nsw_lidar
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
nsw_lidar [2019/02/10 13:59] – bushwalking | nsw_lidar [2019/02/23 08:37] – bushwalking | ||
---|---|---|---|
Line 62: | Line 62: | ||
For more options in compression, | For more options in compression, | ||
* GRASS : [[https:// | * GRASS : [[https:// | ||
+ | V.generalize can also be used to smooth contours - possibly best done prior to simplificiation | ||
==== Cleaning ==== | ==== Cleaning ==== | ||
Line 112: | Line 113: | ||
{{: | {{: | ||
- | The raster channel network can then be classified | + | ==== Classification ==== |
+ | |||
+ | For 1:25000 maps, I've had reasonable results from using the following formula in the Raster Calculator to classify the streams into categories. Different scales may need different bounds, | ||
+ | |||
+ | '' | ||
+ | |||
+ | * Intermittent: | ||
+ | * Minor: 6.15-7.4 | ||
+ | * Major: 7.4+ | ||
+ | |||
+ | ==== Convert to Vector and Simplify ==== | ||
+ | |||
+ | Convert | ||
+ | |||
+ | {{: | ||
+ | |||
+ | The raw stream data is very jagged. Smooth using | ||
+ | * v.generalize | ||
+ | * Algorithm = Hermite (there are other options which can be used, but Hermite has the smoothed line passing through the points of the original) | ||
+ | * Maximal tolerance value = 20 (in m, obviously scale dependent) | ||
+ | |||
+ | Simplify using using: | ||
+ | * Vector geometry : Simplify | ||
+ | Tolerance:? | ||
===== Clifflines ===== | ===== Clifflines ===== | ||
- | The steps below have been tested | + | The steps below are being developed for use in the Blue Mountains, a region that has a significant number of relatively vertical sandstone cliffs. It may be less effective in different terrain. |
This is more a set of ideas than a fully fledged process. The main aims are to get a set of steps that can largely be automated, and that create cliffline vectors that are running in the correct direction. There is still some way to go on this! | This is more a set of ideas than a fully fledged process. The main aims are to get a set of steps that can largely be automated, and that create cliffline vectors that are running in the correct direction. There is still some way to go on this! | ||
Line 128: | Line 153: | ||
using DEM and [1] Maximum Triangle Slope (Tarboton (1997)). I haven' | using DEM and [1] Maximum Triangle Slope (Tarboton (1997)). I haven' | ||
- | Cliff areas can be identified using a range of 60-90 and 70-90 degrees on the Slope file. Using 60-90 degrees helps connect logical cliffs and avoid small breaks. | + | Cliff areas can be identified using a range of say 60-90 and 70-90 degrees on the Slope file. Using 60-90 degrees helps connect logical cliffs and avoid small breaks. |
==== Initial Cleaning ==== | ==== Initial Cleaning ==== | ||
Next convert data to 1 bit (1,2 not 0,1, as Sieve ignores 0s) using Raster Calculator. | Next convert data to 1 bit (1,2 not 0,1, as Sieve ignores 0s) using Raster Calculator. | ||
- | Formula is: (Slope > 0) + 1 | + | Formula is: (Slope > 60) + 1 |
Then Sieve resulting data using a Threshold of 100 and 8-connectedness to get rid of small non-connected cliffs. Note above that Sieve doesn' | Then Sieve resulting data using a Threshold of 100 and 8-connectedness to get rid of small non-connected cliffs. Note above that Sieve doesn' |
nsw_lidar.txt · Last modified: 2023/06/02 12:33 by allchin09