I just thought I'd add that there are some 'pure' Python solutions for several nodes in this workflow, also.
Some file reading and basic processing:
Spectral Python: http://spectralpython.sourceforge.net/
More classification than you'll find in pure remote sensing and GIS packages:
More links I can't share:
6S Python ...
If you really want to use python, and you need functionality similar to GRASS, perhaps the easiest solution would be to use GRASS via Python.
That isn't specific to Landsat8, but I don't think a processing solution should be tied that closely to a specific satellite. You could implement some simple wrappers / higher level functions if you're consistently ...
I just used pyModis the other day, it downloaded fine.
Two things to check:
1) Do you use the current version? The installation works like this:
pip install pyModis
If that does not work, then try to upgrade:
pip install pyModis --upgrade
2) Register at NASA:
Importantly, to be able to download ...
Doing some more searching I found out that a bug related to gdalwarp and NODATA was fixed in version 1.11.2.
Testing on another machine with gdal 1.11.2 worked.
You may want to check http://www.pymodis.org which is a Free and Open Source Python based library to work with MODIS data.
It offers bulk-download for user selected time ranges, mosaicking of MODIS tiles, and the reprojection from Sinusoidal to other projections, convert HDF format to other formats and the extraction of data quality information.
In the ...
That is because you are accessing the HTTP archive at http://e4ftl01.cr.usgs.gov/. ftplib is expected to fail when you try to connect to HTTP instead of FTP.
The FTP archive is located at ftp://ladsweb.nascom.nasa.gov/allData/.
However, both archives do not contain the exact same data. Depending on the MODIS product you are looking for you might find it on ...
First, your file sizes are as expected. When you go from 1000m per pixel, to 30m per pixel, you get 1111-times increase in size, which is close to what you see from 2 MB to 3.4 GB, once you also consider compression etc. The calculation is:
(1000 m/ 30m)^2 = 1111.1
It is squared due to the raster being a 2d array.
The whole point of STARFM, or ESTARTFM (a ...
Recently an updated, improved version of pyMODIS got published:
Please consider to update your installation (see above for instructions). Hopefully the problem is solved then. Otherwise please contact the author.
Outside of pyModis, this can be done by using the LAADS Web Service (LWS) Classic API
LAADS Web Service Classic is a SOAP and REST based Application
Programming Interface (API) that allows users to search, order, and
download MODIS Level-1 and atmosphere data products through a
You will have to first get a List of available ...
This question may be related to this answer https://gis.stackexchange.com/a/2279/103142 , despite you may have other dependencies installed, on windows it is recommended to use pyModis and GDAL from the OSGeo4W Shell.
This is also suggested by pyModis developers. Perhaps you already checked this http://www.pymodis.org/info.html#how-to-install-pymodis , but ...
modis_convert.py and modis_download_from_list.py. are Python scripts therefore in the command prompt, type
With the adequate parameters.
If you want to use PyModis from the command prompt or IDLE, you need to import the module
from pymodis import downmodis
The examples are in the Jupyter/Ipython notebook (/....
pyModis, specifically the modis_mosaic and modis_convert scripts can use either MRT or GDAL to mosaic and/or reproject the data (see modis_mosaic.py documentation).
If pyModis somehow fails for your specific use case you can still use it to download the data and then reproject it with the Modis Swath Tool.
Strangely, it look's like gdalwarp is missing the input vrt NoData declaration (well somehow still it declares it in output tiff...).
Which is a bit odd since you said that in step 1. the NoData value is kept. Check if element <NoDataValue>-3000</NoDataValue> exist for each band of your VRT dataset.
Beside above isue, you can try to force ...