An independent component analysis filtering approach for estimating continental hydrology in the GRACE gravity data

Independent Component Analysis: An Approach to Clustering

Statistical downscaling of GRACE gravity satellite-derived groundwater level data

With the continued threat from climate change, population growth and followed by increasing water demand, the need for hydrological data with high spatial resolution and proper time coverage to be felt more than ago. Therefore, having data such as terrestrial water storage changes and groundwater level changes with high resolution spatial helps to plan and make decisions for water resource mana...

Independent Component Analysis for Filtering Airwaves in Seabed Logging Application

Marine controlled source electromagnetic (CSEM) sensing method used for the detection of hydrocarbons based reservoirs in seabed logging application does not perform well due to the presence of the airwaves (or sea-surface). These airwaves interfere with the signal that comes from the subsurface seafloor and also tend to dominate in the receiver response at larger offsets. The task is to identi...

Hydrology signal from GRACE gravity data in the Nelson River basin, Canada: a comparison of two approaches

The Gravity Recovery and Climate Experiment (GRACE) satellite mission measures the combined gravity signal of several overlapping processes. A common approach to separate the hydrological signal in previous ice-covered regions is to apply numerical models to simulate the glacial isostatic adjustment (GIA) signals related to the vanished ice load and then remove them from the observed GRACE data...

Independent Component Analysis for Binary Data: an Experimental Study