Differences

This shows you the differences between two versions of the page.

--- nsw_lidar [2021/02/17 09:55] – bushwalking
+++ nsw_lidar [2021/02/20 09:52] – bushwalking
@@ Line 8: / Line 8: @@
 ====== Topics ======
-The original topics here have been moved to their own pages
+The original topics here are being progressively moved to their own pages
 ===== Managing DEMs =====
@@ Line 23: / Line 24: @@
 Once you have a depressionless DEM, the following items can be generated:
   * [[qgis_contours|Contours]]
-  * Hydrology (Stream Network)
+  * [[qgis_hydrology|Hydrology (Stream Network)]]
+  * [[qgis_slope|Slopes]] - while not a standard feature of topographic maps, this can be a simple way to identify cliffs
   * Clifflines
-  *
-====== Topographic maps ======
-There are several primary data items for topographic maps that can be generated using the DEM data from the NSW Lidar. The main ones are:
+===== Styles =====
-  * Contours
-  * Hydrology (Stream Network)
-  * Clifflines
-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.
+  * [[qgis_styling|Styling]] - download basic style files
-===== Hydrology (Stream Network) =====
+===== Automation =====
-The starting point for hydrology is a hydrologically sound DEM, as above. Use a fill sinks or channel deepening algorithm.
+  * [[qgis_basic_automation|Basic map creation]] - a set of PyQGIS scripts that will create (and optionally save) a basic topographic map. This map can be used in QField
-==== Catchment Areas ====
+===== Mobile apps =====
-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.
+  * [[qgis_qfield|QField]] - QField is an excellent Android app for for viewing projects created with QGIS
-  * SAGA : Terrain Analysis - Hydrology : Catchment Area
+====== Topographic maps ======
-This gives an output that is best viewed in log scale. You can do this via
+There are several primary data items for topographic maps that can be generated using the DEM data from the NSW Lidar. The main ones are:
-  * Raster -> Raster Calculator...
+  * Contours
-    *  log10 ( "Filled DEM@1" )
+  * Hydrology (Stream Network)
+  * Clifflines
-Use the log scale version to determine the cutoff for what streams you want to see and which ones are too small. 10000 seems to give comparable results to the existing 1:25000 maps.
-Note that if you don't have the entirety of the catchment, you 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 m, obviously scale dependent)
-Simplify using using:
-  * Vector geometry : Simplify
-Tolerance:?
+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.
 ===== Clifflines =====