Nansat is a scientist friendly Python toolbox for processing 2D satellite earth observation data.
The main goal of Nansat is to facilitate:
- easy development and testing of scientific algorithms,
- easy analysis of geospatial data, and
- efficient operational processing.
We appreciate acknowledments of Nansat. Please add "The image analysis was performed with the open-source NanSat (https://github.com/nansencenter/nansat) python package" (or equivalent) if you use Nansat in scientific publications.
The easiest way to install Nansat on a Linux machine is to use anaconda
# download the latest version of miniconda
wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
# make it executable
chmod +x miniconda.sh
# install miniconda virtual environment
./miniconda.sh -b -f -p $HOME/miniconda
# activate the miniconda environment
export PATH=$HOME/miniconda/bin/:$PATH
# update miniconda packages and metadata
conda update -q --yes conda
# install all requirements from conda-forge channel
conda install -q --yes -c conda-forge qt=4.8.7=0 numpy scipy matplotlib nose pillow basemap netcdf4 gdal
# configure environment
export GDAL_DATA=$HOME/miniconda/share/gdal/
export GEOS_DIR=$HOME/miniconda/
# finally install Nansat
pip install https://github.com/nansencenter/nansat/archive/master.tar.gz
# run tests
nosetests nansat
Fore more information see Install-Nansat section or use pre-configure virtual machines as explained on Nansat-lectures
# download a test file
!wget https://github.com/nansencenter/nansat/raw/develop/nansat/tests/data/stere.tif
# import main file opener
from nansat import Nansat
# open a test file
n = Nansat('stere.tif')
# see file content
print n
# view file footpring
n.write_map('stere.footpring.png')
# create RGB with auto-stretched histogram
n.write_figure('stere_rgb.png', [1,2,3], clim='hist')Fore more information see Tutorial or notebooks for Nansat lectures
Development is supported by the Research Council of Norway as a part of NORMAP project (grant no. 195397/V30).