Populating Algorithms: Mogpr from Fusets

algorithm_catalog/fusets_mogpr.json

@@ -0,0 +1,136 @@
+{
+    "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"
+        }
+    ]
+}

benchmark_scenarios/fusets_mogpr.json

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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"
+        }
+    }
+]

openeo_udp/fusets_mogpr/README.md

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+# Sentinel-1 and Sentinel-2 data fusion through Multi-output Gaussian process regression (MOGPR)
+
+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.
+
+## Parameters
+
+The `fusets_mogpr_s1s2` service requires the following parameters:
+
+
+| 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    |
+
+## Supported collections
+
+#### Sentinel-1
+
+* RVI
+* GRD
+
+#### Sentinel-2
+
+* NDVI
+* FAPAR
+* LAI
+* FCOVER
+* EVI
+* CCC
+* CWC
+
+## Limitations
+
+The spatial extent is limited to a maximum size equal to a Sentinel-2 MGRS tile (100 km x 100 km).
+
+## Dependencies
+
+In addition to various Python libraries, the workflow utilizes the following libraries included in the User-Defined Function (UDF):
+
+* 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. 
+
+* 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).
+
+
+
+## Output
+
+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.