Utilities for JRSRP users to interact with common STAC providers
Project description
rss_da_stac - Python utilities for interacting with common STAC providers
Remote Sensing Scientists associated with the JRSRP have several established work practices that have been developed over many years, and predate STAC and cloud-native Earth Observation (EO) data.
This package is designed To help integrate
their current work approaches with modern data providers via STAC. Of particular
interest is the interoperability of the qvf
name convention and how that relates to STAC. Several utilities are designed
to work with qvf style names, such as
qvf2item: Convert one or more QVF files to a STAC ItemCollectionitem2qvf: Given a stac item or itemcollection, provide the equivalent qvf compliant name for each item.
see notes for details on the included scripts and the API.
Installation
Use pip or uv, for example, as part of a uv project:
uv add rss-da-stac
Using as a command-line tool
The quickest way to run rss-stac without setting up a project is with uvx:
uvx rss-da-stac qvf2item cfmsre_t56kkv_20221223_adbm6.tif
This downloads and runs the package in a temporary environment — no installation needed.
If you want the rss-stac command permanently available on your system:
uv tool install rss-da-stac
rss-stac qvf2item cfmsre_t56kkv_20221223_adbm6.tif
Citation
If you use this software in your research, please cite it as:
Denham, Robert (2026). rss_da_stac_source_code: Python utilities for interacting with common STAC providers for remote sensing scientists. Version 0.1.5. The University of Queensland. Data Collection. https://doi.org/10.48610/d3a13bb
BibTeX
@misc{denham_2026_rss_da_stac,
author = {Denham, Robert},
title = {rss\_da\_stac\_source\_code: Python utilities for interacting
with common STAC providers for remote sensing scientists},
year = {2026},
version = {0.1.5},
publisher = {The University of Queensland},
type = {Data Collection},
doi = {10.48610/d3a13bb},
url = {https://doi.org/10.48610/d3a13bb}
}
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