EES data Lab - Spatiotemporal Data Models and Algorithms for Earth and Environmental Sciences / Modelos de dados espácio-temporais e algoritmos para as ciências da terra

2022 - 2023

Synopsis

Scientists and engineers working in fields such as the environmental sciences, the oceans, climate, or earth sciences have access to massive amounts of geo-referenced data. These data allow monitoring and studying the behavior of objects or events of interest over time, making diagnoses and predictions, etc. These tasks assume the existence of good quality data and methods and tools to analyze the data with little effort. Currently, there are many tools help on managing, processing, and analyzing spatial data, but the same does not happen when one intends to work with spatial data that evolves over time.This project focuses on the development of models and tools for the processing of spatiotemporal (SPT) data, based on two case studies: ​​environmental engineering and ​​marine ecology. The focus will be on SPT data modeled as 2D and 3D geometries that can change position, shape, or size continuously over time (moving objects). For example, we can model an iceberg as a 3D moving object (thus representing its movement and changes in size and shape over time). This model has advantages over discrete models, particularly when one intends to represent the evolution of geometrically definable objects or events, as it allows for more compact and intuitive representations, and guarantees the independence of the data from the acquisition process. Two main topics will be investigated: 1. Research work in this area has focused almost exclusively on the modeling of 2D moving objects. In this project, we intend to take the first steps towards the modeling of 3D moving objects in database or data stream systems. In particular, we will investigate the feasibility of using a unified model to represent 2D and 3D moving objects.

Funding

Funding Program: FCT - Projetos de Investigação de Caráter Exploratório no âmbito do Programa MIT Portugal
Funding Total Budget: 49.995,77€
Funding IPLeiria: 14.961,03€
Funding CIIC: 12.199,41€