Finding Magnetic Features and Emerging Flux Regions in HMI Data with SWAMIS

We present an adaptation of the Southwest Automatic Magnetic Identification Suite (SWAMIS) feature tracking algorithm for use in the SDO-HMI pipeline. Feature tracking algorithms have been used by several groups to identify features in what are now relatively small magnetogram datasets. They have been used across a large range of scales, from active regions to the smallest features visible with Hinode SOT. SWAMIS is being incorporated into the SDO-HMI pipeline in two forms: to identify large flux emergence regions, and to track every feature seen by HMI. This will enable real-time detection of events of interest to space weather forecasters, as well as large statistical studies of HMI data. We will describe the status of this code in the HMI pipeline and provide some examples of its use. A stand-alone version of the software for use on fixed-size datasets is also available.