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dissever's Introduction

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dissever: a method for spatial downscaling

What is dissever?

dissever is a general method for spatial downscaling introduced by Malone et al. in their 2012 Computers & Geosciences paper. This method has been extended and generalised by Roudier et al. to use and leverage a wide range of regression methods.

This package implements the latter in R, and modifies it so numerous regression methods can be tested. It leverages the power of the caret package to do so.

Installing dissever

To install the stable version of dissever:

install.packages('dissever')

To install the development version of dissever:

# install.packages('devtools')
devtools::install_github('pierreroudier/dissever')

dissever's People

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dissever's Issues

Problem with NA values for LST downscaling

I have encountered problems related to downscal
errors.zip

ing time series raster stack from 2002 to 2017 Terra MODIS LST data using two predictors -- DEM and Terra MODIS NDVI. I have created raster stack for predictors and raster layer for Modis LST. My study area is South Alps that's why I use DEM as additional explanatory variable.
As an attachment I am sending my code with datasets and short explanation as well.
I would be really grateful for help. Thank you!

Installation failed: row names contain missing values

Hi, when installing dissever from github I get the following:

> devtools::install_github('pierreroudier/dissever')
Downloading GitHub repo pierreroudier/dissever@master
from URL https://api.github.com/repos/pierreroudier/dissever/zipball/master
Installing dissever
Installation failed: row names contain missing values

This happens for me on both for R 3.4.2 under Windows and for R 3.3.3 on Mac OS. Can anybody reproduce this issue?

How to Parallel the function “dissever”?

Dear Pierre Roudier,
Thanks very much for your effort to develop the ‘dissever’ package. I have used it to downscale one precipitation grid file, which took my 4.5 mins. But I have so many file to downscale, so how can I parallel it? I have little time to do this thing.
I need your help. Thanks in advance.

Error in check_dims(x = x, y = y) : nrow(x) > 1 is not TRUE

Hi, I am having this issue when trying to downscale:

res_gam <- dissever(
   coarse = output, # stack of fine resolution covariates
   fine = fine, # coarse resolution raster
   method = "gamSpline", # regression method used for disseveration
   p = p_train, # proportion of pixels sampled for training regression model
   min_iter = min_iter, # minimum iterations
   max_iter = max_iter, # maximum iterations
   verbose = TRUE
 )

Selecting best model parameters
Error in check_dims(x = x, y = y) : nrow(x) > 1 is not TRUE.

Inputs are the following:

output
class : RasterLayer
dimensions : 12, 12, 144 (nrow, ncol, ncell)
resolution : 1.666667, 1.666667 (x, y)
extent : 12.2, 32.2, -14.61667, 5.383333 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +datum=WGS84 +no_defs
source : memory
names : index_6
values : 14295.9, 66365257 (min, max)

fine
class : RasterStack
dimensions : 2260, 2293, 5182180, 6 (nrow, ncol, ncell, nlayers)
resolution : 0.008333333, 0.008333333 (x, y)
extent : 12.2, 31.30833, -13.45, 5.383333 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +datum=WGS84 +no_defs
names : GHS_POP_E//_30ss_V1_0, layer.1, built, layer.2, travel, layer.3
min values : 0.001458411, 0.000000000, ?, 0.046248772, 0.000000000, 0.000000000
max values : 193353.9687, 4.2720, ?, 543.8151, 2964.0000, 72540.0328

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