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included rvi process graph seperately
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,140 @@ | ||
| { | ||
| "id": "RVI", | ||
| "summary": "Radar Vegetation Index(RVI) using Sentinel-1 GRD collection", | ||
| "description": "The Radar Vegetation Index (RVI) is a measure used in remote sensing and agriculture to assess the health and condition of vegetation using radar data. The RVI has been used in several previous research studies, especially for predicting the growth level of crop vegetation over time and many more. However, here, we will stick to a simple example of calculating RVI.\n The formula adopted here is: \n\n $\\mathrm{RVI}=\frac{4 \\sigma^0{ }_{V H}}{\\sigma^0{ }_{V V}+\\sigma^0{ }_{V H}}$,\n\nwhere $\\sigma^0{ }_{V H},\\sigma^0{ }_{V V}$ and $\\sigma^0{ }_{V H}$ are the polarised backscattering coefficients", | ||
| "categories": [ | ||
| " math > indices" | ||
| ], | ||
| "parameters": [ | ||
| { | ||
| "description": "The date range to load.", | ||
| "name": "date_range", | ||
| "schema": { | ||
| "subtype": "temporal-interval", | ||
| "type": "array" | ||
| } | ||
| }, | ||
| { | ||
| "description": "The bounding box to load.", | ||
| "name": "bbox", | ||
| "schema": { | ||
| "subtype": "geojson", | ||
| "type": "object" | ||
| } | ||
| } | ||
| ], | ||
| "returns": { | ||
| "description": "A raster showing crop vegetation over time.", | ||
| "schema": { | ||
| "type": "object", | ||
| "subtype": "raster-cube" | ||
| } | ||
| }, | ||
| "process_graph": { | ||
| "loadcollection1": { | ||
| "arguments": { | ||
| "bands": [ | ||
| "VV", | ||
| "VH" | ||
| ], | ||
| "id": "SENTINEL1_GRD", | ||
| "spatial_extent": { | ||
| "from_parameter": "bbox" | ||
| }, | ||
| "temporal_extent": { | ||
| "from_parameter": "date_range" | ||
| } | ||
| }, | ||
| "process_id": "load_collection" | ||
| }, | ||
| "reducedimension1": { | ||
| "arguments": { | ||
| "data": { | ||
| "from_node": "sarbackscatter1" | ||
| }, | ||
| "dimension": "bands", | ||
| "reducer": { | ||
| "process_graph": { | ||
| "add1": { | ||
| "arguments": { | ||
| "x": { | ||
| "from_node": "arrayelement2" | ||
| }, | ||
| "y": { | ||
| "from_node": "arrayelement3" | ||
| } | ||
| }, | ||
| "process_id": "add" | ||
| }, | ||
| "arrayelement1": { | ||
| "arguments": { | ||
| "data": { | ||
| "from_parameter": "data" | ||
| }, | ||
| "index": 1 | ||
| }, | ||
| "process_id": "array_element" | ||
| }, | ||
| "arrayelement2": { | ||
| "arguments": { | ||
| "data": { | ||
| "from_parameter": "data" | ||
| }, | ||
| "index": 0 | ||
| }, | ||
| "process_id": "array_element" | ||
| }, | ||
| "arrayelement3": { | ||
| "arguments": { | ||
| "data": { | ||
| "from_parameter": "data" | ||
| }, | ||
| "index": 1 | ||
| }, | ||
| "process_id": "array_element" | ||
| }, | ||
| "divide1": { | ||
| "arguments": { | ||
| "x": { | ||
| "from_node": "multiply1" | ||
| }, | ||
| "y": { | ||
| "from_node": "add1" | ||
| } | ||
| }, | ||
| "process_id": "divide", | ||
| "result": true | ||
| }, | ||
| "multiply1": { | ||
| "arguments": { | ||
| "x": 4, | ||
| "y": { | ||
| "from_node": "arrayelement1" | ||
| } | ||
| }, | ||
| "process_id": "multiply" | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| "process_id": "reduce_dimension", | ||
| "result": true | ||
| }, | ||
| "sarbackscatter1": { | ||
| "arguments": { | ||
| "coefficient": "sigma0-ellipsoid", | ||
| "contributing_area": false, | ||
| "data": { | ||
| "from_node": "loadcollection1" | ||
| }, | ||
| "elevation_model": null, | ||
| "ellipsoid_incidence_angle": false, | ||
| "local_incidence_angle": false, | ||
| "mask": false, | ||
| "noise_removal": true | ||
| }, | ||
| "process_id": "sar_backscatter" | ||
| } | ||
| }, | ||
| "public": true | ||
| } |