Snow cover assessment tool using Python
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This document describes a tool created using Python to calculate snow cover area from MODIS Terra datasets and plot the change over time. It uses PyQt4 and PySide for the GUI, GDAL for image processing, NumPy for arithmetic and file listing, and Matplotlib for plotting. The tool allows the user to select input and output folders, runs snow cover calculations on the MODIS files, and displays the results as a graph of snow cover area over time. Future improvements could involve using more GDAL and OGR capabilities to generate output maps of permanent and seasonal snow cover.
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Snow cover assessment tool using Python
- 1. SUBMITTED BY: A N T A R A * , A K S H A R A , S A P N A & M E E N A K S H I SUPERVISED BY: P R A S U N K . G U P T A # GEOINFORMATICS DEPARTMENT INDIAN INSTITUTE OF REMOTE SENSING SNOW COVER ASSESSMENT TOOL USING PYTHON * antaradasgupta26@gmail.com # prasun@iirs.gov.in
- 2. INTRODUCTION AIM: To create a tool using PYTHON which calculates the snow cover area using MODIS Terra Temporal Datasets and plots a graph of the change in the same over time. DATASETS USED: MOD10A2-L8 (8-day composite data) Subdataset used - Maximum Snow Extent over the 8 day period
- 3. MATERIALS AND METHODS SOFTWARES USED: Enthought Canopy Qt Designer PYTHON LIBRARIES USED: For UI design - PyQt4 and PySide For image processing – GDAL For the arithmetic and file listing functions – numpy, glob For the graph - pylab
- 4. MATERIALS AND METHODS(2) METHODOLOGY FOLLOWED Create a GUI using QtDesigner and save the .ui file. Export it to a .py file using the in built utility in PyQt4 – pyuic4. Open the .py file in Canopy, define the required functions and connect the buttons to the requisite functions
- 5. PYQT4 & PYSIDE PyQt is a Python binding of the cross-platform GUI toolkit Qt. It is one of Python's options for GUI programming. PyQt implements around 440 classes and over 6,000 functions and methods including: a substantial set of GUI widgets classes for accessing SQL databases (MYSQL, ORACLE), etc. Notable applications that use PyQt : Orange, a data mining and visualization framework QGIS, a free software desktop GIS, etc. PySide is the Canopy alternative for PyQt4.
- 6. GDAL GDAL (Geospatial Data Abstraction Library) is a library for reading and writing raster geospatial data formats. The related OGR library (OGR Simple Features Library), which is part of the GDAL source tree, provides a similar capability for simple features vector data. Software that uses GDAL/OGR are: ARCGIS, GOOGLE EARTH, MAPSERVER, GRASS GIS, QGIS, etc.
- 7. NUMPY o NumPy is the fundamental package for scientific computing with Python. It is an extension to the Python programming language. o It contains : a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities
- 8. PYLAB Pylab is the module for scientific computing with Python. Pylab is part of matplotlib (in matplotlib.pylab) and tries to give a MatLab like environment. matplotlib.pylab which allow the user to create plots with code quite similar to MATLAB figure generating code.
- 9. GLOB The glob module finds all the pathnames matching a specified pattern according to the rules used by the Unix shell. No tilde expansion is done, but *, ?, and character ranges expressed with [] will be correctly matched. glob.glob(pathname): Return a possibly-empty list of path names that match pathname, which must be a string containing a path specification. pathname can be either absolute (like /usr/src/Python-1.5/Makefile) or relative (like ../../Tools/*/*.gif), and can contain shell-style wildcards.
- 10. THE GUI
- 11. FUNCTIONS USED
- 12. EXECUTION
- 13. OUTPUT GRAPH OF CHANGE IN SNOW COVER AREA
- 14. FUTURE SCOPE The program is currently just generating the area numerically, in future it could be modified using GDAL to generate the output binary files for snow cover and generate permanent and seasonal snow cover maps using OGR capabilities. Such a platform could also be created for the processing of AMSR-E Data for Soil Moisture Studies.
- 15. THANK YOU!