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`''' |