A Spatial Domain Approach for Airborne Gravity Data Processing
Faculty of Computing, Health and Science
School of Computing, Health and Science
Airborne gravity data contain more unwanted noises due to the high sensitivity of the airborne survey system. A common approach to minimise these noises is to smooth the data using various approaches. Traditionally, data smoothing is carried out using separate programs based on different mathematical models. The adaptive spatial data processing system (ASDPS) provides a new way in processing gravity data in spatial domain. ASDPS not only can be implemented as a unique user interface for either selecting an implemented method or defining a new method without recoding and recompilation, but also supports parallel processing in a multithreaded computing environment. This paper presents an application of ASDPS to airborne gravity data processing firstly for reducing the survey noises contained in the original data, and secondly for easy data transformation for different purposes in gravity studies.