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Attackpoint - performance and training tools for orienteering athletes

Training Log Archive: cedarcreek

In the 7 days ending Jan 10, 2016:

activity # timemileskm+m
  Orienteering1 53:28 2.4(22:16) 3.87(13:50) 103
  Total1 53:28 2.4(22:16) 3.87(13:50) 103

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Saturday Jan 9, 2016 #

1 PM

Orienteering 53:28 intensity: (3:29 @2) + (10:20 @3) + (30:47 @4) + (8:52 @5) *** 3.87 km (13:50 / km) +103m 12:12 / km
ahr:151 max:180 shoes: Inov8 Mudclaw

Brown course at Harbin Park, set by Pat Meehan.

A really nice brown course considering the park. There were a few long boring legs from North to South and back, but the other legs were pretty awesome. No complaints. My only real mistake was 11, where I fought through honeysuckle rather than run in the grass until I could see the control and then check there. Probably 1 full minute of delay.

I thought of a new name for honeysuckle as I was fighting with it: Demon Weed Tree. I hate that stuff.

12 hours of sleep. Got up exhausted but feeling better than I have in about two weeks. Still lots of sinus and nasal issues, but---knock on wood---I think I'm through the worst.

Did two lidar jobs for Dan Mattingly this week---two parks in Frankfort, KY. Working on a conversion reference table (CRT) to allow easy upload of OSM vectors into OCAD 11. A CRT is a big list that says "import features with this tag" using "this OCAD symbol". The problem is that the existing OSM import CRT that comes with OCAD is for making maps that don't look like orienteering maps. There are something like 1078 tag combinations that need to be defined, so I'm making a spreadsheet to help assign them. I'll be sorting certain ways so I can assign en bloc. The existing CRT uses 439 different OCAD symbols. The orienteering symbol set for OCAD has about 167 different symbols, so I'm hoping many of the OSM tags aren't important.

Found an interesting new GIS/lidar thing. I've been trying to find lidar filters or algorithms that will find ditches, streams, and rivers and automatically generate vector-format, importable files. Right now my best "ditch detector" is the slope image of ground returns, but it's raster format, so you have to trace them.

In my search, I discovered a hydrology algorithm called "Topographic wetness index". It's a SAGA-GIS thing, but it's implemented in QGIS. You use las2dem to create a DEM and load it into QGIS. Then you click the "Processing" menu item, then "Toolbox", and navigate to "SAGA", "Terrain Analysis - Hydrology", then "Topographic Wetness Index (twi)". I've been using the default options. If you have two or more DEMs, you have to manually select to do any other than the first. To save the images, right-click, "Save As", then click, "as rendered", not "as data", or it won't load into normal (non-GIS) image tools.

My favorite so far is "Catchment Area", *not "modified catchment area". It detects reentrants really well in steep areas, but not in streams or ditches of moderate slope. The other useful one I see is the actual "topographic wetness index" image, which is low contrast, but shows areas it expects to be "wet" or where "water accumulates". All of these are still rasters, not vectors, but they're pretty neat.

If I have time I'll create some that aren't for an "upcoming map" and post some examples.

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