This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors.
InSAR Scientific Computing Environment (ISCE) replaces old InSAR processing algorithms and conventional computing paradigms with modern geodetically accurate algorithms embedded at the core of a modern, flexible, and extensible object-oriented computing framework. The framework enables scientists to easily and efficiently process raw data into useful data products for their science models and investigations." class="caption" align="right">There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth’s ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches.
This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and new codes, abstraction and generalization of the data model for efficient manipulation of objects among modules, and well-designed module interfaces suitable for command-line execution or GUI-programming. The framework is designed to allow users’ contributions to promote maximum utility and sophistication of the code, creating an open-source community that could extend the framework into the indefinite future.
This work was done by Paul A. Rosen, Gian Franco Sacco, and Eric M. Gurrola of JPL/Caltech; and Howard A. Zebker of Stanford University for NASA’s Jet Propulsion Laboratory.
This Brief includes a Technical Support Package (TSP).
InSAR Scientific Computing Environment (reference NPO-47557) is currently available for download from the TSP library.
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