v1.0.4

CHANGELOG.md

@@ -27,8 +27,50 @@ and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 -->
 ------
 ## [1.0.4](https://github.com/asfadmin/Discovery-SearchAPI-v3/compare/v1.0.3...v1.0.4)
+### Added
+- Added experimental ARIA S1 GUNW baseline stacking support
+    - requires: `dataset` keyword be set to "ARIA S1 GUNW" and using the desired frame as the `reference`
+    - returns json object list partially formatted for submitting jobs to ASF's On Demand processing.
+        ``` json
+        [
+            {
+                "date": "2025-06-04T00:26:25Z",
+                "products": [
+                "S1A_IW_SLC__1SDV_20250604T002649_20250604T002716_059489_076290_7E0F",
+                "S1A_IW_SLC__1SDV_20250604T002625_20250604T002651_059489_076290_7FE0"
+                ],
+                "group_granule_idx": 0,
+                "perpendicularBaseline": 0,
+                "temporalBaseline": 0
+            },
+            {
+                "date": "2025-05-23T00:26:25Z",
+                "products": [
+                "S1A_IW_SLC__1SDV_20250523T002650_20250523T002717_059314_075C80_5A5D",
+                "S1A_IW_SLC__1SDV_20250523T002625_20250523T002652_059314_075C80_BBE7"
+                ],
+                "group_granule_idx": 0,
+                "perpendicularBaseline": 47,
+                "temporalBaseline": -12
+            },
+
+            ...
+
+            {
+                "date": "2014-10-12T00:25:42Z",
+                "products": [
+                "S1A_IW_SLC__1SSV_20141012T002607_20141012T002634_002789_00323B_2DB9",
+                "S1A_IW_SLC__1SSV_20141012T002542_20141012T002609_002789_00323B_0E9F"
+                ],
+                "group_granule_idx": 0,
+                "perpendicularBaseline": -160,
+                "temporalBaseline": -3888
+            }
+        ]
+        ```
 ### Changed
-- bumped asf-search to 9.0.0 for nisar search types, browse images, and UAT collections
+- bumped asf-search to 9.0.2 for nisar search types, browse images, and UAT collections, `productionConfiguration` list support, bbox validation, opera-disp jsonlite outputs
+
 
 ------
 ## [1.0.3](https://github.com/asfadmin/Discovery-SearchAPI-v3/compare/v1.0.2...v1.0.3)

requirements.txt

@@ -22,7 +22,7 @@ ujson==5.7.0
 uvicorn==0.21.1
 watchfiles==0.19.0
 
-asf_search==9.0.0
+asf_search==9.0.2
 python-json-logger==2.0.7
 
 pyshp==2.1.3

src/SearchAPI/application/__init__.py

@@ -2,4 +2,5 @@
 from .output import *
 from .logger import *
 from .log_router import *
+from .search import *
 from .application import *

src/SearchAPI/application/application.py

@@ -15,9 +15,10 @@
 from .asf_opts import process_baseline_request, process_search_request, process_wkt_request
 from .health import get_cmr_health
 from .models import BaselineSearchOptsModel, SearchOptsModel
-from .output import as_output, get_asf_search_script
+from .output import as_output, get_asf_search_script, make_filename
 from .files_to_wkt import FilesToWKT
 from . import constants
+from .search import stack_aria_gunw
 import time
 
 
@@ -93,8 +94,19 @@ async def query_baseline(searchOptions: BaselineSearchOptsModel = Depends(proces
     output = searchOptions.output
     reference = searchOptions.reference
     request_method = searchOptions.request_method
-    # Load the reference scene:
 
+    if searchOptions.opts.dataset is not None:
+        if searchOptions.opts.dataset[0] == asf.DATASET.ARIA_S1_GUNW:
+            return JSONResponse(
+                content=stack_aria_gunw(reference),
+                status_code=200,
+                headers= {
+                        **constants.DEFAULT_HEADERS,
+                        'Content-Disposition': f"attachment; filename={make_filename('json')}",
+                    }
+            )
+    # Load the reference scene:
+
     if output.lower() == 'python':
         file_name, search_script = get_asf_search_script(opts, reference=reference, search_endpoint='baseline')
 

src/SearchAPI/application/search.py

@@ -0,0 +1,61 @@
+from collections import defaultdict
+
+import dateparser
+import asf_search as asf
+from shapely.wkt import dumps as dump_to_wkt
+from shapely import Polygon
+
+def stack_aria_gunw(frame: str):
+    reference = asf.search(frame=int(frame), dataset=asf.DATASET.ARIA_S1_GUNW, maxResults=1)[0]
+
+    opts = asf.ASFSearchOptions(
+        relativeOrbit=reference.properties['pathNumber'],
+        processingLevel=asf.PRODUCT_TYPE.SLC, 
+        dataset=asf.DATASET.SENTINEL1, 
+        beamMode='IW', 
+        polarization=['VV','VV+VH'], 
+        flightDirection=reference.properties['flightDirection'],
+        intersectsWith=dump_to_wkt(Polygon(reference.geometry['coordinates'][0]))
+    )
+
+    slc_stack = asf.search(opts=opts)
+
+    groups = defaultdict(list)
+    for product in slc_stack:
+        group_id = product.properties['platform'] + '_' + str(product.properties['orbit'])
+        groups[group_id].append(product)
+    # dateparser.parse(str(value))
+    aria_groups = [
+        {
+            'date': min(dateparser.parse(product.properties['startTime']) for product in group),
+            'products': [product for product in group],
+        }
+        for group in groups.values()
+    ]
+
+    # track group index on each product, naively choose first granule available
+    for idx, group in enumerate(aria_groups):
+        group_granule_idx = None
+        for idy, product in enumerate(group['products']):
+            product.properties['groupIDX'] = idx
+            if group_granule_idx is None:
+                if product.has_baseline():
+                    group_granule_idx = idy
+
+        group['group_granule_idx'] = group_granule_idx
+
+
+
+    stack = asf.ASFSearchResults([group['products'][group['group_granule_idx']] for group in aria_groups if group['group_granule_idx'] is not None])
+    target_stack, warnings = asf.baseline.get_baseline_from_stack(reference, stack)
+    for product in target_stack:
+        group_idx = product.properties.pop('groupIDX')
+        aria_groups[group_idx]['perpendicularBaseline'] = product.properties['perpendicularBaseline']
+        aria_groups[group_idx]['temporalBaseline'] = product.properties['temporalBaseline']
+
+    for group in aria_groups:
+        for idx, product in enumerate(group['products']):
+            group['products'][idx] = product.properties['sceneName']
+        group['date'] = group['date'].strftime('%Y-%m-%dT%H:%M:%SZ')
+
+    return aria_groups