#### Package downloads and build status</b>

##### Downloads from the [RStudio CRAN Mirror](http://cran-logs.rstudio.com/)

This month      | In total
--------------- | -----------
![month](http://cranlogs.r-pkg.org/badges/gimms) | ![total](http://cranlogs.r-pkg.org/badges/grand-total/gimms)

##### Build status

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[![R build status](https://github.com/environmentalinformatics-marburg/gimms/workflows/R-CMD-check/badge.svg)](https://github.com/environmentalinformatics-marburg/gimms/actions)
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CRAN | 
---- | 
[![](http://www.r-pkg.org/badges/version/gimms)](https://www.r-pkg.org:443/pkg/gimms) | 

<hr>

#### Introducing the 'gimms' package

.. was an open-access tutorial that's unfortunately currently unavailable. The aim is to make it available soon and provide documentation and usage examples in future updates. For now, please refer to the package documentation for guidance.

<hr>

#### What's new?

##### 2021-04-16, **gimms** 1.2.0 changes the default server for file retrieval

The default server for online file retrieval changed from ECOCAST to [A Big Earth Data Platform for Three Poles](https://data.tpdc.ac.cn/en/data/9775f2b4-7370-4e5e-a537-3482c9a83d88/) operated by The National Center for Atmospheric Research. ECOCAST is currently not reachable, and will likely no longer be considered in future releases. This change does not affect the core functionality provided by the package.

<hr>

##### 2020-03-19, **gimms** 1.1.3 re-enables ECOCAST file retrieval

Online file retrieval from ECOCAST was recently unavailable due to SSL certificate issues. This has been fixed as of **gimms-1.1.3**. In addition, `gimms:::updateNasanex()` now yields correct online filepaths as outlined in [#3](https://github.com/environmentalinformatics-marburg/gimms/issues/3). 

<hr>

##### 2018-12-07, **gimms** 1.1.1 is out now

Starting with this update, rasterized NDVI3g.v0 images are no longer kept in memory, but properly linked to their corresponding files on disk (only applicable if 'filename' is specified in `rasterizeGimms()`).

<hr>

##### 2018-01-13, **gimms** 1.1.0 is now on CRAN

As of 2018-01-13, the next minor release of **gimms** has finally arrived on CRAN. Check out [NEWS](https://github.com/environmentalinformatics-marburg/gimms/blob/master/NEWS) for a full list of changes. In addition, note that the accompanying [GitBook](https://www.gitbook.com/book/envin-marburg/introducing-the-r-gimms-package/details) will be updated (and hopefully extended) soon.

<hr>

##### 2017-01-02, "traditional" NDVI3g.v0 names from new NDVI3g.v1 files via `oldNaming`
For all users who prefer to work with the now outdated NDVI3g.v0 file names, I've added a function called `oldNaming` to the 'develop' branch. It takes a vector of .nc4 file names as input and transforms them to traditional half-monthly file names, optionally appending a suffix *e.g.* in preparation for `writeRaster`. As this is not on CRAN yet, remember to install the 'develop' version via 
```r
devtools::install_github("environmentalinformatics-marburg/gimms", 
                         ref = "develop")
```
to be able to use that function in the first place.

<hr>

##### 2016-12-17, **gimms** 1.0.0 is now on CRAN
I am happy to announce that the brand-new package update (v1.0.0) has successfully been built for all platforms and is now available from [CRAN](https://cran.r-project.org/package=gimms). Among the major improvements are:

* comprehensive support for the recently released GIMMS NDVI3g.v1 which comes as half-yearly NetCDF container files and spans the period until December 2015. For reasons of convenience, continuing support for NDVI3g.v0 ENVI binary files is maintained. 
* quality control is now directly available through `rasterizeGimms`. In order to make sure older scripts are still operable, separate calls to `qualityControl` are possible, but explicitly require the specification of a 2-layered `RasterStackBrick` object (NDVI and flags).
* `rasterizeGimms` further takes an optional argument 'ext' which is passed to `raster::crop` which, if used, drastically reduces computation times. At the same time, the application of a scale factor and the rejection of 'mask-water' and 'mask-nodata' values is no longer optional.
* parallel processing is no longer realized through **foreach** (alongside with **doParallel**), but instead relies on the built-in **parallel** package only. Therefore, the former two are no longer part of the package Imports section.
* et cetera

<hr>

##### 2016-01-15, **gimms** 0.5.0 is now on CRAN
As of today, **gimms** 0.5.0 is available from [CRAN](https://cran.r-project.org/package=gimms) and has some new functionality:

* enabled flag support in `rasterizeGimms`. In addition to the raw and scaled values of NDVI3g, the function now optionally returns flag layers which can subsequently be used for quality control. Please refer to the official [README](http://nasanex.s3.amazonaws.com/AVHRR/GIMMS/3G/00READMEgeo.txt) for further reading. 
* improved performance of parallel processing.
* revised package documentation.

<hr>

##### 2015-12-16, added parallel support
I decided to add optional multi-core support to `downloadGimms`, `rasterizeGimms` and `monthlyComposite`. The referring arument is called 'cores' and, if not specified otherwise, defaults to 1 (i.e., parallel computing is disabled). In the course of this, the **gimms** package version on branch 'develop' has been incremented to 0.4.0 and can be installed via `devtools::install_github` (see further below).

<hr>

##### 2015-11-13, **gimms** 0.3.0 is now on CRAN
It's Friday 13th and an updated version of the **gimms** package has been published on [CRAN](https://CRAN.R-project.org/package=gimms). The new version includes

* `significantTau` to calculate pixel-based (and optionally pre-whitened) Mann-Kendall trend tests from a previously processed GIMMS NDVI<sub>3g</sub> (or any kind of) 'RasterStack/Brick' object. Note that it also works with simple 'numeric' vectors (i.e., univariate time series observations);
* the below compatibility update of `downloadGimms` that enabled 'Date' input;
* and some minor bug-fixes.

<hr>

##### 2015-11-11, `downloadGimms` now works with 'Date' input
In response to recent user suggestions, I decided to enable 'Date' input for `downloadGimms` which grants the user a finer control over the temporal coverage of the data to be downloaded. The changes are currently available from the 'develop' branch via 


```r
devtools::install_github("environmentalinformatics-marburg/gimms", 
                         ref = "develop")
```

and will be submitted to CRAN soon.

<hr>

##### 2015-11-06, pre-whitened Mann-Kendall trend test via `significantTau`
In order to account for lag-1 autocorrelation when trying to deduce reliable long-term monotonous trends, **gimms** now features a function called `significantTau`. The code imports the standard (i.e., without pre-whitening) procedure included in package **Kendall** (McLeod, 2011) or, if the user decides to apply pre-whitening prior to the actual trend test, one of the algorithms included in **zyp** (Bronaugh and Consortium, 2013). Check out `?significantTau` for further details. 

<hr> 

##### 2015-10-26, `downloadGimms` now works properly on Windows
I recently received a bug report about some strange behavior of `downloadGimms` (when working on Windows platforms) which resulted in a rather awkward look of the rasterized images. 

<center>
  <img src="http://i.imgur.com/MySaI9F.png" alt="windows_bug" style="width: 650px;"/>
</center>

The problem was obviously related to `download.file` which worked just fine on Linux when using the default settings, but introduced distortions on Windows. In the newest package version 0.2.0 which is now brand-new on [CRAN](https://CRAN.R-project.org/package=gimms), I therefore specified `download.file(..., mode = "wb")` to explicitly enable binary writing mode. 

Thanks again for the input! 

<hr>

