https://github.com/isce-framework/sweets
Simple Workflows for End-to-End InSAR Time Series
https://github.com/isce-framework/sweets
geophysics glaciers insar remote-sensing sentinel-1 subsidence synthetic-aperture-radar tectonics time-series
Last synced: 19 days ago
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Simple Workflows for End-to-End InSAR Time Series
- Host: GitHub
- URL: https://github.com/isce-framework/sweets
- Owner: isce-framework
- License: other
- Created: 2023-02-20T16:21:48.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-12-15T18:44:33.000Z (28 days ago)
- Last Synced: 2025-12-19T02:14:07.166Z (24 days ago)
- Topics: geophysics, glaciers, insar, remote-sensing, sentinel-1, subsidence, synthetic-aperture-radar, tectonics, time-series
- Language: Python
- Homepage:
- Size: 854 KB
- Stars: 45
- Watchers: 5
- Forks: 12
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# sweets
[](https://results.pre-commit.ci/latest/github/isce-framework/sweets/main)
Workflow for creating unwrapped interferograms from Sentinel-1 geocoded SLCs.
## Install
`sweets` is available to install via conda-forge:
```bash
mamba install -c conda-forge sweets
```
Alternatively, the following will install `sweets` into a conda environment.
1. Download source code:
```bash
git clone https://github.com/opera-adt/sweets.git && cd sweets
```
2. Install dependencies:
```bash
mamba env create --file conda-env.yml
```
or if you have an existing environment:
```bash
mamba env update --name my-existing-env --file conda-env.yml
```
3. Install `sweets` via pip:
```bash
conda activate sweets-env
python -m pip install .
```
## Usage
From the command line, installing will create a `sweets` executable. You can run `sweets --help` to see the available options.
```bash
sweets --help
```
To configure a workflow, the minimum inputs are
- the bounding box of the area of interest in degrees longitude/latitude as (left, bottom right top)
- the start date (and end date, or it is assumed to be today)
- the track (relative orbit) number.
For example:
```bash
sweets config --bbox -102.2 32.15 -102.1 32.22 --start 2022-12-15 --end 2022-12-29 --track 78
```
This will make a YAML configuration file (by default `sweets_config.yaml`). You can inspect it to see all the configuration defaults.
Then you can kick off the workflow using
```bash
sweets run sweets_config.yaml
```
### Configuration from Python
Alternatively, you can configure everything in python:
```python
from sweets.core import Workflow
bbox = (-102.3407, 31.9909, -101.9407, 32.3909)
start = "2020-01-01" # can be strings or datetime objects
track = 78
w = Workflow(bbox=bbox, asf_query=dict(start=start, end=end, relativeOrbit=track))
w.run()
```
You can also save the workflow to a config file for later use/to inspect or change parameters:
```
w.to_yaml() # Saves to sweets_config.yml for inspection/tweaking
```
If you want to run this later from the config, you can do
```python
w = Workflow.from_yaml("sweets_config.yml")
w.run()
```
You can also print an empty config file to edit any parameters manually
```bash
sweets config --print-empty
```
## License
This software is licensed under your choice of BSD-3-Clause or Apache-2.0 licenses. See the accompanying LICENSE file for further details.
SPDX-License-Identifier: BSD-3-Clause OR Apache-2.0