Compute and generate the composed of a raster images stack
Project description
# StackComposed
The StackComposed compute the stack composed of a specific statistic of band values for several time series of georeferenced data (such as Landsat images), even if these are in different scenes or tiles. The result is a output of statistic compute for all valid pixels values across the time axis (z-axis), in the wrapper extent for all input data in parallels process.
## Documentation
Home page documentation: [https://smbyc.github.io/StackComposed](https://smbyc.github.io/StackComposed)
## Source code
The latest sources can be obtained from official repository: [https://github.com/SMByC/StackComposed](https://github.com/SMByC/StackComposed)
## Issue Tracker
Issues, ideas and enhancements: [https://github.com/SMByC/StackComposed/issues](https://github.com/SMByC/StackComposed/issues)
## Installation
The StackComposed use the following apps/libraries:
Python3
Gdal
Numpy
[Dask](http://dask.pydata.org)
### Using Pip
You can install from PyPi repository:
`bash pip3 install stack-composed `
### From source code
To install StackComposed from source:
`bash git clone https://github.com/SMByC/StackComposed cd StackComposed python3 setup.py install # or pip3 install -e . `
## About us
StackComposed was developing, designed and implemented by the Group of Forest and Carbon Monitoring System (SMByC), operated by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) - Colombia.
Author and developer: Xavier C. Llano Theoretical support, tester and product verification: SMByC-PDI group
### Contact
Xavier C. Llano: xavier.corredor.llano@gmail.com SMByC: smbyc (a) ideam.gov.co
## License
StackComposed is a free/libre software and is licensed under the GNU General Public License.
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