kandi X-RAY | gimms Summary
kandi X-RAY | gimms Summary
cran | ---- | |. ... is an open-access tutorial about the gimms package which has been developed using gitbook. the default server for online file retrieval changed from ecocast to a big earth data platform for three poles 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. 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. starting with this update, rasterized ndvi3g.v0 images are no longer kept in memory, but properly linked to their corresponding
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Trending Discussions on gimms
I want to download and process the
GIMMS NDVI 3g.v1 collection with R. With the
gimms package, I managed to download the full collection but I do not know how to assign dates on the files. My final result, I want to be a raster stack with NDVIs of good quality (zero flag value). So, 2 observations per month, per year. I would really appreciate any help.
ANSWERAnswered 2019-Jul-10 at 19:17
I'd recommend you take a look at Florian Detsch's (The package maintainers) blog post on using the package. Why? Florian does a good job of highlighting how to import the files using Gimms and how the package can address organizing the files temporally (i.e. in time order) using update_inventory() and rearrangeFiles() - which my sense is the issue you are encountering.
I hope this points you in the right direction.
Florian also wrote a book guide to the package:
the above cover the use and application of the package.Cited Article (Imported for simplicity)
This is a guest post by Florian Detsch
What it is all about
With the most recent update of the AVHRR GIMMS data collection to NDVI3g (Pinzon and Tucker, 2014), we decided to create a package from all functions we have written so far to download and process GIMMS binary files from the NASA ECOCAST server. The package is called gimms and features a collection of fundamental work steps required to get the data into R:
- updateInventory to list all GIMMS files available online and
- rearrangeFiles to sort (online or local) files by date,
- downloadGimms to download selected files,
- rasterizeGimms to import the binary data as 'Raster*' objects into R and
- monthlyComposite to aggregate the bi-monthly datasets to monthly value composites.
The gimms package (version 0.1.1) is now officially on CRAN and can be installed directly via
I am trying to download data from the following website
This website has NDVI data from MODIS sensors. The folders are arranged according to years and days of the year all of which I need to download.
As a test, I tried downloading just one data...
ANSWERAnswered 2018-Aug-10 at 15:12
To read in memory, try:
I am trying to extract the residuals from a regression run pixel by pixel on a raster stack of NDVI/precipitation. My script works when i run it with a small part of my data. But when i try to run the whole of my study area i get: "Error in setValues(out, x) : values must be numeric, integer, logical or factor"
The lm works, since I can extract both slope and intercept. I just cant extract the residuals.
Any idea of how this could be fixed?
Here is my script:...
ANSWERAnswered 2017-Oct-23 at 13:04
Your function only test if the first layer shows
NA values to avoid fitting the model. But there may be
NA in other layers. You know that because you added
na.action = na.exclude in your
The problem is that if the model removes some values because of
NA, the residuals will only have the length of the non-NA values. This means that your resulting
r vector will have different lengths depending on the amount of
NA values in layers. Then,
calc is not be able to combine results of different lengths in a stack a a defined number of layers.
To avoid that, you need to specify the length of
r in your function and attribute residuals only to non-NA values.
I propose the following function that now works on the dataset your provided. I added (1) the possibility compare more layers of each if you want to extend your exploration (with
nlayers), (2) avoid fitting the model if there are only two values to compare in each layer (perfect model), (3) added a
try if for any reason the model can fit, this will output values of
-1e32 easily findable for further testing.
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