| 18 | | 1. The source table of geometries (points, line or polygons) can contain one geometry or many (eventually millions). We want the method to scale well whatever the number of source geometry. |
| 19 | | 2. The desired raster is specified with parameters or by referencing an existing raster. |
| 20 | | 3. Sometimes the resolution of the desired raster is so high that the whole raster coverage cannot be stored in one PostgreSQL row. The approach must be able to produce a tiled raster coverage stored into many rows. |
| 21 | | 4. Source geometries might be outside the extent of the desired raster. |
| 22 | | 5. The approach should work well in a number of situations: |
| 23 | | a. small number of sources vs low resolution raster, |
| 24 | | b. small number of sources vs high resolution raster |
| 25 | | c. large number of sources vs low resolution |
| 26 | | d. large number of sources vs high resolution Large raster coverage |
| 27 | | 6. The user can specify a maximum distance to the source. When the source is too far from the geometry it gets assigned a nodata value. |
| 28 | | 7. We want the implementation to be generic enough to be reused to implement more general interpolation methods like nearest neighbor, IDW, spline or kriging. Otherwise we want it to be generic enough to be reused to implement more general cost distance methods. |
| | 18 | 1. The source table of geometries (points, line or polygons) can contain one geometry or many (eventually millions). We want the method to scale well whatever the number of source geometry.[[BR]] |
| | 19 | 2. The desired raster is specified with parameters or by referencing an existing raster.[[BR]] |
| | 20 | 3. Sometimes the resolution of the desired raster is so high that the whole raster coverage cannot be stored in one PostgreSQL row. The approach must be able to produce a tiled raster coverage stored into many rows.[[BR]] |
| | 21 | 4. Source geometries might be outside the extent of the desired raster.[[BR]] |
| | 22 | 5. The approach should work well in a number of situations: [[BR]] |
| | 23 | a. small number of sources vs low resolution raster[[BR]] |
| | 24 | b. small number of sources vs high resolution raster [[BR]] |
| | 25 | c. large number of sources vs low resolution [[BR]] |
| | 26 | d. large number of sources vs high resolution Large raster coverage[[BR]] |
| | 27 | 6. The user can specify a maximum distance to the source. When the source is too far from the geometry it gets assigned a nodata value.[[BR]] |
| | 28 | 7. We want the implementation to be generic enough to be reused to implement more general interpolation methods like nearest neighbor, IDW, spline or kriging. Otherwise we want it to be generic enough to be reused to implement more general cost distance methods.[[BR]] |
