Merge pull request #48 from ESA-PhiLab/develop

merge latest developments

Dockerfile

@@ -1,7 +1,7 @@
 FROM ubuntu:18.04
 
 LABEL maintainer="Petr Sevcik, EOX"
-LABEL OpenSARToolkit='0.10.1'
+LABEL OpenSARToolkit='0.11.1'
 
 # set work directory to home and download snap
 WORKDIR /home/ost
@@ -10,8 +10,8 @@ WORKDIR /home/ost
 COPY snap8.varfile $HOME
 
 # update variables
-ENV OTB_VERSION="7.1.0" \
-    TBX_VERSION="7" \
+ENV OTB_VERSION="7.3.0" \
+    TBX_VERSION="8" \
     TBX_SUBVERSION="0"
 ENV TBX="esa-snap_sentinel_unix_${TBX_VERSION}_${TBX_SUBVERSION}.sh" \
     SNAP_URL="http://step.esa.int/downloads/${TBX_VERSION}.${TBX_SUBVERSION}/installers" \

ost/graphs/S1_SLC2ARD/S1_SLC_TNR_CalBeta_Deb_ML_TF_Sub.xml

@@ -70,9 +70,10 @@
       <demResamplingMethod>${dem_resampling}</demResamplingMethod>
       <externalDEMFile>${dem_file}</externalDEMFile>
       <externalDEMNoDataValue>${dem_nodata}</externalDEMNoDataValue>
+      <externalDEMApplyEGM>${egm_correction}</externalDEMApplyEGM>
+      <outputSimulatedImage>false</outputSimulatedImage>
       <additionalOverlap>0.15</additionalOverlap>
       <oversamplingMultiple>1.5</oversamplingMultiple>
-      <outputSimulatedImage>false</outputSimulatedImage>
     </parameters>
   </node>
   <node id="Subset">

ost/s1/burst_to_ard.py

@@ -283,7 +283,7 @@ def create_coherence_layers(
 
         # run co-registration
         try:
-            slc.coreg2(
+            slc.coreg(
                 master_import, slave_import, out_coreg, coreg_log, config_dict
             )
         except (GPTRuntimeError, NotValidFileError) as error:

ost/s1/refine_inventory.py

@@ -37,8 +37,10 @@ def _remove_double_entries(inventory_df):
     )['ingestiondate'].transform(max) == inventory_df['ingestiondate']
 
     # re-initialize GDF geometry due to groupby function
-    crs = fiona.crs.from_epsg(4326)
-    gdf = gpd.GeoDataFrame(inventory_df[idx], geometry='geometry', crs=crs)
+    gdf = gpd.GeoDataFrame(
+        inventory_df[idx], geometry='geometry', crs='epsg:4326'
+    )
+
     logger.info(
         f'{len(inventory_df[idx])} frames remain after double entry removal'
     )
@@ -91,7 +93,7 @@ def _handle_equator_crossing(inventory_df):
     crossing the equator the relative orbit will increase by 1.
 
     This routine checks for the appearance of such kind and unifies the
-    relativeorbitnumbers so that the inventory is complinat with the
+    relativeorbit numbers so that the inventory is compliant with the
     subsequent batch processing routines of OST
 
     Args:
@@ -247,7 +249,8 @@ def _remove_incomplete_tracks(aoi_gdf, inventory_df):
                 out_frame = out_frame.append(gdf_date)
 
     logger.info(
-        f'{len(out_frame)} frames remain after removal of non-full AOI crossing'
+        f' {len(out_frame)} frames remain after'
+        f' removal of non-full AOI crossing'
     )
     return out_frame
 
@@ -279,9 +282,10 @@ def _handle_non_continous_swath(inventory_df):
 
         for date in dates:
 
-            subdf = inventory_df[(inventory_df['acquisitiondate'] == date) &
-                                 (inventory_df['relativeorbit'] == track)
-                                 ].sort_values('slicenumber')
+            subdf = inventory_df[
+                (inventory_df['acquisitiondate'] == date) &
+                (inventory_df['relativeorbit'] == track)
+            ].sort_values('slicenumber')
 
             if (len(subdf) <= int(subdf.slicenumber.max()) -
                     int(subdf.slicenumber.min())):
@@ -320,8 +324,9 @@ def _forward_search(aoi_gdf, inventory_df, area_reduce=0):
     out_frame = gpd.GeoDataFrame(columns=inventory_df.columns)
 
     # loop through dates
-    for date in sorted(inventory_df['acquisitiondate'].unique(),
-                       reverse=False):
+    for date in sorted(
+            inventory_df['acquisitiondate'].unique(), reverse=False
+    ):
 
         # set starting date for curent mosaic
         if start_date is None:
@@ -391,8 +396,10 @@ def _backward_search(aoi_gdf, inventory_df, datelist, area_reduce=0):
     for dates in datelist:
 
         # extract scenes for single mosaics
-        gdf = inventory_df[(inventory_df['acquisitiondate'] <= dates[1]) &
-                           (inventory_df['acquisitiondate'] >= dates[0])]
+        gdf = inventory_df[
+            (inventory_df['acquisitiondate'] <= dates[1]) &
+            (inventory_df['acquisitiondate'] >= dates[0])
+        ]
 
         # we create an emtpy list and fill with tracks used for the mosaic,
         # so they are not used twice
@@ -413,12 +420,15 @@ def _backward_search(aoi_gdf, inventory_df, datelist, area_reduce=0):
                     included_tracks.append(track)
 
                     # get all footprints for each date and track
-                    track_gdf = gdf[(gdf['acquisitiondate'] == date) &
-                                    (gdf['relativeorbit'] == track)]
+                    track_gdf = gdf[
+                        (gdf['acquisitiondate'] == date) &
+                        (gdf['relativeorbit'] == track)
+                    ]
 
                     # re-initialize GDF due to groupby fucntion
-                    track_gdf = gpd.GeoDataFrame(track_gdf,
-                                                 geometry='geometry')
+                    track_gdf = gpd.GeoDataFrame(
+                        track_gdf, geometry='geometry'
+                    )
 
                     # get a unified geometry for date/track combination
                     union = track_gdf.geometry.unary_union
@@ -520,7 +530,8 @@ def search_refinement(
             (inventory_df['orbitdirection'] == orb)]
 
         logger.info('{} frames for {} tracks in {} polarisation.'.format(
-            len(inv_df_sorted), orb, pol))
+            len(inv_df_sorted), orb, pol)
+        )
 
         # calculate intersected area
         inter = aoi_gdf.geometry.intersection(inv_df_sorted.unary_union)

ost/s1/slc_wrappers.py

@@ -189,7 +189,6 @@ def calibration(
     :param outfile:
     :param logfile:
     :param config_dict:
-    :param region:
     :return:
     """
 
@@ -198,9 +197,10 @@ def calibration(
     cpus = config_dict['snap_cpu_parallelism']
     dem_dict = ard['dem']
     region = ''
+
     # calculate Multi-Look factors
     azimuth_looks = 1  # int(np.floor(ard['resolution'] / 10 ))
-    range_looks = 5  # int(azimuth_looks * 5)
+    range_looks = 6  # int(azimuth_looks * 5)
 
     # construct command dependent on selected product type
     if ard['product_type'] == 'RTC-gamma0':
@@ -220,6 +220,7 @@ def calibration(
             f"-Pdem_file=\'{dem_dict['dem_file']}\' "
             f"-Pdem_nodata={dem_dict['dem_nodata']} "
             f"-Pdem_resampling={dem_dict['dem_resampling']} "
+            f"-Pegm_correction={dem_dict['egm_correction']} "
             f"-Pregion=\'{region}\' "
             f"-Pinput={str(infile)} "
             f"-Poutput={str(outfile)}"
@@ -311,7 +312,6 @@ def coreg(master, slave, outfile, logfile, config_dict):
     command = (
         f'{GPT_FILE} Back-Geocoding -x -q {2*cpus} '
         f'-PdemName=\'{dem_dict["dem_name"]}\' '
-        #f'-PdemName=\'SRTM 3Sec\' '
         f'-PdemResamplingMethod=\'{dem_dict["dem_resampling"]}\' '
         f'-PexternalDEMFile=\'{dem_dict["dem_file"]}\' '
         f'-PexternalDEMNoDataValue=\'{dem_dict["dem_nodata"]}\' '