HI @GabiZuccolotto we have a product guide that you are more then welcome to check out, it's located at https://hyp3-docs.asf.alaska.edu/guides/insar_product_guide/
If it doesn't have the answers you are looking for then please let us know
Hi all, I'm curious if it is advisable/possible in the future to request RTC Sentinel-1 with a Terrain Correction Pixel Spacing (m) of 10 meters instead of 30 meters (even if the Copernicus 30 meter DEM is used)? I'm thinking that in this case, the 30 meter DEM would be resampled to 10 meter for the correction.
My thinking is this would bring in some assumptions of slope at that resolution that may or may not be true, but could lead to higher res/higher quality data in areas without substantial topography differences, so maybe having the option would be valuable?
S1B_IW_GRDH_1SDV_20190102T141245_20190102T141316_014316_01AA2B_6D78
S1B_IW_GRDH_1SDV_20200109T141251_20200109T141322_019741_02552C_F6F8
S1B_IW_GRDH_1SDV_20210103T141258_20210103T141328_024991_02F96E_EFDC
S1A_IW_GRDH_1SDV_20190111T161259_20190111T161324_025432_02D14C_2B50
S1A_IW_GRDH_1SDV_20200118T161305_20200118T161330_030857_038A73_D4FC
S1A_IW_GRDH_1SDV_20210112T161311_20210112T161336_036107_043B8E_E752
S1B_IW_GRDH_1SDV_20190102T084921_20190102T084950_014313_01AA16_5582
S1B_IW_GRDH_1SDV_20200109T084927_20200109T084956_019738_025516_724C
S1B_IW_GRDH_1SDV_20210103T084933_20210103T085002_024988_02F958_E58F
S1B_IW_GRDH_1SDV_20190112T070657_20190112T070722_014457_01AEBA_CE7B
S1B_IW_GRDH_1SDV_20200107T070703_20200107T070728_019707_025425_2339
S1B_IW_GRDH_1SDV_20210101T070709_20210101T070734_024957_02F867_1112
S1B_IW_GRDH_1SDV_20190104T231244_20190104T231309_014351_01AB40_D0FA
S1B_IW_GRDH_1SDV_20200111T231250_20200111T231315_019776_025643_788C
S1B_IW_GRDH_1SDV_20210105T231256_20210105T231321_025026_02FA86_628D
S1B_IW_GRDH_1SDV_20190127T174852_20190127T174917_014683_01B5F0_5A7F
S1B_IW_GRDH_1SDV_20200110T174859_20200110T174924_019758_0255B5_5B9F
S1B_IW_GRDH_1SDV_20210104T174905_20210104T174930_025008_02F9F4_DF69@rbavery submitted! You can watch for them to finish with this script:
import hyp3_sdk as sdk
job_ids = [
'0f850ede-7cf2-45b7-bcd7-0c907f20d932',
'604ed554-368d-4119-a7bf-9d607ace4ce2',
'1b3243f5-fe28-4ec1-94f6-fb46d2388b8e',
'52645c9e-dc7a-48d9-9736-acd2c630410a',
'0c0e0b11-ae1e-459e-a30e-b0cbba961f0a',
'6dac1e03-cd3a-4a3a-886c-4d7e58d5d9ab',
'77063ba9-f539-47a1-a954-9a12540e2535',
'a0491555-e7f5-4d1d-95a1-3e7183bc036e',
'17c68c67-8cbc-4f6c-aa73-fb9baa20faa3',
'12ee1451-b5f2-481e-8cbe-79a2e13cb244',
'a5f2f57b-615e-4b92-9a3a-ffe78fe6e2c0',
'83ef4b6e-32c4-4e23-9ee8-b1432e8706ba',
'7c889f37-0f08-4802-8cd4-2d5bb440ed0a',
'32f7393b-d7f0-4b24-b15e-8a01074b9722',
'39cd0e25-94f1-4ebd-83d0-85b35ac42085',
'0d6bdf48-e7fb-47cd-bdd0-cf24b4e7f7b0',
'c6997015-9b2b-40d9-80df-3e787900fb09',
'da4df95a-4b79-4185-a9b8-b1ef78c11f4f',
]
hyp3 = sdk.HyP3('https://hyp3-watermap.asf.alaska.edu', prompt=True)
jobs = sdk.Batch()
for ii in job_ids:
jobs += hyp3.get_job_by_id(ii)
jobs = hyp3.watch(jobs)
# download
jobs.download_files('data/')
# print urls
for job in jobs:
print(job.files[0]['url'])of if you prefer, I can just post the URLs when they are done
Job.from_dict({'job_id': '7c889f37-0f08-4802-8cd4-2d5bb440ed0a', 'job_type': 'RTC_GAMMA', 'request_time': '2021-09-07T22:57:58+00:00', 'status_code': 'FAILED', 'user_id': 'jhkennedy', 'name': 'rbavery-10m-rtc', 'job_parameters': {'dem_matching': True, 'granules': ['S1B_IW_GRDH_1SDV_20190104T231244_20190104T231309_014351_01AB40_D0FA'], 'radiometry': 'gamma0', 'resolution': 10, 'scale': 'power', 'speckle_filter': True}, 'logs': ['https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/7c889f37-0f08-4802-8cd4-2d5bb440ed0a/7c889f37-0f08-4802-8cd4-2d5bb440ed0a.log'], 'expiration_time': '2021-09-23T00:00:00+00:00'}),
Job.from_dict({'job_id': '32f7393b-d7f0-4b24-b15e-8a01074b9722', 'job_type': 'RTC_GAMMA', 'request_time': '2021-09-07T22:57:58+00:00', 'status_code': 'FAILED', 'user_id': 'jhkennedy', 'name': 'rbavery-10m-rtc', 'job_parameters': {'dem_matching': True, 'granules': ['S1B_IW_GRDH_1SDV_20200111T231250_20200111T231315_019776_025643_788C'], 'radiometry': 'gamma0', 'resolution': 10, 'scale': 'power', 'speckle_filter': True}, 'logs': ['https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/32f7393b-d7f0-4b24-b15e-8a01074b9722/32f7393b-d7f0-4b24-b15e-8a01074b9722.log'], 'expiration_time': '2021-09-23T00:00:00+00:00'}),
Job.from_dict({'job_id': '39cd0e25-94f1-4ebd-83d0-85b35ac42085', 'job_type': 'RTC_GAMMA', 'request_time': '2021-09-07T22:57:58+00:00', 'status_code': 'FAILED', 'user_id': 'jhkennedy', 'name': 'rbavery-10m-rtc', 'job_parameters': {'dem_matching': True, 'granules': ['S1B_IW_GRDH_1SDV_20210105T231256_20210105T231321_025026_02FA86_628D'], 'radiometry': 'gamma0', 'resolution': 10, 'scale': 'power', 'speckle_filter': True}, 'logs': ['https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/39cd0e25-94f1-4ebd-83d0-85b35ac42085/39cd0e25-94f1-4ebd-83d0-85b35ac42085.log'], 'expiration_time': '2021-09-23T00:00:00+00:00'}),84e073d2-d8cc-4e2d-b804-6839c90fc1f2:https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/84e073d2-d8cc-4e2d-b804-6839c90fc1f2/S1B_IW_20210105T231256_DVP_RTC30_G_gpufem_7A91.zip
6dfd43e7-e535-4213-8fe6-7813a00d1560:https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/6dfd43e7-e535-4213-8fe6-7813a00d1560/S1B_IW_20190104T231244_DVP_RTC30_G_gpufem_0BA6.zip
8cc4b01a-879b-4f9f-ae8d-a52e2300b931:https://hyp3-watermap-contentbucket-1rg5gnumqc8vw.s3.us-west-2.amazonaws.com/8cc4b01a-879b-4f9f-ae8d-a52e2300b931/S1B_IW_20200111T231250_DVP_RTC30_G_gpufem_A7DE.zipS1B_IW_GRDH_1SDV_20190102T141245_20190102T141316_014316_01AA2B_6D78and with these parameters:
speckle_filter=True, include_rgb=True, radiometry="gamma0", scale = "power", dem_matching=False, resolution=10dem_matching=False because the ESA precices orbits are such high quality. Caveat: we haven't looked seriously at that comarison in a year-ish
@rbavery We haven't done a deep dive on the impacts of DEM matching on products generated with the Copernicus DEM, but when using the legacy DEMs we do not recommend using the DEM matching for products that would be used in a time series analysis. DEM matching can shift the geolocation of the products, and the shifts are not always consistent from one RTC product to the next. This results in features not aligning well when RTC images are stacked through time.
In some cases, RTC results of individual products are improved when using the DEM matching, because it ensures that the slopes in the image align well with the DEM. If you don't match the DEM and there are geolocation offsets between the image and the DEM, the slopes may be a bit offset between the image and the DEM, so the normalization of the backscatter and the alignment of the ridges might not be as good as if DEM matching is applied.
For most time series analysis (with the legacy DEMs), we found that the geolocation shifts introduced by DEM matching were more of a detriment to analysis than the reduction in RTC quality that results from not matching. We left the option available for those who are less interested in time series analysis, and are looking at potentially maximizing the RTC quality when looking at a particular image.
We thought that perhaps with the Copernicus DEM there wouldn't be as much of an offset, but a 40m offset is quite significant. Was the issue resolved by having the DEM matching option disabled? With the legacy DEMs, we found that offsets were more likely to occur in areas that were lacking distinctive topographic features. Without clear features to match to the DEM, features can be matched to the DEM incorrectly; that may still be the case with the Copernicus DEM in areas of low relief.
For older missions, DEM matching often improved the geolocation of the output product, but because the orbit information for Sentinel-1 is so precise, the geolocation of the S1 data is often better than the legacy DEMs. It seems like the Copernicus DEM has better geolocation, which suggests that the DEM matching should work better, but perhaps that's also a reason not to bother with DEM matching; if both the image and the DEM have good geolocation, the features should align well even without matching.
Hi Everyone! I'm new to using HyP3 and have a question about what types of granules are supported. I'd like to process a GRD_MD file over the Lincoln sea (the specific granule is S1B_EW_GRDM_1SDH_20190909T141720_20190909T141825_017962_021D12_8083). However, it doesn't look like it is possible to process that granule on Vertex or using the SDK. When I try to submit the granule using the SDK I get a 400 Client Error message. On vertex, it looks like all of the GRD_HD files can be processed, but not the GRD_MD files.
Is that right?
Are there specifics types of granules that are not supported by Hyp3? Thanks so much for your help. This looks like a fantastic tool and I'm excited to become more familiar with it.
3 replies
I have been using HYP3 over the past several years and update order inventories every few months for a forest degradation project, ROI the lowland Choco of Ecuador. I no longer see Sentinel-1 10 m product availability for RTC GAMMA processing. This is a topographically complex region so the higher resolution data is preferred as I temporal filter the time series data. Is the 10 meter product feature available for this project?
I have used HYP3 to obtain ~550 scenes at 30 m and would like to reprocess ~300 of these scenes at 10 m for comparison. Thank you for your guidance . HYP3 is a godsend
Or you can check our newsfeed: https://hyp3-docs.asf.alaska.edu/whats_new/
