Data · dataset · 2022
StaMPS-SBAS InSAR Data of landslide in Maoxian County, Sichuan Province
Listed in ScienceDB
1.
Description
Preprocess the sentinel-1a data of 22 scenes covering the landslide area of Mao County from October 19, 2020 to July 10, 2021. By setting the baseline threshold, a total of 67 differential interferograms are generated for time series analysis.2.
Use GAMMA software to preprocess sentinel data. The main steps of preprocessing are:Data extraction::S1_BURST_tab_from_zipfile,S1_import_SLC_from_zipfilesGeocoding:multi_look_ScanSAR,dem_import,gc_map2,pixel_area,create_diff_par,offset_pwrm,offset_fitm,gc_map_fine,pixel_area,geocodeImage registration:ScanSAR_coreg.pyDeramp:S1_deramp_TOPS_slave3.The data input into stamps software consists of three folders:dem,geo,SMALL_BASELINE.The corresponding data under the folder are:• ./SMALL BASELINES/yyyymmdd yyyymmdd/yyyymmdd.rslc a resampled SLC for the master image in every interferogram • ./SMALL BASELINES/yyyymmdd yyyymmdd/yyyymmdd.rslc a resampled SLC for the slave image in every interferogram • ./SMALL BASELINES/yyyymmdd yyyymmdd/yyyymmdd.rslc.par the SLC parameter file for the super-master • ./SMALL BASELINES/yyyymmdd yyyymmdd/yyyymmdd yyyymmdd.diff the interferograms • ./SMALL BASELINES/yyyymmdd yyyymmdd/yyyymmdd yyyymmdd.base a base file for every interferogram • ./geo/yyyymmdd dem.rdc the DEM in super-master radar coordinates • ./geo/yyyymmdd.lon the longitude of every pixel in the super-master SLC • ./geo/yyyymmdd.lat the latitude of every pixel in the super-master SLC4.The data set is opened with stamps software, and the software download address is: homepages.see.leeds.ac.uk/~earahoo/stamps/。Run ps_plot ('v-dao ',' a_linear ') under the SMALL_BASELINES folder to get the average deformation rate and observe obvious landslide.
Links
Where it is published
- DOI doi.org/10.11922/sciencedb.01610 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.11922%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Image 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.11922/sciencedb.01610 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |