MIT License

项目介绍

ESA-PhiLab/OpenSarToolkit 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 248 个 Star、57 次 Fork。

仓库全名
ESA-PhiLab/OpenSarToolkit
开源许可证
MIT License
Star 数
248
Fork 数
57
未关闭 Issue
13

README 摘要

.. image:: https://raw.githubusercontent.com/ESA-PhiLab/OpenSarToolkit/main/docs/source/images/headerimage.PNG :alt: cool ost image Open SAR Toolkit (OST) ====================== :target: LICENSE :alt: License: MIT :alt: PyPI version :target: https://pypi.org/project/opensartoolkit/ :alt: PyPI - Download :target: https://github.com/psf/black :target: https://conventionalcommits.org :alt: conventional commit :target…

完整内容见 GitHub 原始 README 或本页 。

常见问题

OpenSarToolkit 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 248 个 Star。

OpenSarToolkit 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 OpenSarToolkit 的源码?

可以直接克隆仓库:git clone https://github.com/ESA-PhiLab/OpenSarToolkit.git,默认分支为 main;安装与运行步骤见仓库 README。

OpenSarToolkit 最近还在维护吗?

仓库最近一次更新为 2月4日,当前有 13 个未关闭 Issue;Star 数为 248,可作为社区活跃度的参考。

关于

High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language.

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

简要分析

热度分
377
价值分
166
活跃状态
活跃

语言占比

Dockerfile
Python

Release

README

… image:: https://raw.githubusercontent.com/ESA-PhiLab/OpenSarToolkit/main/docs/source/_images/header_image.PNG :alt: cool ost image

Open SAR Toolkit (OST)

… image:: https://img.shields.io/badge/License-MIT-yellow.svg :target: LICENSE :alt: License: MIT

… image:: https://badge.fury.io/py/opensartoolkit.svg :target: https://badge.fury.io/py/opensartoolkit :alt: PyPI version

… image:: https://img.shields.io/pypi/dm/opensartoolkit?color=307CC2&logo=python&logoColor=gainsboro
:target: https://pypi.org/project/opensartoolkit/ :alt: PyPI - Download

… image:: https://img.shields.io/badge/code style-black-000000.svg :target: https://github.com/psf/black :alt: Black badge

… image:: https://img.shields.io/badge/Conventional Commits-1.0.0-yellow.svg :target: https://conventionalcommits.org :alt: conventional commit

… image:: https://codecov.io/gh/ESA-PhiLab/OpenSarToolkit/branch/main/graph/badge.svg?token=P32CMJSSA9 :target: https://codecov.io/gh/ESA-PhiLab/OpenSarToolkit :alt: codecov report

… image:: https://readthedocs.org/projects/opensartoolkit/badge/?version=latest :target: https://opensartoolkit.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

… image:: https://img.shields.io/badge/all_contributors-5-orange.svg :target: https://opensartoolkit.readthedocs.io/en/latest/setup/contributors.html :alt: all-contributor

Objective

This python package lowers the entry barrier for accessing and pre-processing Sentinel-1 data for land applications and allows users with little knowledge on SAR and python to produce various Analysis-Ready-Data products.

Functionality

The Open SAR Toolkit (OST) bundles the full workflow for the generation of Analysis-Ready-Data (ARD) of Sentinel-1 for Land in a single high-level python package. It includes functions for data inventory and advanced sorting as well as downloading from various mirrors. The whole pre-processing is bundled in a single function and different types of ARD can be selected, but also customised. OST does include advanced types of ARD such as combined production of calibrated backscatter, interferometric coherence and the dual-polarimetric H-A-Alpha decomposition. Time-series and multi-temporal statistics (i.e. timescans) can be produced for each of these layers and the generation of spatially-seamless large-scale mosaic over time is possible a well.

The Open SAR Toolkit realises this by using an object-oriented approach, providing classes for single scene processing, GRD and SLC batch processing routines. The SAR processing itself relies on ESA’s Sentinel-1 Toolbox as well as some geospatial python libraries and the Orfeo Toolbox for mosaicking.

Please refer to our documentation <https://opensartoolkit.readthedocs.io/en/latest/>__ to get started.

Examples

Ecuador VV-polarised Timescan Composite ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  • Year: 2016
  • Sensor: Sentinel-1 C-Band SAR.
  • Acquisitions: 6 acquisitions per swath (4 swaths)
  • Output resolution: 30m
  • RGB composite:
    • Red: VV-maximum
    • Green: VV-minimum
    • Blue: VV-Standard deviation

… image:: https://raw.githubusercontent.com/ESA-PhiLab/OpenSarToolkit/main/docs/source/_images/ecuador_VV_max_min_std.png :alt: Ecuador VV-polarised Timescan Composite

Ethiopia VV-VH polarised Timescan Composite ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  • Year: 2016-2017
  • Sensor: Sentinel-1 C-Band SAR.
  • Acquisitions: 7 acquisitions per swath (about 400 scenes over 8 swaths)
  • Output resolution: 30m
  • RGB composite:
    • Red: VV-minimum
    • Green: VH-minimum
    • Blue: VV-Standard deviation

… image:: https://raw.githubusercontent.com/ESA-PhiLab/OpenSarToolkit/main/docs/source/_images/eth_vvvh_ts.jpeg :alt: Ethiopia VV-VH polarised Timescan Composite

Origin of the project

Open SAR Toolkit was initially developed at the Food and Agriculture Organization of the United Nations under the SEPAL <https://github.com/openforis/sepal>__ project between 2016-2018. It is still available there <https://github.com/openforis/opensarkit>, but has been completely re-factored and transferred into a simpler and less-dependency rich Python 3 version, which can be found on this page here. Instead of using R-Shiny as a GUI, the main interface are now Jupyter notebooks <https://opensartoolkit.readthedocs.io/en/latest/example/index.html> that are developed in parallel to this core package and should help to get started.

Authors

meet our contributors <https://opensartoolkit.readthedocs.io/en/latest/setup/contributors.html>__.

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