xue1.0
ISCE SAOCOM L-SAR数据处理示例
AOCOM是阿根廷空间局CONAE发射的地球观测卫星，SAOCOM 1A于2018年10月8日发射，SAOCOM 1B于2020年8月30日发射，L波段（约1.275 GHz），分辨率7-100米，覆盖范围在50-400公里。SAOCOM系统与意大利COSMO-SkyMed星座在X波段联合运行，可以提供每天两次覆盖，生成X和L波段SAR数据。
1. 配置文件
设定stripmapApp.py参数的XML文件StripmapApp_SAOCOM.xml:<?xml version="1.0" encoding="UTF-8"?> <insarApp> <component name="insar"> <property name="sensor name">SAOCOM_SLC</property> <component name="reference"> <catalog>/home/bodo/Dropbox/Argentina/SAOCOM/reference_SAOCOM.xml</catalog> </component> <component name="secondary"> <catalog>/home/bodo/Dropbox/Argentina/SAOCOM/secondary_SAOCOM.xml</catalog> </component> <property name="demFilename"> <value>/home/bodo/Dropbox/Argentina/SAOCOM/demLat_S33_S31_Lon_W070_W068.dem.wgs84</value> </property> <property name="do denseoffsets">True</property> <property name="do split spectrum">True</property> <property name="unwrapper name">snaphu</property> <property name="do dispersive">True</property> <property name="dispersive filter kernel x-size">800</property> <property name="dispersive filter kernel y-size">800</property> <property name="dispersive filter kernel sigma_x">100</property> <property name="dispersive filter kernel sigma_y">100</property> <property name="dispersive filter kernel rotation">0</property> <property name="dispersive filter number of iterations">5</property> <property name="dispersive filter mask type">connected_components</property> <property name="dispersive filter coherence threshold">0.6</property> </component> </insarApp>包含主影像信息的XML文件reference_SAOCOM.xml:
<component name="reference"> <property name="IMAGEFILE"> /raid/InSAR/SAOCOM/Master/67496-EOL1ASARSAO1A515794/Data/slc-acqId0000008546-a-sm7-0000000000-s7dp-vv </property> <property name="XEMTFILE"> /raid/InSAR/SAOCOM/Master/67496-EOL1ASARSAO1A515794/S1A_OPER_SAR_EOSSP__CORE_L1A_OLF_20200221T122503.xemt </property> <property name="XMLFILE"> /raid/InSAR/SAOCOM/Master/67496-EOL1ASARSAO1A515794/Data/slc-acqId0000008546-a-sm7-0000000000-s7dp-vv.xml </property> <property name="OUTPUT"> /raid/InSAR/SAOCOM/Master/67496-EOL1ASARSAO1A515794/slc-acqId0000008546-a-sm7-0000000000-s7dp-vv </property> </component>包含辅影像信息的XML文件secondary_SAOCOM.xml:
<component name="reference"> <property name="IMAGEFILE"> /raid/InSAR/SAOCOM/Slave/67498-EOL1ASARSAO1A515796/Data/slc-acqId0000010907-a-sm7-0000000000-s7dp-vv </property> <property name="XEMTFILE"> /raid/InSAR/SAOCOM/Slave/67498-EOL1ASARSAO1A515796/S1A_OPER_SAR_EOSSP__CORE_L1A_OLF_20200221T122606.xemt </property> <property name="XMLFILE"> /raid/InSAR/SAOCOM/Slave/67498-EOL1ASARSAO1A515796/Data/slc-acqId0000010907-a-sm7-0000000000-s7dp-vv.xml </property> <property name="OUTPUT"> /raid/InSAR/SAOCOM/Slave/67498-EOL1ASARSAO1A515796/slc-acqId0000010907-a-sm7-0000000000-s7dp-vv.slc </property> </component>2. SRTM DEM
使用dem.py自动下载DEM demLat_S33_S31_Lon_W070_W068.dem.wgs84
fixImageXml.py -f -i demLat_S33_S31_Lon_W070_W068.dem.wgs843. 干涉处理
stripmapApp.py
stripmapApp.py --steps /home/bodo/Dropbox/Argentina/SAOCOM/stripmapApp_SAOCOM.xml 2>&1 | tee SAOCOM_test.log使用mdx.py查看结果
mdx.py -P interferogram/filt_topophase.unw.geo mv out.ppm SAOCOM_filt_topophase.unw.geo.ppm convert -density 300 -fuzz 1% -trim SAOCOM_filt_topophase.unw.geo.ppm SAOCOM_filt_topophase.unw.geo.jpg滤波后解缠图
mdx.py -P interferogram/phsig.cor.geo mv out.ppm SAOCOM_phsig.cor.geo.ppm convert -density 300 -fuzz 1% -trim SAOCOM_phsig.cor.geo.ppm SAOCOM_phsig.cor.geo.jpg滤波后相干性图
使用ImageMagick的convert命令生成快速预览图
convert -density 300 -crop 2000x400+0+1000 +repage SAOCOM_filt_topophase.unw.geo.jpg SAOCOM_filt_topophase.unw.geo.crop.jpg电离层影响分析
使用ISCE split-spectrum处理（Heresh Fattahi et al.; Cunren Liang et al.），可以估计电离层的色散和非色散成分，并校正干涉图。该SAOCOM示例包含了一些电离层扰动。
电离层
示例数据下载
https://catalogos.conae.gov.ar/catalogo/catalogoSatSaocomAdel.html参考链接
https://up-rs-esp.github.io/posts/2020/11/SAOCOM-Ifgs-and-ISCE/#quick-views-of-ionospheric-impact
https://github.com/isce-framework/isce2