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Open SAR Toolkit (OST)

License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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

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

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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.

Authors

meet our contributors.

About

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

opensartoolkit.readthedocs.io/en/latest/

Topics

earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar

Resources

Readme
MIT license

Contributing

Contributing
Activity
Custom properties

Stars

246 stars

Watchers

15 watching

Forks

59 forks
Report repository

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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cool ost image
Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages

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Open SAR Toolkit (OST)
License: MITPyPI versionPyPI - DownloadBlack badgeconventional commitcodecov reportDocumentation Statusall-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 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
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
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 project between 2016-2018. It is still available there, 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 that are developed in parallel to this core package and should help to get started.
Authors
meet our contributors.
About
High-level functionality for the inventory, download and pre-processing of Sentinel-1 data in the python language. 
opensartoolkit.readthedocs.io/en/latest/
Topics
earthobservationesapythonremote-sensingsarsentinel-1syntheticapertureradar
Resources
Readme
MIT license
Contributing
Contributing
Activity
Custom properties
Stars
246 stars
Watchers
15 watching
Forks
59 forks
Report repository
Releases
Used by
Contributors
Languages