Title: InSAR Scientific Computing Environment
Presenting Author: Eric M Gurrola
Organization: Jet Propulsion Lab
Co-Author(s): Paul Alan Rosen(1), Gian Franco Sacco(1), Piyush Agram(1), Howard A Zebker(2)
(1) Radar Science and Engineering, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. (2) Electrical Engineering, Stanford University, Stanford, CA, USA.

Abstract:
The InSAR Scientific Computing Environment (ISCE) is a software development effort within the NASA Advanced Information Systems and Technology program. The ISCE provides a computing environment for geodetic image processing for InSAR sensors that enables scientists to reduce measurements directly from radar satellites and aircraft to new geophysical products without first requiring them to develop detailed expertise in radar processing methods. The environment can serve as the core of a centralized processing center to bring Level-0 raw radar data up to Level-3 data products, but is adaptable to alternative processing approaches for science users interested in new and different ways to exploit mission data. The proposed NASA-ISRO SAR (NISAR) Mission would deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystem. The InSAR Scientific Computing Environment is planned to become a key element in processing projected NISAR data into higher level data products, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these new data than current approaches. At the core of ISCE is both legacy processing software from the JPL/Caltech ROI_PAC repeat-pass interferometry package as well as a new InSAR processing package containing more efficient and more accurate processing algorithms developed at Stanford for this project. These new algorithms are based on experience gained in developing processors for missions such as SRTM and UAVSAR. Around the core InSAR processing programs we are building object-oriented wrappers to enable their incorporation into a more modern, flexible, extensible software package that is informed by modern programming methods, including rigorous componentization of processing codes, abstraction and generalization of data models, and a xml-based user interface with selectable exposure to the levels of sophistication, allowing novices to apply it readily for common tasks and experienced users to mine data with greater facility and flexibility. The environment is designed to easily allow user contributions, enabling an open source community to extend the framework into the indefinite future. In this paper we describe the new computing environment, and how it is currently being adapted to work in several processing paradigms: 1) it is the basis of a prototype production system known as ARIA-MH for systematically reducing wide area acquisitions of radar data; 2) it is one of the core technologies being used to demonstrate cloud-based computing and learning through Earthkit and CESCRE; 3) it is being baselined for the NISAR algorithm core; and 4) it has been upgraded to support time-series of UAVSAR interferometry and polarimetric data. We describe the ISCE architecture and features that permit this kind of multi-program flexibility, extensibility and ease-of-use, and will discuss plans for future testing and version releases.