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5a8e899
mogpr to openeo_udp
Pratichhya f13121c
changed process id
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moved dir due to sys path issue
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algorithm catalog
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benchmark scenario
Pratichhya bb8e7fb
updated namespace
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preetify json
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ruff checked
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updated the README.md file
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updated requirement txt
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addressed the suggested changes on the set_path function
Pratichhya cdd5dff
finalised changes with udp
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fusets_version
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back to insert instead of append
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updated benchmark scenario and results
Pratichhya 73ee639
updated udp to mogpe_s1s2
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updated benchmark scenario
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output format
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solution for sys path in UDF
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latest changes in dependencies implemented
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corrected encoding
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temporary link
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minor changes with text
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removed fusets from requirements
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{ | ||
"id": "fusets_mogpr", | ||
"type": "Feature", | ||
"conformsTo": [ | ||
"http://www.opengis.net/spec/ogcapi-records-1/1.0/req/record-core" | ||
], | ||
"geometry": null, | ||
"properties": { | ||
"created": "2025-01-09T00:00:00Z", | ||
"updated": "2025-01-29T00:00:00Z", | ||
"type": "apex_algorithm", | ||
"title": "Multi output gaussian process regression", | ||
"description": "Integrates timeseries in data cube using multi-output gaussian process regression. The service is designed to enable multi-output regression analysis using Gaussian Process Regression (GPR) on geospatial data. It provides a powerful tool for understanding and predicting spatiotemporal phenomena by filling gaps based on other indicators that are correlated with each other.", | ||
"cost_estimate": 12, | ||
"cost_unit": "platform credits per km²", | ||
"keywords": [ | ||
"timeseries", | ||
"Gaussian Process Regression (GPR)" | ||
], | ||
"language": { | ||
"code": "en-US", | ||
"name": "English (United States)" | ||
}, | ||
"languages": [ | ||
{ | ||
"code": "en-US", | ||
"name": "English (United States)" | ||
} | ||
], | ||
"contacts": [ | ||
{ | ||
"name": "Bram Janssen", | ||
"position": "Researcher", | ||
"organization": "VITO", | ||
"links": [ | ||
{ | ||
"href": "https://www.vito.be/", | ||
"rel": "about", | ||
"type": "text/html" | ||
}, | ||
{ | ||
"href": "https://github.com/JanssenBrm", | ||
"rel": "about", | ||
"type": "text/html" | ||
} | ||
], | ||
"contactInstructions": "Contact via VITO", | ||
"roles": [ | ||
"principal investigator" | ||
] | ||
}, | ||
{ | ||
"name": "Pratichhya Sharma", | ||
"position": "Researcher", | ||
"organization": "VITO", | ||
"links": [ | ||
{ | ||
"href": "https://www.vito.be/", | ||
"rel": "about", | ||
"type": "text/html" | ||
}, | ||
{ | ||
"href": "https://github.com/Pratichhya", | ||
"rel": "about", | ||
"type": "text/html" | ||
} | ||
], | ||
"contactInstructions": "Contact via VITO", | ||
"roles": [ | ||
"service provider" | ||
] | ||
}, | ||
{ | ||
"name": "VITO", | ||
"links": [ | ||
{ | ||
"href": "https://www.vito.be/", | ||
"rel": "about", | ||
"type": "text/html" | ||
} | ||
], | ||
"contactInstructions": "SEE WEBSITE", | ||
"roles": [ | ||
"processor" | ||
] | ||
} | ||
], | ||
"themes": [ | ||
{ | ||
"concepts": [ | ||
{ | ||
"id": "Normalised vegetation difference index (NDVI)" | ||
}, | ||
{ | ||
"id": "Radar Vegetation Index (RVI)" | ||
}, | ||
{ | ||
"id": "Multi-output Gaussian Process Regression (MOGPR)" | ||
} | ||
], | ||
"scheme": "https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords" | ||
} | ||
], | ||
"formats": [ | ||
{ | ||
"name": "JSON" | ||
} | ||
], | ||
"license": "other" | ||
}, | ||
"linkTemplates": [], | ||
"links": [ | ||
{ | ||
"rel": "openeo-process", | ||
"type": "application/json", | ||
"title": "openEO Process Definition", | ||
"href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/09413be3c27e0e695d426c9ffe5a0fe90beefe65/openeo_udp/fusets_mogpr/fusets_mogpr.json" | ||
}, | ||
{ | ||
"rel": "service", | ||
"type": "application/json", | ||
"title": "CDSE openEO federation", | ||
"href": "https://openeofed.dataspace.copernicus.eu" | ||
}, | ||
{ | ||
"rel": "license", | ||
"href": "https://apex.esa.int/license" | ||
}, | ||
{ | ||
"rel": "example", | ||
"type": "application/json", | ||
"title": "Example output", | ||
"href": "https://s3.waw3-1.cloudferro.com/swift/v1/apex-examples/fusets_mogpr/fusets_mogpr.nc" | ||
} | ||
] | ||
} |
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[ | ||
{ | ||
"id": "fusets_mogpr", | ||
"type": "openeo", | ||
"description": "Multi output gaussian process regression example on NDVI timeseries", | ||
"backend": "openeofed.dataspace.copernicus.eu", | ||
"process_graph": { | ||
"fusetsmogpr": { | ||
"arguments": { | ||
"s1_collection": "RVI", | ||
"s2_collection": "NDVI", | ||
"spatial_extent": { | ||
"coordinates": [ | ||
[ | ||
[ | ||
5.178303838475193, | ||
51.252856237848164 | ||
], | ||
[ | ||
5.178003609252369, | ||
51.25109194151486 | ||
], | ||
[ | ||
5.179280940922463, | ||
51.25103833409551 | ||
], | ||
[ | ||
5.179565949577788, | ||
51.25278555186941 | ||
], | ||
[ | ||
5.178303838475193, | ||
51.252856237848164 | ||
] | ||
] | ||
], | ||
"type": "Polygon" | ||
}, | ||
"temporal_extent": [ | ||
"2021-01-01", | ||
"2021-12-15" | ||
] | ||
}, | ||
"namespace": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/09413be3c27e0e695d426c9ffe5a0fe90beefe65/openeo_udp/fusets_mogpr/fusets_mogpr.json", | ||
"process_id": "fusets_mogpr" | ||
} | ||
}, | ||
"reference_data": { | ||
"timeseries.nc": "https://s3.waw3-1.cloudferro.com/swift/v1/apex-examples/fusets_mogpr/fusets_mogpr.nc" | ||
} | ||
} | ||
] |
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# Sentinel-1 and Sentinel-2 data fusion through Multi-output Gaussian process regression (MOGPR) | ||
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This service is designed to enable multi-output regression analysis using Gaussian Process Regression (GPR) on geospatial data. It provides a powerful tool for understanding and predicting spatiotemporal phenomena by filling gaps based on other correlated indicators. This service focuses on fusing Sentinel-1 and Sentinel-2 data, allowing the user to select one of the predefined data sources. | ||
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## Parameters | ||
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The `fusets_mogpr_s1s2` service requires the following parameters: | ||
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| Name | Description | Type | Default | | ||
| --------------- | -------------------------------------------------------------- | ------- | ------- | | ||
| spatial_extent | Polygon representing the AOI on which to apply the data fusion | GeoJSON | | | ||
| temporal_extent | Date range for which to apply the data fusion | Array | | | ||
| s1_collection | S1 data collection to use for the fusion | Text | RVI | | ||
| s2_collection | S2 data collection to use for fusing the data | Text | NDVI | | ||
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## Supported collections | ||
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#### Sentinel-1 | ||
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* RVI | ||
* GRD | ||
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#### Sentinel-2 | ||
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* NDVI | ||
* FAPAR | ||
* LAI | ||
* FCOVER | ||
* EVI | ||
* CCC | ||
* CWC | ||
|
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## Limitations | ||
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The spatial extent is limited to a maximum size equal to a Sentinel-2 MGRS tile (100 km x 100 km). | ||
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## Dependencies | ||
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In addition to various Python libraries, the workflow utilizes the following libraries included in the User-Defined Function (UDF): | ||
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* Biopar: The `biopar` package retrieves biophysical parameters like FAPAR, FCOVER, and more, that were passed as the S2_collection. The biopar package is a Python package that calculates biophysical parameters from Sentinel-2 satellite images as described [here](https://step.esa.int/docs/extra/ATBD_S2ToolBox_L2B_V1.1.pdf). The `fusets_mogpr` udp directly uses the biopar udp shared in the APEX Algorithms repository. | ||
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* FuseTS: The `fusets` library was developed to facilitate data fusion and time-series analytics using AI/ML to extract insights about land environments. It functions as a Time Series & Data Fusion toolbox integrated with openEO. For additional information, please refer to the [FuseTS documentation](https://open-eo.github.io/FuseTS/installation.html). | ||
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## Output | ||
|
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This User-Defined-Process (UDP) produces a datacube that contains a gap-filled time series for all pixels within the specified temporal and spatial range. This datacube can be seamlessly integrated with other openEO processes. |
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