Parcel Delineation - Fixes

algorithm_catalog/vito/parcel_delineation/openeo_udp/README.md

@@ -1,4 +1,20 @@
-# Parcel delineation
-This is an [openEO](https://openeo.org/) example for delineating agricultural parcels based on a neural network, using Sentinel-2 input data.
+# Parcel Delineation
+Parcel delineation refers to the identification and marking of agricultural boundaries. 
+This process is *essential* for tasks such as crop yield estimation and land management. 
+Accurate delineation also aids in classifying crop types and managing farmland more effectively.
+
+## Algorithm for Parcel Delineation Using Sentinel-2 Data  
 
-[VITO Remote Sensing](https://remotesensing.vito.be)
+This algorithm performs parcel delineation using Sentinel-2 data and a pre-trained`U-Net machine learning model. The process involves the following steps:
+1. **Pre-processing Sentinel-2 Data:**
+   1. Filter data to ensure a maximum of 10% cloud coverage.  
+   2. Apply a cloud mask based on the SCL layer.  
+2. **Compute NDVI:**
+   1. The Normalized Difference Vegetation Index (NDVI) is calculated from the pre-processed data.
+   2. The NDVI serves as input to the U-Net model. 
+3. **Predict Delineation:**
+   1. The U-Net model predicts parcel delineation boundaries. 
+4. **Optimization and Labeling:**
+   1. Apply a Sobel filter to enhance edge detection.  
+   2. Use Felzenszwalb's algorithm for segmentation and labeling of delineated parcels.
+

algorithm_catalog/vito/parcel_delineation/openeo_udp/generate.py

@@ -85,7 +85,7 @@ def generate() -> dict:
         process_graph=sobel_felzenszwalb,
         process_id="parcel_delineation",
         summary="Parcel delineation using Sentinel-2 data retrieved from the CDSE and processed on openEO.",
-        description="Parcel delineation using Sentinel-2",
+        description= (Path(__file__).parent / "README.md").read_text(),
         parameters=[spatial_extent, temporal_extent],
         default_job_options=job_options,
     )

algorithm_catalog/vito/parcel_delineation/openeo_udp/parcel_delineation.json

@@ -207,7 +207,7 @@
   },
   "id": "parcel_delineation",
   "summary": "Parcel delineation using Sentinel-2 data retrieved from the CDSE and processed on openEO.",
-  "description": "Parcel delineation using Sentinel-2",
+  "description": "# Parcel Delineation\nParcel delineation refers to the identification and marking of agricultural boundaries. \nThis process is *essential* for tasks such as crop yield estimation and land management. \nAccurate delineation also aids in classifying crop types and managing farmland more effectively.\n \n## Algorithm for Parcel Delineation Using Sentinel-2 Data  \n\nThis algorithm performs parcel delineation using Sentinel-2 data and a pre-trained`U-Net machine learning model. The process involves the following steps:\n1. **Pre-processing Sentinel-2 Data:**\n   1. Filter data to ensure a maximum of 10% cloud coverage.  \n   2. Apply a cloud mask based on the SCL layer.  \n2. **Compute NDVI:**\n   1. The Normalized Difference Vegetation Index (NDVI) is calculated from the pre-processed data.\n   2. The NDVI serves as input to the U-Net model. \n3. **Predict Delineation:**\n   1. The U-Net model predicts parcel delineation boundaries. \n4. **Optimization and Labeling:**\n   1. Apply a Sobel filter to enhance edge detection.  \n   2. Use Felzenszwalb's algorithm for segmentation and labeling of delineated parcels.\n ",
   "default_job_options": {
     "udf-dependency-archives": [
       "https://artifactory.vgt.vito.be/auxdata-public/openeo/onnx_dependencies.zip#onnx_deps",

algorithm_catalog/vito/parcel_delineation/records/parcel_delineation.json

@@ -2,8 +2,8 @@
   "id": "parcel_delineation",
   "type": "Feature",
   "conformsTo": [
-      "http://www.opengis.net/spec/ogcapi-records-1/1.0/req/record-core",
-      "https://apex.esa.int/core/openeo-udp"
+    "http://www.opengis.net/spec/ogcapi-records-1/1.0/req/record-core",
+    "https://apex.esa.int/core/openeo-udp"
   ],
   "geometry": null,
   "properties": {
@@ -91,7 +91,7 @@
       "rel": "application",
       "type": "application/vnd.openeo+json;type=process",
       "title": "openEO Process Definition",
-	"href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/4edc975de279d2800e5d5367032340090d554761/algorithm_catalog/vito/parcel_delineation/openeo_udp/parcel_delineation.json"
+      "href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/4edc975de279d2800e5d5367032340090d554761/algorithm_catalog/vito/parcel_delineation/openeo_udp/parcel_delineation.json"
     },
     {
       "rel": "code",
@@ -110,6 +110,21 @@
       "type": "text/html",
       "title": "OpenEO Web Editor",
       "href": "https://editor.openeo.org/?wizard=UDP&wizard~process=parceldelination&wizard~processUrl=https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/4edc975de279d2800e5d5367032340090d554761/algorithm_catalog/vito/parcel_delineation/openeo_udp/parcel_delineation.json&server=https://openeo.dataspace.copernicus.eu"
+    },
+    {
+      "rel": "thumbnail",
+      "type": "image/png",
+      "href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/refs/heads/main/algorithm_catalog/vito/parcel_delineation/images/header.png"
+    },
+    {
+      "rel": "preview",
+      "type": "image/jpeg",
+      "href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/refs/heads/main/algorithm_catalog/vito/parcel_delineation/images/preview_1.jpg"
+    },
+    {
+      "rel": "preview",
+      "type": "image/jpeg",
+      "href": "https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/refs/heads/main/algorithm_catalog/vito/parcel_delineation/images/preview_2.jpg"
     }
   ]
-}
+}