GAM Fusion function major modification, separation of monhtly and daily steps, Venezuela prediction

Data covariates preparation, slight modifications and updates

GAM Fusion fusion initial reorganization of code to reduce time and predict for Venezuela

GAM fusion function, modifications for first fusion prediction in Venezuela

GAM fusion raster prediction, further modificationfor Venzuela tmax interp

GAM fusion function first change to adapt code for any region

GAM Fusion, Venzuela tmax interp, modification to make code more general

Data preparation Venezuela, added monthly query from Postgres station database

Venezuela preparation of data for tmax prediction

LST climatology, added tile loop, downloading and calculation of climatology for 6 tiles in Venezuela

LST climatology, added loop to produce monhtly mean and write out tif from GRASS database

LST climatology, added function to create list of files per month and other modifications

LST climatolgoy, modified download function and added section for downloading of tiles

LST climatology, initial commit script from Jim Regetz commit 01b3830e, task#375 and task#316

LST climatology, using IDRIS API modification using datetime module, OR task#375 and task#416

LST climatology initial commit script using IDRISI API and python

Kriging tmax OR raster predictions

Database stations extraction combined with covariates for tmax and any given region

Covariates production, modified projection and distance to coast, added writing up of multiband covariates brick

Covariates production, major reorganization, added sections for LST, LC and other covariates

Covariates production for processing tile/region: general code-initial commit

GAM fusion function, IBS 2013 models and additional cleaning of code

GAM fusion raster prediction, IBS 2013 run, tmax OR

GAM fusion raster prediction tmax OR, added cleaning of LST values and other modifications

GAM fusion raster prediction tmax OR, added constant sampling, multisampling,GAM bias models

GAM fusion function, added GAM models for bias surface and extraction of monthly mean tmax OR

GAM CAI function, models for IBS 2013 conference and modifications

GAM CAI raster predictions, modifcations and model running for IBS conference 2013

GAM CAI function correction constant sampling and GAM climatology models, tmax OR

GAM CAI raster prediction OR tmax,corretion constant sampling and GAM climatology models

GAM CAI function added climatology GAM models for OR tmax interpolation

GAM CAI, added constant sampling over year and monthly extraction for climatology fitting

GAM CAI function for raster prediction, task #493, tmax OR interpolation
i

GAM CAI raster prediction first commit, task #491, OR tmax interpolation

Methods comp part7-task#491- SNOT-GHCN data updated script debugged to run through mcapply

Methods comp part7-task#491- SNOTEL and GHCN analyses update main script calling function

Methods comp part7-task#491- function for residuals analyses comparison SNOTEL and GHCN through dates

Methods comp part7-task#491- residuals analyses using SNOTEL data, initial commit

Methods comp part6-task#491- Download FTP script and data prepartion for SNOTEL Data

Methods comp part5-task#491- residuals analyses, spatial transect through stations with diff and elevation

Methods comp part5-task#491- initial commit, residuals analyses with focus on differences,land cover and covariates plots

Methods comp part4-task#491- residuals analyses update plot res per elevation classes

Methods comp part4- task#491-, residuals analses, cleaning, added functions, residuals by land cover and temporal profiles

Methods comp part4 task#491 initial commit, residuals analyses at specific station for FUS and CAI

Methods comp part3-task#491- clean up, verification of results for specific dates

Method comp part3,initial commit task#491 check extremes for LST and ELEV, exploratory analysis Land cover

Methods comp part2: task-#491-major modifications, transect through images and stations, temporal profiles etc.

Methods comp part2: initial commit-task#491-,accuracy and closest training stations, multisampling etc.

Method comp part1 -task#491, major clean up, production of boxplots and visual maps

Initial commit-task#491-methods comparison part 1: kriging, GAM, GWR, FUS, CAI

Accuracy and spatial distance to closest fitting stat., intial commit task #491

Multi sampling kriging raster prediction, initial commit, task #491

Multisampling Kriging function interpolation initial commit raster prediction task #491

Method comparison initial commit task #491

GAM FUSION, multi sampling function initial commit

GAM FUSION, multi sampling accuarcy assessment main script initial commit

GWR, raster pred. modification model 8, function

GWR, modification of code for model 8, raste prediction

GWR, raster prediction -function used in the main script

GWR, raster prediction full year main script

KRIGING, full raster predition over on year: code clean up

KRIGING, modified function for memory clean up and other improvements

KRIGING, raster prediction full year, function used in main script

KRIGING, raster prediction for full year using function TASK#364

KRIGING, raster prediction-major changes for spatially explicit interp.

OR, Kriging using automated fitting of variograms TASK#364

FUSION function to predict raster, clean up of mod object using as.formula

FUSION, GAM and fusion comparison raster prediction modified return object to solve memory issues in mod object

FUSION, raster prediction using function in mcapply

FUSION, using parallel for raster prediction with function

FUSION, adding option to use same proportion of training for fusion and gam

FUSION, comparison to GAM models using the same testing and training data

FUSION, using GAM for bias surface, correction aspects

FUSION, training and testing for year 2010 read from the GHCND database

FUSION, modifications saving plots and adding GAM models for delta surface

Initial modification by Benoit-adding testing points for 10 dates

Initial commit: first fusion code from Brian

OR data preparation, initial commit for extraction of covariates from raster stack

OR data preparation task#363, modified code for ghcn to create a shapefile

GHNCD station data selection using Postgres database, initial commit, task #363

GAM LST, added specific and general diagnostic measures (e.g.MAE) GAM+Kriging, task #364 and #406

GAM LST, adding lines to summarize samling RMSE using plots, task #409

GAM LST, first code to test effect of sampling on GAM, task #409

GAM LST, added model and modified summary plots, run on 365 dates GAM+Kriging, task #364 and #406

GAM LST, modify code to generalize number of models and assessment,GAM+Kriging task #364

GAM LST, major modifications to create GAM+Kriging code, task #364

GAM LST, adding lines to assess RMSE per month over 365 dates, task #406

GAM LST, added model with forest only term -364 dates assessment, task #406

GAM LST, added section to save training and test residuals in shapefiles, task #361

GAM LST, changed triple nesting lat,long,Elev to double, 365 dates run, task #406 and #361

GAM LST, used monthly LST average instead of daily, task #361

GAM LST, adding new model with grass land cover, task #361

GAM using LST as input variable task #361

GAM, modification of nesting of models and clean up, task #361

Kriging, adding LST for co-kriging: task #364

Kriging, slight modification and clean up, task #364

Kriging, modification to save kriged surfaces in geotiff and png files, task #364

Kriging, modifying code to save training and testing samples in shapefiles: task #364

Kriging for OR, this is the first script, task #364

GWR modified code to save plots and images, task #364