Open AccessSIFTing through satellite imagery with the Satellite Information Familiarization Tool
Author(s) -
Jordan Gerth,
Raymond Garcia,
David Hoese,
Scott B. Lindstrom,
Timothy J. Schmit
Publication year - 2020
Publication title -
journal of operational meteorology
Language(s) - English
Resource type - Journals
ISSN - 2325-6184
DOI - 10.15191/nwajom.2020.0810
Subject(s) - computer science , scale invariant feature transform , geostationary orbit , satellite imagery , software , satellite , remote sensing , visualization , multispectral image , computer graphics (images) , artificial intelligence , geography , feature extraction , engineering , aerospace engineering , programming language
The Satellite Information Familiarization Tool (SIFT) is an open-source, multi-platform graphical user interface designed to easily display spectral and temporal sequences of geostationary satellite imagery. The Advanced Baseline Imager (ABI) and Advanced Himawari Imager (AHI) on the “new generation” of geostationary satellites collect imagery with a spatial resolution four times greater than previously available. Combined with the increased number of spectral bands and more frequent imaging, the new series imagers collect approximately 60 times more data. Given the resulting large file sizes, the development of SIFT is a multiyear effort to make those satellite imagery data files accessible to the broad community of students, scientists, and operational meteorologists. To achieve the objective of releasing software that provides an intuitive user experience to complement optimum performance on consumer-grade computers, SIFT was built to leverage modern graphics processing units (GPUs) through existing open-source Python packages, and runs on the three major operating systems: Windows, Mac, and Linux. The United States National Weather Service funded the development of SIFT to help enhance the satellite meteorology acumen of their operational meteorologists. SIFT has basic image visualization capabilities and enables the fluid animation and interrogation of satellite images, creation of Red-Green-Blue (RGB) composites and algebraic combinations of multiple spectral bands, and comparison of imagery with numerical weather prediction output. Open for community development, SIFT users and features continue to grow. SIFT is freely available with short tutorials and a user guide online. The mandate for the software, its development, realized applications, and envisioned role in science and training are explained.