Updated Kitware Results on the IARPA SMART Program

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Originally Aired - Tuesday, May 7 3:30 PM - 3:35 PM

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Event Location

Location: Innovation Hub, Exhibit Hall 2219

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Title: Updated Kitware Results on the IARPA SMART Program


The IARPA SMART program is bringing together many government agencies, companies, and universities to research new methods and build a system to search through enormous catalogs of satellite images from various sources to find and characterize relevant change events as they evolve over time.  Imagery used includes Landsat, Sentinel-2, Worldview, and PlanetScope.  Kitware is leading one of the performer teams on this program including DZYNE Technologies, Rutgers University, Washington University, and the University of Connecticut.  Our team is addressing the problems of broad area search to find man-made change – initially construction sites.  This is a “changing needle in a changing haystack” search effort.  Our system further categorizes detected sites into stages of construction with defined geospatial and temporal bounds and will predict end dates for activities that are currently in progress.  Our solution is called WATCH (Wide Area Terrestrial Change Hypercube) and has been deployed on AWS infrastructure to operate at scale.  Furthermore, the software for WATCH, called “geowatch” has been released as open source and is for freely available on Gitlab and PyPI.

In this talk we will summarize significant progress made during the eighteen-month Phase 2 of the program, which ended in December, and show improvements since our previous results presented at GEOINT 2023.  Notably, our detection scores on validation regions improved by a factor of three across Phase 2.  We will briefly highlight our research results, system integration/deployment, and developed open source tools and AI models which are available for community use.  We will conclude with a teaser of new directions in progress for Phase 3 including a new web-based user interface and tools to adapt the search to new tasks, such as detection of short term events (e.g. fairs and festivals).

Type: Lightning Talk


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