| 179 | | |
| 180 | | |
| 181 | | [[Image(interp_with_mask.png,width=100)]] |
| 182 | | {{{ |
| 183 | | #!html |
| 184 | | <p style="text-align: center">Figure: Interpolated point cloud data after implementing a mask.</p> |
| 185 | | }}} |
| 186 | | |
| 187 | | To extend the coverage of your DEM, if required, it is suggested to patch on external DEM data. If you have access to a good quality DEM then use that, else the SRTM 3 arc second DEM is freely available and covers most of the globe between +-60 degrees latitude. To see how to make a DEM from SRTM data see the [wiki:Processing/SRTMDEMs SRTM DEM] page. Make sure to select the projection the same as your LIDAR DEM. Also, be aware that the SRTM elevations are with respect to a geoid model and will need to be converted to the LIDAR vertical datum. |
| 188 | | |
| 189 | | Once you have an SRTM DEM of sufficient coverage you can patch the LIDAR and SRTM DEMs together, such that the LIDAR takes precedence. This means the lidar_dem should be the first of the input maps on the r.patch command. If the mask is still applied then remove it before patching: |
| 190 | | |
| 191 | | 10. '''`r.mask input=<maskmapname> -r`''' |
| 192 | | |
| 193 | | 11. '''`r.patch in=lidar_dem,srtm_dem out=combined_dem`''' |
| 194 | | |
| 195 | | [[Image(combo_srtm_lidar.png,width=100)]] |
| 196 | | {{{ |
| 197 | | #!html |
| 198 | | <p style="text-align: center">Figure: Interpolated point cloud data after implementing a mask with SRTM DEM data to fill in the rest of the region.</p> |
| 199 | | }}} |
| 200 | | |
| 201 | | To output the DEM (as ascii) and set null values as 0: |
| 202 | | |
| 203 | | 12. '''`r.out.ascii input=<DEMmapname> output=<outputDEMfile> null=0`''' |