Update processes according to discussions

CHANGELOG.md

@@ -8,7 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Update the processes based on `raster-cube` or `vector-cube` to work with `datacube` instead
 - Rename `create_raster_cube` to `create_data_cube`
-- `add_dimension`: Added new dimension type `vector`
+- `add_dimension`: Added new dimension type `geometries`
 - New definition for `aggregate_spatial`:
     - Allows more than 3 input dimensions
     - Allow to not export statistics by changing the parameter `target_dimension`
@@ -53,7 +53,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 
 - `aggregate_spatial`:
-  - Clarified that vector properties are preserved for vector data cubes and all GeoJSON Features. [#270](https://github.com/Open-EO/openeo-processes/issues/270)
+  - Clarified that feature properties are preserved for vector data cubes and all GeoJSON Features. [#270](https://github.com/Open-EO/openeo-processes/issues/270)
   - Clarified that a `TargetDimensionExists` exception is thrown if the target dimension exists.
 - `apply` and `array_apply`: Fixed broken references to the `absolute` process
 - `apply_neighborhood`: Parameter `overlap` was optional but had no default value and no schena for the default value defined.

add_dimension.json

@@ -40,9 +40,9 @@
                 "type": "string",
                 "enum": [
                     "bands",
+                    "geometries",
                     "spatial",
                     "temporal",
-                    "vector",
                     "other"
                 ]
             },

aggregate_spatial.json

@@ -26,7 +26,7 @@
         },
         {
             "name": "geometries",
-            "description": "Geometries for which the aggregation will be computed. Vector properties are preserved for vector data cubes and all GeoJSON Features.\n\nOne value will be computed per label in the dimension of type `vector`, GeoJSON `Feature`, `Geometry` or `GeometryCollection`. For a `FeatureCollection` multiple values will be computed, one value per contained `Feature`. For example, a single value will be computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons.\n\n- For **polygons**, the process considers all pixels for which the point at the pixel center intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nThus, pixels may be part of multiple geometries and be part of multiple aggregations.\n\nTo maximize interoperability, a nested `GeometryCollection` should be avoided. Furthermore, a `GeometryCollection` composed of a single type of geometries should be avoided in favour of the corresponding multi-part type (e.g. `MultiPolygon`).",
+            "description": "Geometries for which the aggregation will be computed. Feature properties are preserved for vector data cubes and all GeoJSON Features.\n\nOne value will be computed per label in the dimension of type `geometries`, GeoJSON `Feature`, `Geometry` or `GeometryCollection`. For a `FeatureCollection` multiple values will be computed, one value per contained `Feature`. For example, a single value will be computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons.\n\n- For **polygons**, the process considers all pixels for which the point at the pixel center intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nThus, pixels may be part of multiple geometries and be part of multiple aggregations. No operation is applied to geometries that are outside of the bounds of the data.\n\nTo maximize interoperability, a nested `GeometryCollection` should be avoided. Furthermore, a `GeometryCollection` composed of a single type of geometries should be avoided in favour of the corresponding type (e.g. `MultiPolygon`).",
             "schema": [
                 {
                     "type": "object",
@@ -37,7 +37,7 @@
                     "subtype": "datacube",
                     "dimensions": [
                         {
-                            "type": "vector"
+                            "type": "geometries"
                         }
                     ]
                 }
@@ -101,13 +101,13 @@
         }
     ],
     "returns": {
-        "description": "A vector data cube with the computed results and restricted to the bounds of the geometries. The spatial dimensions is replaced by a vector dimension and if `target_dimension` is not `null`, a new dimension is added.",
+        "description": "A vector data cube with the computed results and restricted to the bounds of the geometries. The spatial dimensions is replaced by a geometries dimension and if `target_dimension` is not `null`, a new dimension is added.",
         "schema": {
             "type": "object",
             "subtype": "datacube",
             "dimensions": [
                 {
-                    "type": "vector"
+                    "type": "geometries"
                 }
             ]
         }

filter_bbox.json

@@ -31,7 +31,7 @@
                     "subtype": "datacube",
                     "dimensions": [
                         {
-                            "type": "vector"
+                            "type": "geometries"
                         }
                     ]
                 }
@@ -135,7 +135,7 @@
                 "subtype": "datacube",
                 "dimensions": [
                     {
-                        "type": "vector"
+                        "type": "geometries"
                     }
                 ]
             }

filter_spatial.json

@@ -1,7 +1,7 @@
 {
     "id": "filter_spatial",
     "summary": "Spatial filter raster data cubes using geometries",
-    "description": "Limits the raster data cube over the spatial dimensions to the specified geometries.\n\n- For **polygons**, the filter retains a pixel in the data cube if the point at the pixel center intersects with at least one of the polygons (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nMore specifically, pixels outside of the bounding box of the given geometry will not be available after filtering. All pixels inside the bounding box that are not retained will be set to `null` (no data).",
+    "description": "Limits the raster data cube over the spatial dimensions to the specified geometries.\n\n- For **polygons**, the filter retains a pixel in the data cube if the point at the pixel center intersects with at least one of the polygons (as defined in the Simple Features standard by the OGC).\n- For **points**, the process considers the closest pixel center.\n- For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line.\n\nMore specifically, pixels outside of the bounding box of the given geometry will not be available after filtering. All pixels inside the bounding box that are not retained will be set to `null` (no data).\n\n Alternatively, use ``filter_bbox()`` to filter by bounding box.",
     "categories": [
         "cubes",
         "filter"
@@ -37,7 +37,7 @@
                     "subtype": "datacube",
                     "dimensions": [
                         {
-                            "type": "vector"
+                            "type": "geometries"
                         }
                     ]
                 }

load_collection.json

@@ -104,7 +104,7 @@
                     "subtype": "datacube",
                     "dimensions": [
                         {
-                            "type": "vector"
+                            "type": "geometries"
                         }
                     ]
                 },

mask.json

@@ -1,7 +1,7 @@
 {
     "id": "mask",
     "summary": "Apply a raster mask",
-    "description": "Applies a mask to a raster data cube. To apply a vector mask use ``mask_polygon()``.\n\nA mask is a raster data cube for which corresponding pixels among `data` and `mask` are compared and those pixels in `data` are replaced whose pixels in `mask` are non-zero (for numbers) or `true` (for boolean values). The pixel values are replaced with the value specified for `replacement`, which defaults to `null` (no data).\n\nThe data cubes have to be compatible so that each dimension in the mask must also be available in the raster data cube with the same name, type, reference system, resolution and labels. Dimensions can be missing in the mask with the result that the mask is applied to each label of the dimension in `data` that is missing in the data cube of the mask. The process fails if there's an incompatibility found between the raster data cube and the mask.",
+    "description": "Applies a mask to a raster data cube. To apply a polygon as a mask, use ``mask_polygon()``.\n\nA mask is a raster data cube for which corresponding pixels among `data` and `mask` are compared and those pixels in `data` are replaced whose pixels in `mask` are non-zero (for numbers) or `true` (for boolean values). The pixel values are replaced with the value specified for `replacement`, which defaults to `null` (no data).\n\nThe data cubes have to be compatible so that each dimension in the mask must also be available in the raster data cube with the same name, type, reference system, resolution and labels. Dimensions can be missing in the mask with the result that the mask is applied to each label of the dimension in `data` that is missing in the data cube of the mask. The process fails if there's an incompatibility found between the raster data cube and the mask.",
     "categories": [
         "cubes",
         "masks"

mask_polygon.json

@@ -37,7 +37,7 @@
                     "subtype": "datacube",
                     "dimensions": [
                         {
-                            "type": "vector",
+                            "type": "geometries",
                             "geometry_type": [
                                 "Polygon",
                                 "MultiPolygon",

merge_cubes.json

@@ -1,7 +1,7 @@
 {
     "id": "merge_cubes",
     "summary": "Merge two data cubes",
-    "description": "The process performs the join on overlapping dimensions. The data cubes have to be compatible. A merge operation without overlap should be reversible with (a set of) filter operations for each of the two cubes. As such it is not possible to merge a vector and a raster data cube.\n\nOverlapping dimensions have the same name, type, reference system and resolution, but can have different labels. One of the dimensions can have different labels, for all other dimensions the labels must be equal. Equality for vector labels follows the definition in the Simple Features standard by the OGC. If data overlaps, the parameter `overlap_resolver` must be specified to resolve the overlap.\n\n**Examples for merging two data cubes:**\n\n1. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the first cube and `B3` and `B4`. An overlap resolver is *not needed*. The merged data cube has the dimensions `x`, `y`, `t` and `bands` and the dimension `bands` has four dimension labels: `B1`, `B2`, `B3`, `B4`.\n2. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the first data cube and `B2` and `B3` for the second. An overlap resolver is *required* to resolve overlap in band `B2`. The merged data cube has the dimensions `x`, `y`, `t` and `bands` and the dimension `bands` has three dimension labels: `B1`, `B2`, `B3`.\n3. Data cubes with the dimensions (`x`, `y`, `t`) have the same dimension labels in `x`, `y` and `t`. There are two options:\n   1. Keep the overlapping values separately in the merged data cube: An overlap resolver is *not needed*, but for each data cube you need to add a new dimension using ``add_dimension()``. The new dimensions must be equal, except that the labels for the new dimensions must differ by name. The merged data cube has the same dimensions and labels as the original data cubes, plus the dimension added with ``add_dimension()``, which has the two dimension labels after the merge.\n   2. Combine the overlapping values into a single value: An overlap resolver is *required* to resolve the overlap for all values. The merged data cube has the same dimensions and labels as the original data cubes, but all values have been processed by the overlap resolver.\n4. A data cube with dimensions (`x`, `y`, `t` / `bands`) or (`x`, `y`, `t`, `bands`) and another data cube with dimensions (`x`, `y`) have the same dimension labels in `x` and `y`. Merging them will join dimensions `x` and `y`, so the lower dimension cube is merged with each time step and band available in the higher dimensional cube. This can for instance be used to apply a digital elevation model to a spatio-temporal data cube. An overlap resolver is *required* to resolve the overlap for all pixels.\n\nAfter the merge, the dimensions with a natural/inherent label order (with a reference system this is each spatial and temporal dimensions) still have all dimension labels sorted. For other dimensions where there is no inherent order, including bands, the dimension labels keep the order in which they are present in the original data cubes and the dimension labels of `cube2` are appended to the dimension labels of `cube1`.",
+    "description": "The process performs the join on overlapping dimensions. The data cubes have to be compatible. A merge operation without overlap should be reversible with (a set of) filter operations for each of the two cubes. As such it is not possible to merge a vector and a raster data cube. It is also not possible to merge vector data cubes that contain different base geometry types (points, linestrings, polygons). The base geometry types can be merged with their corresponding multi geometry types. In case of such a conflict, the `IncompatibleGeometryTypes` exception is thrown.\n\nOverlapping dimensions have the same name, type, reference system and resolution, but can have different labels. One of the dimensions can have different labels, for all other dimensions the labels must be equal. Equality for geometries follows the definition in the Simple Features standard by the OGC. If data overlaps, the parameter `overlap_resolver` must be specified to resolve the overlap.\n\n**Examples for merging two data cubes:**\n\n1. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the first cube and `B3` and `B4`. An overlap resolver is *not needed*. The merged data cube has the dimensions `x`, `y`, `t` and `bands` and the dimension `bands` has four dimension labels: `B1`, `B2`, `B3`, `B4`.\n2. Data cubes with the dimensions (`x`, `y`, `t`, `bands`) have the same dimension labels in `x`, `y` and `t`, but the labels for the dimension `bands` are `B1` and `B2` for the first data cube and `B2` and `B3` for the second. An overlap resolver is *required* to resolve overlap in band `B2`. The merged data cube has the dimensions `x`, `y`, `t` and `bands` and the dimension `bands` has three dimension labels: `B1`, `B2`, `B3`.\n3. Data cubes with the dimensions (`x`, `y`, `t`) have the same dimension labels in `x`, `y` and `t`. There are two options:\n   1. Keep the overlapping values separately in the merged data cube: An overlap resolver is *not needed*, but for each data cube you need to add a new dimension using ``add_dimension()``. The new dimensions must be equal, except that the labels for the new dimensions must differ by name. The merged data cube has the same dimensions and labels as the original data cubes, plus the dimension added with ``add_dimension()``, which has the two dimension labels after the merge.\n   2. Combine the overlapping values into a single value: An overlap resolver is *required* to resolve the overlap for all values. The merged data cube has the same dimensions and labels as the original data cubes, but all values have been processed by the overlap resolver.\n4. A data cube with dimensions (`x`, `y`, `t` / `bands`) or (`x`, `y`, `t`, `bands`) and another data cube with dimensions (`x`, `y`) have the same dimension labels in `x` and `y`. Merging them will join dimensions `x` and `y`, so the lower dimension cube is merged with each time step and band available in the higher dimensional cube. This can for instance be used to apply a digital elevation model to a spatio-temporal data cube. An overlap resolver is *required* to resolve the overlap for all pixels.\n\nAfter the merge, the dimensions with a natural/inherent label order (with a reference system this is each spatial and temporal dimensions) still have all dimension labels sorted. For other dimensions where there is no inherent order, including bands, the dimension labels keep the order in which they are present in the original data cubes and the dimension labels of `cube2` are appended to the dimension labels of `cube1`.",
     "categories": [
         "cubes"
     ],
@@ -83,6 +83,9 @@
     "exceptions": {
         "OverlapResolverMissing": {
             "message": "Overlapping data cubes, but no overlap resolver has been specified."
+        },
+        "IncompatibleGeometryTypes": {
+            "message": "The geometry types are not compatible and can't be merged."
         }
     },
     "links": [

proposals/filter_labels.json

@@ -25,7 +25,7 @@
                 "parameters": [
                     {
                         "name": "value",
-                        "description": "A single dimension label to compare against. The data type of the parameter depends on the dimension labels set for the dimension.",
+                        "description": "A single dimension label to compare against. The data type of the parameter depends on the dimension labels set for the dimension. Please note that for some dimension types a representation is used, e.g.\n\n* dates and/or times are usually strings compliant to [ISO 8601](https://en.wikipedia.org/wiki/ISO_8601),\n* geometries can be a WKT string or an identifier.",
                         "schema": [
                             {
                                 "type": "number"