Exploring the Synergies between ‘Commercial’ and Open Source Software Gregg Petrie, Cosmic Project Lee Miller, Pacific Northwest National Laboratory

Outline Introduction Study Approach Specific Examples Conclusions Action Items Questions

Introduction : Disclaimer Represent Users-Hyperspectral Remote Sensing NOT claiming to be an expert hacker

Introduction : Motivation Current Impression Current Hope: The Whole > Parts

Introduction : Goals Identify, develop, test, refine, and demonstrate synergies using real world examples Demonstrate how open source community can support users of commercial software Promote the support of open source by commercial vendors

Introduction : More Information COSMICPROJECT.ORG

Outline Introduction Study Approach Give Some Concrete Examples Conclusions Action Items Questions

Approach Survey of Open Source Possibilities Create and Experiment With a Loosely Coupled Environment Create and Experiment With a Tightly Coupled EnvironmentCreate and Experiment With a Tightly Coupled Environment

Approach: Survey 238 Open Source Geospatial Packages 24 Scientific Open Source Python Packages

Approach-Survey Observations : Python Provide access to a wide range of additional tools High level structures promote rapid prototyping Self Documenting Builds on the Python/ESRI Experience Widely used to glue capabilities together Well supported (e.g..NET) Python supports both UNIX and WINDOWS Use of Python growing in the scientific world

Approach-Survey Observations : Python Issues SPEED.NET Moore's Law More C code

Approach-Loosely Coupled Environment: Dealing with the ‘Tower of Babel’ file format problem GDAL Vendor DLL Write your own

Loosely Coupled Environment: Actual Solution for the ‘Tower of Babel’ file format problem TIFF files Flexible Supported by many commercial packages Stable Dealing with large file sizes Well Known

Tiff Flexibility :Two Edged Sword

Outline Introduction Study Approach Specific Examples Conclusions Action Items Questions

Examples: Leica Imagine Imagine provides ‘standard’ remotes sensing tools that include: Registration File creation Display Registration Classification File import/export Python tools Interface to Windows/UNIX AIP AI tools Easy access to FORTRAN and C software packages Quick GUI development tools Access to.NET SciPy toolkit WEB tools SDC Morphology toolbox ‘Twisted’ for event-driven networking CGAL for computational geometry IDL like capabilities to write advanced Hyperspectral analysis tools COSMIC Photoshop for presentation graphics Python

Example: Imagine

Advantage Essentials Professional Cost Capabilities

Example 1: Web Mapping

Examples: Web Mapping

Step 1: Trail Extraction

Step 2: Annotation of Nodes Used Open Source to translate to ASCII files Used Python to add USGS elevation data to nodes and calculate distance Used the Open Source PIL software to create gif file

Example 2: Color Compression

Example 2: Imagine Approach

Example 2: Combined Approach For each class find the average color and update the LUT

Example 2: Results Top Half=RGB image Lower Left= Unsupervised color Lower Right =Imagine color Menu Maze Problem

Example 2: Real Usefulness Image source: Pick the 3 best BANDS for each land cover

Outline Introduction Study Approach Specific Examples Conclusions Action Items Questions

Conclusions Advantage Essentials Professional Cost Capabilities Whole > Sum of the Parts 0 Cost Open Source

Conclusions: NumPy and Python can be used to “glue” software And now for something completely different... +

Conclusions: Tiff files, with a ‘little’ improvement’ can greatly mitigate the ‘Tower of Babel’ file format problem

Advantage Cost Professional Conclusions: Vendor Specific Essentials Capabilities Commercial Advantages Know QA factors Good documentation Not all users programmers Can be faster Can be cheaper Can by bureaucratically compatible Open Source

Conclusions: Vendor Specific Empower Users Help current developers reduce both prototyping costs and time to market Increase the rate at which new ideas· developed by users could be prototyped, tested and moved into ‘native’ proprietary commercial tool kit Provides an alternative to the Menu Maze Build on the Python/ARC ESRI Experience New pathway for new users

Outline Introduction Study Approach Specific Examples Conclusions Action Items Questions

Action Items For Vendors Continue Support BigTiff Work together to establish Tiff conventions for hyperspectral data sets Build on the ESRI/Python Model Support a Tightly Coupled Environment

Action Items For Open Source Support BigTiff Work together to establish Tiff conventions for hyperspectral data sets Move toward tightly coupling commercial and open source data Improve Documentation for GeoTiff data Couple systems (e.g. GRASS) to Commercial packages

Questions