| 115 | | * Functions searching for the pixel value in a raster coverage. This is the same principle as ST_Union() except that the rasters do not have to be aligned (nice advantage!). |
| 116 | | |
| 117 | | * Functions searching for the pixel value in a vector coverage. This is the same principle as ST_UnionToRaster() and ST_BurnToRaster(). |
| 118 | | |
| 119 | | * Functions aggregating pixel values from a neighbourhood. This is the same principle as ST_MapAlgebraFctN |
| 120 | | |
| 121 | | * Functions deriving metric values HERE |
| 122 | | |
| 123 | | * Some of them, not working on pixel neighbour area, hence only on aligned pixels from overlapping rasters, should eventually be replaced by the optimized version of ST_Union() (itself dependent on the optimized version of ST_MapAlgebra See Objective FV.25 above). Those alternative are less flexible than their future ST_Union alternative in that they only work on a whole table, not on a selection of a table (i.e. they are not aggregates like ST_Union is. One can always create a view on a table to work on a table subset though). |
| | 115 | 1) Functions searching for the pixel value in a raster coverage. This is the same principle as ST_Union() except that the rasters do not have to be aligned (nice advantage!). |
| | 116 | |
| | 117 | 2) Functions searching for the pixel value in a vector coverage. This is the same principle as ST_UnionToRaster() and ST_BurnToRaster(). |
| | 118 | |
| | 119 | 3) Functions aggregating pixel values from a raster neighborhood. This is the same principle as ST_MapAlgebraFctNbg() except that the rasters do not have to be aligned (nice advantage!). |
| | 120 | |
| | 121 | 4) Functions aggregating pixel values from a neighborhood. This is the only way to do that. |
| | 122 | |
| | 123 | 5) Functions deriving metric values from a raster or a geometry coverage. This is very similar to the two previous items but the result is not an aggregate value. e.g. Distance to something. |
| | 124 | |
| | 125 | Category 1), not working on pixel neighbour area, hence only on aligned pixels from overlapping rasters, should eventually be replaced by the optimized version of ST_Union() (itself dependent on the optimized version of ST_MapAlgebra See Objective FV.25 above). Those alternative are less flexible than their future ST_Union alternative in that they only work on a whole table, not on a selection of a table (i.e. they are not aggregates like ST_Union is. One can always create a view on a table to work on a table subset though). |
| 127 | | * ST_FasterUnion('schemaname', 'tablename', 'rastercolumnname'), an alternative to ST_Union(rast, 'LAST') to merge all the tiles of a table together into a single raster. This function is described [http://geospatialelucubrations.blogspot.fr/2012/07/a-slow-yet-1000x-faster-alternative-to.html here]. this function is dependent on the ST_FirstRasterValue4ma() ST_MapAlgebraFct() custom function. |
| 128 | | |
| 129 | | * ST_FirstGeomValue4ma() http://postgis.refractions.net/pipermail/postgis-users/2012-April/033875.html |
| | 129 | * ST_FasterUnion('schemaname', 'tablename', 'rastercolumnname'), an alternative to ST_Union(rast, 'LAST') - Merge all the tiles of a table together into a single raster. This function is described [http://geospatialelucubrations.blogspot.fr/2012/07/a-slow-yet-1000x-faster-alternative-to.html here]. this function is dependent on the ST_FirstRasterValue4ma() ST_MapAlgebraFct() custom function. |
| | 130 | |
| | 131 | * ST_FirstGeomValue4ma() - Get the value from a specified column from the first geometry intersecting with the shape of the pixel (See [http://postgis.refractions.net/pipermail/postgis-users/2012-April/033875.html this post to postgis-users]) |
| 133 | | * ST_GeomToRaster('schemaname', 'tablename', 'geomolumnname', 'METHOD') - A generalization of ST_FirstGeomValue4ma() described above but accepting more methods of value extraction. |
| | 135 | * ST_GeomToRaster('schemaname', 'tablename', 'geomolumnname', 'METHOD') - A generalization of ST_FirstGeomValue4ma() described above but accepting more methods of value extraction, depending on the type of coverage we want to extract from. This is very much like doing an intersection (actually more like an "identify" overlay operation) between a raster and a vector coverage. |
| | 136 | |
| | 137 | The METHOD could be: |
| | 138 | |
| | 139 | * from any kind of coverage: COUNT, DISTINCT_COUNT, COUNT_MOST_FREQUENT, COUNT_LEAST_FREQUENT, MOST_FREQUENT_VALUE, LEAST_FREQUENT_VALUE, MAXIMUM, MINIMUM, RANGE, SUM, MEAN, STDDEV |
| | 140 | |
| | 141 | * from a line coverage could also be LENGTH_MAX, LENGTH_MIN, LENGTH_RANGE, LENGTH_SUM, LENGTH_MEAN, LENGTH_STDDEV, LENGTH_OF_BIGGEST_VALUE, LENGTH_OF_SMALLEST_VALUE, LENGTH_OF_MOST_FREQUENT_VALUE, LENGTH_OF_LEAST_FREQUENT_VALUE, VALUE_OF_LONGEST, VALUE_OF_SHORTEST, VALUE_OF_COMBINED_LONGEST, VALUE_OF_COMBINED_SHORTEST. To be continued... |
