05/22/2012

10:14 AM Task #363: Assemble all GHCN data into a single database

If useful for some specific purpose, we could generate relevant synoptic views or subsetted table dumps pivoted back ... Jim Regetz

08:25 AM Task #363: Assemble all GHCN data into a single database

Perhaps it would make sense to keep the data in the "one-row-per-month" format in the database and transform it on th... Adam Wilson

07:52 AM Task #418 (New): Explore Landcover - LST interactions

Use the full gridded datasets (rather than just station locations) to explore relationships between LST and various (... Adam Wilson

05/17/2012

11:38 PM Task #416: Scope out workflow for calculating monthly LST climatologies

I've now written some Python+GRASS code to do a good bit of what I think we want. For a user-specified _tile_, _year_... Jim Regetz

03:05 PM Task #416 (In Progress): Scope out workflow for calculating monthly LST climatologies

Assess feasibility of running LST climatologies ourselves by implementing a basic scripted workflow and estimating ov... Jim Regetz

03:44 PM Task #375: Assemble monthly mean MODIS LST values for the complete record (2000-2012) for Oregon

See task #416 for progress on developing and evaluating a procedure for doing this ourselves.
But I will add a com... Jim Regetz

05/16/2012

12:01 PM Task #207: Produce global fused DEM layer

A global 90m product is now available, though the individual pieces have not been mosaiced together due to file size.... Natalie Robinson

06:40 AM Task #415: Process MOD06_L2 Cloud data

See presentation on current progress here [[https://projects.nceas.ucsb.edu/nceas/documents/18]] Adam Wilson

06:40 AM Task #415 (New): Process MOD06_L2 Cloud data

Download and process the MODIS cloud product (MOD06_L2) and produce monthly 1km summaries of key variables. Adam Wilson

05/15/2012

11:22 AM Task #411 (In Progress): Insert DEM adaptive smoothing procedure into terrain workflow

I developed two alternative implementations of the adaptive DEM smoothing procedure (@multiscalesmooth9a_clean.aml@):... Jim Regetz

09:52 AM Task #411 (In Progress): Insert DEM adaptive smoothing procedure into terrain workflow

The original Oregon terrain processing workflow, implemented as a set of AML scripts, included the application of Joh... Jim Regetz

09:57 AM Task #208: Evaluate existing E&O AML scripts

I recently reorganized all AML scripts into a single directory in the code repo, here:
source:terrain/research/orego... Jim Regetz

05/14/2012

10:00 AM Task #363: Assemble all GHCN data into a single database

Quick example comparing SQLite vs PostgreSQL timings on a simple aggregate query that doesn't use any indexes. SQLite... Jim Regetz

05/13/2012

11:16 PM Task #363: Assemble all GHCN data into a single database

Vaguely concerned about performance and manageability of such a large SQLite database, I wrote a second script to loa... Jim Regetz

11:14 PM Task #363: Assemble all GHCN data into a single database

Belated update. The TMIN/TMAX data loaded in ~6 hours total, yielding a 25GB SQLite file with nearly 600 million rows. Jim Regetz

05/10/2012

08:49 AM Task #363: Assemble all GHCN data into a single database

Data loading slowed to a crawl overnight, thanks to a record count query tucked inside in the bulk insert function th... Jim Regetz

05/09/2012

11:49 PM Task #363: Assemble all GHCN data into a single database

Committed an R script that orchestrates the processing and loading of all 75000+ *.dly files into a SQLite database. ... Jim Regetz

11:10 AM Task #363 (In Progress): Assemble all GHCN data into a single database

We decided to organize and load _all_ available GHCN data (i.e., all dates and stations, globally) into SQLite databa... Jim Regetz

03:40 PM Task #408: Capturing LST spatial structure using spatial eigenvectors

I started writing the R code using the two functions from spdep package: ME() and SpatialFiltering()
I am trying to ... Benoit Parmentier

03:32 PM Task #364: Integrate spatial variables and structure in the GAM methodology

I am currently exploring a two stage regression involving:
1) Step 1: GAM models using Lat, long, ELEV_SRTM, DISTOC,... Benoit Parmentier

05/08/2012

04:31 PM Task #406: OR-GAM predictions-model assessment over 365 dates, year 2010

RMSE were calculated per month over the year 2010. Results show that contrary to my expectation RMSE are higher in S... Benoit Parmentier

05/02/2012

11:57 AM Task #393: Identify Focal Regions

We are currently proposing the following regions (and MODIS tiles):
Oregon: H08V04, H09V04, H08V05, H09V0... Adam Wilson

05/01/2012

02:24 PM Task #361: Test and compare the GAM method on several days (10 days for now) for Oregon

Many models have been explored using the GAM methodology. At this stage, more detailed diagnostics is needed so for t... Benoit Parmentier

02:16 PM Task #409 (New): Effect of sampling on GAM: hold out proportions and sampling observations

This task examines the effect of the sampling and hold out proportions on tmax predictions. This task will help in de... Benoit Parmentier

02:08 PM Task #364: Integrate spatial variables and structure in the GAM methodology

Kriging has been done so far by using variograms fitted from stations' locations. The next step is to examine the fit... Benoit Parmentier

02:03 PM Task #408 (New): Capturing LST spatial structure using spatial eigenvectors

Spatial filtering is explored to assess its usefulness in capturing the LST spatial structure by creating spatial var... Benoit Parmentier

01:56 PM Task #406 (New): OR-GAM predictions-model assessment over 365 dates, year 2010

Models have so far been assessed on 10 dates spread over the year for the Oregon study area. This task provides an as... Benoit Parmentier

01:20 PM Task #375: Assemble monthly mean MODIS LST values for the complete record (2000-2012) for Oregon

The NASA Ames team is willing to generate the monthly LST climatologies, but we'll need to be specific about what we ... Adam Wilson

01:20 PM Task #393: Identify Focal Regions

Do we want to look at a mediterranean-type climate? Guess western part of South Africa qualifies. Or interior tempe... Rob Guralnick

01:13 PM Task #393: Identify Focal Regions

The folks at NASA Ames suggested that scaling up to the globe will much easier to do if we process the data using the... Adam Wilson

04/27/2012

11:05 AM Task #393: Identify Focal Regions

Natalie is ready to help MODIS data assembly once we have decided this. Can we plan to talk about this on the Tuesda... Rob Guralnick