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nsw_lidar [2018/12/09 21:56] – [Hydrology (Stream Network)] bushwalkingnsw_lidar [2019/08/30 19:35] bushwalking
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-Page for documenting NSW lidar processing 
 ====== Intro ====== ====== Intro ======
 NSW Spatial Services have undertaken a program to map all of NSW using lidar (light detecting and ranging) NSW Spatial Services have undertaken a program to map all of NSW using lidar (light detecting and ranging)
 For details, see information on their [[http://spatialservices.finance.nsw.gov.au/mapping_and_imagery/environmental_spatial_programs|elevation program]]. For details, see information on their [[http://spatialservices.finance.nsw.gov.au/mapping_and_imagery/environmental_spatial_programs|elevation program]].
  
-Elevation data can best be accessed through the [[http://elevation.fsdf.org.au/|Geoscience Australia ELVIS program]], and then processed with a GIS such as [[https://www.qgis.org/en/site/index.html|QGIS]] to create useful topographic maps.+Elevation data can best be accessed through the [[http://elevation.fsdf.org.au/|Geoscience Australia ELVIS program]]
 + 
 +It can then processed with a GIS such as [[https://www.qgis.org/en/site/index.html|QGIS]] to create useful topographic maps. Instructions below are specifically for use with QGIS, though the general outline may be useful for other GISs.
  
 ====== Resources ====== ====== Resources ======
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 The steps below are works in progress to determine effective (the best?) ways to extract the various items out of the DEM data for use in topographic maps. Any feedback/suggestions of improvements are welcome. The steps below are works in progress to determine effective (the best?) ways to extract the various items out of the DEM data for use in topographic maps. Any feedback/suggestions of improvements are welcome.
 +
 +===== Merge DEMs =====
 +
 +The NSW DEM data is supplied in 2km squares. The squares need to be merged into a single DEM for further operations.
 +
 +While this can be done in theory using a Virtual Raster, I have had poor performance with this. Any operation seems to result in screen redrawing, so moving around and zooming in and out is quite slow and painful. Possibly more recent versions of QGIS have resolved these issues.
 +
 +Instead, I generally use the the Raster- > Miscellaneous -> Merge... function
 +
 +Note that while most of the eastern ranges, where a lot of bushwalking happens, are 2m DEMs, the coast is typically 1m, and the western slopes and plains are 5m (with major rivers 1m!). QGIS appears to merge DEMs to the highest resolution (ie a combination of 1m and 2m DEMs will be merged to a 1m resolution output file). This may not always be desired. The 1m DEMs can be downsampled to say 2m in QGIS using the Warp (reproject) tool with an Output resolution of 2.
 +
 +===== Fill Sinks =====
 +
 +From the initial DEM, first step is to Fill Sinks. Otherwise you will get sinks in the middle of watercourses, which will impact contours and stream networks. Note that the this approach needs to be used with care in areas where there are actual depressions.
 +
 +There are various related tools in the Processing Toolbox that will do this, including:
 +  * SAGA : Terrain Analysis - Hydrology : Fill Sinks
 +  * SAGA : Terrain Analysis - Hydrology : Fill Sinks (Wang and Liu)
 +  * SAGA : Terrain Analysis - Hydrology : Fill Sinks XXL (Wang and Liu) 
 +
 +The results from all will be similar, but the Wang and Liu versions should be faster. 
 +
 +There are other approaches that deepen channels rather than fill sinks in order to get a hydrologically sound drainage network. For example
 +  * SAGA : Terrain Analysis - Hydrology : Sink Removal 
 +has an option for this.
  
 ===== Contours ===== ===== Contours =====
-See page on [[[qgis_contour_labelling|QGIS Contour Labelling]]+==== Basic Processing ==== 
 +There are various contour extraction algorithms in QGIS, for example: 
 +  * GDAL : Raster Extraction : Contour (same as Raster -> Extraction -> Contour...) 
 + 
 +Below is an example of contours created without and with sink removal. The contours on the right have been derived from a DEM where the sinks (in yellow on the left) have been filled. 
 +{{:2019_02_08_12_17_09_untitled_project_qgis.png?300|}} 
 +{{:2019_02_08_12_17_57_untitled_project_qgis.png?300|}} 
 + 
 +Even with sink removal, small  
 + 
 +==== Simplifying ==== 
 + 
 +Vectors can be compressed by using something like: 
 +  * Vector geometry : Simplify 
 +A tolerance of 1(m) seems reasonable for 1:25000 mapping. Smaller tolerances may be appropriate for larger scale maps (eg 1:10000, 1:5000). 
 + 
 +For more options in compression, look at: 
 +  * GRASS : [[https://grasswiki.osgeo.org/wiki/V.generalize_tutorial|v.generalize]] 
 +V.generalize can also be used to smooth contours - possibly best done prior to simplificiation 
 + 
 +==== Cleaning ==== 
 + 
 +Once simplified, it is worth removing small closed loops, such as those in the image below. 
 +{{:contour_loops.png|}} 
 + 
 +Here is one approach, which involves adding a length attribute to each contour, and removing those that fall below a certain length. It may cause issues if you have short sections of contour near the edge of the map that you need. 
 + 
 +  * Open Attribute Table (F6) 
 +  * Open field calculator (Ctrl+I) 
 +  * Add new attribute length, calculated as $length 
 +{{::qgis_add_field.png|}} 
 +  * Select all features and filter on length < 25 (or whatever length is appropriate for your scale) 
 +{{:qgis_filter_field.png|}} 
 + 
 +==== Contour Labelling ==== 
 + 
 +See separate page on [[[qgis_contour_labelling|QGIS Contour Labelling]] 
 ===== Hydrology (Stream Network) ===== ===== Hydrology (Stream Network) =====
  
-Fill Sinks+The starting point for hydrology is a hydrologically sound DEM, as above. Use a fill sinks or channel deepening algorithm.
  
-From the initial DEM, first step is to Fill Sinks. There are various related tools that will do this, including: +==== Catchment Areas ====
-  * Fill Sinks +
-  * Fill Sinks (Wang and Liu) +
-  * Fill Sinks XXL (Wang and Liu) +
  
-Catchment Areas+Next step is to create Catchment Areas. Again, there is a Catchment Area tool (in fact several), and six methods within the tool. For the purpose of delineating watercourses in steep terrain, the choice of method probably makes little difference.
  
-Next is to create Catchment AreasAgain, there is a Catchment Area tool (in fact several), and six options within the tool. For the purpose of delineating watercourses in steep terrainthe choice of option probably makes little difference.+  * SAGA : Terrain Analysis - Hydrology : Catchment Area 
 + 
 +This gives an output that is best viewed in log scale. You can do this via  
 +  * Raster -> Raster Calculator... 
 +    *  log10 ( "Filled DEM@1" )  
 + 
 +Use the log scale version to determine the cutoff for what streams you want to see and which ones are too small10000 seems to give comparable results to the existing 1:25000 maps. 
 + 
 +Note that if you don't have the entirety of the catchmentyou may get erroneous results. 
 + 
 +==== Channel Network ==== 
 + 
 +The following tool can be used to create channels (streams) - there are other options: 
 +  * SAGA : Terrain Analysis - Channels : Channel Network 
 + 
 +Use 
 +  * Elevation = Filled DEM 
 +  * Initiation Grid = Catchment Area 
 +  * Initiation Type = Greater Than 
 +  * Initiation Threshold = 10000 (or whatever number you have determined) 
 + 
 +{{:2019-02-08_12_41_50-channel_network.png?600|}} 
 + 
 +==== 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, and this doesn't account for significantly larger rivers. 
 + 
 +''( log10 ( "Catchment Area@1" ) >= x) * ( log10 ( "Catchment Area@1" ) < y) * ("Channel Network@1" != 0)'' 
 + 
 +  * Intermittent: 4-6.15 (x-y) 
 +  * Minor: 6.15-7.4  
 +  * Major: 7.4+ 
 + 
 +==== Convert to Vector and Simplify ==== 
 + 
 +Convert to vector using r.to.vect 
 + 
 +{{:qgis_raw_stream.png?600|}} 
 + 
 +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 mobviously scale dependent) 
 + 
 +Simplify using using: 
 +  * Vector geometry : Simplify 
 +Tolerance:?
  
  
 ===== Clifflines ===== ===== Clifflines =====
  
-The steps below have been tested in the Blue Mountains, a region that has a significant number of relatively vertical sandstone cliffs. It may be less effective in different terrain.+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!
  
 ==== Initial analysis of slope, aspect ==== ==== Initial analysis of slope, aspect ====
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 using DEM and [1] Maximum Triangle Slope (Tarboton (1997)). I haven't tested any other algorithms.  using DEM and [1] Maximum Triangle Slope (Tarboton (1997)). I haven't tested any other algorithms. 
   
-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't like 0s. 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't like 0s.
nsw_lidar.txt · Last modified: 2024/04/05 19:00 by bushwalking

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