MinValue>DEFAULT</MinValue>
|
||||
<OptionValue>DEFAULT</OptionValue>
|
||||
|
|
@ -51,7 +51,7 @@
|
|||
<ParaType>File</ParaType>
|
||||
<DataType>csv</DataType>
|
||||
<ParaSource>Man</ParaSource>
|
||||
<ParaValue>E:\VP-lk\VegetationPhe_samples.csv</ParaValue>
|
||||
<ParaValue>G:\VegetationPhenology-likun\rusuoces\VegetationPhe_samples.csv</ParaValue>
|
||||
<MaxValue>DEFAULT</MaxValue>
|
||||
<MinValue>DEFAULT</MinValue>
|
||||
<OptionValue>DEFAULT</OptionValue>
|
||||
|
|
@ -65,7 +65,7 @@
|
|||
<ParaType>File</ParaType>
|
||||
<DataType>tif</DataType>
|
||||
<ParaSource>Man</ParaSource>
|
||||
<ParaValue>E:\VP-lk\landcover.tif</ParaValue>
|
||||
<ParaValue>G:\VegetationPhenology-likun\rusuoces\landcover.tif</ParaValue>
|
||||
<EnModification>True</EnModification>
|
||||
<EnMultipleChoice>False</EnMultipleChoice>
|
||||
<Control>File</Control>
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ from tool.algorithm.xml.CreatMetafile import CreateMetafile
|
|||
from tool.algorithm.algtools.ROIAlg import ROIAlg as alg
|
||||
from VegetationPhenologyXmlInfo import CreateDict, CreateStadardXmlFile
|
||||
from VegetationPhenologyAuxData import PhenoloyMeasCsv_geo
|
||||
|
||||
from tool.algorithm.polsarpro.AHVToPolsarpro import AHVToPolsarpro
|
||||
from tool.algorithm.xml.CreateMetaDict import CreateMetaDict, CreateProductXml
|
||||
from tool.file.fileHandle import fileHandle
|
||||
from tool.algorithm.algtools.ROIAlg import ROIAlg as roi
|
||||
|
|
@ -95,7 +95,7 @@ class PhenologyMain:
|
|||
|
||||
self.__workspace_path = self.__alg_xml_handler.get_workspace_path()
|
||||
self.__create_work_space()
|
||||
self.__processing_paras = InitPara.init_processing_paras(self.__input_paras)
|
||||
self.__processing_paras = InitPara.init_processing_paras(self.__input_paras, self.__workspace_preprocessing_path)
|
||||
self.__processing_paras.update(InitPara(DEBUG).get_mult_tar_gz_infs(self.__processing_paras, self.__workspace_preprocessing_path))
|
||||
SrcImagePath = self.__input_paras["AHVS"]['ParaValue']
|
||||
paths = SrcImagePath.split(';')
|
||||
|
|
@ -295,23 +295,38 @@ class PhenologyMain:
|
|||
# train_data, test_data, type_map = csvh.trans_VegePhenology_measdata_dic(csvh.readcsv(self.__processing_paras['MeasuredData']), ori_sim_path)
|
||||
logger.info("read phenology Measure.csv success!")
|
||||
|
||||
# 添加四极化后向散射系数到特征图中
|
||||
feature_tif_dir = os.path.join(self.__workspace_processing_path, name, 'features')
|
||||
if not os.path.exists(feature_tif_dir):
|
||||
os.makedirs(feature_tif_dir)
|
||||
origin_xml = self.__processing_paras[name + "_Origin_META"]
|
||||
|
||||
# 特征分解
|
||||
hh_hv_vh_vv_list = ["","","",""]
|
||||
for key in key_list:
|
||||
if "_HH" in key :
|
||||
hh_hv_vh_vv_list[0] = self.__preprocessed_paras[key]
|
||||
outPath = os.path.join(feature_tif_dir, 'cal_HH.tif')
|
||||
AHVToPolsarpro.sar_backscattering_sigma(hh_hv_vh_vv_list[0], origin_xml, outPath)
|
||||
if "_HV" in key:
|
||||
hh_hv_vh_vv_list[1] = self.__preprocessed_paras[key]
|
||||
outPath = os.path.join(feature_tif_dir, 'cal_HV.tif')
|
||||
AHVToPolsarpro.sar_backscattering_sigma(hh_hv_vh_vv_list[1], origin_xml, outPath)
|
||||
if "_VH" in key:
|
||||
hh_hv_vh_vv_list[2] = self.__preprocessed_paras[key]
|
||||
outPath = os.path.join(feature_tif_dir, 'cal_VH.tif')
|
||||
AHVToPolsarpro.sar_backscattering_sigma(hh_hv_vh_vv_list[2], origin_xml, outPath)
|
||||
if "_VV" in key:
|
||||
hh_hv_vh_vv_list[3] = self.__preprocessed_paras[key]
|
||||
outPath = os.path.join(feature_tif_dir, 'cal_VV.tif')
|
||||
AHVToPolsarpro.sar_backscattering_sigma(hh_hv_vh_vv_list[3], origin_xml, outPath)
|
||||
|
||||
cols = self.imageHandler.get_img_width(hh_hv_vh_vv_list[0])
|
||||
rows = self.imageHandler.get_img_height(hh_hv_vh_vv_list[0])
|
||||
|
||||
featureInput = self.__getInputFeatures()
|
||||
feature_dir = CreateFeature.decompose_single_tar(hh_hv_vh_vv_list, self.__workspace_processing_path, self.__workspace_preprocessing_path, name, self._env_str, rows, cols, FILTER_SIZE=3, debug=DEBUG, FeatureInput=featureInput)
|
||||
|
||||
feature_geo_dir = self.features_geo(feature_dir, paramter, sim_ori_path, name)
|
||||
# # 获取训练集提取特征的信息
|
||||
# ids = []
|
||||
|
|
|
|||
Loading…
Reference in New Issue