open-source sea ice drift algorithm for sentinel-1 sar imagery using a combination of feature tracking and pattern matching
Clicks: 227
ID: 151154
2017
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
227 views
33 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #28 of 134 articles by views in journal of applied polymer science
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 134 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is
introduced based on the combination of feature tracking and pattern matching.
Feature tracking produces an initial drift estimate and limits the search
area for the consecutive pattern matching, which provides small- to medium-scale drift adjustments and normalised cross-correlation values. The
algorithm is designed to combine the two approaches in order to benefit from
the respective advantages. The considered feature-tracking method allows for
an efficient computation of the drift field and the resulting
vectors show a high degree of independence in terms of position, length,
direction and rotation. The considered pattern-matching method, on the other
hand, allows better control over vector positioning and resolution. The
preprocessing of the Sentinel-1 data has been adjusted to retrieve a feature
distribution that depends less on SAR backscatter peak values. Applying the
algorithm with the recommended parameter setting, sea ice drift retrieval
with a vector spacing of 4 km on Sentinel-1 images covering
400 km × 400 km, takes about 4 min on a standard 2.7 GHz processor with 8 GB
memory. The corresponding recommended patch size for the pattern-matching
step that defines the final resolution of each drift vector is 34 × 34 pixels
(2.7 × 2.7 km). To assess the potential performance after
finding suitable search restrictions, calculated drift results from
246 Sentinel-1 image pairs have been compared to buoy GPS data, collected in 2015 between 15 January and 22 April and covering an area from 80.5 to 83.5° N and 12 to 27° E. We found a logarithmic normal distribution of the displacement difference with a median at 352.9 m using HV polarisation and 535.7 m using HH polarisation. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.
| Reference Key |
muckenhuber2017theopen-source
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;S. Muckenhuber;S. Sandven |
| Journal | journal of applied polymer science |
| Year | 2017 |
| DOI |
10.5194/tc-11-1835-2017
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.