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NASA's GONASA technology is a mathematical formula / algorithm built around creating a grid composed of equal-area cells that span the entire visible hemisphere of a spherical object. Traditional longitude and latitude grids produce cells that diminish in size toward the poles due to convergence of longitudinal lines. GONASA circumvents this problem by carefully adjusting the latitude increments, resulting in a network of truly equal-area cells. This adjustment ensures that any feature observed on the spherical surface is accurately represented, regardless of its location. To implement GONASA, the spherical surface is first segmented into discrete latitude bands or rings, each chosen to encompass an identical surface area. Within each ring, longitude divisions maintain equal cell areas, creating a uniform Cartesian grid. The result is a consistent, distortion-corrected matrix suitable for automatic computation, enabling simplified, efficient, and accurate measurements of spatial characteristics such as feature area, centroid location, perimeter, compactness, orientation, and aspect ratio. GONASA grids are computationally efficient and readily adaptable to a range of data processing workflows, from spreadsheets to sophisticated data analysis frameworks like Pandas data frames in Python. Due to their consistent cell sizing and straightforward indexing, GONASA grids facilitate automation, enabling rapid, high-volume data processing and analysis, essential for modern remote sensing and planetary missions that require immediate, reliable data analysis in limited-bandwidth communications environments. At NASA, GONASA has already been successfully implemented to study images of Titan (e.g., mapping its clouds) taken by the Cassini space probe.