Comparison of Cloud-to-Cloud Distance Calculation Methods: Is the Most Complex Always the Most Suitable?

Cloud-to-cloud (C2C) distance calculations are frequently performed as an initial stage in change detection and spatiotemporal analysis with point clouds. There are various methods for calculating C2C distance, also called inter-point distance, which refers to the distance between two corresponding point clouds captured at different epochs....

Improving Satellite-based precipitation estimates: A spatiotemporal object-oriented approach to error analysis and correction

Satellite Precipitation Products (SPP) have been revolutionary in water resources management and flood-related disaster response. However, estimating extreme rainfall is subject to multiple systematic and aleatory errors that need to be corrected. This dissertation addresses errors in satellite data to estimate extreme rainfall events in space...

4D objects-by-change: Spatiotemporal segmentation of geomorphic surface change from LiDAR time series

Time series of topographic data are becoming increasingly widespread for monitoring geomorphic activity. Dense 3D time series are now obtained by near-continuous terrestrial laser scanning (TLS) installations, which acquire data at high frequency (e.g. hourly) and over long periods. Such datasets contain valuable information on topographic...

St-corabico: A spatiotemporal object-based bias correction method for storm prediction detected by satellite

Advances in near real-time rainstorm prediction using remote sensing have offered important opportunities for effective disaster management. However, this information is subject to several sources of systematic errors that need to be corrected. Temporal and spatial characteristics of both satellite and in-situ data can be combined to enhance...

STAPP: SpatioTemporal Analysis of Plantar Pressure Measurements using Statistical Parametric Mapping

<br/>Background<br/><br/>Pedobarography produces large sets of plantar pressure samples that are routinely subsampled (e.g. using regions of interest) or aggregated (e.g. center of pressure trajectories, peak pressure images) in order to simplify statistical analysis and provide intuitive clinical measures.<br/><br/>Research Question<br/><br/>We...

Revisiting Urban Dynamics through Social Urban Data: Methods and tools for data integration, visualization, and exploratory analysis to understand the spatiotemporal dynamics of human activity in cities

The study of dynamic spatial and social phenomena in cities has evolved rapidly in the recent years, yielding new insights into urban dynamics. This evolution is strongly related to the emergence of new sources of data for cities (e.g. sensors, mobile phones, online social media etc.), which have potential to capture dimensions of social and...