ariesteam/aries — Issue #60: the big training issue
Author: kbagstad
Created: 2012-02-28 06:02:34+00:00
State: open

@fvilla @bvoigt @lambdatronic

Alright folks I was gonna do this as an email then my better instincts won out so it's going in as an issue. I've successfully trained the following BNs: Puget carbon source, Puget flood sink, Puget sediment source, San Pedro carbon source, Madagascar carbon source, Madagascar carbon sink, California carbon source. Five minor issues are holding up all the other ones, of which fixing Puget and San Pedro are most urgent. Get these done and we should be set on training for everything except Ontario (and I imagine fixing these will make Ontario training go more smoothly)

Here are the problems I've encountered:
1. The soil carbon storage layer is causing problems for most of the carbon sink models. The data are there if you measure -d them, but model -d's show no data, and no (or minimal) evidence enters the training system. Oddly enough this is a single global layer and it seems to be working fine for Madagascar but not for Puget, San Pedro, or California.

2. For the Puget carbon model, zeroes in the data are being incorrectly interpreted as nodata.

3. There are overlap problems with "tiled" datasets (that aren't really square tiles but are designed to fit together seamlessly) like NLCD and NBCD that are used in training for some models, particularly the San Pedro carbon models. I encountered this problem separately as github issue #32 and have never been able to get a straight answer as to whether this is an easy or a hard problem to fix.

4. Some model -o statements, particularly for the San Pedro surface water sink and Madagascar carbon source models are giving an error I've never seen before - trying either model -o mgcsource14.nc core.models.carbon-mg/source core.contexts.mg/mg-mainland-simple OR model -o spwater14.nc core.models.water-san-pedro/infiltration-sink core.contexts.san-pedro/san-pedro-watershed-us-real yields the error "observation urn:uuid:ins:f442d9c2-19b2-4c61-b433-e9a09101fc74 has no observable" - what does this mean?

5. In trying to train the California flood sink models I get the error "Input/output error: usa:nlcd_4: I/O error reading image metadata!: url = http://ecoinformatics.uvm.edu/geoserver/wcs?service=WCS&version=1.0.0&request=GetCoverage&coverage=usa:nlcd_4&bbox=-118.19829941621056,33.230093820887824,-116.69965953631186,34.38727144967037&crs=EPSG:4326&responseCRS=EPSG:4326&width=158&height=122&format=geotiff". This is strange as I used NLCD data to successfully train the California carbon models and many others.